Foundation Concepts of Health Management Information Systems

Foundation Concepts of Health Management Information Systems
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PART
I
Foundation Concepts
of Health Management
Information Systems
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CHAPTER
1
Health Management
Information Systems:
A Managerial Perspective
Joseph Tan
CHAPTER OUTLINE
Scenario: Key Trends Contributing to the Merging of Enterprise and Health Information
Exchange Models
I. Introduction
II. Evolution of HMIS
III. HMIS Components and Basic Functions
● HMIS Components
● HMIS Basic Functions
IV. HMIS Cultures
V. Conclusion
Notes
Chapter Questions
Mini-Case: MinuteClinic
3
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Scenario: Key Trends Contributing to the Merging of Enterprise
and Health Information Exchange Models1
Informatics Corporation of America (ICA), with its website (www.icainformatics.com) offering
insightful materials for the interested readers, is a health information technology (HIT) organization whose mission is to provide clinicians and healthcare providers with more or less seamless access to information extracted from various uncoordinated systems for patient diagnosis
and evaluation. Recently, ICA sent out a press release to various stakeholders in the healthcare
informatics (HI) community outlining five key trends shaping the development of health information exchanges (HIE) among large healthcare organizations:
1.
2.
3.
4.
5.
The growing impetus for healthcare provider connectivity.
An increasing focus on the need to manage chronic diseases.
Increased patient expectation of personal involvement in the care process.
Market pressures for improved hospital–physician alignment.
Advances in technology facilitating system interoperability.
With an increasing number of baby boomers and the elderly constituting the U.S. population,
it is envisaged that these trends will become more prevalent for U.S. healthcare services organizations in the near future.
“These trends highlight the benefits which community-based healthcare models can offer all
constituents—physicians, patients, and healthcare providers across the continuum of care,” says
Gary M. Zegiestowsky, chief executive officer (CEO) of ICA. “The gap between traditional enterprises and HIE is closing, with growing connectivity for physicians and ultimately the entire
healthcare community in certain cities or regions. We believe this is signaling a paradigm shift
that has both near- and long-term implications for healthcare and HIT.”
“In order to keep pace with these trends,” Zegiestowsky continues, “physicians in every community first need intuitive, proven technology solutions aligned with clinical workflow to speed
the adoption of electronic health records. Moving toward patient-centric care will be possible
when all providers across the broad spectrum of care are able to access and utilize a unified patient record in combination with tools that enable better care.”
ICA’s response to this growing trend is the use of an exchange platform created for both enterprise and HIT systems, such as the A3Align Solution™. For 10 years, practicing physicians
and informatics professionals from Vanderbilt Medical Center have developed this technology,
which has eventually been installed at Bassett Healthcare’s enterprise comprising four hospitals
and 27 clinics in Cooperstown, New York. A3Align Solution will also be implemented by both
the Montana and Northwest Healthcare for HIE. In addition, Vanderbilt distributed this same
technology across its 40 facilities in the Mid-South eHealth Alliance, a successful HIE in western Tennessee.
With these major trends encouraging HIE among healthcare services organizations, what do
you believe are the benefits of having all of your health information made freely accessible and
interchangeable among all of your caregivers? What would be your worst fear?
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I. INTRODUCTION
5
I. Introduction
As we enter this world, how did we become aware and conscious of who we are, and of things
that surround us? How did we learn about the myriad ideas, sights, sounds, and smells and the
many events that we see, hear, feel, and witness in the surrounding space in which we live and
breathe for each day of our lives? Aren’t “data” and “information” the essential constructing
blocks in our lives? Isn’t “knowledge” the central intellectual core that links everything else to
form meanings, interpretations, and actions? Aren’t “information systems” innate in each and
every one of us as human beings who find it so very natural to process incoming streams of
“stimuli” continuously, seamlessly, and automatically—irrespective of how cognitively complex
these stimuli may at first appear to be? Seemingly, all of us have already been introduced somewhat to the subject of health management information systems (HMIS) even from the first day
of birth as we “woke up” from our “deep sleep” inside our mother’s wombs, most likely, within
the confines of a healthcare or maternal health-related facility.
