St. Petersburg University
Graduate School of Management
Master in Management Program
HEALTHCARE INFORMATION SYSTEM
SELECTION MODEL FOR MEDICAL CLINICS
Master’s Thesis by the 2nd year student
Concentration — Master in Management
Vera Mikhnevich
Research advisor:
Professor, Head of Information
Technologies in Management Department,
Tatiana A. Gavrilova
St. Petersburg
2016
ЗАЯВЛЕНИЕ О САМОСТОЯТЕЛЬНОМ ХАРАКТЕРЕ ВЫПОЛНЕНИЯ
ВЫПУСКНОЙ КВАЛИФИКАЦИОННОЙ РАБОТЫ
Я, Михневич Вера Павловна, студент второго
курса магистратуры
направления «Менеджмент», заявляю, что в моей магистерской диссертации на тему
«Модель
выбора
медицинских
информационный
систем
в
медицинских
учреждениях», представленной в службу обеспечения программ магистратуры для
последующей
передачи
в
государственную
аттестационную
комиссию
для
публичной защиты, не содержится элементов плагиата.
Все прямые заимствования из печатных и электронных источников, а также
из защищенных ранее выпускных квалификационных работ, кандидатских и
докторских диссертаций имеют соответствующие ссылки.
Мне известно содержание п. 9.7.1 Правил обучения по основным
образовательным программам высшего и среднего профессионального образования
в СПбГУ о том, что «ВКР выполняется индивидуально каждым студентом под
руководством назначенного ему научного руководителя», и п. 51 Устава
федерального государственного бюджетного образовательного учреждения высшего
профессионального
образования
«Санкт-
Петербургский
государственный
университет» о том, что «студент подлежит отчислению из Санкт-Петербургского
университета за представление курсовой или выпускной квали фикационной работы,
выполненной другим лицом (лицами)».
(Подпись студента)
25.05.2016
(Дата)
2
STATEMENT ABOUT THE INDEPENDENT CHARACTER
OF THE MASTER THESIS
I, Vera Mikhnevich, (second) year master student, program «Management», state
that my master thesis on the topic « Healthcare Information System Selection Model for
Medical Clinics », which is presented to the Master Office to be submitted to the Official
Defense Committee, for the public defense, does not contain any elements of plagiarism.
All direct borrowings from printed and electronic sources, as well as from master
theses, PhD and doctorate theses which were defended earlier, have appropriate references.
I am aware that according to paragraph 9.7.1. of Guidelines for instruction in major
curriculum programs of higher and secondary professional education at St. Petersburg
University «А master thesis must be completed by each of the degree candidates
individually under the supervision of his or her advisor», and according to paragraph 51 of
Charter of the Federal State Institution of Higher Professional Education Saint-Petersburg
State University «a student can be expelled from St. Petersburg University for submitting
of the course or graduation qualification work developed by other person (persons)».
(Student's signature)
25.05.2016
(Date)
3
АННОТАЦИЯ
Автор:
Вера Михневич
Название магистерской
Модель выбора медицинских информационный систем
диссертации:
в медицинских учреждениях
Факультет:
Высшая Школа Менеджмента
Направление подготовки:
Менеджмент
Год:
2016
Научный руководитель:
Гаврилова Татьяна Альбертовна
Описание цели, задач и
Целью данного исследования является разработка
основных результатов
модели выбора медицинской информационной системы
в медицинских учреждениях. Данное исследование
основано на сравнительном анализе 50
информационных систем (30 Российских и 20
зарубежных) и 6 интервью с экспертами из СанктПетербургских медицинских учреждений, которые уже
имеют опыт в использовании подобных
информационных систем. В ходе исследования было
выделено 13 характеристик медицинских
информационных систем: 5 ключевых и 7
дополнительных. Данные характеристики были
использованы при создании модели выбора
информационной системы. Чтобы сократить алгоритм и
избежать дублирования ветвей дерева решения были
использованы переменные. Вопросы в разработанной
модели просты для понимания обычного сотрудника
медицинских учреждений и не требуют специальных
знаний в области информационных технологий.
Ключевые слова:
здравоохранение, информационные системы,
медицинские информационные системы, модель
выбора, модель выбора информационной системы
4
ABSTRACT
Author:
Vera Mikhnevich
Title of thesis:
Healthcare Information System Selection Model for Medical
Clinics
Faculty:
Graduate School of Management (St.-P. State University)
Major subject:
Management (MIM)
Year:
2016
Academic Advisor’s name:
Professor Tatiana A. Gavrilova
Description of the goal,
The issue of selecting an appropriate healthcare information
tasks and main results
system is a very essential one. If implemented healthcare
information system doesn’t fit particular healthcare
institution; it wastes its resources and its efficiency
decreases. The purpose of this research is to develop a
healthcare information system selection model to assist the
decision-making process of choosing healthcare information
system. Appropriate healthcare information system helps
healthcare institutions to become more effective and
efficient and keep up with the times. The research is based
on comparison analysis of 50 healthcare information
systems and 6 interviews with experts from St-Petersburg
healthcare institutions that already have experience in
healthcare information system utilization. 13 characteristics
of healthcare information systems: 5 key and 7 additional
features are identified and considered in the selection model
development. Variables are used in the selection model in
order to narrow the decision algorithm and to avoid
duplication of brunches. The questions in the healthcare
information systems selection model are designed to be
easy-to-understand for common a decision-maker in
healthcare institution without permanent establishment.
Keywords:
healthcare, information system, healthcare information
system, medical information system, selection model,
information system selection model, decision algorithm
5
List of Content
Introduction ............................................................................................................................7
Chapter 1. Healthcare information system - theoretical review .............................................9
1.1
Healthcare information system and its importance: state of the art ........................9
1.1.1 What is healthcare information system .................................................................9
1.1.2
Importance of Healthcare Information System implementation ....................16
1.2 Modern peculiarities of Healthcare information systems: state of the art .................21
1.2.1 Mobile-Commerce in healthcare .........................................................................21
1.2.2 Big Data in healthcare .........................................................................................25
1.2.3 Cloud computing in healthcare ...........................................................................30
1.3 Research gap ..............................................................................................................36
1.4 Summary of Chapter 1 ...............................................................................................39
Chapter 2. Methodology of healthcare information system selection..................................41
2.1
Modern Methods of Business Research ................................................................41
2.2 Comparison analysis of healthcare information systems ...........................................43
2.3 Analysis of the interviews with experts from healthcare institutions ........................59
2.4 Summary of chapter 2 ................................................................................................70
Chapter 3. Development of healthcare information system selection model for medical
clinics ...................................................................................................................................71
3.1 Healthcare information system selection model ........................................................71
3.2
Managerial implications of main findings.............................................................85
3.3
Summary of chapter 3 ...........................................................................................87
Limitations and validation ...................................................................................................88
Discussion ............................................................................................................................89
Conclusion ...........................................................................................................................92
List of references ..................................................................................................................94
Appendix 1. Healthcare Information System Selection Model .........................................102
6
Introduction
Health is rooted to everyday life of every person all over the world; no doubt it is
one of the most essential parts of peoples’ lives.
IT technologies nowadays are deeply rooted not only in people’s everyday life, but
in almost all areas of business; and healthcare industry is not an exception. There are
several segments in healthcare: scientific, which is responsible for inventions of new
methodologies, equipment and medicines, and administrative which is performed by public
and private healthcare institutions. Both of these segments are important, though only the
latter will be considered in this paper. Information technologies appeared in healthcare
institutions in 1960s with first electronic applications and the industry is moving forward
very fast, especially recent years.
Currently, IT solutions become more and more advanced and seem to bring lots of
benefits. Healthcare institutions all over the world started implementing modern
technologies; such systems are called healthcare information systems. Many researches
and studies concerning healthcare information systems were conducted to explore the
benefits of IT solutions implementation and the implementation process itself. However
there is still a big issue – how companies should choose healthcare information systems
that would fit their needs? There is a gap in studying the preliminary stage of healthcare
information systems implementation – selection of appropriate system.
A plenty of healthcare institutions implement healthcare information systems to
increase efficiency and automate some processes and this innovation becomes more and
more popular. However there are so many different kinds of systems with different
functionality that managers, who are supposed to choose the system become confused as
they don’t know which system would fit the healthcare institution the best.
In Russia this issue becomes a hot topic as the healthcare industry develops and
healthcare information systems gain popularity. Technologies entered both governmental
and private sectors of the industry. To be more efficient and competitive clinics start to
implement healthcare information systems, so the issue of healthcare information systems
selection becomes very essential. In case information system doesn’t fit particular
healthcare institution, for example there are unnecessary functions; healthcare institution
7
wastes its resources and the efficiency decreases. Therefore, it is necessary to select an
appropriate healthcare information system to get all the potential benefits.
The purpose of this research is to develop a healthcare information system selection
model to assist the decision-making process of choosing healthcare information system.
The research is based on comparison analysis of several healthcare information systems
and expert opinion of several healthcare institutions that already have experience in
healthcare information system utilization.
The research questions of this study are as following:
1. What are healthcare information systems characteristics that affect the selection
process?
2. How healthcare institutions select healthcare information systems?
3. How to select an appropriate healthcare information system?
The first chapter it focused at defining and describing what healthcare information
system is and for what purpose it is needed. Then different modern peculiarities of
healthcare information systems are distinguished and described.
The second chapter is aimed at collecting and analyzing data for creating a
healthcare information systems selection model.
50 different healthcare information
systems are reviewed and compared. Based on the comparison the main features of
healthcare information systems are identified and described. Then interview questionnaire
for experienced in information systems usage healthcare institutions is created. The
purpose of the interview with experts is to identify how particular healthcare institutions
selected their healthcare information systems, what factors they were guided by and if their
opinion about the selection criteria has changed.
In the third chapter healthcare information system selection model for healthcare
institutions is developed based on the healthcare information systems comparison analysis
and on the results of the interviews. The selection model is aimed at helping healthcare
institutions to choose an appropriate healthcare information system according to their
needs.
8
Chapter 1. Healthcare information system - theoretical review
1.1 Healthcare information system and its importance: state of the art
1.1.1 What is healthcare information system
Healthcare is a very essential industry that relates to most, if not all of us. This
industry is one of the largest and fast growing sectors in the world. Moreover, healthcare is
one of the world’s most critical industries [Bernard, 2013]. It is a heavily human-oriented
and knowledge-intensive, healthcare processes and their management have a direct impact
on healthcare service quality and related costs, and the reputation of the healthcare
institution [Quaglini, 2010]. Healthcare is known as an industry where cutting edge
technologies and modern scientific breakthroughs are used to cure diseases more
effectively and to be able to reveal the most dangerous for peoples’ lives diseases at very
early stages. Nevertheless, generally healthcare industry is enormously slow in
implementing emergent technologies for improving administrative needs and management
practices [Wickramasinghe, Mills, 2001]. Despite this fact new technologies enter the
industry and become more and more popular.
There are many different challenges in the healthcare industry and it is generally
recognized that the prime solution to them is introduction and usage of information
technologies and systems in healthcare [Stegwee and Spil, 2001, 1–10]. Healthcare
management challenges and the possible solutions to them are described and discussed in
the next part.
There are different opinions on what is a healthcare information system; some
researches assume such system to be an information portal for end-customers, while others
consider healthcare information system to be an integrated solution for healthcare
institutions. Therefore, it is necessary to consider definitions of healthcare information
system proposed by different researchers to determine the one which will be used in this
study.
According to World Healthcare Organization (WHO) healthcare information
system is a system that integrates data collection, processing, reporting, and use of the
information necessary for improving health service effectiveness and efficiency through
better management at all levels of health services. 1
1
World Health Organization (1993)
9
Some researches name such systems Hospital Information System and give them
the following definitions. Healthcare information system is a set of computer systems and
telecommunications equipment, which is designed to manage all hospital information,
medical and administrative matters [Mersini, Sakkopoulos, Tsakalidis, 2013]. It is a
comprehensive system supported by computers and designed to deal with different kinds of
information in hospitals. Mersini, Sakkopoulos and Tsakalidis (2013) identified three key
issues on which such systems are focused. Firstly, healthcare information systems help
medical employees to be more effective and efficient. Secondly, such systems help to
increase the healthcare services’ quality. Finally, information systems in healthcare
institutions are used to manage costs.
According to other researchers healthcare information system combines
communication and information technologies. Such systems include a wide range of
functions from electronic patients’ medical records and prescriptions to new services
aimed at reducing data errors and queuing and waiting time [Matysiewicz, Smyczek,
2009].
In business terms healthcare information system is a knowledge-based, decision
support aid that provides immediate assistance, guidance and feedback.
The main goal of a healthcare information system is to enable healthcare
institutions to provide better medical care and to assist managing costs. Also there are
several secondary objectives associated with healthcare provision itself. These targets are
improvement of intercommunications among medical employees, reduction of waiting
time, and supporting the decision making during medical care. From the point of managing
costs the goal of healthcare information systems is to decrease personnel expenses, medical
assistance time and administrative burdens and to improve management of healthcare
institution resources.
In this study healthcare information system is a computer-assisted system that deals
with different kinds of information from medical records to internal documents that aims at
providing high quality medical care and managing costs of the healthcare institution.
The process of healthcare information systems development and their functionality
is reviewed for better understanding of the issue what such information systems are and
how they operate.
10
First healthcare information systems appeared in 1960s and their main function in
those times was to enter patient care requests in computer systems of healthcare institution
[Saba, Johnson, Simpson, 1994]. In 1971 World Health Organization developed 8 main
criteria every healthcare information system should meet:
1. Ability to identify persons positively by name and place – name, date of birth, race,
gender and postal code should be recorded to identify patient.
2. Avoiding unnecessary data agglomeration – no useless data, no doubling of data,
one medical record for one patient.
3. Problem or trend orientation – ability to research by diagnosis related group – a
scheme of classifying patients in a way that the type of patient treated by the
healthcare institution relates to the carried costs [Averill et al, 2003].
4. Goal orientation to assist monitoring evaluation.
5. Functional and operational terms employment – the system should be able to
generate standardized reports with standard terms and standard codes.
6. Records of data that refers to population groups, services, resources and outcomes
of medical care – all the recorded data should be categorized for facilitating the
data input and search.
7. Brief, unambiguous and imaginative information expression – ease of use of input
and output.
8. Feedback and appropriate sharing of data – interdepartmental collaboration and
Internet capability.
Listed healthcare information systems criteria are rather disputable; they are not
precisely described and partly overlapping. Firstly, it is not clear what data is considered to
be useless, there is no criterion of useful for healthcare institution information. Also if all
the data should be categorized and the input points are standardized how the recorded
information can be useless? Then it is hard to imagine how medical records can be
imaginative as it stated in requirement 7. Moreover nothing is said about the ability to
connect with other systems which is essential, too, as it would facilitate information
exchange with other institutions.
The requirements to healthcare information systems were far from ideal, thus in
2008 World Health Organization reworked the list and identified a set of 4 primary
functions that enable healthcare information system to maintain and improve the efficiency
of health care.
11
1. data generation – the data collection process by which input information reaches a
database
2. data compilation – the ability to categories data and to drill it
3. data analysis and synthesis – the ability to create reports
4. communication and use – the ability to exchange information within the system
All these functions are needed for healthcare information systems to be able to
work properly: collect, process, store, report and share data. Also 7 additional functions
that allow healthcare information systems to be a tool facilitating the process of making
decisions and affect the efficiency and effectiveness of the organization were determined:
1. alert and early warning capability
2. supporting patient and health facility management
3. enabling planning
4. supporting and stimulating research
5. permitting health situation and trends analysis
6. supporting global reporting
7. underpinning communication of health challenges to diverse users [World Health
Organization, 2008].
This list was supposed to complement the primary functions; however there are
some overlaps between the lists. Both primary and additional healthcare information
system functions point out the ability of creating reports named “data analysis and
synthesis” and “supporting global reporting” respectively. Also “underpinning
communication of health challenges to diverse users” meaning the ability to communicate
with other professionals to solve the problem is similar to primary communication
function. Another questionable point is “supporting and stimulating research” function, it
is incomprehensible how this function can be performed.
Wager, Lee, & Glaser (2009) in their research proposed a list of healthcare
information systems functions, too. From the researchers point of view every healthcare
information system should perform the following functions: e-health records and
prescriptions, computer assisted sorting and entry of suppliers’ orders. However several
essential functions like information exchange or cost planning were not included in the list,
so the necessary functionality of healthcare information systems was not fully identified.
12
In this study the list of necessary healthcare information system functions combines
the proposals of the World Health Organization and Wager el at (2009). As a result the
following list of healthcare information systems functions was created.
1. Electronic health records (including data generation and data compilation)
A healthcare information system should have standardized input form to record only useful
information about the patient, this form can be developed by the healthcare institution itself
according to its activities, for example the range of services – the number of medical fields
covered (surgery, stomatology, cardiology, etc.) It will facilitate the process of imputing
the data a lot. HIS also should be able to triage data into different categories and
subcategories and derive only issued. It is very essential that no data should be doubled;
only one medical record should be created for one patient.
2. Enabling planning
This function is needed for better management of healthcare institution’s costs. The system
should contain information about equipment, inventories and costs from operations to
provide a base for administrative decision making.
3. Data analysis and synthesis
HIS should create standardized reports with standard terms and standard codes that are
brief and clear. With the help of this function the outputs of the system would be easy to
get and understand. Reports should be created for all information stored at the system
related both to patients and the clinic itself (costs, etc.). Also this function includes alert
and early warning capability, which means that the system checks the results of the
medical tests comparing them to “normal” for healthy person values and to the historical
values and highlights mismatching or significant changes. Warning capability should refer
to management of costs, too, if the actual data doesn’t match the plan the system should
report it to the responsible person.
4. Communication and data exchange
All the data collected and stored in the system including reports should be available for all
physicians in the system as many medical fields are interconnected. Also physicians should
have an ability to share data and collaborate with each other to solve complicated and
questionable issues. As a result healthcare institution will identify diseases earlier and
provide higher quality treatment.