The field of HMIS is inherently complex. Take the myriad terminologies employed in this
text as an example. There are subtle differences even with major terminologies used to describe
the field. For instance, health management information systems (HMIS), which is the term used
liberally throughout the first edition of this text, has, in and of itself, a managerial slant, and
whereas healthcare information technology (HCIT or health IT–HIT) has a technology slant,
health information systems (HIS) or healthcare information systems (HCIS) may be interpreted as
the umbrella term with a systems or information systems connotation. Informatics is another
commonly used term among European researchers, and health informatics or clinical informatics
generally refers to the application of data methods in medicine, healthcare services, and clinical
practices. For this reason, some authors, as will become apparent in the latter part of the text,
use the terms health informatics (HI) and medical informatics (MI) as well as e-health (electronic
health). Thus, in this edition of the HMIS text, for the sake of simplicity and to further reduce
complexities for less sophisticated readers, we allow the usage of these several and diverse terminologies to be more or less interchangeable among the works accumulated by the different contributing authors and accompanying editors. Also, to ease the disruption in the readings and
simplify the editing process, we have generally dropped the “s” that is typically appended to
many of these acronyms to create the plural sense and simply use these acronyms in more or less
the plural sense unless it is specifically preceded with an article such as “a” or “the” when attaching a verb to the specific acronyms or using it as a descriptive adjective, as in “the HMIS” field.
More importantly, the HMIS conceptualization we have drawn in this text comes from an
eclectic well of traditionally established as well as newer disciplines. Academic researchers, educators, and practitioners from diverse disciplines—including, but not limited to, electrical and
computing engineering, industrial engineering, clinical and management engineering, nursing
and allied health, health informatics, health management, organizational behavior, computer
science, and cognitive science—have all contributed, in one form or another, to the development and accumulation of HMIS knowledge domains.
Indeed, as early as the 1960s, cognitive scientists have modeled the human cognition as an
information processing system. Here, the human brain is perceived to act just like the computer,
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and experiments conducted on the human stimuli-response system inform us of the familiar
story of how different external stimuli (information) can exert different patterns of resulting or
induced behaviors among the human observers. In other words, the information systems
within humans are exemplified by the cognitive activities recurring within the human brain.
In the HMIS analogy, the information processors are likened to the eyes and minds of the
health organization.
In this newly revised edition, the term adaptive HMIS has been used specifically to emphasize the need for a flexible approach to health information administration and management.
HMIS students must learn how to apply information science, information systems, and health
informatics concepts from an adaptive but integrated health management perspective. More
generally, this text aims to provide the students with a state-of-the-art managerial perspective of
health information technological systems in the coming years so that they are well prepared to
face the many challenges of acquiring and applying new forms of HCIT for healthcare services
management purposes in this century and beyond. In this first chapter, we briefly cover the HMIS
evolution, its underlying architecture, and its basic functions. We then close the chapter with a
brief survey of the role HMIS technology plays in driving today’s healthcare and healthcarerelated businesses.
II. Evolution of HMIS
In its broadest sense, HMIS encompasses diverse concepts, methods, and applications from
many related fields. Its genesis may be traced to multiple roots, including general systems thinking, information economics, management science, information systems development methodologies, software engineering, computer science and communication theory, medical
computing, health organization behavior, health management, policy, and health services research. From a practical viewpoint, the evolution of HMIS over the past several decades has
been largely driven by strategic, tactical, and operational applications of various information
technology (IT) and advanced systems concepts for healthcare services delivery within an individual, group, and, more appropriately, an organizational perspective. The regional or even national health coalitions are also on the horizon, enabled by the establishment of electronic
health information exchange infrastructures.
In a world where growing competition for healthcare services delivery is defined by rapidly
changing technology and maturing organizational arrangements, it is critical to understand
how evolving HMIS technologies operate and how HMIS interact within all key aspects of an
organization. In other words, it is important to know how HMIS are developed or procured;
how they are managed and maintained; how their functions are executed to support daily operations and more advanced activities, such as continuous quality improvement programs and
medical research; and finally, how to evaluate their performance and cost-effectiveness. More
importantly, with globalization and the emergence of large-scale computing systems such as
electronic health records (EHR) and innovative business-driven applications such as enterprise
resource planning (ERP), customer relationship management (CRM), supply chain management
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(SCM) systems, and patient-centric applications such as personal health records (PHR), the resulting landscape for future-oriented HMIS is bound to change quickly.