13
The range of healthcare information system users is quite broad; the system can be
utilized by administrative staff, medical professionals, nurses and technical specialists of a
healthcare institution. Also government institutions, insurance companies, customers and
other members of healthcare industry can be users of healthcare information systems; it
depends on the particular solution.
Classifications of healthcare information systems
Nowadays there is a great range of healthcare information systems and different
researchers have their own classifications of such systems. The point is that these
classifications are really different and sometimes it is rather difficult to understand how
they related to each other.
For instance, only Chen (2006) has 4 different categorizations of healthcare
information systems. Firstly, he divides information systems by functional areas and
identifies four main types of them: administrative, financial, clinical and research. Similar
classification of healthcare information systems was proposed by Stone (2014), who
suggested dividing information systems into 3 groups: clinical, administrative, and
management support. However, Stone highlights that to get full benefits of such systems
usage these groups should be used together. Currently, mentioned functions are integrated
in the majority of modern healthcare information systems.
The second classification of healthcare information systems suggested by Chen
(2009) divides information systems into groups by the “extent of structure that they impose
on working practice”: providing access to information, information tools and enforcement
of rules meaning automatization process.
The third classification proposed by Chen (2006) suggests splitting healthcare
information systems according to their span across the healthcare institution, so the
information systems can be individual, work group, organizational and outside
organization. However, according to the researcher’s explanation healthcare information
systems mostly refer to organizational ones as they are used by employees in the whole
organization.
The last categorization proposed by Chen (2006) refers to the purpose of the
healthcare information system. This classification divides information systems to
14
transaction processing systems, management information systems, decision support
systems and office automation systems.
Generally, according to the list of functions healthcare information systems are
supposed to have [World Health Organization, Wager el at, 2009] Chen’s classification is
not suitable for this study because it considers different parts of healthcare information
systems as different systems. Nowadays healthcare information systems are modular in
nature and combine different functions and as a result have several purposes. Therefore,
none of classifications proposed by Chen (2009) is going to be used in this study, moreover
as healthcare information systems become more complex these classifications are no
longer seem to be viable.
Jones et al (2014) suggested their own classification of healthcare information
systems. The researchers consider that the information systems can be split into 3 groups:
electronic medical records, electronic health records and personal health records. These
groups differ by the width of usage, where e-medical records include records only from a
particular medical professional, e-health records – records from all patients’ clinicians and
personal health records differ from the previous type by the patient’s ability to access and
manage it.
This classification is more suitable for single-function healthcare information
systems that are focused on managing patients’ data. However, this study is mainly
focused on multi-function healthcare information systems, which are more spread on the
market.
All in all there are different characteristics by which healthcare information systems
can be divided into groups, however, these classifications can hardly be used together as
there is no connection among groups from different classification.
Thus healthcare
information systems with particular function, for instance, can refer to different purposes
or span differently across the organization. It makes it even more difficult to understand
the variety of existing information systems. This leads to a “zoo” problem, which is very
typical one for IT-systems selection. This problem refers to the difficulty of choosing one
information system from a great variety on the market [Gavrilova, 2003]. As there were
more than 650 different healthcare information systems in Russian market in 2012
according to official statistics [Gusev, 2012] is seems that the “zoo” problem in this sphere
is a topical one.
15
1.1.2 Importance of Healthcare Information System implementation
Healthcare information systems implementation gains popularity nowadays as it
helps to overcome challenges of the healthcare management mentioned in the previous
part. To prove the importance of healthcare information systems usage the main benefits
and opportunities of such systems implementation are considered in this part.
There are different opinions about benefits that such systems bring and the
beneficiaries who enjoy them. The majority of researches suppose that the range of both
advantages and those who enjoy them are quite broad. However there is another point of
view. For instance, Shin-Yuan Hung et al (2014) in their study mentioned that some
researchers believe that the only beneficiaries from the healthcare information systems
adoption are healthcare institution’s investors who enjoy increases in profits because of
declined operational costs and customers who get higher quality services faster. Medical
care personnel in turn perceive HIS adoption as additional workload and face lots of
obstacles mainly in the context of up-and-running healthcare information systems.
The opposite opinion supported by the majority of the researches is that healthcare
information systems can help overcome many challenges the healthcare management faces
nowadays. There are several opinions about the most significant challenges in healthcare.
According to Goldberg and Wickramasinghe (2002) the main challenge for healthcare
industry in general is cost effectiveness and cost efficiency of provision healthcare services
of high quality. It is essential for medical care providers to control and manage costs and
raise productivity without affecting the quality, despite the fact that healthcare consumers
are rather not sensitive to the cost of medical services.
Wickramasinghe and Mills (2001) consider that the key challenges of management
in healthcare industry nowadays are costs that increase exponentially, customer who
became much more empowered and informed and focus shifted from curing itself to the
diseases prevention [Wickramasinghe, 2002]. Healthcare spending increase can be
explained by several changes in today’s world. Life expectancies lengthen and the standard
of living advances; such situation creates more opportunities to get medical care of high
quality. Moreover technological progress creates new opportunities for treating diseases
and providing healthcare services [Demirkan, 2013].
16
According to Nambiar and Sethi (2013) one of the biggest challenges in healthcare
management is financial one – healthcare spending need to be optimized while the quality
of care should be improved. This issue is really essential for different stakeholders from
customers and healthcare providers to government agencies [Nambiar, Sethi, 2013].
According the Institute of Medicine report, approximately $750 billion which is about 30%
of healthcare spending in US are spend in vain as this money don’t contribute to healthcare
outcomes advancement. This fact confirms the problem of mismanagement in healthcare
industry.
There are some more key challenges in healthcare industry highlighted by Nambiar
and Sethi (2013). These challenges include rising costs of medical assistance, increasing of
number of patients, aging of population and shortage of healthcare workers.
The real challenge in healthcare management nowadays is how to find, collect,
analyze and manage information to make people's lives healthier and easier, by
contributing not only to understand new diseases and therapies but also to predict
outcomes at earlier stages and make real-time decisions [Asri et al, 2015].
Gibbons, Arzt et al (2007) believe that one of the big issues in healthcare industry is
interoperability of information among different healthcare institutions. This creates two
more problems: "problems in communication among healthcare departments" and
"problems in communication with different organizations", which can be solved by using a
proper healthcare information system [Gibbons et al, 2007].
Caldeira et al (2011) support the idea that healthcare information systems usage
brings a lot of benefits. The researchers identified 54 benefits that the healthcare
organization including personnel and patients can get from investing in HIS
implementation. The main outcomes are costs reduction or financial results improvement,
raising satisfaction of patients and improvement of working conditions in healthcare
institutions. Also Caldeira et al created a classification of the benefits that consists of 8
groups according to the sphere benefited. The list of benefits groups with the most notable
examples is provided below.
1. Greater precision in diagnosis and clinical prescription
a. Faster and better justified clinical decision making
b. Reduction in radiation levels received by patient
2. Reduction in costs for tests and clinical analyses
17
a. Reduction in the number of inventory for tests ordered
b. Reduction in number of analyses ordered (no doubling)
3. Greater systematicity in information for management purposes
a. Computation of the real cost per patient treated;
b. Real time processing and emission of invoices in Emergency Room.
4. Reduction in personnel costs (in different departments of the institution)
5. Reduction in costs for facilities, equipment and material supplies
a. Reduction in paper and office supplies consumption
b. Elimination of the use of printed/photocopied forms
c. Elimination of paper based exchange
6. Improved patient service
a. Reduction in patient waiting time for various operations
b. Increase in confidentiality and security of personal and health data in
clinical files
7. Improved working conditions for professional health workers
a. Elimination of difficulties in reading handwriting in different orders
b. Reduction in administrative work
c. Improvement in quality of consultations among physicians
8. Increase in activity–outpatient appointments
a. Coping with the rise in outpatient appointments
Ammenwerth et al (2000) and Versel (2002) made a suggestion that the main
benefit of healthcare IT solutions is the increased access to clinical information; all other
benefits follow it. In 2006 Anderson added one more key benefit from electronic system
implementation – facilitating communications with external medical databases. It gives
physicians an opportunity to collaborate with their colleagues from other institutions and
reduce diagnosis and treatment inaccuracy. Also the workload of the healthcare personnel
is reduced in case of new patients come from another healthcare institution, if all medical
records can be shared there is no need to double it. It gives benefits for the patients, too, as
they don’t have to spend their time for doubling procedures and get more accurate
healthcare.
Altowaijri, Mehmood and Williams (2010) state in their article that there is a huge
number of factors that confirms the need of Information and communications technology
(ICT) based healthcare. The main drivers which justify the necessity of such shift in
healthcare industry are system inefficiencies, rising healthcare costs, a large number of
18
medical errors, increased demand for access to high-quality medical care, great variations
in quality of care, ageing population and more transparency of government spending,
including healthcare ones. The researchers admit that unfortunately there are some social
reasons like sensitivity, privacy and trust and lack of efficient business models which do
not allow using the full potential of ICT [Altowaijri, Mehmood and Williams, 2010].
Daniel Walsh et al (2005) propose that as a result of healthcare information systems
adoption the level of flexibility and portability in workflow of healthcare institution
increases significantly; institutions become able to update healthcare records immediately
and respond more quickly and with more appropriate actions.
Healthcare information systems can provide a prompt way to access and process
huge volumes of patients’ information, help to avoid paper wasting and save storage space.
Also such information systems bring an essential benefit of solving the issue of human
errors [Bamiah, 2012].
Another healthcare information system utilizing benefit is the speed of processing
information. Different medical activities, for example, drug monitoring and maintenance,
laboratory tests, patient medical records exchange among medical providers generate a lot
of information that need a huge number of people or just a system to be processed. Also
the information system is active and accessible at any time; this feature solves the problem
of on time transmission of correct data, which is one of key success factors for offering
high-quality medical services.
Matysiewicz and Smyczek (2009) mention such benefits of healthcare information
system as increased access to data and resources of healthcare institution, enabling
customers to make informed decisions and increasing level of their satisfaction by
improving quality of care and arranging internal organizational processes and transactions.
Shahin, Moudani, Chakik and Khalil (2014) stated that healthcare information
systems can be also used to decline the chance of misdiagnosis and eliminate irrelevant
treatment using systematic analysis of electronic healthcare records [Kraft, Desouza,
Androwich, 2003], consequently, the patients’ safety improves and the cost/time expenses
reduce.
There is a large number of benefits that implementation of healthcare information
system brings to the healthcare institutions and different stakeholders like medical
19
employees, patients, etc. The quality of medical services increase, the amount of human
errors and misdiagnosis decrease, the costs and recourses are managed in a more effective
and efficient way; and this is not the end of the list of healthcare information systems usage
advantages. Therefore, it becomes obvious why such systems implementation becomes
more and more popular nowadays in different healthcare institutions all over the world.
20
1.2 Modern peculiarities of Healthcare information systems: state of the
art
There is a huge number of different healthcare information systems in the world;
however there are several specific points connected to all of them. These things are mainly
connected to newly, compared to the healthcare information systems foundation,
developed technologies. Mobile-commerce (M-commerce), Big data and Cloud computing
issues are the most significant ones as they bring more benefits and open more
opportunities to healthcare information systems utilization. In this part these modern
technologies are described and discussed from the point of their operation, benefits and
challenges with reference to the healthcare industry. It is necessary to consider this
information to distinguish how modern technologies influence the industry and how they
are related to healthcare information systems and the issue of their selection.
1.2.1 Mobile-Commerce in healthcare
M-commerce is a term founded in 1997 by Kevin Duffey which means delivery of
electronic commerce capabilities directly to the customer, anywhere and anytime, through
wireless technology. In healthcare industry M-commerce is technology that exchanges or
transmits medical information using mobile devices. Mobile technologies have already
become an integral part of people everyday life and now they are spreading to other
industries and healthcare is not an exception. Mobile applications for healthcare as
healthcare information systems are designed to increase quality of healthcare services,
decrease costs and improve research and teaching. It worth mentioning that such
applications can be a part of a healthcare information system and make it even more
effective and efficient as it would become more accessible. Mobile technologies in
healthcare are gaining popularity as deal with different medical issues and patients’ groups
and also can be used by a great number of people [Klug et al, 2010; Karan et al, 2012;
Boulos et al, 2011].
Goldberg and Wickramasinghe (2002) listed the requirements to m-commerce in
healthcare. There are 3 main parties that are directly relevant to the healthcare institution
and m-commerce in healthcare: customer, producer and management. According to these
participants the requirements are divided into 3 groups. The application should satisfy all
the requirements from each perspective.
21
1. Customer
From the consumer point of view there are 3 main requirements to m-commerce in
healthcare: flexibility, value-adding and mobile technology basis. Requirement of
flexibility implies the need to be accessible anytime, anywhere and anyhow. M-application
should add value to the consumer though improving productivity, personalization and
adaptability to localization. The latter requirement refers to enhancing the quality of life
with the help of innovative and distinguishing characteristics of mobile technology.
2. Producer
From the producers’ point of view there are also 3 requirements to m-commerce in
healthcare: modularity, layers and bundling.
According to the first specification m-
applications in healthcare should be built from several separate parts (modules) that can be
recombined in order to adapt the product or service to a particular context. Such
requirement is needed to provide flexibility of the application. Layers requirement refers to
building the application in layers to make it possible to add attributes and characteristics.
This makes the healthcare m-commerce adaptable to such things as customer
personalization, localization, brand profiles, and privacy. This requirement is connected to
the value-adding one from the customer perspective. The last element of the producer
perspective is bundling which means combining modular products and services to get more
out of using the mobile technology basis.
3. Management
There are 3 vital requirements from the management point of view: 1) value/cost ratio, 2)
primary activities [Porter, 1985] and 3) business model. The firs requirement refers to
showing a good value in terms of application cost against similar solutions. The
development of revenue model and pricing strategy is based on value/cost ratio. The
second element means the presence of unique, innovative features opposed to similar
products and services in terms of primary activities of the firm (logistics, production,
marketing, services). The last requirement assumes the use of innovative and
distinguishing characteristics of mobile technologies in healthcare to encourage new
business models.
Goldberg and Wickramasinghe (2002) found that m-commerce in healthcare can
help healthcare institution to succeed in 4 critical management activities: improving patient
care, increasing quality of services, reducing costs and enhancing teaching and research.
The usage of wireless and mobile technologies can help to reduce costs through reducing
IT infrastructure costs and achieving rapid healthcare delivery improvements. There are 6
22
essential points connected to improving patient care and healthcare quality, some of them
were considered by other researchers:
•
safety in healthcare – the patient shouldn’t be injured during medical care;
•
effectiveness – services based on scientific knowledge should be provided
only to those, who need them, under and overuse are not allowed;
•
patient-centering – care should be provided with respect to personal needs,
desires and values of the patient;
•
timeliness – waiting time and sometimes harmful delays should be reduced
for both patients and personnel;
•
efficiency – avoiding time and resources waste;
•
equitability – the quality of medical care should be independent from
individual characteristics of the patient.
Kuiper (2008) considered two (1st and 5th) points in his study. He considered
“safety in healthcare” as reduction of medication errors and misdiagnosis, which can be
realized with the help of mobile technologies as they provide immediate access to data and
eliminate reliance only on memory. The researcher states reduction of healthcare costs for
“efficiency” from the Goldberg’s and Wickramasinghe’s (2002) list, which implies saving
different kinds of resources including time and money.
One of the benefits distinguished in Buck’s et al (2005) study is similar to the point
of “patient-centering”. Buck et al considers that mobile technologies help medical
professionals to concentrate on building relationships with their patients instead of paying
attention only to documentation during the appointment. Thus portable technologies help
not only to increase the level of medical care as the medical employee delves more into the
patient’s problem, but also increases customer satisfaction as he feels more important.
Another benefit of mobile technologies usage was proposed by Cleland et al
(2007). The researchers consider that one of the most essential advantages of mobile
technologies is communication issue – medical professionals can communicate with their
colleagues without face-to-face consultation, save a lot of time and get immediate
response.
Mersini, Sakkopoulos and Tsakalidis (2013) studied a specific issue that refers to
m-commerce in healthcare – QR codes. Quick Response code (QR code) is a matrix, twodimensional barcode that has square shape and contains coded information [Santos-Pereira
et al, 2012]. To get access to the information such codes should be scanned and decoded
23
with special quick response software. This software doesn’t require any special equipment
as it is available on every smartphone that has touch-screen and camera, some phones have
scanners built in camera and don’t require even special application.
The researchers found that managing QR codes through information system,
significantly improves interoperability inside healthcare institution and its divisions. In the
study the authors propose to use QR codes for easy access and managing the patient’s
medical information. Also Mersini et al (2013) proposes to use SQLite in healthcare
practices. SQLite 2 is an embedded SQL database engine without a separate server process,
which reads and writes directly to ordinary disk files. This helps to avoid doubling and
makes managing information much easier. The proposed mobile solutions can not only
save time, but also they improve planning in laboratories through timely updates, so they
can schedule their tasks more effectively. Time management improvements refer not only
laboratories but also the health personnel reducing the office work. As a result medical
personnel have more time for patients and provide patients with more comprehensive
treatment.
Overall, utilization of such mobile applications as QR codes and SQLite improves
the work of the whole medical unit, provides an opportunity to join up different healthcare
facilities and шimprove the performance of healthcare information system to which the
mobile application is embodied.
There are also some challenges connected with the usage of mobile technologies.
Ding, Iijima and Ho (2004) identified two main challenges of mobile commerce usage –
usability and technical. The former refers to less convenience of portable devices usage
compared to personal computers – they have smaller screens and keyboards, also the
number of messages and browsing of information is rather limited. The latter relates to the
rather low computer power of mobile devices, small amount of memory and shortage of
bandwidth and data transfer capacity. The technical challenge was also mentioned by
Schwiderski-Grosche and Knospe (2002) in addition to two other issues. Firstly, portable
devices are usually subjects to theft and destruction as they are rather fragile, so they are
considered as non-durable access devices. Another challenge of mobile devises proposed
by Schwiderski-Grosche and Knospe (2002) is security threat and the level of safety
usually depends on a particular mobile application. However, not all of them provide all
necessary security mechanisms.
2
Android SQLite: http://www.sqlite.org
24
Generally mobile technologies are used in healthcare industry to increase the level of
flexibility of medical professionals as it enables them to access data from anywhere
anytime. Also it gives medical employees more opportunities for communication and
consequently it increases the overall quality of medical care and the level of patients’
satisfaction.
1.2.2 Big Data in healthcare
The next specific point about healthcare information systems is connected to the
recent changes in healthcare sector. The amount of information in the healthcare industry is
growing beyond the processing capacity of the healthcare organizations very fast. 26
billion mobile devices were estimated to be functional by 2020 and generate the amount of
traffic large enough to place it in the category of big data [Middleton, Kjeldsen and Tully,
2013]. At the same time there is a plenty of other sources of medical information like
medical professional, equipment and so on. Therefore, the volume of information in
healthcare industry is increasing significantly and the issue of Big Data usage becomes a
topical one. The McKinsey Global Institute estimates a $100 billion increase in profits
annually, if Big data strategies are leveraged to the fullest potential [Groves, Kayyali,
Knott, Kuiken, 2013].
The term “big data” refers to the agglomeration of large and complex data sets that
are beyond traditional data management systems’ the capabilities to store, manage, and
process it in a timely and economical manner [Patil and Seshadri, 2014].
Several studies [Asri et al, 2015; Mathew, Pillai, 2015; Marr, 2015] consider 5 specific
features of Big Data that can be applicable to different industries, including healthcare:
volume, variety, velocity, veracity and value.
1. Volume
As it was already mentioned medical data grows dramatically; health care systems use
terabytes and petabytes of different information. Digitized medical data is coming in from
both internal and external sources, it comes from portable devices, wearable sensors and
monitoring devices [Jiang et al, 2014; Salih, Salih, Abraham, 2014], electronic patients’
records and clinical notes, medical equipment, etc. Mathew and Pillai (2015) identified 6
main sources of different types of healthcare data: providers – medical data; payers –
applications and data on expenditures; researchers – academic studies; customers and
marketers – consumer behavior and feedback data; government – population and public
health data and developers – R&D in new medical devices and pharmaceutics. According
25
to KPMG report [Galloro, 2008], the volume of healthcare data reached 150 exabytes in
2013, and it is increasing at a prominent rate of 1, 2 – 2, 4 exabytes a year.
2. Variety
Medical information is generated by at least 6 different sources [Mathew, Pillai, 2015] and
is quite complex. This data can be divided into 3 groups by the arrangement: structured,
semi-structured and unstructured. Structured one, like clinical data, is easy to manipulate,
store and analyze by machine. However, the majority of medical data: office medical
records, doctor notes, paper prescriptions, images, and radiograph films is unstructured or
semi-structured. Such types of data are more complicated to process and analyze. One of
the most challenging aspects in healthcare connected to Big data is that traditional data is
combined with new forms of data. And it is impossible to avoid this mixture as the latter is
necessary to get the best medical solution for a specific patient.
3. Velocity
Big data analytics needs the real-time data processing, while the data is continuously
generated in large volumes.
4. Veracity
Healthcare data can be of different quality, pertinence and meaning, while for achieving
effective results in data analytics the high quality data is needed.
5. Value
The data should be valuable otherwise it is useless. The value of data depends on quality of
governance strategy and mechanism.
To get the benefits the healthcare Big data should be properly processed and
analyzed. Big data analytic tools are used for this purpose. Nambiar and Sethi (2013)
believe that Big Data analytics can revolutionize the whole healthcare industry. The
authors mention that analytical tools can improve operational efficiencies and the quality
of clinical trials monitoring, enhance forecasting and epidemics responses planning and
optimize expenditures at all levels of healthcare industry from end-customers to healthcare
institutions and government. Moreover, analytical tools improve searching necessary
information during the care provision and make medical practices safer, faster, more
efficient and cost effective [Nambiar, Sethi, 2013]. According to Bernard (2013) the top
priority of Big data usage in healthcare industry is enhancing effectiveness of medical
treatment, especially chronic diseases’ and reducing the number of readmissions. Another
26
significant benefit of healthcare Big data analytics is that it allows to capture insights from
data gathered from sources indicated by Institute of Medicine (IOM) as critical gaps:
researches, clinical care and operational settings. Healthcare can also be improved by
evidence-based learning model powered by Big data analytical tools [IMS Institute, 2012].
Nambiar and Sethi (2013) suppose that Big data analytics can help to move from mass
medicine to more personalized care using patient specific data like genomics by profiling
of similar patients and their responses. Mathew and Pillai (2015) and Patil and Seshadri
(2014) believe that healthcare sector should focus on prediction and prevention activities to
improve the outcomes of medical care and it can be reached by using Big data analytics.
Patil and Seshadri (2014) suppose that the analysis of medical information can enable a
shift from reactive to proactive healthcare which will definitely improve the quality and
decrease the costs of medical care.
Researchers distinguish 3 types of Big data analytics: Predictive, Descriptive and
Prescriptive analytics [Houser et al, 2012; Chen, Mao, Liu, 2014]. The first type –
Predictive Analytics is used to predict the future through different statistical approaches. It
searches through the large patient data sets and processes this data to forecast individual
patient outcomes. Descriptive Analytics uses the past and current medical data to identify
trends; also it is used to improve the quality of healthcare decisions. Prescriptive analytics
refers to predictive type of analytics and is used to facilitate decision making process by
prescribing necessary actions. This type of Big data analytics is commonly used in
evidence based medicine in order to increase the quality of medical care and to improve
business practices.
Asri, Mousannif, Moatassime and Noel (2015) defined 3 main aspects where Big data
analytics can be useful in healthcare.
1. Patients
Big data analytics can help patients make the right decision timely. As a result the
analytical tool provides patient with “proactive care” recommendations or informs if there
is a need of change in the lifestyle to avoid health condition degradation. Also the patients
get the opportunity to share their private information in order to help other people and
become more social-responsible and may be save some one life. This aspect was also
studied by Sheriff et al (2015) and included in “pathways” right living and right care.
Rudin at al (2014) and Mathew and Pillai (2015) explored this aspect, too, and named it
“clinical decision support”. However, this issue refers to predicting outcomes and offering
alternative treatments, which is connected to “proactive care”. Also analysis of data from
27
personal wearable devices as a part of “personalized care” plays a large role in healthcare
as it enables to detect the disease at a very early stage even before the development of
visible symptoms [Mathew, Pillai, 2015].
2. Researchers and Developers (R&D)
Big data analytics can be used to improve researches about new diseases and therapies.
Google, for instance, has applied algorithms of data mining and machine learning to detect
influenza epidemics through search queries [Ghani et al, 2014; Lazer et al, 2014]. This
issue was also mentioned by Sheriff et al (2015) in right innovation “pathway” and by
Mathew and Pillai (2015) in their research.
3. Healthcare providers
Big data analytics can help healthcare institutions to recognize high risk population and act
appropriately (i.e. propose preventive acts). Sheriff et al (2015) reviewed similar issue
named right provider and considering the issue of gaining more professionalism and
effectiveness and as a result select better treatment. According to W. Raghupathi and V.
Raghupathi (2014) Big data analytics can be also used in evidence based medicine by
using statistical and quantified data as evidence in stating diagnosis.
Another aspect in healthcare industry, where Big data analytics can be useful was
defined by Konasani et al (2012). Researchers suggested using different predictive models
to detect frauds at the point of transactions.
Apart from benefits Big data usage has some challenges and limitations in usage.
Mathew and Pillai (2015) in their research identified 8 Big Data challenges in healthcare
industry.
1. No standards for medical information
There is a really huge stream of medical data from different sources from different agents
and there is no common standard even for particular types of information. For example
receipts or patients records can differ in different institutions, so it is difficult to process
such semi- or unstructured medical data.
2. Heterogeneous sources of data
Medical data is spread across different departments of healthcare institutions where it is
created and collected. Such dispersion is a significant barrier for data integration,
especially taking into account the previous challenge.
28
3. Skilled resources
A particular set of knowledge and skills is required to use Big data solutions. As such
solutions are not so widespread in healthcare industry nowadays there is a shortage of such
specialists as data scientists and data analysts who have the needed competences.
4. Privacy and security
Privacy and security issue is very significant in healthcare industry as medical information
is private and shouldn’t be disclosed without owner permission. The challenge is that
traditional privacy and security measures don’t work with massive and streaming data sets
and there is a need to improve them according to the Big data requirements.
5. Infrastructure Issues
Some healthcare institutions have already implemented information systems and their
compatibility with new technologies is quite questionable. Therefore, integration of new
technologies like Big data analytics becomes rather complicated.
6. Insufficient real time processing
Despite the fact that Big data analytics can process huge amount of data it cannot do it
immediately because of such features of Big data as volume and variety. It means that time
delays can occur during the data processing, which can potentially lead to lower quality of
care, especially if the situation requires immediate actions and leaves no time for
processing.
7. Analysis of analytical results
To receive desired outcome in a form of useful valuable data the data should be interpreted
in a right way. The combination of several factors can be understood and interpreted
differently, so the analyst should get the proper clinical support.
8. Data Quality
To make decisions related to patients care the data should be reliable, so the quality of the
Big data analysis is very essential. The quality of the analysis outcome is often influences
by the input information, if it was low-quality data it is likely to get the result of the same
quality.
Asri, Mousannif, Moatassime, Noel (2015) highlighted 5 limitations of the Big data
usage that are similar to Mathew and Pillai (2015) limitations. Firstly, the utilization of Big
data can be complicated because the input data is heterogeneous – in different format from
different sources. Secondly, the quality of medical data which is usually unstructured,
29
improper, and non-standardized is a serious limitation of getting the proper result of the
analytics. Then Big data requires quite large investments not only in the technology
purchase itself, but in personnel, too, as the Big data usage requires specific set of
competences. It means that the healthcare institution needs not only a data analyst but also
some training for the medical personnel so they can work with the system, otherwise there
won’t be any data for analysis. The last limitation defined by the researchers is the great
variation and errors in the results which cannot be excluded unless the input data is of not
so high quality and heterogeneous.
Analyzing the main challenges and limitations of the Big data usage it can be seen
that the initial and one of the most significant problems is heterogeneity of the medical
data. In the research of Mathew and Pillai (2015) some viable solution of the problem is
proposed. Firstly, the authors follow Zhang, Sarcevic, and An (2013) path and suggest
implementing three-tier architecture, where client tier provides access to the system,
middle tier defines the rules and processing tier that deals with data itself. The processing
tier includes heterogeneous medical data collection from different sources and data
extraction from multiple sources, which is stored in NoSQL database. Middle tier converts
extracted healthcare data to standard format like XML or HL7 through reference
information model. Client tier realizes interpretation of data analysis, which should use
clinical support to drawn appropriate conclusions. The analysis of medical data is
performed by both middle and client tier.
Generally, Big data is used in healthcare industry as analytical tool that processed a
huge volumes of data generated by different sources like equipment, medical professionals,
laboratories and so on. Such tools are necessary to generalize information and identify
trends related to different issues from epidemics to internal usage of resources.
1.2.3 Cloud computing in healthcare
Another specific point of healthcare information systems is Cloud computing.
Cloud computing is an approach based on delivering software, infrastructure and the whole
computation platform as a service over the Internet by large data computing centers on
pay-as-you-go base [Gibbons et al, 2007].
Mell and Grance (2010) define cloud computing as "a model for enabling
convenient, on demand network access to a shared pool of configurable computing
resources that can be rapidly provisioned and released with minimal management effort or
30
service providers’ interaction". In other words cloud computing means storing information
in the Internet for a fee on third-party servers instead of having own on premises servers.
Liu and Park (2014) consider that nowadays at least 4% of medical data have
already been downloaded and stored online in clouds in 2014 and this number is expected
to grow to 20.5% in 2015.
According to Bamiah, Brohi, Chuprat, Berhad (2012) there are 5 main unique
features of cloud computing: on-demand self-service, ubiquitous network access, resource
pooling, rapid elasticity and pay-per-use pattern, which seem to be the main advantages of
such solutions. The last feature (pay-per-use) gives healthcare institutions an opportunity to
use the newest software, which results in significant decrease of operating costs because of
covering only the most important issues.
The researchers defined 4 main types of clouds depending on the extent of access to
it: private, public, community and hybrid. Private cloud has strong security features and
works within single organization. Public cloud can be used by industry group or the
society. Community cloud can be accesses by a several companies sharing the same
interest. Hybrid cloud is characterized by combination of two or more cloud types’
features. [Bamiah et al, 2012].
Chang, Chou and Ramakrishnan (2009) determined 4 key features that every cloud
computing solution should perform. The first attribute of cloud computing is information
sharing and privacy protection which intends the ability to access data in particular
boundaries. The second feature is service composition, coordination, and competition
which imply using information from different sources to provide complex and high-quality
medical care. The third trait of cloud solutions is safety, security and scalability which
means that the ecosystem of healthcare institution should be protected from external
attacks, while the individual organisms should be protected from unfair competitions and
practices. Also a sufficient amount of resources should be provided so that the ecosystem
can grow and be sustainable. The last attribute is self-governing and automated
management, which intends system complexity and the operational costs reduction.
From the technical perspective healthcare is aimed at providing reliable medical
information quickly, safely and efficiently. And cloud computing helps to achieve this goal
by providing data persistence, durability and security as well as high computational power
[Dawoud, Takouna, Meinel, 2010]. From the medical point of view easy access to e-health
31
records is a very essential point. Providing ability to access personal medical history much
easier and quicker comparing to general data centers cloud computing improves healthcare
services by speeding up treatment and avoiding complications [Feng, Chen, Liu, 2010; Hu,
Lu, Khan, Bai, 2012]. Hu, Lu, Khan and Bai (2012) compared traditional solutions of ehealth to cloud computing and defined a number of benefits of the latter. Cloud solutions
offer integrated platform for eHealth services (cloud healthcare information systems) and
provide large infrastructure, quick access, and efficient storage. As the most significant
issue in healthcare is efficient sharing of information cloud computing has a great
advantage in this sphere in contrast with traditional solutions. Cloud computing is believed
to be a new technology with good performance in storing and accessing information [Hu,
Lu, Khan, Bai, 2012].
Bamiah, Brohi, Chuprat, Berhad (2012) pointed out a significant issue in healthcare
industry – the process of converting traditional paper-based records to electronic format
was not efficient enough. Implementation costs of electronic patients’ records are rather
high, moreover it requires not only resources, but also integration and maintenance. Cloud
computing solves this problem as it reduces the complexity and costs referring to
ownership and maintenance; and provides the ability to share and manage EHRs and as a
result improves tracking patients and diseases. It allows healthcare institutions focus on
utmost importance activity – delivery of medical services rather than managing IT
infrastructure issues [Bamiah et al, 2012]. Another significant for healthcare industry
feature of cloud computing is providing data backups and recovery capabilities performed
by replicating information in several locations for higher level of availability and safety
[AI, 2012].
Laohakangvalvit and Achalakul (2014) identified 3 essential for healthcare industry
targets that can be achieved through cloud-based healthcare information systems utilizing.
Firstly, cloud solutions reduce the costs of processing and storing medical data amounts of
which are continuously increasing. Secondly, it provides an access and interoperability of
electronic patients’ records. Finally, cloud-based healthcare information systems reduce
time necessary for development of new applications. One of the brightest examples of such
solutions usage is the emergency cases. There are many critical situations when medical
data from previous healthcare institution is needed immediately. If necessary records are
not delivered timely, the accuracy of the diagnosis and treatment can be lower or it can
even lead to medical errors. In such cases cloud-based systems would help to avoid
unpleasant consequences [Laohakangvalvit, Achalakul, 2014].
32
Houlding (2011) supposes that cloud computing can be used in different fields of
healthcare, for example, it can improve emergency support by providing an immediate
access to results of laboratory tests. In public healthcare, for instance, using cloud
computing in healthcare information systems can improve information tracking for better
maintenance of diseases response, monitoring of adverse drug effects or even chemical or
biological attacks.
Cloud solutions have some challenges connected with its usage. One of the primary
issues is that cloud data storing requires constant connecting to the Internet as all the data
is located on remote servers provided by a third-party company [Aljabre, 2012; Miller,
2009]. The security issue of cloud storages is one of the most essential and the most
arguable issues concerning cloud solutions. Grossman (2009), Aljabre (2012) and Miller
(2009) consider this issue to be a drawback of cloud computing. The researchers suppose
that cloud storage is not safe, firstly, because the data is accessible for the third-parties (the
cloud server providers) and also it can be hacked and in this case the data can be accessed
by unauthorized people.
The second challenge of cloud solutions is that the usage is affected much by
technical characteristics of the equipment. Grossman (2009) considers the latency-related
and bandwidth-related issues, which means that there can be some delays in response of
the servers or slow speed of work because of not enough capacity of the internet
equipment. According to the researcher this issue refers to all remote applications that need
Internet connection. Miller (2009) and Aljabre (2012) also highlight the issue that cloud
solutions can be slow and have lags in responses, which is similar to the “latency-related”
issue of Grossman (2009). Also the researchers considered the problem of poor work in
case of low speed connection, which causes slow working, too, but has another reason.
Miller (2009) and Aljabre (2012) in their studies reviewed two more challenges of
using cloud solutions: limited features and unsafety in term of losing data. The researchers
believe that internet applications can be not “as full-featured as” the desktop-based ones.
Many web applications have a full range of functions, however not all of them, so it is
necessary to check the functionality before shifting to cloud solutions. The last issue is the
threat of losing data, which means that in case of cloud going down the user lose all the
data if there are no backups and according to Miller (2009) very few cloud storage users
make additional backups on physical carrier.
33
Generally, cloud computing in healthcare is used for storing different kinds of data
in the internet without using on premises servers. This type of data storing has its own
advantages and disadvantages and it is difficult to determine clearly if it worth using or
not. Therefore, this issue of healthcare information systems is going to be included in the
selection model.