New advances in HMIS are vital to our society because these technologies guide our everyday lives; without them, life would be rather difficult. Imagine, for example, while visiting with
your doctor today, you find him or her searching busily through a mountain of incoherent, unorganized, and piecemeal data about you for all of the different visits that you may have made
to the different clinics that may now be part of a merged health maintenance organization
(HMO), or, what if your doctor has to spend most of his or her time making clarification
phone calls to laboratories and pharmacies to gather information rather than focusing on diagnosing and treating your illnesses? Imagine also that these data were recorded using various
data-coding schemes by different clinicians with different recording media (such as paper
records, tapes, and film images) and stored in multiple locations. How different would it be for
your doctor to manage you and your information if these data had been “digitally” captured in
standardized formats on nano-chips and could now be easily recombined, reorganized, and
made securely accessible and available to him or her quickly even before meeting with you?
Indeed, past technologies such as file folders, paper-and-pencil entries, tape recordings, and
X-ray films are both physically limited and very restrictive in terms of keeping secure, accessible, portable, and available records about you and capturing progressive changes to your health
and wellness status each time you visit with one of your care providers, who may be practicing
in different hospitals and clinics associated with your HMO. These traditional recording methods are limited because the captured data and information can only be kept largely in a “physical” form and not easily accessible, transportable, or available “virtually” or “digitally” to other
expert clinicians or even to you, who may decide to travel to another country seeking a second
opinion, or who may have been placed in emergencies outside the state of your residence. New
forms and modes of HMIS technology such as wearable devices and embedded chips promise
to give you the ability to access such recorded information that has been accumulated over the
years both conveniently and securely at any time, anywhere. In the foreseeable future, you will
also be able to control and access your own personal health records stored online and contributed by all of your care providers. As amazing as new technologies can be, it is important to
first understand the type(s) and basic functions of HMIS technologies that currently exist and
how these technologies will likely evolve due to increased globalization, continuous healthcare
reforms, the corporatization of medicine, and other major trends such as the formation of new
alliances and consolidations among healthcare provider organizations.
Apparently, the emergence of satellite-based, wireless, user-friendly portables; the proliferation
of cellular networks; new computing privacy and security technologies; and new implementation
of various powerful network-based systems such as sensor networks and Internet-based data
warehouses are now in the order of multimillion-dollar projects to serve large populations with
massive capabilities of automated collection, manipulation, and analysis of multidimensional
data sets. These emerging trends are now pressuring senior healthcare executives and managers to
become seriously interested in understanding and endorsing cost-beneficial, integrative, and innovative HMIS solutions.
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III. HMIS Components and Basic Functions
Publicly, as health consumers become more aware, more informed, and better trained in accessing electronic and social media and as they become more intelligent in evaluating alternative
healthcare services (such as using Leapfrog’s hospital ratings), engaging in online forums for
health information sharing, and participating in physician/hospital referrals among patients
and/or virtual marketing using social network sites, consumers are exerting greater pressures for
a revolution in HMIS technological applications. With the expansion of the aging baby boomer
generation and the accelerating growth in U.S. healthcare expenditures, we can confidently expect the continuing growth of HMIS applications during the coming decades to have a significant impact on primary healthcare, pharmaceutical, rehabilitative, palliative, and home
healthcare services. Therefore, management should not and cannot afford to leave the job of designing, developing, and implementing network-based, integrated HMIS in the hands of IT experts or commercial vendors alone. Instead, they must now take a personal interest in paving
the way for new generations of HMIS technology—technology that satisfies both organizational requirements and patient needs. As such, the importance of using an adaptive managerial
perspective in HMIS design and development within an organizational context for the coming
decades cannot be overly emphasized. Let us now turn to an overview of the basic HMIS components and functions.
HMIS Components
An understanding of the adaptive but integrated HMIS begins with differentiating among its
five major components and their interrelationships:
1.
2.
3.
4.
5.
Data/information/knowledge component.
Hardware/software/network component.
Process/task/system component.
Integration/interoperability component.
User/administration/management component.
The data/information/knowledge component forms the central core, the content, of all HMIS.
It encompasses the specification of, organization on, and interrelationship among data, information, and knowledge elements required of integrated HMIS.
Raw data form the basic building blocks for generating useful information that is to be
stored in any HMIS; processed data are transformed into information that serves as useful output for HMIS end-users to make informed and intelligent decisions. Some pieces of data about
your child may be that of his or her demographics or the medication that he or she is allergic to
(e.g., penicillin). Another example would be his or her childhood vaccination records. Here, the
data would be immunization dates and type. Putting all these data together to form a view of a
child’s immunization schedule derives information. Determining whether the child is due for a
vaccine requires knowledge, specifically, the captured experience and knowledge of the attending physician, which could further be stored and recorded into existing HMIS and passed on to
another care provider for future care delivery.
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The combination of effective data, information, and knowledge resource management involves designing the critical databases and instituting various intelligent data-mining algorithms, rule engines, and online analytical processing (OLAP) tools to manage the increasingly
complex and information-intensive care decision situations physicians are facing in this day and
age. In other words, organized information and captured experience will, in turn, yield the essential knowledge and business intelligence for guiding healthcare services for the individual
care provider, a group of care providers managing related health problems, or an entire health
provider organization trying to deliver healthcare services. Figure 1.1 shows the conceptual flow
of the data/information/knowledge paradigm within the HMIS organizational and healthcare
provider decision-making context.
Ultimately, the HMIS used to support key decision-making functions of healthcare
providers and administrators within the organization must be reformed to achieve greater integration of data, information, and knowledge across organizational stakeholders. ICA’s newly
proposed A3Align Solution, discussed in the chapter-opening scenario, is an example of how
innovative HMIS applications can better integrate enterprise databases (such as EHR) and
other uncoordinated data systems [such as computerized physician order entry (CPOE) and
clinical decision support systems (CDSS)] and to support integrated healthcare delivery at a regional level. In an integrated and well-designed HMIS, the goal is to distribute these informationrelated elements efficiently, effectively, and appropriately throughout the organization for enriching
learning among organizational users and for enhancing the delivery of healthcare services among
care providers.
The next critical component within “information systems,” aside from the “information”
core, is the “technology” layer. Here, the hardware/software/network component features
prominently as it entails the choice deployment of various information and computing-related technologies to support HMIS applications and use. Briefly, this component involves
configuring various hardware, software, user interface, and communication-enabling infrastructures, associated devices, and applications in such a way as to best achieve efficient and
effective information services integration throughout while connecting individuals, groups,
and organizations.
Knowledge
Data
Information
Feedback Loop
FIGURE 1.1
Decision
Action
A Data/Information/Knowledge Decision System.
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ICA’s A3Align Solution, for example, is an exchange platform created for integrating data
and information from both enterprise and HIT systems. It would be important to ensure that
all connected devices can access the HMIS applications seamlessly; better yet, these devises can
access an adapted version of an application customized to a device platform. In this sense, for
any healthcare organization, the technology layer must be supportive of the people (internal
users), aiding the performance of tasks to be accomplished by these users and helping them to
thrive in the resulting technology-driven environment. Furthermore, new and emerging
HMIS technologies and methods play an increasingly significant role in enhancing healthcare
organizational delivery of patient care–related services. This brings us to the third basic HMIS
component.
The process/task/system component exemplifies the routine and internalized driving engine
for HMIS. Here, our focus should be on the cohesion to be achieved within established “local”
processes, tasks, and applications. In other words, existing administrative-based HMIS, such as
financial information systems, human resources information systems, facility utilization and
scheduling systems, materials management systems, facilities management systems, and office
automation systems, as well as clinical-based HMIS applications such as EHR, CPOE, and
CDSS, must be designed to collect relevant data and accumulate useful information for organizational task-processing and decision-making activities. It is possible, too, that over time organizational structural and procedural changes and/or regulatory changes may require certain
different routine processes that have been instituted previously to be changed or completely
deleted, yielding room to new processes, tasks, and applications. Therefore, a systems perspective is critical in order to achieve optimal functionality among the different task processes and
applications.
Surely, the integration/interoperability component is a key determinant of HMIS success
from an enterprise view. Often, the key to positioning today’s healthcare services organizations
for future success is the interoperability of systems used in managing existing and ongoing
healthcare information services vis-à-vis its competitive marketplace environment. The “interoperability” for much of the computerized information processing within the organizational
framework must be upheld both internally and externally to achieve efficient, effective, and excellent delivery of healthcare services. This requires not only an elaborate understanding of
evolving technological innovations and changing needs in organizational task processes, but
also knowledge of the market structure and changing characteristics of the healthcare services
industry and how the different current systems should be designed to fit well with every other
HMIS application to achieve an integrated, enterprisewide HMIS.
In fact, as early as 1980, Lincoln and Korpman recognized the difficulties with computer applications in healthcare services delivery.2 In their classic paper, “Computers, Healthcare, and
Medical Information Science,” they argued that the goals for medical information science, although easy to state, are difficult to achieve for several reasons. First, adapting well-tested information processing procedures and methods from other fields into medicine is difficult because of the
uncertainty and sophistication surrounding the medical context; the wide spectrum of medical
data; and the vagueness, disparity, and variation of organizational healthcare objectives. Second,
this difficulty is further exacerbated by the apparent dissonance between the often-embedded
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ambiguity in medical data structure and the rigidity of computer logic structure. Specifically, in
medicine, the materials cover the entire range of patient care data and the methods used span a
wide range of disciplines, including the management, behavioral, and fundamental sciences, not
just information processing and communications.