All the mentioned newly developed technologies can be used in Healthcare
together. Combining different solutions increases the effectiveness and efficiency of the
medical care. Demirkan (2013) supposes that cloud healthcare information systems used
together with big data presented by electronic medical records and modern mobile
solutions like biosensors and wearable devices has a really great potential in delivering
sustainable, intelligent and automated medical services. Also this idea is supported by the
fact that different authors studied the particular technology in tandem with another one.
Big Data analytics is often reviewed in conjunction with mobile devices that produce huge
amount of data to be analyzed. For instance, Nambiar and Sethi (2013) believe that Big
Data is a very useful tool in enhancing the healthcare system when there are so many
sources of medical information, especially mobile ones. Bamiah, Brohi, Chuprat and
Berhad (2012) believe that cloud solutions can gather data from different sources and then
integrate and analyze it in real-time. This definition reminds Big data functions and it can
be assumed that cloud computing here is considered along with Big data technologies.
Cloud computing is also tightly connected to mobile technologies, too, as one of the
advantages of the cloud services is an opportunity to reach it anytime and anywhere which
assumes mobile devices usage.
Some challenges of the particular technologies were already mentioned. However
there are some challenging issues that are relevant to all healthcare information systems
regardless of what technologies are used. According to several researchers the major
problem of healthcare information systems utilization is a security and privacy issue.
According to a study of Ponemon Institute LLC (2012) more than 90% of healthcare
institutions had at least one security breach during the several past years. The study also
shows that healthcare institutions were attacked mostly by insiders rather than external
parties. Patil and Seshadri (2014) believe that, while healthcare institutions enjoy the
benefits of modern technologies like Big data and cloud computing, security and privacy
issues become the center of emerging threats and vulnerabilities. Therefore, real-time
security risks analysis is really necessary in prosperous healthcare industry [Demirkan,
2013]. Altowaijri, Mehmood, Williams (2010) and Nambiar and Sethi (2013) also defined
34
maintaining of patients’ medical information privacy and security to be one of the most
important areas for attention in healthcare sector.
From the point of view of Slonim, Callaghan, Daily, Leonard, Wheeler, Gollmar,
Young, (2007) and Chang, Chou and Ramakrishnan (2009) another critical challenge in
healthcare industry today is “deficient care linkage” (DCL). There is a need of better
communication among multiple specialists during treatment of a patient with comorbidity
compared to usually carried out. For this purpose standards-based infrastructure
(compatible healthcare information system) should be implemented, otherwise there
appears a challenge of common accessibility of information and data sources.
Demirkan (2013) in his research distinguished another critical point for healthcare
information systems – coordination challenge. This issue is connected not only to technical
compatibility of systems like the DCL challenge but also to the social aspect like common
language and system complexity.
Bamiah, Brohi, Chuprat and Berhad (2012) distinguished 5 main challenges for
healthcare information systems. Two of the challenges second and third were studied by
other researchers, too [Kuziemsky et al, 2011; Yang et al, 2012].
•
Heterogeneous healthcare computing infrastructure issue, which is similar to the
DCL one, where information can’t be accesses because of incompatibility of
information systems in different healthcare institutions.
•
Limited access to patient data during decision making process and ineffective
communication process among medical professionals. Kuziemsky et al (2011)
found that difficulties are caused by the fact that usually necessary information can
be accessed only from the place of care, which makes it less flexible. Moreover,
patients' care team members can be scattered in various institutions, which
decreases the effectiveness of communication a lot.
•
Current technologies are insufficient to deal with modern solutions in terms of
dynamicity, scaling and low cost. Not all information systems can handle huge
amounts of data, also some modern solutions are non-affordable in terms of costs
for small and medium healthcare institutions [Yang et al, 2012].
•
Healthcare institutions usually store information data on-premises and incur both
human and environmental threats.
•
Volume, velocity, and variety of medical information is continuously grows and it
leads to two main challenges for healthcare institutions: increased complexity and
IT costs.
35
1.3 Research gap
The research area of healthcare information systems combines such areas as
healthcare and information technologies in general. Nowadays, it includes such particular
areas of information technologies as Big data, Cloud computing and M-Commerce as they
are becoming an integral part of healthcare information systems.
There are different studies focused on several aspects of healthcare information
systems.
Different
researchers,
for
example,
Shin-Yuan
Hung
et
al
(2014),
Wickramasinghe (2002) and Caldeira et al (2011) studied the issue of healthcare
information systems’ importance and benefits that they bring to healthcare institutions and
different groups of stakeholders. The development of healthcare information systems is
also a quite studied area. Such authors as Wager, Lee, & Glaser (2009) studied the basic
functionality of such systems. Implementation and adoption phases are also studied well
and there are many researches that cover this topic. For example Saba et al (1994) and
Hung et al (2014) studied the issue of healthcare information systems adoption by nurses.
However, there is a limited number of researches focused at selection of healthcare
information systems, which is the initial stage of the information systems implementation.
Therefore, this issue is considered as a research gap. The identified research gap is
graphically presented on figure 1.
Figure 1. Research gap
36
The issue of selecting an appropriate healthcare information system is a very
essential one. If the organization pays little attention to selection of healthcare information
system and as a result the system doesn’t fit particular healthcare institution, for example
there are unnecessary functions; healthcare institution wastes its resources and the
efficiency decreases.
It was found that there is a plenty of different classifications of healthcare
information systems. It seems that it should be easier to select an information system if
they are classified. However, the situation is the other way round because there is no
unique
categorization
of
healthcare
information
systems.
Moreover
suggested
classifications are not connected to each other and consider different features of the
systems which makes the selection process even more complicated. Also some
classifications can’t be fully applied to modern healthcare information systems as they
consider particular features of modern systems, the majority of which are integrated and
modular, as different systems.
The great variety of different healthcare information systems and different
classifications of the systems create a kind of a “zoo problem”, which means the difficulty
to pick one option from the huge variety, especially when for a common user they seem
very similar. Selection process of healthcare information systems if quite complicated for
healthcare institutions because there are more than 650 systems and around 240 developers
on the market [Gusev, 2012] and all of them seem to be unique, so the decision-makers
become confused and can select not suitable information system.
Therefore, the purpose of this research is to develop a healthcare information
system selection model to assist the decision-making process of choosing healthcare
information system. The research is based on comparison analysis of several healthcare
information systems and expert opinion of several healthcare institutions that already have
experience in healthcare information system utilization.
The research questions of this study are as following:
1. What are healthcare information systems characteristics that affect the selection
process?
2. How healthcare institutions select healthcare information systems?
3. How to select an appropriate healthcare information system?
37
The result of this study is the development of a healthcare information systems
selection model that will help healthcare institutions without permanent establishment to
choose from a large number of healthcare information systems the one that suits the
institution the most. After answering the questions of the model healthcare institution
receives the list of recommended features of healthcare information systems basing on
which it should select the system.
38
1.4 Summary of Chapter 1
There are different opinions on what is a healthcare information system; some
researches assume such system to be an information portal for end-customers, while others
consider healthcare information system to be an integrated solution for healthcare
institutions. According to World Healthcare Organization healthcare information system is
a system that integrates data collection, processing, reporting, and use of the information
necessary for improving health service effectiveness and efficiency through better
management at all levels of health services. The main goal of a healthcare information
system is to assist delivery of high quality medical care and better cost management.
The main healthcare information systems benefits highlighted by different researchers
are:
•
increased access to clinical information
•
facilitating communications among medical professionals
•
quicker respond and more appropriate medical actions
•
reduced number of human errors
•
saving papers and storage space
•
high speed of processing information
There is a huge number of different healthcare information systems in the world;
however there are several specific points connected to all of them. M-commerce, Big data
and Cloud computing issues are the most significant ones as they bring more benefits and
open more opportunities to healthcare information systems utilization. These technologies
can be used in healthcare together. Combining different solutions increases the
effectiveness and efficiency of the medical care.
There are some challenging issues that are relevant to all healthcare information
systems regardless of what technologies are used. The major challenges of healthcare
information systems utilization are:
•
security and privacy issue;
•
“deficient care linkage” (DCL);
•
coordination challenge;
•
limited access to patient records during decision making process;
•
ineffective communication among medical professionals;
•
complexity and increased IT expenditures.
39
There is a plenty of healthcare information systems on Russian market and several
classifications of such systems, which can be hardly connected to each other and
generalized. Therefore, there is a great problem of choosing the appropriate healthcare
information system for a particular healthcare institution.
This research is focused at facilitating the decision-making process of choosing
healthcare information system. The result of this study is a healthcare information systems
selection model that will help healthcare institutions without permanent establishment to
choose from a large number of healthcare information systems the one that suits the
institution the most.
40
Chapter 2. Methodology of healthcare information system selection
2.1 Modern Methods of Business Research
Research methodology is a systematic path followed to solve a research problem
[Rajasekar et al, 2013]. Research methodology includes a range of research methods and
techniques used during the study to answer the research questions and the logic that lies
behind their choice [Kothari, 2004]. There is a great variety or research methods and
techniques that can be used during researches. Two research methods were used during this
study to answer the research questions: content analysis and interviews.
To answer the first research question (What are healthcare information systems
characteristics that affect the selection process?) content analysis of existing healthcare
information systems was conducted. This method is usually used for qualitative analysis
for identifying general information from the existing sources [Kothari, 2004]. Therefore,
content analysis is used in this study for distinguishing healthcare information systems
characteristics. 30 Russian and 20 foreign existing healthcare information systems were
studied through the company web-sites’ content and systems’ reviews if there were any. A
comparison table of 50 healthcare information systems was created based on the gathered
information.
To answer the second research question (How healthcare institutions select
healthcare information systems?) an interview method is used. This method is used to
collect relevant and reliable data [Kahn, Cannell, 1957]. According to Dochartaigh (2002)
data can be assessed by the reputation of the source, which means that data from wellknown source is more likely to be reliable. Several interviews with experts from wellknown healthcare institutions in St-Petersburg were conducted to identify the initial
selection criteria and if they have changed after getting some experience in using
healthcare information systems. Two types of questions were used during the interviews:
open-ended and multiple-choice questions. Open questions are designed to encourage a
respondent to characterize a situation or event in extensive manner [Torrington, 1991]. In
this study the aim of such questions was to identify the initial selection criteria of
healthcare information system and the reasons of choosing and ways of using particular
options of the system features. Multiple-choice (closed) questions are usually used to
confirm some facts or to gather some specific information [Folkestad, 2008]. In this
research such questions were used to identify the most frequently selection options of the
41
information systems features and the most significant selection criteria from experienced
users the point of view.
As the number of responses is less than 40 no computer-based analytical tools can
be used for analyzing the results, therefore, traditional method is used [Adams et al., 2007].
Cross-case analysis method is used in order to analyze the results of the interview because
it gives an opportunity to get deeper understanding of phenomenon and at the same time
generalize received information [Miles, Huberman, 1994]. This method of analyzing
results of interviews is commonly used for structured interviews with clearly defined
requirements to selecting respondents [Folkestad, 2008]. Interviews conducted during this
study have a clear structure as 27 questions were created in advance; also there were
several requirements to the respondents: the respondents’ healthcare institution should
have implemented healthcare information system and the respondent should have been
involved into decision-making process.
The detailed description of the utilized research methods is provided in the sections
2.2 (Comparison analysis of healthcare information systems) and 2.3 (Analysis of the
interviews with experts from healthcare institutions) below.
42
2.2 Comparison analysis of healthcare information systems
To create healthcare information system selection model it is necessary to
understand what is healthcare information system in reality is and how it works. For this
purpose content analysis of existing healthcare information systems was used. 50 different
healthcare information systems, 30 Russian and 20 foreign ones, were analyzed and then a
comparison table of reviewed healthcare information systems was created. Every
healthcare information system was studied through the company web-site and several
reviews if there were any. As a result the main characteristics of the systems were
identified: platform, deployment, features, portable device access, patient portal, big data
analytics, and training programs. A part of the comparison table is presented on figure 2.
Figure 2. Comparison table of existing healthcare information systems
Platform characteristic intends metafamilies of graphical interface–based operating
systems which are compatible with the particular healthcare information system. There are
3 most frequently used operating systems on which the analyzed systems run: Mac OS,
Microsoft Windows and Linux. Windows operating system is compatible with all reviewed
healthcare information systems. Also several healthcare information systems are
compatible with UNIX and OpenVMS operational systems. This issue is worth considering
for companies, which have not Windows operating system. For instance, if a company with
Mac OS purchases the software compatible with Windows as it requires the usage of
Microsoft Internet Explorer, it will face the problem with installation which can be solved
43
only though additional soft installation. This solution may be useless in some cases; also it
requires extra payments, firstly, for additional software and, secondly, for additional work.
Deployment characteristic implies the place where all data is located. There are two
options of deployment – cloud-based or on premises. Cloud based deployment suggests
locating data on third-party servers and requires only computers or other devices to access
the data. This type of deployment implies that the healthcare organization doesn’t have to
own any servers because they are rented from the software provider. On premises
deployment requires usage of client’s hardware including both servers and computers or
other devices for access. Also all the hardware is placed at client’s location. Information
stored in cloud can be accessed via the internet, while information stored on premises
servers can be accessed from computers via the local network or from other devices via
Wi-Fi network. Both options have its benefits and drawbacks and usually users don’t know
what they should choose. As cloud technology is a modern solution and it delivers new
exciting advantages, described in the previous part, the majority of users choose it even if
it is not needed.
So there is a need to identify when there is a need to choose cloud technology and
when on premises deployment is the best solution for an organization. One of the biggest
traps connected to this choice is comparing cloud and on premises options in only one
dimension – monthly subscription costs and the costs of new hardware / software
[Wlodarz, 2014]. However there are much more things to consider while choosing the
appropriate deployment option.
Heat Software company suggests a questionnaire which can help potential users to
choose cloud or on premises deployment. There are 8 key questions to consider before
choosing the deployment option, which help to determine the most suitable solution.
1. Do you focus on year 1 costs or a long-term total cost of ownership?
If the organization focuses on year 1 costs it should choose cloud service as the cost of on
premises option is 50-75% higher during this period. From the point of total cost of
ownership for organizations working more than 3 years it is preferably to use on premises
deployment. Also those, who prefer annual subscription model, should choose cloud
technologies, while those, who prefer perpetual license model, should choose on premises
deployment.
44
However, Wlodarz (2014) suggests another point of view – anyway total cost of
ownership of the hardware and software exceeds the sum of subscription fee. Usually the
life-cycle of hardware is 5 years of 24/7 usage [Garretson, 2010]. Wlodarz calculated and
compared a generic line of business app server on premises and the cloud one hosted up in
a large Azure virtual machine. The results of the calculation are presented on figure 3.
Figure 3. Cost of on premises and cloud deployment Derrick Wlodarz’s case
Source: Derrick Wlodarz, 2014
The graph on the figure 3 shows that the total cost of ownership several times
exceeds the subscription fee. The author reviewed a particular case, so the results of
another one can be different, so it was decided to look at a standard template seen as
common situation in this calculator. The calculation was made with the help of Total Cost
of Ownership Calculator on the web-resource of Software Advice Company, which is a
part of Gartner – the world's leading information technology research and advisory
company; so it was considered as reliable source. The standard template of such
calculations is presented on figure 4.
Figure 4. Cost of on premises and cloud deployment standard template
Source: Total Cost of Ownership Calculator, http://www.softwareadvice.com/tco/
45
It can be seen that in common case the sum of periodical subscription payment
reaches the total cost of ownership only in year 9, which is nearly twice exceeds the
hardware life-cycle. It means that in common case it is more beneficial for the organization
in terms of costs to use cloud technologies. Also it should be admitted that companies
shouldn’t ignore the average hardware life-cycle because stretching hardware lifespan is
followed by several risks: risk of unexpected failure during the work or migration to new
software, which can cause data loss; and more costly data migration fees because of
obsolescence of used technologies [Wlodarz, 2014].
2. What is the state of your IT resources?
If the company has its own IT specialist, who can manage and upgrade local network,
hardware and software Heat Software company recommends to use on premises
deployment as well as if the company already owns all or the major part of needed
equipment. In case the company has no local system administrator and no or obsolete
servers and no desire to replace them it should use cloud services. Also if there is no place
to locate the hardware it is better to move the data offsite and use cloud technologies.
3. Does your organization have experience with Cloud?
There is no sense for the company which currently uses cloud solutions even in another
field, is satisfied with it and already pays for cloud solution support to change the
deployment option. As well the company which uses applications and systems deployed on
premises and have no cloud solutions shouldn’t implement them. Also if the executive
team of organization does not trust cloud technology and see it as unreliable there is no
need to use it.
4. What is your history with Application upgrades?
If the company has a skilled IT professional with right skills and the upgrade process is
established on premises deployment of the system is preferred. When the company is
lacking in-house skills and experienced several upgrade failures it worth using cloud
services.
5. Rate your readiness for ‘out-of-the-box’?
According to Heat Software company method on premises deployment is preferred by the
companies, which have unique business processes and need a lot of customization. While
the cloud option is preferred by those which embrace standard applications for instance
because of bad experience with custom applications and have quite standardized business.
46
However, currently, in medical software market both cloud and on-premises based
solutions are highly customizable. In terms of technical features like data capacity cloud
services are usually more flexible as they provide almost unlimited space on their servers,
while in case of on-premises deployment the amount of space is limited by the user’s
capacity of servers. In terms of features and alignment with business processes cloud
systems cannot immediately be modified within existing modules to suit the customer
needs, which might adversely affect a customer’s competitive advantage [Belt, 2015].
Cloud providers don’t have the time and sometimes bandwidth to customize the services
for each client, so such service is usually charged additionally.
6. How are your users distributed?
Companies which have reliable Internet access and highly distributed user base are
suggested to use cloud based solutions. Organizations with low number of locations and
high quality servers are suggested to use on premises deployment.
Suggested by Heat Software company answers refer to organizations which already
have cloud or on premises system deployment. If the company already has high quality
servers it doesn’t need to choose the deployment option. Also the quality of hardware and
Internet access are not related at all to the distribution of users.