This brings us to the final but most critical HMIS component, the users. The user/
administration/management component brings together and intelligently coordinates all of the
other HMIS components. Based on a shared technological infrastructure, for example, various
users are, in turn, empowered to perform designated tasks and activities that will support the
overall business goals of the organization—that is, to serve their clients both inside and outside
the organization in the most efficient, productive, and effective manner. The function of this
critical user component, when blended appropriately with all the other HMIS components, is
to engender a holistic conceptualization that absorbs the many insights and interactions inherent in any organizational HMIS endeavor.
Altogether, an adaptive, managerial HMIS perspective encompasses a combined interaction
of data-related elements, appropriate technologies and methods, designated task processes, and
intended users to gather, store, manipulate, and supply the needed information to support key
organizational decision-making activities. The HMIS is an integral part of the organizational
system, a mechanism that is central to integrating the enterprise and its various components.
Every unit of that enterprise, which presumably is interrelated, must necessarily complete its
purpose by working in unity. Like a jigsaw puzzle comprising a mass of irregularly shaped pieces
that form a picture when fitted together, an adaptive, integrated HMIS emerges when the different components of the enterprise fit together. Still, the HMIS must fit in with the existing
culture and organization work environment. An adaptive, integrated HMIS approach therefore
exemplifies a holistic conceptualization of the fit among various enterprise components within
the context of an adaptive, integrated management perspective. The relationships among these
major enterprise components are illustrated in Table 1.1, which may be further used to outline
the different parts of this text.
Part I, comprising Chapters 1 through 3, emphasizes HMIS foundational concepts. Chapter
1 provides an overview of HMIS from the health managerial perspective. Chapter 2 highlights
the roles and responsibilities of chief executive and chief information officers in healthcare services organizations followed by Research Brief I, discussing how a personal digital assistant
(PDA) can enhance data collection efficiency for wait-time reductions in emergency departments. Chapter 3 discusses online health information–seeking behavior among Internet users,
accompanied by Technology Brief I, which focuses on the fundamentals of Internet and associated technologies for healthcare services organizations.
Part II, comprising Chapters 4 through 7, surveys the technology and application layers of
HMIS. Chapter 4 focuses on HMIS enterprise software, the new generation of HMIS administrative applications, accompanied by Technology Brief II, a refresher overview of basic hardware,
software, and interface design concepts. Chapter 5 concentrates on community health information networks (CHIN) to interconnect healthcare provider organizations and build virtual
communities. Technology Brief III, focusing on HMIS telecommunications and networks, follows this chapter. Chapter 6 familiarizes readers with three key patient-centric management
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Table 1.1 HMIS Text: Content and Organization
Part I
Foundation Concepts
of HMIS
Chapter 1. HMIS: A Managerial Perspective
Joseph Tan
Chapter 2. HMIS Executives: Roles and Responsibilities of Chief
Executive Officers and Chief Information Officers in Healthcare
Services Organizations
Joseph Tan
Research Brief I: Personal Digital Assistants Enhance Data
Collection Efficiency during a Study of Waiting Times in an
Emergency Department
N. Elkum, W. Greer, and A. Al-Madouj
Chapter 3. Online Health Information Seeking: Access and Digital
Equity Considerations
Fay Cobb Payton and Joseph Tan
Technology Brief I: Fundamentals of Internet and Associated
Technologies for Healthcare Services Organizations
Joshia Tan
Part II
HMIS Technology and
Applications
Chapter 4. HMIS Enterprise Software: The New Generation of HMIS
Administrative Applications
Joshia Tan with Joseph Tan
Technology Brief II: Basic Hardware, Software, and Interface Concepts
for Healthcare Services Organizations
Joshia Tan and Joseph Tan
Chapter 5. CHIN: Building Virtual Communities and Networking
Health Provider Organizations
Jayfus T. Doswell, SherRhonda R. Gibbs, and Kelley M. Duncanson
Technology Brief III: Telecommunications and Network Concepts for
Healthcare Services Organizations
Joseph Tan
Chapter 6. Trending toward Patient-Centric Management Systems
Joseph Tan with Joshia Tan
Technology Brief IV: Database, Data-Mining, and Data-Warehousing
Concepts for Healthcare Services Organizations
Joshia Tan and Joseph Tan
Chapter 7. HMIS Integration: Achieving Systems Interoperability
with Web Services
J. K. Zhang and Joseph Tan
Part III
HMIS Planning and
Management
Chapter 8. HMSISP/IR: Health Management Strategic IS Planning/
Information Requirements
Jon Blue and Joseph Tan
Chapter 9. HMIS Development: Systems Analysis and Development
Methodologies
Joseph Tan
Chapter 10. Data Stewardship: Foundation for HMIS Design,
Implementation, and Evaluation
Bryan Bennett
(continues)
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Table 1.1 (Continued)
Chapter 11. Managing HMIS Projects: HMIS Implementation and IT
Services Management
Joseph Tan
Part IV
HMIS
Standards, Policy,
Governance, and Future
Chapter 12. HMIS Standards: Standards Adoption in Healthcare IT
Sanjay P. Sood, Sandhya Keeroo, Victor W. A. Mbarika, Nupur Prakash, and
Joseph Tan
Policy Brief I: HIPAA, Privacy, and Security Issues for Healthcare
Services Organizations
Joseph Tan and Fay Cob Payton
Chapter 13. HMIS Governance, Policy, and International Perspectives:
HMIS Globalization through E-Health
Anantachai Panjamapirom and Philip F. Musa
Chapter 14. HMIS Innovation: HMIS Innovation Diffusion in
Healthcare Services Organizations
Tugrul U. Daim, Nuri Basoglu, and Joseph Tan
Part V
Case 1. Emergency Medical Transportation Resource Deployment
HMIS Practices and Cases Homer H. Schmitz
Case 2. The Clinical Reminder System (CRS)
Kai Zheng
Case 3. Integrating Electronic Medical Records and Disease
Management at Dryden Family Medicine
Liam O’Neill and William Klepack
Case 4. Delivering Enterprisewide Decision Support through
E-Business Applications
Rajiv Kohli and Henry J. Groot
Case 5. Mapping the Road to the Fountain of Youth
Joshia Tan
systems, namely, EHR, CPOE, and CDSS. Technology Brief IV, focusing on the fundamentals
of HMIS database, data warehousing, and data-mining concepts, accompanies this chapter.
Lastly, Chapter 7, which centers on the idea of achieving HMIS integration with systemsinteroperable Web services, provides closure to Part II.
Part III, which encompasses Chapters 8 through 11, concentrates on HMIS planning, design, and management issues. Chapter 8 covers HMIS strategic planning and methods to elicit
organizational information requirements. Chapter 9 presents HMIS analysis and development
methodologies, whereas Chapter 10 offers practical advice on HMIS design, implementation,
and evaluation from a data stewardship perspective. Chapter 11 then closes Part III by reinforcing the concepts of HMIS implementation from the perspective of IT project management as
well as IT service management concepts.
Part IV, which covers Chapters 12 through 14, acquaints the readers with HMIS standards,
policy, governance, and the future. Chapter 12 presents HMIS standards and is augmented
with Policy Brief I, focusing on the Health Information Portability and Accountability Act
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(HIPAA), privacy, and security issues that govern HMIS design, deployment, and use; Chapter
13 opens up the scope of earlier discussions by transitioning into HMIS governance, policy,
and international perspectives based on emerging trends of globalization and the e-healthcare
paradigm; and Chapter 14 jumps forward with a look at the future of HMIS by dwelling on innovation diffusion.
This ushers us into the final part of the text, Part V, which is devoted completely to selective
cases intended to pull together parts and pieces of HMIS concepts, methods, and applications
as presented throughout the different parts of this text. Briefly, five selective contributions of
HMIS applications cases are covered in Part V. Case 1, which focuses on strategic planning for
HMIS in the context of an emergency medical transportation (EMT) setting, opens the case
discussions for examining the applications of HMIS solutions to real-world problems. Case 2,
“The Clinical Reminder System,” offers insights into the development, utilization, and acceptance of a patient-oriented system to aid clinical workflow activities and routine decision making. Interestingly, Case 3, “Integrating Electronic Medical Records and Disease Management at
Dryden Family Medicine,” zooms in on HMIS implementation within a small physician group
practice, while Case 4, “Delivering Enterprisewide Decision Support through E-Business
Applications,” shows how different generations of decision support evolved for a large-scale
healthcare services delivery system. Case 5, “Mapping the Road to the Fountain of Youth,” is an
accumulation of the concepts covered in the cases in Part V and brings a closure to the entire
text. With this overview, it is important to get back to the fundamental conceptualization of an
HMIS and what are its basic functions.