7. Are Capital Expense or Operating Expense budgets more favorable?
The company which prefers operating expenses, paying rather small periodical
subscription fees and have rather small financial impact per year should use cloud based
services. If the company prefers capital expenses, perpetual license and doesn’t mind to
face large financial impact in the first year it should deploy the solution on premises.
This question is similar to the first one and is based on the idea that the sum of
subscription payments reaches the total cost of hardware ownership after 3 years of usage.
According to Gartner member information the common situation differs from this
assumption by 3 times. It worth reformulate this question and ask potential users if they are
ready to invest quite a lot of money or it is more convenient for them to pay periodically.
The method of choosing the healthcare information system deployment suggested
by Heat Software company seems to be incomplete as it lacks several essential issues
related to cloud or on premises solutions issues. First of all the price of software and
hardware for on premises deployment and the subscription fee for cloud deployment are
not all needed payments connected with the utilization of both of them. For on premises
47
solutions public utility payments are usually forgotten to be included in total cost of
ownership. Commonly one server uses from 500 to 1200 watt 3. The average price of
electricity (kw/h) in USA is about $ 0,125 4, in Europe the average price is € 0,18 5 which is
about $ 0,2 (€1 = $1,0995), in Russia – ₱3 which is $0,04 ($1 = ₱73,8). A server 850 watt
average uses (850watt* 24hours*365 days)/1000 = 7446 kw per year. It means that an
average server usage costs $893,5 in US, $1489, 2 in Europe and $297,8 in Russia; these
costs should be included in total cost of ownership of each server. Such costs for
computers and other devices are not included because they do not differ in case of another
deployment option. Talking about cloud based solution there are some extra fees which
users usually don’t take into account choosing the deployment model. Cloud storage
providers offer unlimited inbound bandwidth, which means that their clients can upload
almost any amounts of information on the server. However, some of them limit free
outbound bandwidth, which means that the users can download from server only a
particular amount of data. If the user needs to download more data from server the provider
offers this service for an additional fee. For instance, Microsoft Azure provides users with
5GB of free outbound any additional outbound is charged extra $0.12 in average per GB 6.
So if the company uses 1TB/month it is charged additional $120 per month.
Another issue is uptime – the official rates of average uptime of cloud and on
premises solutions are similar [Wlodarz, 2014]. However, using cloud services the user
can’t control or even influence the uptime, while on premises deployment is the user
responsibility. Concerning this issue the choice of the deployment options is an issue of
trust to provider and desire to shift the responsibility.
The last issue affecting the choice of deployment option is time of implementation.
Cloud based solutions require around a month to implement which is much less than the
time of on premises ones implementation.
One of the most controversial issues concerning choosing the deployment option is
the security issue. There is no common opinion which option is safer. From the one hand
the security system is usually breached within a company’s own boarders, often by
employees [Ponemon Institute LLC, 2012; Perry, 2013]. Though from the other hand,
firstly, the company could be sharing space and services with its biggest competitors and
3
J.T. Barett, How Much Electricity Does a Computer Use Per Hour?
The U.S. Energy Information Administration (EIA), Short-Term Energy and Summer Fuels Outlook, 2016
5
Fondation EurActiv, Evan Lamos, Electricity prices in Europe, 2015
6
Microsoft Azure website: https://azure.microsoft.com/en-us/pricing/details/data-transfers/
4
48
lose some competitive advantages in case of breach. Also if the security system of the
server provided is breached all the data leaks, while internal breaches can be conducted for
getting some particular information. Also modern information systems have authentication
functions and it will be easier to detect the violator and perhaps prevent the data
transmission.
All in all there are 9 issues to consider while choosing the deployment model:
•
State of IT resources
•
Experience with cloud solutions
•
History with application upgrades
•
Need to customize
•
Users distribution
•
Readiness to invest
•
Total cost of ownership vs total cost of cloud service usage
•
Trust to provider and desire to shift the responsibility
•
Time of implementation
The majority of healthcare information systems on the market are multifunctional.
Only one of the fifty analyzed software solutions (2%) had only one function – electronic
medical record; other systems have a number of different functions.
About 75% of
reviewed healthcare information systems have 6 main functions:
•
electronic medical record
•
medical billing
•
patient scheduling
•
medical accounting
•
communications systems
•
image support.
Electronic medical record (EMR) function facilitates creating and storing
information about patients in a form of digital patient records. It assists in tracking
demographics, patient notes and history. This feature of the healthcare information system
is a primary one as it digitalizes personal information of patients and performs as the first
step to personalization of the medical care.
49
The second function is medical billing which manages the process of receiving the
payment for rendered by a healthcare institution services. This function supports working
with both individual patients using paid services and health insurance companies.
Medical billing includes such steps as coding, claim scrubbing, eligibility inquiry,
electronic claim submission, payment posting and reporting.
The next function is patient scheduling which facilitates the process of making
appointments of patients’ visits. Except for making appointments this function usually
includes reminders and automated control of visits execution.
Another essential function of healthcare information system is medical accounting.
It automates accounting procedures and assists in keeping track of purchases, payrolls and
accounts receivable, managing billing and prepare financial statements.
Communication function allows healthcare institution employees to contact each
other to discuss some issues or to get necessary information. Also this function supports
electronic document automation which improves communication and saves time by
removing the need to walk between the medical offices.
The last function image support allows to store and exchange images data like Xrays, CAT scans, MRIs etc. It assists in storage, searching, manipulating and distributing of
such information.
Besides specified functions there are several unique features provided by some of
the software solutions. All in all, there are 7 additional functions that can be used in
healthcare information systems:
•
biometric authentication
•
integration with governmental systems
•
SMS reminder
•
build-in reminder
•
3D reconstruction
•
allergy checks
•
handwriting and speech recognition
For example, Amulet healthcare information system offers biometric authentication
used for verification of medical professional identity for secure access to the electronic
system. This function improves the safety and security of the patients’ information and
50
helps to avoid internal security breaches which happen more frequently according to Third
Annual Benchmark Study on Patient Privacy and Data Security conducted by Ponemon
Institute LLC in 2013.
Medical software Medved proposes an ability of integration with governmental
information systems. It means that healthcare institutions using Medved are able to redirect
and receive data and documents to and from other governmental institutions.
3 healthcare information systems from the list ArchiMed, Infoclinic and Medexis
have such additional function as SMS reminder. This feature is an application for
independent arrangement of SMS-mailing which can compose SMS templates, schedule
mailing on a specific date and time and track delivery status of every sent SMS. With the
help of this functions healthcare institutions remind their clients of the date and time of the
appointment and decrease non-attendance rate.
DrCloudEMR has similar to SMS notification function – build-in reminder. This
reminder can be used both by medical workers and patients. Medical workers can fill in
their calendar and the system reminds about important dates, for instance the deadlines for
submitting the report. From the clients’ point of view this function is similar to the SMS
notifications; it reminds of the appointments on the patient portal.
Healthcare information system Jemys offers function of 3D reconstruction. From a
set of successive sections this function creates a three-dimensional array; sections of the
array are displayed on the screen and the section planes can be interactively changed. 3D
reconstruction allows not only creating volumetric objects, but also it provides an
opportunity to zoom, rotate, measure the distance and change light, color and transparency
of the object. This function is not new and unique in general as there is such software on
the market, however healthcare information systems usually don’t provide such functions.
MediTouch EHR has a build-in function of allergy checks. This function implies an
automatic check at the point of care of patient’s allergy list and an alert if the patient is
allergic to a medicine that is going to be prescribed. This function increases the efficiency
of care and decreases the time of care by removing the necessity to check this information
by hand.
Sevocity and PrognoCIS healthcare information systems have handwriting and
speech recognition function, which facilitates data entry as it allows inputting information
without using a keyboard. This function can be especially useful for aged medical workers,
51
who can be not so skilled in typing or have poor eyesight. Handwriting recognition can
also interpret intelligible written text from paper documents or photographs by optical
scanning, which makes work with paper-based document much easier and allows gradually
digitalizing all the documents in the healthcare institution.
The next identified characteristic of healthcare information systems is portable
device access. This feature allows medical personnel to reach the healthcare information
system not only from personal computers in the office, but from their tablets and mobile
phones, too. This ability gives medical professional an opportunity to be more flexible and
assist in many essential tasks. Usually healthcare information systems have a special
module in a form of specific mobile application to provide such access. This module can
be included in the basic configuration of healthcare information systems or sometimes it
can be purchased as an additional one depending on the system provider. In case of using
cloud deployment mobile devices connect to the information system through the Internet,
while in case of on premises deployment the access realized via the local network.
Portable devices can be used by medical professionals in 3 main ways: for
information and time management, for communication, which are similar to healthcare
information system functions, and for education. Using mobile devices during the
workflow improves such aspects as information and time management. Portable device
access gives medical personnel an opportunity to access and maintain health records on the
go outside the office, so there is no need to return back to the office to accomplish this job.
Though mobile devices users can reach two main types of information: professional
information: medical literature, podcasts and calculators, textbooks and guidelines or drug
references; and patient related information: electronic medical records, laboratory
information systems or picture archiving and communication systems. Information
searching is the most popular activity among mobile devices users, which occupies around
50% of “phone time” [Chase, 2013]. Also mobile application contains all information
about clinician’s appointments, so it helps him to be everywhere on-time.
Portable device access function also facilitates communication and consulting
process, especially with colleagues in different locations. It decreases the average waiting
for response time and increases the response rate as all the personnel is always available
through mobile application and can reply almost immediately. Using mobile devices can
also be used for communication with long-distance patients, who can send clinicians text
or pictures regarding problems or questions. This opportunity is connected rather to
52
general portable devices usage in healthcare institutions than to their compatibility with the
information system. However it worth noting because it plays a large role in the caring
process as it helps patients to be treated timely and avoid unpleasant consequences [Kiser,
2011]. Using mobile devices users obtain the following communication capabilities – voice
calling, video conferencing, e-mails, text and multimedia messaging. According to
Wallace, Clark and White (2012) study about 85% of medical personnel use portable
devices at least once a day for clinical purposes like information and time management or
communication with colleagues.
Mobile devices are used by medical professionals for education and training
purposes, too. Watching professional web videos is one of the most frequently performed
activity; 67% of medical personnel use laptops for this purpose, 29% – tablets and 13% –
smartphones [Chase, 2013]. Currently mobile devices have become a “learn anywhere”
resource for accessing information or double-checking knowledge [Payne, Wharrad, Watts,
2012; Wallace, Clark and White, 2012]. For education purpose clinicians usually use
already mentioned sources of professional information: textbooks, medical calculators,
drug references, etc.
Using portable devices during the workflow also helps to improve patient
management. High level of availability of medical records, lab tests and other needed
information and the communication function of the mobile solutions enable to make more
precise and appropriate diagnosis and prescriptions. This, in turn, makes the clinical
decision-making at the point of care more effective and efficient in terms of time and
accuracy [Mosa, Yoo, Sheets, 2012; Mickan et al, 2013].
In general portable devices access feature allows medical professionals to perform
some of the healthcare information systems functions like information and time
management and communication and consulting remotely. Furthermore using mobile
devices like phone and tablets gives clinicians and opportunity to educate and doublecheck their knowledge.
Another feature of some healthcare information systems is availability of a patient
portal. Patient portal is an online application for the healthcare institution clients used to
interact with the medical care provider via the Internet. Usually such portals are available
for patients 24/7. As portable device access function this one can be a part of the basic
configuration of healthcare information systems or can be purchased as additional module
depending on the system provider. Michelle Holmes, a principal with ECG Management
53
Consultants in Seattle, considers the average price of the patient portal to be about $30-$40
per provider per month in US. There are two main types of patient portals: one-way
communication ones, which enable patients to interact with the information system only
and two-ways communication portals, which allow patients to contact medical
professionals, including providers, care teams, and administrative staff [Terry, 2015].
Patients use secure user name and password to log in to their personal accounts on the
portal.
There are several features that are available for patients. Firstly, patient portal
enables users to schedule appointments and view and refill requests online. This function
facilitates choosing the proper date and time of the appointment, especially compared to
the phone call, because all the available appointments are listed on the screen. Also it
allows avoiding extra visits to the medical provider. This feature helps to reduce the
number of phone calls and queues in the healthcare institutions and increase efficiency of
administrative processes.
The next feature of the patient portal is ability to access personal medical records,
visit summaries and lab tests results. This function helps patients to keep abreast of the
latest news and visit the medical provider timely. However, it is important to take into
account self-treatment trend in some countries, for instance in Russia. Searching
information from the medical reports patients follow treatments, that can be inappropriate
and even worsen the situation, found in the Internet without visiting the medical adviser.
Self-treatment is frequently followed by incorrect self-diagnosis that can lead to unpleasant
and sometimes harmful effects like masking of a severe disease, incorrect choice of
therapy, dangerous drug interactions and delays in seeking medical advice when needed
[Ruiz, 2010].
That’s why some patient portals have another feature – patients’ education. The
primary goal of this feature is to increase the general medical education of the patients, so
they would take less reckless actions and care more about their health. Portals can be used
to send educational materials and preventive and chronic care alerts to patients to inform
them about the first signs and preventive measures of some diseases and so on. Patient
general medical education helps to reduce the number of self-treatments and helps patients
to understand the importance of timely professional visits.
Some patient portals also offer an opportunity to pay bills online through the
personal account or sometimes without logging in. This function is quite popular,
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especially among young users. Software Advice Company conducted a survey and
identified that the most popular patient portal features among aged customers and men are
scheduling meetings with clinicians and requests for refilling prescriptions. Young patients
and women at the same time use patient portal more frequently to get results of laboratory
tests and pay for medical services [Eastwood, 2014].
Another feature of patient portal is secure messaging. This function is available
only in two-way connection portals as it assumes direct contact to the medical
professionals. Using this function patient can ask their medical adviser different questions,
clarify prescriptions and as a result avoid extra visits. It facilitates the communication
process as patients can almost immediately ask the question online instead of going to the
healthcare institution or hanging on the telephone line waiting for a response. Moreover
it’s easier for medical personnel to answer to a message or e-mail on a patient portal than
to answer a phone call.
However, there is a challenge – how to attract patients to the portal and make them
use it. One of the main reasons of patients’ reluctance is connected with the alignment of
the portal’s work with the healthcare institution’s business processes and its usability.
According to Software Advice study 34% of the patients name "unresponsive staff" the top
frustration factor of the patient portal, the second one is "confusing interface" mentioned
by 33% of the respondents.
All in all there are 5 main functions provided by patient portal as a module of a
healthcare information system:
•
Scheduling appointments and managing requests
•
Access personal medical information
•
General medical education
•
Paying bills
•
Secure messaging
Functions 1-4 are available on both one- and two-ways communication portals,
while the last feature can be uses only on the latter ones. The number of available functions
is different on different patient portals and depends on the medical software provider.
The next characteristic of the healthcare information systems is availability of Big
data analytics. Big Data analytics in healthcare is usually used for curing diseases,
improving quality of life, avoiding preventable deaths and predicting epidemics [Marr,
55
2015]. This function is necessary for analysis of heterogeneous data and reports creation.
Big data analytics function processes huge amounts of data continuously generated by
different
kinds
of
medical
equipment,
for
instance
radiological
apparatus,
electrocardiographs or MRI machines. Therefore this function is necessary in healthcare
institutions that use different medical equipment to make the analysis more convenient.
The last identified characteristic is training programs availability. Training program
is needed for medical personnel, who are going to use the healthcare information system,
to get acquainted with the system, its interface and functions. This education is needed
teach future users how the system works to avoid problems and wasting time during the
workflow. Implementing the healthcare information system is aimed at increasing
effectiveness and efficiency of the healthcare institution, improving services and as a result
patients’ satisfaction, so medical personnel should be able to somehow use the system
when it is put into practice. In case medical professionals learn on the fly all the processes
will speed down and the level of patients’ disappointment will increase. The majority of
medical software providers consider training programs as an integral part of the
information systems, while the others deliver it as an additionally paid service. Usually
medical software providers have several special programs for different kind of personnel
(administrative, medical, IT, etc.) within the training course which lasts from 1-2 days to
more than a week. Also healthcare institutions are also provided with phone or online
consultations, which can be free or paid in most cases depending on the available hours
and the need of personal consultations.
For instance, SP.ARM company offers courses in 6 different fields regarding
different modules and functions of its healthcare information system qMS. The company
offers the following training programs:
•
Analytics HIS qMS – introductory courses on analytical tools of the information
system qMS. These courses are addressed to skilled IT-professionals and medical
statisticians. The goal of the courses is to teach users to solve problems in the
processing and analysis of data using analytical tools in qMS system. There are 2
courses in analytics: general course «Analytics in qMS" and "Analytical potential
qMS». The courses last 5 and 3 working days respectively.
•
Administration of healthcare information system qMS – the course is designed for
administrators, and employees participating in the implementation and maintenance
of the system in medical institutions. The course lasts 10 working days.
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•
Laboratory information system management – the course is intended for laboratory
professionals, medical assistants, laboratory technicians, and IT specialists who
carry out configuration of the system and consult end-users. The courses last 1
working week.
•
qMS Pharmacy – the course is held for specialists in the field of medicines and
medical products inventory control within the healthcare organization and lasts 4
working days.
•
Introduction to qWord-XML development – the course is designed for
professionals in working with databases. During the training, users learn how to
work in qWord-XML environment in such fields as development of graphical user
interface, output forms and mechanisms of interaction with databases. The course
lasts 3 working days.
•
Managing Caché database – the course is addressed to professionals who ensure the
functioning of Caché database in the contracting authority (usually system
administrators or database administrators). The course lasts 2-3 working days.