HMIS Basic Functions
It is critical that beginning HMIS students achieve a good grasp of the basic functions of an information system. Historically, all information systems, including HMIS, are built upon the
conceptualization of three fundamental but iterative information-processing phases: data input,
data management, and data output. The data input phase includes data acquisition and data
verification. The data management or processing phase includes data storage, data classification, data update, and data computation. Finally, the data output phase includes data retrieval
and data presentation. Altogether, these eight elements and three phases define a typical information system as represented schematically in Figure 1.2.
Data acquisition involves both the generation and the collection of accurate, timely, and relevant data. Data are the raw materials needing verification, organization, and transformation
before they can be useful information. The process of data generation in HMIS is normally
achieved through the input of standard coded formats (e.g., the use of bar codes), thereby allowing rapid mechanical reading and capturing of data. The process of data collection differs
from that of data generation in that data can be entered directly at the source (e.g., the use of a
point-of-care bar code scanner), thereby enhancing data timeliness, validity, and integrity. Data
verification involves the authentication and validation of gathered data. It is generally known
that the quality of collected data depends largely on the authority, validity, and reliability of the
data sources. The garbage in garbage out (GIGO) principle is an important factor to consider
in this process; that is, data containing inaccuracies and inconsistencies should be detected as
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Data
Acquisition
Data
Input
Data
Verification
Data
Management
Data
Storage
Data
Classification
Data
Computation
Data
Update
Data
Retrieval
Data
Output
Data
Presentation
FIGURE 1.2
Basic Functions of a Health Management Information System.
early as possible in the system to allow immediate correction and minimize the eventual costs of
system output errors.
The preserving and archiving of data may be regarded as part of the data storage function.
Memory (i.e., a physical storage system) and indexing (i.e., the selection of key words to determine major subject areas) are primary means of amassing data. When accumulated data are no
longer actively used in the system, a method to archive the data for a certain period is usually
advisable and may sometimes be mandatory, as when it is required by legislation. A closely related element to data storage is data classification (or data organization). It is a critical function
for increasing the efficiency of the system when the need arises to conduct a data search.
Moreover, imposing a taxonomy on the data that have been collected and stored provides
greater understanding of how the data can be reused. Most data classification schemes are based
on the use of certain key parameters. For example, data referring to a patient population may be
classified and sorted according to various diagnostic classification schemes, such as the widely
accepted ICD-9-CM, a clinical modification of the original ICD-10 system developed by the
National Center for Health Statistics (NCHS). More recently, the ICD-10-PCS (the
International Classification of Diseases, 10th Procedure Coding System) has replaced volume 3
of ICD-9-CM.3,4 While ICD-10-PCS is yet to be implemented, awaiting propagation from the
World Health Organization (WHO), such an organized patient data system is useful for conducting a case-mix analysis because it comprises a set of diagnostic codes of thousands of patient classifications. Each code has seven alphanumeric characters, including section, body
system, root operation, body part, approach, device, and qualifier. Indeed, the particular taxonomy employed will have a powerful influence on the way the data can be subsequently used.
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This is because a high degree of semantics is implied in any particular data classification. Crowe
and Avison noted that if the wrong classification is chosen, a great deal of potentially useful information could be lost.5 This, however, is not a problem that can be easily resolved due to the
lack of standardization among competing taxonomies. System integration and data interoperability have, therefore, been an enduring challenge for HMIS researchers and practitioners.
New and changing information is accounted for through the element of data update. The
dynamic nature of such data modification calls for constant monitoring. For HMIS to maintain current data, mechanisms must be put in place for updating changes in the face of any ongoing manual or automated transactions. The concept of processing a transaction (i.e.,
whenever an event alters the current state of the system) is critical for ensuring data timeliness.
Such updates can be either online (real-time) or batch processed sequentially. Due to legal and
ethical considerations, archiving and tracking each data update can be a critical requirement in
designing and implementing HMIS. Data computation involves various forms of data manipulation and data transformation, such as the use of mathematical models, statistical and probabilistic approaches, linear and nonlinear transformation, and other data analytic processes.
Computational tasks allow for further data analysis, synthesis, and evaluation so that data can
be used for strategic decision-making purposes other than tactical and/or operational use.