All in all the comparison analysis of 50 different healthcare information systems
revealed that there are X main characteristics of healthcare information systems with
several options for each. The characteristics of healthcare information systems are:
•
platform (operating system)
•
data storage deployment
•
portable device access
•
patient portal
•
features
•
Big data analytics
•
training programs
The functionality was divided into 2 main parts: common functionality, which is
almost the same for all reviewed healthcare information systems, and additional
functionality, which means some extra functions that might be unnecessary for some
healthcare institutions. All in all there are 13 different functions, 6 main and 7 additional,
that reviewed healthcare information system can offer to its users:
•
electronic medical record
•
medical billing
•
patient scheduling
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•
medical accounting
•
communications systems
•
image support
•
biometric authentication
•
integration with governmental systems
•
SMS reminder
•
build-in reminder
•
3D reconstruction
•
allergy checks
•
handwriting and speech recognition
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2.3 Analysis of the interviews with experts from healthcare institutions
Based on characteristics of healthcare information systems identified through
comparative analysis a list of 27 questions was created. It was designed only for healthcare
institutions that have already implemented and started to use healthcare information
system. The aim of the survey is to identify based on what criteria healthcare institutions
choose healthcare information systems in fact. It consists of 2 types of questions: openended and multiple choice questions. The questions are based on different characteristics
of healthcare information systems that can be used by healthcare institutions. Also there
are some questions aimed at identification of the reason of selection the particular function
or option. The survey questions and answer options are presented in the Table 1 below.
Table 1. The survey for healthcare institutions
1. What is the name of the healthcare
institution?
2. What healthcare information system do
you use?
3. How many employees utilize healthcare
information system?
Yes
4. Do you have an employee who supports No
the healthcare information system?
Healthcare information system provider
supports the system
5. Who selected the healthcare information
system?
6. What
factor
influenced
healthcare
information system selection the most?
59
Yes, trainings were included in the
information system purchase
7. Were there any specific trainings for Yes, trainings were additional to the
employees about how to use the information system purchase
information system?
Yes, trainings were conducted by our
employee
No, employees learned on fly
Windows
8. Which operating system is installed in Linux
your healthcare institution?
Mac OS
Other:
9. Do you use own servers for data Yes
storing?
No
10. Do you use cloud services for data Yes
storing?
No
11. Why did you choose data storage type
you use? (on premises / cloud)
Don’t use portable devices
Smartphones
12. Which portable devices your employees
use during the working process?
Tablets
Notebooks
Other:
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Yes,
application
from
healthcare
13. Do you use any special application for information system provider
mobile devices that provide access to the
information system?
Yes, application from third party provider
No
14. Are there any analytical functions in the
healthcare information system that you
use? How do you use these functions?
15. If there are no analytical functions in
your information system, would you like
to use them? How would you use them?
16. Do
you
have
special
electronic Yes
appointments function?
No
17. Do you have patient portal with personal Yes
account for patients?
No
Personal visit
18. How do patients often communicate Phone
with your medical institution?
Internet
Other:
Primary
Important
19. How important is the cost of a
healthcare information system for you?
Important enough
It does not matter
Generally it is not a selection criterion
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Recurring payments
20. What payment method for healthcare
information
system
is
more One-time payment
advantageous for you?
Other:
Yes, information system provider
21. Do you trust data protection to third
parties?
Yes, third party organization
No
22. What method of data protection is used
at your healthcare institution?
23. Is there user authentication in your Yes
healthcare information system?
No
24. Are there different access rights to the Yes
different categories of staff in your
No
information system?
25. Is there any category of employees that Yes:
can use information system without any
No
access restrictions? Which category?
26. Do you pay attention to the protection Yes
against internal security threats?
No
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Supported operating system
The type of data storage
Support for portable devices
27. Please mark all the factors that you
consider to be important when choosing Patient portal
a healthcare information system.
Analytical functions
Staff training
Other:
The sample of healthcare institutions that answered the survey consists of 6
different medical institutions from St.-Petersburg. The names of the healthcare institutions
are not disclosed by the wishes of the respondents, so in this study they are named
healthcare institutions A – F.
Healthcare institution A is a huge multidisciplinary clinic that was found in 1980s.
It has 5 big centers in St.-Petersburg and employs more than 1000 people who work in
more than 30 different medical directions. Healthcare institution A utilizes healthcare
information system qMS for about 5 years.
Healthcare institution B is a multidisciplinary clinic that was found in 2000s. It had
3 branch offices in St-Petersburg, however due to the significant expansion of activities
from 2012 it has one big clinic in the center of St-Petersburg. Healthcare institution B
works in about 20 different medical directions. This medical institution utilizes healthcare
information system Medialog for about 4 years.
Healthcare institution C is a multidisciplinary clinic that was found more than 200
years ago. It has 2 huge clinics in St-Petersburg with more than 200 medical professionals
employed. Healthcare institution C works in about 20 different medical directions. This
medical institution utilizes its own healthcare information system for about 3 years.
Healthcare institution D is a highly specialized clinic that was found in 2000s in StPetersburg. It is a network of 6 active rehabilitation clinics, 2 of them are located in
Moscow and 4 – in St-Petersburg mostly in the northern part of the city. Healthcare
institution D specializes in 2 main directions: neurology and orthopedics and several
63
related directions such as ultrasonography, massage, physiotherapy and some others.
Healthcare institution D employs about 130 medical specialists with 15 years of working
experience in average. This medical institution utilizes healthcare information system
Medialog for about 8 years.
Healthcare institution E is a multidisciplinary clinic that was found in 2000s. It has
13 centers in 10 cities including Moscow and St-Petersburg. Healthcare institution E
works in about 20 different medical directions. This medical institution utilizes healthcare
information system Infoclinic for about 5 years.
Healthcare institution F is a huge multidisciplinary clinic that was found in 2000s.
It has 13 medical centers in 8 districts of St.-Petersburg and employs about 700medical
professionals who work in more than 30 different medical directions. Healthcare institution
F utilizes healthcare information system Medialog for more than 10 years.
The answers for the survey from all healthcare institutions were analyzed. As a
result it was found that in most cases healthcare institutions gave similar answers. However
there are some differences among them, too.
6 interviewed healthcare institutions use 4 different healthcare information systems.
The most popular healthcare information system is Medialog used by 3 respondents (50%);
one institution utilizes healthcare information system designed specifically for it, 2 others
use qMS and Infoclinic healthcare information systems.
In majority of the interviewed healthcare institutions the number of employees
more or less differs from the number of healthcare information system users and
sometimes from the number of “working places” in the system. The number of healthcare
information system copies for offices in medical institution is meant by the number of
“working places”. However, the difference between these numbers is rather big. For
example, healthcare institution B answered that 25 medical professionals utilize the
system, but on the web-site of the system producer the number of “working places” for this
clinic is 10, which is much lower than the number of employees who use the system. Also
healthcare institution F has the same case of employing about 700 medical professionals
but using only 250 “working places” according to information of the system producer website. There can be 2 possible explanations of this situation. Firstly, it can be due to the fact
that several institutions’ B medical professionals use the same office, computer and
working place in the system according to their timetable. So there is no need for an
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individual copy in the system for every employee. Also the producer could indicate only
initial number of purchased copies and lose sight of others which were bought later. Also
in healthcare institution C the number of healthcare information system users is much
lower than the number of employees because the system is used mostly for getting
statistical information, not for medical care. In other healthcare institutions the number of
system users differs from the number of employees because usually nursing staff doesn’t
have personal “working places” and use the system much less compared to medical
professionals.
Talking about the support of healthcare information systems 5 respondents told that
the system producer is responsible for this issue and performs all the tunings and updates.
Healthcare institution B answered that it hasn’t its own employee to be responsible for this
issue, so it can be assumed that it uses the services the third-party company or specialist as
this option was not included in the question. The majority of medical institutions (A, C, E
and F) have IT-department or IT-specialist who help to maintain used hardware and
software and took part in healthcare information system selection; however as other
institutions they don’t perform the support activities on their own. So it can be concluded
that it is more convenient for them to use the external support and this issue is essential for
the system selection.
In the majority of healthcare institutions (4 of 6) healthcare information system was
selected by medical professional with the help of the IT specialists. Three of these medical
institutions (A, C and F) are quite large and have IT specialist among employees; another
one hired an IT-specialist before the information system was selected, so he took part in
the selection process, too. What is more healthcare institution C didn’t purchase readymade information system; it was designed specifically for it. In healthcare institutions B
and D the choice was made by chief accountant and administrative staff respectively.
Therefore, their choice was based on the references about the system and the list of
deployments.
It means that at present special IT knowledge seems to be needed to
understand all the peculiarities of the healthcare information systems to make the
deliberate choice. The choice of healthcare institutions that used IT-specialists help was
more perceived as IT-specialists know more in technical field and have special background
that helps them to understand technical issues better and faster. Also their choice was
based on several criteria like functionality, technical support in St-Petersburg, modularity,
software-base of the platform and domestic development. Nevertheless not all ITspecialists possess the necessary knowledge and can take into account all the necessary
65
criteria. As it can be seen from the results of the survey some essential issue were not
considered during the healthcare information system selection process. For example, such
criteria as type of the data deployment or special educational trainings provision were not
taken into account. Also despite the fact that the choice was based on the functionality in
the majority of the healthcare institutions that used IT-specialist help the question of how
the necessary functionality was identified remains open. There are 3 main paths concerning
the functionality of the healthcare information system: purchasing the system with the
largest number of different function, purchasing the system with minimum necessary
functions and purchasing the system with the optimal functions necessary for particular
healthcare institution. Taking into account the choice of the healthcare institutions A, E, F
it can be concluded that they chose the third path as the selected systems don’t have the
widest or the narrowest range of functions. The main threat of this path is choosing
functions that are not really needed, so there is a question how correctly the optimal list of
functions is identified. A particular function may seem very attractive, but it can be
unsuitable for a healthcare institution. For example, application for mobile devices access
can bring many benefits to the medical institution, however before considering this
function as necessary it worth thinking about the suitability. If there are many aged
medical professionals, there is no opportunity to provide medical practitioners with
compatible mobile devises or the mobile devices usage rate is low the advantage of this
function will be much lower than it seemed to be.
Judging by the results of the survey all the reviewed healthcare institutions have
some functions in the information system that they don’t use. For example, healthcare
institution A uses information system qMS that has special electronic appointments
function for its patients, however the majority of the patients communicate with it by
phone. 5 of 6 healthcare institutions have this function, but only 2 of them marked Internet
as one of the most frequent way to communicate with the medical institution. In healthcare
institution D, for instance, medical professionals use smartphones quite often, but there is
no mobile device access function in its healthcare information system. While healthcare
institution F has such function because employees use tables on the work place. What is
more only healthcare institution C has private accounts for patients, however as it was
already mentioned healthcare information system is used mostly for statistical reports than
for medical care. Moreover patients usually use phone and personal visits to communicate
with the institution, so it is unclear why this feature was included in the system. It means
that every function necessity should be considered carefully with respect to a particular
66
healthcare institution to identify the optimal list of necessary functions and range them as
some functions can be indispensable, while other just beneficial, whether it is a specifically
designed or purchased system. This issue is going to be solved by the healthcare
information system selection model that will be created as a result of this study. It will
facilitate the selection of the necessary functions, suitable healthcare information system
and help to avoid ineffective choice.
All respondents who purchased ready-made healthcare information systems
received educational trainings as an obligatory part of the system purchase. The majority of
ready-made healthcare information systems providers offer educational training on how to
use the information system for free as a part of the purchase of for a fee as an additional
service. So during the selection process it is important to consider if there is a need in such
trainings and if yes which option of educational training purchase is more convenient. For
example, if the majority of employees have already used similar system may be there is no
need in obligatory trainings for all the staff.
The majority (5 of 6) of the interviewed medical institutions use solely on premises
data storing. 3 of them do not trust external parties the security of patients’ information and
prefer to be independently responsible for data leak prevention that’s why they store data
on their own servers. Also healthcare institution D considers servers to be more secure than
cloud deployment, but it entrusts the security issue to the provider because of his
reputation and absence of its own IT specialist. Healthcare institution B supposes on
premises deployment to be the cheapest way of storing data despite the fact that it is not
true considering the total cost of ownership; however this is the opinion of the institution.
Also it entrusts the security issue to a third-party company. Healthcare institutions use
different methods of data protection like data encryption, firewalls, etc. All of them have
user authentication in the healthcare information systems to prevent external people access
to confidential data and personalize system usage. Also all interviewed medical institutions
have different access rights for the different categories of staff, so every employee uses
only necessary for him/her information. Also these two actions help to protect against
internal security threats, which are more frequent than external ones [Ponemon Institute
LLC, 2012; Perry, 2013]. Also personalized usage of the information system facilitates the
process of disturber identification. In 4 of 6 healthcare institutions there is only one group
of people which can use information system without any access restrictions – system
administrator. In healthcare institution C except system administrator the director has no
access restrictions in the information system. In healthcare institutions B there is no
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category of employees that can use information system without any access restrictions. As
it can be seen from the survey there is no unified way of providing data security, they are
similar but not identical, so there is a need for every healthcare institution to decide what
means it would utilize and what the optimal level of security is.
Every interviewed healthcare institution has a large flow of patients and,
accordingly, a large flow of new data. This data is in different formats: images, tables, text,
etc. Interviewed healthcare institutions use analytical tools in their information systems for
statistical reports of different levels and times, so it can be concluded that this function is a
necessary one, which is frequently used. For instance, getting analytical features was the
main purpose of implementing healthcare information system in healthcare institution C.
All the interviewed healthcare institutions, except institution C, considered the
information system cost issue as important, but not primary one. Considering the main
information system selection criteria mentioned by healthcare institutions the issue of how
the system works is much more important for the majority of them. Talking about the way
of payment half of the respondents mentioned the pay as you buy option which means the
gradual purchase of modules. Also 2 healthcare institutions prefer one-time payment. It is
interesting fact that healthcare institution B would prefer recurring payments, which are
typical for cloud deployment, however it stores data on own servers. This contradiction
shows that some healthcare institutions may not have clear vision of reasons for choosing
particular information system features.
The last question of the survey was aimed at identifying which factors are
considered to be important for selecting the information system after the healthcare
institutions got experience in this sphere. Only healthcare institution C almost didn’t
change its mind about the selection criteria. This can be explained by the fact that this
healthcare institution ordered a system specifically designed for them. Other interviewed
healthcare institutions purchased their healthcare information systems and based their
choices on what seemed to be the most important. After some time of usage the
information system and the interview they changed the opinion of what is essential to
consider. All the options of the last question were selected at least once; the most popular
ones are educational trainings, analytical functions and the deployment type, which were
not initially considered as selection criteria at all.
Generally, the respondents were divided into two groups according to the initial
parties involved in the selection process. The first group of respondents (healthcare
68
institutions A, C, E and F) selected healthcare information system with the help of IT
specialists and the initial selection criteria were functionality of the system, technical
support in St-Petersburg (domestic region) and domestic development, which means than
only Russian information systems were considered as alternatives. The second group of
healthcare institutions (B and D) selected their information systems without any IT support
and relied on the list of healthcare information system deployments and references.
However, after getting experience in utilizing healthcare information systems both
groups’ opinion about selection criteria of information system became more or less similar.
Supported operating system, type of data storage deployment, portable devices support,
patient portal, analytical functions and staff training were mentioned as “experienced”
healthcare information system selection criteria at least once.
69
2.4 Summary of chapter 2
In this study 2 methods of business research were used: comparison analysis and
expert opinion.
Firstly, 50 different healthcare information systems: 30 Russian information
systems and 20 foreign ones were reviewed, and then the comparison table was created. As
a result of healthcare information systems comparison analysis the main characteristics of
the systems were identified: platform, deployment, features, portable device access, patient
portal, big data analytics, and training programs. Then every identified characteristic was
described in terms of possible options to use and functionality.
Then based on the comparison analysis of healthcare information systems a
questionnaire for experts from St-Petersburg healthcare institutions experienced in
healthcare information systems utilization was created. The aim of the survey is to discover
the experts’ opinion on the healthcare information system selection criteria. 6 different
healthcare institutions participated in the survey. Firstly, healthcare institutions mentioned
different criteria of selecting healthcare information systems, which they used being
unexperienced in this issue. However, after several years of healthcare information systems
utilization interviewed healthcare institutions changed their initial opinion. Generally, all
the options identified through the healthcare information systems comparison analysis
were selected at least once. The most popular characteristics appeared to be educational
trainings, analytical functions and the deployment type, which were not initially considered
as selection criteria at all.
Finally, the results of the experts’ opinion analysis showed that all of the healthcare
information systems characteristics should be considered during the healthcare information
system selection model creation.
70
Chapter 3. Development of healthcare information system selection
model for medical clinics
3.1 Healthcare information system selection model
The healthcare information system selection model is aimed at facilitating the
process of selecting an information system for a healthcare institution without permanent
establishment. This model is going to help a decision maker to choose characteristics of
healthcare information system that are necessary for a particular healthcare institution. As
it was already mentioned it is rather difficult for a person without specific knowledge to
understand if a particular characteristic or function of the information system is really
needed or it only seems to be necessary. There are different peculiarities of using different
characteristics of the systems which will be included in the selection model to reveal
decision makers from the necessity deal with them. From the healthcare institution point of
view the selection model will look like a survey where after several easy-to-understand
questions it gets a list of necessary healthcare information system characteristics. From the
technical point of view the selection model is a decision-tree that includes the identified
characteristics of the healthcare information system and their options.
There are 13 identified characteristics of the healthcare information systems; every
characteristic has 2 or 3 options to choose from. The characteristics are: the operating
system, deployment, patient portal, portable device access, Big Data analytics, training
programs and 7 additional functions of healthcare information system: biometric
authentication, integration with government systems, SMS reminder, build-in reminder, 3D
reconstruction, allergy checks and handwriting and speech recognition. The first
characteristic has 6 different options to choose, the next two have 3 options, while other
presumes only 2 options presence or absence. All in all there would be approximately 55
000 different combinations (lists) of healthcare information system characteristics. A
decision tree with such a huge number of results can hardly be realized and presented, so
for the purpose of study additional functionality of the healthcare information systems will
be presented as a separate part. Also it was decided to use variables in the decision
algorithm to narrow the decision tree, so that branches do not repeat several times. The
result of the healthcare information system selection algorithm is a list of functions
recommended to a particular healthcare institution depending on the answers. Created
healthcare information system selection model is entirely presented in Appendix 1.
Different parts of the model are described in details and presented further in this chapter.
71
The first healthcare information system characteristic to consider is operating
system. There are 3 main options: Windows, Linux and Mac OS, but some organizations
have more than one operating system installed. There are 2 main options of having several
operating systems installed in a healthcare institution: having several operating systems
installed on one PC or different operating systems on different PCs. The main reason why
healthcare institutions can have several operating systems is that different operating
systems have its own uses and advantages. Having several operating systems allows
switching between them quickly and having the best tool for the job [Hoffman, 2014].
There is some software that works only on “old” operating systems and is not supported by
the modern ones, so there is a need to have an “older” version of operating system to use
such software. Also some programs work only on particular operating system, only on Mac
OS or only on Windows, so to use them on the same PC there is need to install both
operating systems. If healthcare institution has different operating systems on different PCs
information system can be installed on all PCs in case it is compatible with both operating
systems. If several operating systems are installed on the same PC there is a need to choose
the platform for healthcare information system installation. In choosing between operating
systems to install healthcare information system there are 2 main points. Firstly, the choice
can be made basing on the frequency of operating system usage. Healthcare information
system is going to be used in every-day working activities, so it is more convenient to
install it on the primary operating system which is usually used during the work. Also if
Windows is installed on the PC it can be chosen as a platform for information systems as
almost all of them are compatible with this operating system, therefore there will be more
options to choose from. This characteristic has 6 possible outcomes: Windows, Linux, Mac
OS, Windows & Linux, Windows & Mac OS and Linux & Mac OS. The part of the
healthcare information system selection model reflecting operating system characteristic is
presented on Figure 5.
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Figure 5. Healthcare information system selection model – operating system selection
The next healthcare information system feature to consider is deployment of data
storage. There are two main options of deployment from the point of view of data storing:
cloud and on premises, however the latter can be divided into 2 options considering the
provider services: on premises deployment with provider support and on premises
deployment without such service. Therefore there are 3 options of deployment that can be
chosen:
cloud deployment, on premises deployment with provider support and on
premises deployment without provider support. Firstly, it is needed to choose between two
main options; then in case of on premises deployment selection it is necessary to choose
the option related to the support services. In the previous part 9 issues to consider while
choosing the deployment model were defined by combining different researchers’ point of
view:
•
State of IT resources
•
Experience with cloud solutions
•
History with application upgrades
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•
Need to customize
•
Users distribution
•
Readiness to invest
•
Total cost of ownership vs total cost of cloud service usage
•
Trust to provider and desire to shift the responsibility
•
Time of implementation
To make a decision algorithm there is a need to use only cutoff factors which
enable to definitely choose which characteristic option should be selected. This
requirement excludes such questionable issues of deployment as need to customize and
total cost of ownership vs total cost of cloud service usage. Currently, in medical software
market both cloud and on premises deployment solutions are highly customizable and there
is no exact answer which is worth choosing in a particular case. Also total cost of
ownership vs total cost of cloud service usage is rather ambiguous issue as the decision if
the organization is ready to invest is influenced by many different factors like current state
of IT resources or trust to third parties. The remaining 7 issues are included in the selection
model. Also there are 2 issues that absolutely cut off one of the options. Firstly, cloud
based solutions require continuous and reliable Internet access and if there is no stable
Internet connection, there is no other way than selecting on premises deployment. Another
issue is an opposite one, on premises deployment requires a server room and if there is no
place for locating servers the only way is cloud deployment. In all other situations the
preferable deployment of the data storage depends on the decision maker choice.
First of all it is important to identify if the healthcare institution has servers that can
be used for data storage. Usually the life-cycle of such hardware as servers is 5 years of
24/7 usage [Garretson, 2010]. So it is essential that servers can be uses at least for a couple
of years. If servers are out of date it is essential to identify is the healthcare institution
going to replace them regardless the implementation of the healthcare information system.
The question about replacing servers in the near future arises if servers are 3 years old or
more.
The next point is the time of information system implementation. According to
information given of the healthcare information systems providers’ web-sites
implementation of the system on cloud-based solutions takes less time and equals
approximately to a month or less. Implementation of the information system on premises
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takes more time, respectively. Therefore, if the time limits are essential for the healthcare
organization cloud deployment would be more suitable without considering other factors.
Another important issue concerning the type of deployment is rather subjective and
argued; there is no common opinion which type of deployment is more secure. As both
types are safe enough this issue is more about trust to third parties and willing to be
personally responsible for security of data. The next point is the location of the healthcare
institution.
Several experts recommend using cloud data storage in case of dispersed locations
[Crump, 2008; Byrne, 2011; Pinkett, 2015]. So if there are several healthcare institution
centers located remotely from each other it is more convenient to use cloud solutions.
Generally, scattered locations can be connected and store data on premises, however it is
more complicated to organize such network and also it requires a good Internet connection,
too. It worth noting that if healthcare institution is located in one place it doesn’t mean that
it shouldn’t use cloud solutions.
Payment method is another issue that influences the choice of deployment type.
Some healthcare institutions prefer to make one-time payment for the healthcare
information system or modular payments, which suppose initial one-time payment for a
module and subsequent payments for additional modules if they are considered as
necessary. This type of payment is typical for on premises deployment as the software is
considered to be a product and requires purchasing a license to use a solution. Some
healthcare institutions prefer periodical payments for the information system. This type of
payments is typical for cloud data storage as the software is considered to be a service of
delivering application through the Internet and requires a subscription fee.
Experience of using cloud services plays a rather significant role in choosing the
deployment model. If an organization got positive experience of using cloud storage it is
more likely that it would like to continue using it. Negative experience of cloud based data
storing would prevent the organization from using such storage again with a high
probability [Wlodarz, 2014].
This is a natural reaction of a human being to avoid
something that turned to be bad.
The last point to consider is willing to try cloud data storing. It is connected with
the previous one, so those, who had negative experience of cloud solutions usage, are more
likely to avoid trying it again. While having good experience is likely to cause willing to
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use it again. However, the decision is highly subjective and is influenced by many factors
including tacit ones.
Some decision maker choices can contradict each other, in such case the decision
maker has to select the point that is more important for him. For example, healthcare
institution would like to implement the information system very quickly, but at the same
time it would like to be personally responsible for the data security. In this situation the
decision maker has to choose what is more important for him the time of implementation
or the security issue as these choices lead to different deployment models.
Talking about the options of on premises deployment, the choice depends on the
availability of internal human resources. If the healthcare institution has IT- specialist(s)
who are able to support the healthcare information system and the hardware it makes sense
to choose on premises deployment without support, especially taking into account the fact
that the majority of information system providers offer remote support in case of some
problems. Finally, there are 3 options of deployment that can be chosen:
cloud
deployment, on premises deployment with provider support and on premises deployment
without provider support. The part of the healthcare information system selection model
reflecting data storage deployment is presented in Appendix 1.
The next characteristic of healthcare information systems is portable devise access.
This feature allows medical personnel to reach the healthcare information system not only
from personal computers in the office, but from their tablets and mobile phones, too. The
main benefit of this function is providing a high level of flexibility for medical
professionals. It is very convenient to have an access to information at different locations
of the healthcare institution. However, unlike medical professional in hospitals, who needs
to move around medical chambers, medical professional in healthcare institutions without
permanent establishment have fixed personal offices and don’t need to move around the
institution on job purposes. So it seems that this benefit of portable devices access is a bit
overestimated as not all medical professionals need so much flexibility and the opportunity
of remote access as a result. Almost all medical professionals in most cases need different
tests results to diagnose and treat the patient. Medical tests, except of lab tests, are usually
presented in graphical format: MRIs, X-rays, ultra-sonographies, electrocardiograms,
gastroscopies, etc. To evaluate the results of medical examinations it is more convenient to
see them on a big high resolution screen to catch all the details. Portable devices like
tablets can also be used for assessing medical examinations results as they also can have
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rather big screen with high resolution. However, Evaluation of the tests results is not the
only duty that medical professionals do; there is also a need to fill in the medical records
and type prescriptions which is more convenient to do with a physical keyboard rather than
on the virtual one. According to some tests the typing speed is a bit higher on a physical
keyboard among experienced portable device users and almost twice higher among
average portable device users [McCracken, 2010; McKinlay, 2012; Shultz, 2014]. It can be
explained by the fact that the physical keyboard is more commonly and frequently used,
especially by adults; also physical keyboard buttons are fixed and have tactile feedback, so
there is less possibility to confuse adjacent buttons [McKinlay, 2012]. Also onscreen
typists use fewer fingers (usually two thumbs) than physical keyboard typists, who usually
use 6 fingers in average. Therefore personal computers are more beneficial and convenient
for medical professionals’ in healthcare institutions without permanent establishment every
day activities than portable devices. Also if there is a need to double check any information
it is more familiar to do it on PC and there is no need to use portable devices as it doesn’t
bring any benefits. Communication with colleagues can be realized through the
smartphone; however it doesn’t require special application or access to the information
system. The last issue to consider is nurses, who help medical professionals in healthcare
institutions without permanent establishment. Their common job is to write prescriptions
and make referrals to other medical professionals if it is necessary and make appointments.
This job can be done using portable devices, however patients can make their appointments
by themselves, especially taking into account the need of aligning the appointments to
personal timetable. Also it is irrational to provide several technological units to one office
as the nurse can use the PC in the office while the medical professional is talking to the
patient. Also usually medical professional dictate information to record to the nurse during
the examination; this also proves the absence of necessity in 2 technical devices. Finally,
despite the popularity of portable devices usage this feature is considered to be
unnecessary for healthcare institutions without permanent establishment as its main benefit
– flexibility is not used in such organizations. Therefore this characteristic was excluded
from the healthcare information system selection model.
Another characteristic of healthcare information system is availability of patient
portal. Patient portal allows patients online access to their health data and bring almost no
direct benefits to the healthcare institution. The main advantage of the patient portal is that
it adds value to the healthcare institution services [Reicher et al, 2015; Guercio, 2014;
Guerrero, 2015]. Also some patient portals consider themselves as value-added service
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[North Alabama Health Information Exchange]. Therefore, if healthcare institution wants
to add value to its patients it should include patient portal in the healthcare information
system. There are 2 different options of patient portal: one direction patient portal and two
direction patient portal. Two direction patient portals bring more value to patients as they
can communicate with the healthcare institutions and get initial consultations remotely.
Moreover, it can decrease the number of self-treatments as the patient can consult online
and exactly know if there is a need to visit the medical professional. From the healthcare
institution point of view two direction patient portal costs more, but at the same time it can
increase the rate of attendance because of self-treatment decrease. Also patients will be
more loyal and switching cost for them will become higher.
However, the medical
professional is not able to communicate with patients online during the working hours, so
there is a need to hire wide-profile medical consultant to reply the questions. Therefore,
both types of patient portals bring value to patients; two direction patient portals add more
value for customers, but cost more. It is difficult to precisely define which one is better as
both have its own advantages and disadvantages. So the decision maker should define
which option is more suitable for him and what is more preferable to save money or to
bring more value to patients and increase loyalty. The part of the healthcare information
system selection model reflecting patient portal feature is presented on Figure 6.
Healthcare information systems have such function as Big Data analytics. This
function is necessary for processing heterogeneous information of different formats and
creating report of different levels and time. Medical information is heterogeneous –
medical record of one patient can include such information formats as text, images, tables
and sometimes even videos. To process this data special analytical tools are necessary.
Therefore, if healthcare institution uses special medical equipment like radiological
apparatus, electrocardiographs or MRI machines it is necessary to include Big Data
Analytics module to the information system. Also this feature is needed if healthcare
institution is willing to get statistics and have an ability to drill it up and down. Getting
statistical reports can be used not only for keeping track of the KPIs, but for optimizing
business processes and making decisions, too. Big Data analytics is a good business
intelligence tool that helps in all activities of a healthcare institution from the medical care
to procurement and finance.
So if healthcare institution has special medical equipment,
wants to keep track of the statistics or is willing to optimize its work it should include Big
Data analytics module into its healthcare information system. Generally, there are two
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options: to implement Big Data analytics or not. The part of the healthcare information
system selection model reflecting Big Data analytics feature is presented on Figure 6.
Figure 6. Healthcare information system selection model – patient portal feature & Big
Data analytics
The last primary characteristic of healthcare information system is training
programs. The majority of healthcare information systems providers offer training
programs that can be included in the information system purchase or provided on the
provider web-site for free or can be purchased as additional service. Training programs are
absolutely necessary for unexperienced users or those, who are not sure in their skills. Also
79
healthcare institution might not purchase training programs if it has internal resources for
education, for example there is an employee, who is familiar with information systems and
can teach others how to use it. Generally, there are two options: to get educational trainings
or not. The part of the healthcare information system selection model reflecting training
programs is presented on Figure 7.
Figure 7. Healthcare information system selection model – training programs
Finally, there are 5 key characteristics to consider in the first part of the selection
model: operating system, data storage deployment, availability of patient portal, Big Data
analytics and training programs. Portable device access was excluded from the selection
model as it was considered to be unnecessary for healthcare institutions without permanent
establishment.
There are also 7 additional functions of healthcare information systems each of
which has two options to implement it or not.
The first function to consider is biometric authentication. Biometric authentication
is a tool that uses unique biological characteristics of a person to verify identity for secure
access to electronic systems. This feature is used for a great variety of activities from
searching for known individuals to verifying that the individual has no identity in the
system at all. However, the primary goal of this feature is providing high level of security
of the information system as all the actions are aimed at not giving access to “external” no
the system individuals [Wayman et al, 2005]. The security of information systems using
traditional authentication methods (logins and passwords) usually suffer from 4 main
problems. Firstly, it is recommended to use complex passwords that include numbers,
letters, and special symbols. Such passwords are very hard to remember and it takes time
to input them, that’s why many organizations take risk and don’t use so complex ones
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[Jackson, 2013; Orloff, 2015]. Secondly, it is recommended to change passwords several
times a year to protect the information from brutes. However, not all organizations follow
this advice as it can be difficult to remember new passwords. The problem of remembering
passwords leads to the third security threat – some users write down their passwords and
moreover sometimes attach them to the monitor screen. The last security threat is
exchanging passwords among the users in case someone didn’t come to the job and shared
password to the colleague to provide access to his account. All these problems can be
solved by using biometric authentication as unique biological characteristics can’t be
exchanged or hacked. Also biometric authentication is recommended to use if healthcare
institution employs aged medical professionals who have good IT skills to use information
system but it is hard for them to remember logins and passwords. It worth noting that as
this feature is necessary for those who concern much about the information security it is a
bit illogically to implement it on the cloud solutions as the organization entrusts this
essential issue to third parties. However, if the function is used to facilitate authentication
process it can be utilized. The algorithm of deciding on the necessity of the biometrical
authentication feature is presented on figure 67.
Talking about aged medical professional without any IT skills it is recommended
for healthcare institutions to implement handwriting and speech recognition function. It is
very hard to make aged employees without IT skills to use information system and it is
likely that they would resist and use paper-based medical records as this procedure is
familiar to them. This problem can be solved by handwriting and speech recognition
function that enables to convert handwritten text into e-format. The algorithm of deciding
on the necessity of the handwriting and speech recognition function is presented on figure
7.
The next additional feature is 3D reconstruction, which is needed for those, who
already use such software and would like to combine it with the healthcare information
system. Talking about integration with government systems this function as the previous
one is necessary for those who exchange documents with the governmental institutions.
The algorithms of deciding on the necessity of the 3D reconstruction and integration with
government systems functions are presented on figure 8.
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Figure 8. Healthcare information system selection model – additional healthcare
information systems functions: biometrical authentication, handwriting and speech
recognition, 3D reconstruction, integration with government systems
82
The next feature is SMS reminder, which is used to remind patients of their
appointments. This additional function is necessary for healthcare institutions with high
level of missing appointments without any notifications. There is also a similar feature –
build-in reminder, which is used not only for patients’ recalling, but also for medical
personnel. From the users’ point of view it works like a calendar and reminds medical
professionals of important events. This feature is needed if medical personnel frequently
forget and miss deadlines and meetings. As this feature pertly overlaps the previous one
there is no need to include both in the information system simultaneously. The algorithm
of deciding on the necessity of the SMS reminder or Build-in reminder is presented on
figure 9.
The last additional feature of the healthcare information systems is allergy checks.
This function implies an automatic check at the point of care of patient’s allergy list and an
alert if the patient is allergic to a medicine that is going to be prescribed. This function
increases the efficiency of care and decreases the time of care by removing the necessity to
check this information by hand. Allergy check function can be considered as a risk
management tools as it manages the risk of prescribing the wrong medicine and dealing
with the negative consequences of such mistake. According to internet journal Medicine in
Russia drug allergy is one of the 5 most frequent allergies in Russia. According to Russian
Institute of Immunology about 10-20% of the country population suffers from drug allergy
in average. Healthcare institutions with higher or equal to country average percentage of
drug allergic patients are recommended to include allergy check feature into their
healthcare information systems. Other healthcare institutions can implement this feature if
they wish. The algorithm of deciding on the necessity of the allergy checks feature is
presented on figure 9.
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Figure 9. Healthcare information system selection model – additional healthcare
information systems functions: SMS reminder, Build-in reminder, Allergy checks
Finally, the second part of the selection model includes 7 additional functions that
can be included in the information system or not: biometric authentication, handwriting
and speech recognition, 3D reconstruction, integration with government systems, SMS
reminder, build-in reminder, allergy checks function. Build-in reminder is the only feature
that excludes the usage of another feature (SMS reminder), while all other features are
compatible with each other.
As a result healthcare institution gets a list of recommended healthcare information
system features from 5 key characteristics: operating system, data storage deployment,
availability of patient portal, Big Data analytics and training programs; and 7 additional
characteristics: biometric authentication, handwriting and speech recognition, 3D
reconstruction, integration with government systems, SMS reminder, build-in reminder,
allergy checks function.
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3.2
Managerial implications of main findings
The results of this research can be used by healthcare institutions several different
ways. Firstly, the results of interviews with experts from healthcare institutions
experienced in utilizing healthcare information systems can be used by unexperienced in
this issue decision-makers to assess their knowledge in this field. Decision-makers, who
are going to select healthcare information system can create the list of their own initial
selection criteria and compare it to the opinion of experienced healthcare institutions. If the
lists turned up to be similar them decision-maker seems to have enough knowledge in this
sphere and can take into account his own opinion. However, he also should use the
developed model as there are also different options in each of the criteria and several
additional functions. In case the initial decision-maker’s criteria don’t resemble the
“experienced” criteria, decision-maker shouldn’t rely on his own opinion because of lack
of knowledge and should use the developed model to select the system.
Developed healthcare information system selection model can be useful for both
experienced and unexperienced healthcare institutions. Unexperienced healthcare
institution without any information system can use the developed model to choose its first
healthcare information system that will be appropriate particularly for it. Using the
selection model healthcare institution will get recommendations about the options of key
healthcare information system features: operating system, deployment, patient portal, Big
Data analytics and training programs; and about the necessity to implement any of
additional features like biometric authentication, integration with government systems,
SMS reminder, build-in reminder, 3D reconstruction, allergy checks or handwriting and
speech recognition. As a result healthcare institution will be able to choose healthcare
information system that has recommended features.
Talking about healthcare institutions that already have healthcare information
system there are two possible ways of utilizing developed selection model. Firstly, it can
be used to check suitability of the currently used healthcare information system. In such
case healthcare institution should answer the questions of the selection model considering
the initial situation before the information system implementation. After going through the
whole decision-tree healthcare institution will get the list of recommended features to
compare with features of existing information system. As a result current system can be
either appropriate or not appropriate for healthcare institution. If the current system was
considered not suitable for healthcare institution, it can use the recommended features to
85
choose the new system or improve the current one if it is modular and necessary modules
are available. Secondly, the model can be used by experience healthcare institutions
initially for choosing the new information system if they are not satisfied by the current
one.
Comparative table of 50 healthcare information systems can also be used by
healthcare institutions after getting the list of recommended features from the selection
model. Healthcare institutions can select healthcare information systems using appropriate
features from the created list of compared systems. Also this comparison table can be used
for getting briefly acquainted with the general features of different healthcare information
systems.
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3.3
Summary of chapter 3
The third chapter is dedicated to the development of healthcare information system
selection model for healthcare institutions without permanent establishment. Healthcare
institutions with permanent establishment require different methodology and conducting a
separate study, so they were not considered in this research. The selection model is aimed
at helping healthcare institutions to choose an appropriate healthcare information system
according to their needs. This model is presented in a form of an algorithm with easy-tounderstand questions. After answering all the questions healthcare institution gets the list
of necessary functions that should be included into healthcare information system to be
suitable for a particular institution.
The selection model is based on the healthcare information systems comparison
analysis and on the results of the interviews. There are 13 characteristics of healthcare
information systems considered in the selection model: 5 key features and 7 additional
ones. Every characteristic has at least 2 options, so it was decided to use variables in the
decision algorithm to narrow it and to avoid duplication of brunches. The questions in the
healthcare information systems selection model were designed in the way to be
understandable for decision-makers with limited IT knowledge. Therefore, there is no need
to deep in technical details of healthcare information systems and to make additional
efforts to select and appropriate healthcare information system. The full healthcare
information system selection model is presented in Appendix 1.
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Limitations and validation
The healthcare information systems selection model created as a result of this study
is suitable only for healthcare institutions without permanent establishment. Availability of
permanent establishment in healthcare institution requires special modules in healthcare
information systems or even special information systems. Also permanent establishment
requires individual analysis as it is necessary to consider more factors, for example issues
connected with managing beds paces. Therefore, there is a need to conduct a separate study
for healthcare institutions with permanent establishment concerning the healthcare
information systems selection issue. Consequently, it was decided to exclude healthcare
institutions with permanent establishment from this study to narrow the research and focus
on a particular field.
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Discussion
There are many different challenges in the healthcare industry and it widely agreed
that the key solution is information systems and information technology implementation in
healthcare management [Stegwee and Spil, 2001, 1–10]. Therefore, the problem of
healthcare information systems selection is a topical one as only appropriate healthcare
information system can bring all the potential benefits to the healthcare institution.
The research is based on con analysis of 50 different healthcare information
systems and expert opinion of 6 healthcare institutions in St-Petersburg that already have
experience in healthcare information system utilization.
The content analysis of existing healthcare information systems is aimed at
distinguishing key features of such systems and available options regarding these features.
After the analysis 13 different features of healthcare information systems were identified. 6
of them were considered as the key characteristics as their options take place in the
majority of healthcare information systems. The list of the key features of healthcare
information systems is as following:
•
operating system
•
data storage deployment
•
patient portal
•
portable device access
•
Big Data analytics
•
training programs
Though, only 5 of them were then included in the healthcare information system
selection model. Portable device access feature was excluded from the list of selection
criteria according to the limitations of the study. The main benefit of this characteristic is
medical personnel flexibility. However, for medical professional in healthcare institutions
without permanent establishment this point ceases to be an advantage as they meet patients
is their fixed offices. In case of a permanent work place personal computers have a great
advantage over mobile devices like size and resolution of the screen or physical keyboard
for more effective typing.
Other 7 features of healthcare information systems were considered as additional
functions as they occur only in some of the reviewed information systems. All the
additional characteristics were included in the healthcare information systems selection
89
model with 2 options either existence or absence of the feature. The list of the additional
features of healthcare information systems is as following:
•
biometric authentication
•
handwriting and speech recognition
•
integration with government systems
•
SMS reminder
•
build-in reminder
•
3D reconstruction
•
allergy checks.
6 interviews with experts from St-Petersburg healthcare institutions that are
experienced in healthcare information systems usage were conducted. The aim of the
interviews was to distinguish how healthcare institutions choose healthcare information
systems and how the experience affected the selection criteria. There were two main
groups of the respondents: healthcare institutions that selected healthcare information
system with the help of IT-specialists and healthcare institutions that selected healthcare
information system themselves. The main difference among these groups was the initial
selection criteria. The first groups based their choice on such criteria as functionality,
technical support in St-Petersburg and domestic development. The second group selected
information system basing on more subjective criteria like reviews and references. After
several years of healthcare information system usage both groups changed their opinion
about the selection criteria. All key features of healthcare information systems
distinguished from the content analysis were chosen as selection criteria at least once.
Basing on this information all the features except portable device access were included in
the healthcare information systems selection model.
This study aims at helping healthcare institutions to choose suitable healthcare
information system and avoiding wasting financial resources for unnecessary for the
particular medical institution features. Appropriate healthcare information system helps
healthcare institutions to become more effective and efficient and keep up with the times.
Created healthcare information system selection model is relevant only for
healthcare institutions without permanent establishment as there is a separate group of
healthcare information systems and modules which are used in clinics with permanent
establishment. Further research should be conducted to adapt this selection model to
hospitals and other medical institutions which have permanent establishment. This
90
healthcare information systems selection model can be a base for further researches in this
field and the similar methodology can be used to expand the model so that it can be used
by healthcare institutions with permanent establishment. Also there is a need to review
information systems and modules used for considering places for permanent establishment
and other factors connected with this issue.
Besides, there can be more than 7 additional features of healthcare information
systems found during the content analysis of 50 selected healthcare information systems.
Further studies can take into consideration a greater number of healthcare information
systems and include some individually designed systems into comparison to broaden the
list of available in healthcare information systems functions. Also more foreign healthcare
information systems should be included in the further researches as they can contain more
additional features that were distinguished through the comparison analysis during this
study.
The last point is that issue of healthcare information systems selection was
considered only from technical point of view. However, there can be some features of the
healthcare institution that influence the choice. Further researches can be conducted to
identify whether any features of organization, for example, size or the number of medical
areas, affect the healthcare information systems selection.
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Conclusion
Currently, IT technologies are developing in different industries all over the world
and healthcare industry is not an exception. Information technologies appeared in
healthcare institutions in 1960s with first electronic applications and the industry is moving
forward very fast, especially recent years. IT technologies become more and more
advanced and attractive.
Healthcare institutions all over the world started implementing modern
technologies; such systems are called healthcare information systems. This rapid
development of IT solutions brings many opportunities and benefits to healthcare
institutions and helps them to become more effective and efficient and to increase the level
of care. Many researches and studies concerning healthcare information systems were
conducted to explore the benefits of IT solutions implementation and the implementation
process itself.
However, the development of technologies brings some challenges, too. It became
very difficult for healthcare institutions to define how they should choose healthcare
information systems that would fit their needs? There is a gap in studying the preliminary
stage of healthcare information systems implementation – the selection of appropriate
system.
In Russia this issue becomes a hot topic as the healthcare industry develops and
healthcare information systems gain popularity. In case information system doesn’t fit
particular healthcare institution, for example there are unnecessary functions; healthcare
institution wastes its resources and the efficiency decreases. Therefore, it is necessary to
select an appropriate healthcare information system to get all the potential benefits.
The purpose of the study was to fill the research gap and identify how to healthcare
institutions without permanent establishment should select healthcare information system.
This study aims at helping healthcare institutions to choose suitable healthcare information
system and avoiding wasting financial resources for unnecessary for the particular medical
institution features. Appropriate healthcare information system helps healthcare institutions
to become more effective and efficient and keep up with the times.
The research was based on content analysis of 30 Russian and 20 foreign healthcare
information systems and expert opinion of 6 healthcare institutions that already have
experience in healthcare information system utilization, which are presented in Chapter 2.
92
As a result a healthcare information systems selection model was created for healthcare
institutions without permanent establishment. The development of healthcare information
system selection model is presented in Chapter 3. This model is aimed at facilitating the
decision making process concerning the issue of choosing an appropriate healthcare
information system. The selection model is presented in a form of a decision tree and
designed in a way that a decision-maker without special IT knowledge could use it to make
a choice. 12 healthcare information system characteristics distinguished during the content
analysis of existing solutions were included in the selection model. The significance of the
features as selection criteria were proved by their analysis and the expert opinion of
healthcare institutions experienced in healthcare information systems usage.
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101
Appendix 1. Healthcare Information System Selection Model
Start
Do you have stable
internet connection?
no
no
Can your problems be
solved?
yes
yes
yes
Do you have servers?
What is the age of
your servers?
<3
serv:=1
>3
yes
yes
Are you ready to
purchase new servers
in nearest future?
no
Do you have place for
servers placement?
no
no
serv:=‐1
>1 month
How fast do you want
to implement HIS?
<1 month
speed:=‐1
no
Would you
entrust data storage
to third party?
yes
trust:=1
Are your
departments located
far from each
other?
yes
102
Are your
departments located
far from each
other?
yes
loc:=‐1
no
Which type of
payment is more
appropriate for you:
one‐time or
subscription?
one‐time
subscription
payment:=1
Do you have an
experience of using cloud
services?
yes
negative
payment:=‐1
Was it positive or
negative?
positive
exp:=1
no
Would you like to try
to use cloud services?
no
yes
desire:=1
desire:=‐1
If (exp=1)AND(desire=‐1)
True
exp:=0
103
If (exp=1)AND(desire=‐1)
True
exp:=0
False
False
If (serv=1)AND(speed=‐1)
servers
True
What is more
important for you: to use
existing servers or
fast (<1month)
implementation?
speed:=0
False
If (serv=1)AND(loc=‐1)
yes
serv:=0
True
With your location
cloud use is highly
recommended. Still want to
use existing servers?
loc:=0
If (serv=1)AND(desire=‐1)
no
If (serv=‐1)AND(trust=1)
no
serv:=0
True
Do you prefer cloud
use despite the fact that
you have servers?
loc:=0
False
speed
yes
serv:=0
True
104
False
If (serv=‐1)AND(trust=1)
no
True
Cloud use requires
entrusting security issues.
Would you like to buy own
servers?
trust:=0
False
If (serv=‐1)AND(payment=1)
no
serv:=0
True
Cloud use means
a subscription payment type.
Would you like to buy servers
to have one‐time
payment?
payment:=0
False
If (serv=‐1)AND(exp=1)
cloud
If (speed=‐1)AND(trust=1)
entrust
yes
serv:=0
True
Would you try cloud
despite the bad experience or
purchase servers?
exp:=0
False
yes
servers
serv:=0
True
Fast implementation
(<1month) is possible only
with cloud that requires to entrust
data. Would you entrust data
or refuse from fast
implementation?
refuse
105
exp:=0
speed:=0
or refuse from fast
implementation?
speed:=0
exp:=0
If (speed=‐1)AND(payment=1)
accept subscription
False
True
Fast implementation
(<1month) is possible only
with cloud that requires
subscription payments. Would you
accept subscription
or refuse from fast
implementation?
exp:=0
If (speed=‐1)AND(exp=1)
yes
refuse
speed:=0
True
Fast implementation
(<1month) is possible only
with cloud use. Would you try it
again despite the bad
experience?
no
False
exp:=0
If (trust=1)AND(loc=‐1)
no
speed:=0
True
With your location
cloud use is highly recommended.
Would you entrust the data to third
party?
yes
False
loc:=0
trust:=0
106
False
loc:=0
If (trust=1)AND(desire=‐1)
no
trust:=0
True
Cloud use means to entrust
the data to third parties. Would
you do that?
yes
False
desire:=0
If (loc=‐1)AND(payment=1)
yes
trust:=0
True
With your location
cloud use is highly recommended,
which means subscription payments.
Would you agree to pay
subscription?
no
False
payment:=0
If (loc=‐1)AND(exp=1)
yes
loc:=0
True
With your location
cloud use is highly recommended.
Would you agree to try
cloud again?
no
False
payment:=0
False
If (payment=1)AND(desire=‐1)
loc:=0
True
107
False
If (payment=1)AND(desire=‐1)
no
True
Cloud use means
subscription payments. Would you
agree to subscription?
desire:=0
payment:=0
If (serv=1)OR(trust=1)OR(payment=1)OR(exp=1)OR(desire=1)
True
no
Are different OS
installed on one PC or
different ones?
different
False
Deployment:=Cloud
Do you have an IT
specialist(s) who can
conduct server
maintenance?
Deployment:=ServerSup
several
yes
yes
Deployment:=ServerNoSup
What operating
system (OS) do you
use?
108
Are different OS
installed on one PC or
different ones?
different
same
Macintosh
Windows
Do you need all OS
to support information
system or only one?
Which OS do you use
more often?
Linux
Macintosh
all
only one
Linux
Windows
Which OS do
you have?
Which one?
Windows and Linux
OS:=Windows
Windows
OS:=Linux
OS:=Macintosh
Linux
Windows and Macintosh
Macintosh
Linux and Macintosh
OS:=Windows+Linux
OS:=Windows+Macintosh
OS:=Linux+Macintosh
no
Would you like to
create additional value for
clients by introducing online
patient portal?
Portal:=False
no
yes
A better result can be
achieved by providing two‐way
communication with inline
consultants. Would you like to
introduce this feature?
yes
109
no
communication with inline
consultants. Would you like to
introduce this feature?
Portal:=1way
Do you use or plan to use
special medical equipment?
(MRI, cardiograph etc.)
yes
Portal:=2way
yes
no
Would you like to get
statistical reports?
yes
Would you like to use
Big Data for business processes
optimization?
yes
no
no
BigData:=False
no
BigData:=True
Do you have experience
of HIS use?
no
yes
Can you organize
training with internal
resources?
yes
110
training with internal
resources?
no
Training:=True
yes
Training:=False
If (Deployment=Cloud)
False
Do you want to use
biometrical identification to
increase data security?
no
True
Do you have aged
employees who will use HIS?
no
yes
yes
yes
Do they have sufficient IT skills
to use HIS?
no
Handwriting:=True
Biometry:=True
111
Do you use or plan to
use equipment for 3D
reconstruction?
yes
3D:=True
no
Do you exchange
any documents with
government?
yes
no
Government:=True
How often do your
clients miss appointments
without notifying?
often
How often do your
employees miss deadlines or
meetings?
not often
SMS:=True
Buildin:=True
112
How many clients with drug
<13%
How many clients with drug
allergy do you have?
>13%
Allergy:=True
False
If (Deployment=Cloud)
If (Deployment=ServerSup)
True
False
Write “Deployment: Server
without support” to the
Characteristics file
True
Write “Deployement:
Cloud” to the
Characteristics file
Write “Deployment: Server
with support” to the
Characteristics file
False
If (OS=Linux)
If (OS=Windows)
True
True
Write “OS: Windows” to
the Characteristics file
113
False
False
Write “OS: Linux” to the
Characteristics file
If (OS=Macintosh)
True
False
If (OS=Windows+Linux)
Write “OS: Macintosh” to
the Characteristics file
True
False
Write “OS: Windows
and Linux” to the
Characteristics file
If (OS=Windows+Macintosh)
True
False
Write “OS: Linux and
Macintosh” to the
Characteristics file
Write “OS: Windows
and Macintosh” to the
Characteristics file
False
False
Write “Patient Portal:
two way” to the
If (Portal=1way)
If (Portal=False)
True
Write “Patient Portal:
one way” to the
True
114
Write “Patient Portal:
two way” to the
Characteristics file
True
Write “Patient Portal:
one way” to the
Characteristics file
False
If (BigData=True)
True
Write “Big Data
Analytical Tools” to the
Characteristics file
False
If (Training=True)
True
Write “Training Programs”
to the Characteristics file
If (Biometry=True)
True
False
Write “Biometrical
Authentication” to
the Features file
If (Handwriting=True)
False
True
Write “Handwriting and
Voice Recognition” to
the Features file
115
False
the Features file
If (3D=True)
False
True
Write “3D Reconstruction”
to the Features file
If (Government=True)
True
Write “Integration with
Government Systems” to
the Features file
False
If (SMS=True)
True
False
Write “SMS Reminder” to
the Features file
If (Buildin=True)
False
Write “Build‐in Reminder”
to the Features file
If (Allergy=True)
False
True
True
116
If (Allergy=True)
True
False
Write “Allergy Checks”
to the Features file
Dislay
Characteristics
Display
Features
End
117
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