Data retrieval is concerned with the processes of data transfer and data distribution. The data
transfer process is constrained by the time it takes to transmit the required data from the source
to the appropriate end-user. A key problem in data transmission is the existence of noise (i.e.,
distortion) that could be both internal and external to HMIS. The data distribution process ensures that data will be accessible when and where needed. There must also be ways to ensure
that unauthorized users are denied access to sensitive data in the system. This is normally
achieved through the institution of data security and access control mechanisms, such as the use
of firewalls, passwords, user authentication, and other forms of user identification. One significant criterion to be considered in the data retrieval function is the economics of producing the
needed information. Many early systems (particularly stand-alone hospital information systems) were far too costly to operate, and the costs were simply not justified relative to the value
of information that was finally produced. This situation has largely changed with advancing
HMIS techniques and technologies available at decreasing costs.
Finally, data presentation has to do with how users interpret the information produced by
the system. In situations where only operational or even tactical managerial decision making is
expected, summary tables and statistical reports may suffice. However, certain managerial decision making involves strategic thinking and active collaboration. The use of presentation graphics for higher-level managerial decision analysis is particularly encouraged because these appear
to provide a better intuitive feel of data trend. Tan and Benbasat6 and Tan7 have presented a
theory to explain and predict the human processing of graphical information, which is valuable
to guide HMIS designers in the matching of presentation graphics to tasks.
To illustrate these various HMIS data phases, we can use the case of a computerized patient
health records system for inpatients, which is usually supported with bedside terminals. In this
system, data acquisition comprises the generation and gathering of daily notes on symptoms,
treatments, diagnoses, progress notes, discharge summaries, registration of orders for laboratory
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tests, operations, anesthesia, and other sources of information such as patient demographics
and physicians’ findings. The data may also come from other interconnected HMIS through
live or batched data feeds. The data to be coded and automated are usually formatted into specific and normalized elements, fields, and records.
Figure 1.3 illustrates an abstract of a patient health record that could be implemented as a
Web-based system for monitoring patient medical conditions and treatments in a healthcare
services organization. As for data verification, the system relies on the ease with which the
coded data may be mechanically processed and properly decoded. In many cases, standard
forms and standard terms are used in recording patient data to ensure data integrity and consistency. Most computerized patient record systems have built-in capabilities to reject invalid data
inputs through the use of range checks (e.g., specifying a patient’s age to fall within a verifiable
1. Patient Medical
Insurance Number:
3. Date of Admission:
/
/
2. Patient Name:
4. Date of Discharge:
Mo/Day/Yr:
/
/
5. Sex:
— Male
— Female
6. Birthdate:
/
/
12. Discharge Status:
Alive:
— With Approval
— Against Notice
PROCEDURES
15. Principal Procedure:
a.
Date:
/
16. Additional Procedures
a.
b.
c.
Death:
— Autopsy
— No Autopsy
7. Tel. No.:
8. Next of Kin:
9. Address:
10. Admission Source:
— Admitting
— Emergency
— Outpatient
11. Location
of Patient:
/
Transfer to:
— Other Institution
— Home
17. History/Physical:
13. Type of Death:
— Anesthesia
— In Operating Room
— Postoperative
— Other
18. Laboratory:
19. Radiology:
14. General Remarks:
PHYSICIANS
DIAGNOSIS
20. Principal Specialist:
21. Principal Diagnosis:
Second Specialist:
Family Physician:
22. Additional Diagnoses:
a.
b.
c.
FIGURE 1.3
A Sample Abstract for a Computerized Patient Medical Record System.
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range of classification) and other means (e.g., using batched totals). After data input, the data
are kept securely (data storage) in a database, a central data repository. This is to ensure that the
data are accessible to the healthcare services providers on any subsequent visits by the same patient. A unique patient identifier and a master patient index (MPI) are used to identify the exact locations of all related records of a specific patient. This type of data organization also allows
for easy processing and regular updating by care provider organizations.
Updating and maintenance of the data (data update) to ensure timeliness and integrity can
be carried out either on a daily basis (i.e., routinely) or interactively (real-time). For example,
some hospitals collate their daily census through batch processing around midnight. Additional
data-processing functions include data analysis and synthesis to transform and combine various
elements of the input data into useful and meaningful information (data computation). The
data retrieval function ensures that the appropriate end-users (e.g., physicians, nurses, quality
improvement managers, and medical researchers) have access to accurate, timely, and relevant
information from the system. The distribution of information to end-users typically occurs
through Web-based services, where appropriate users can be authenticated whenever they want
to abstract certain views of the stored data or perform queries. Ultimately, data presentation in
the context of the preceding example is concerned with generating reports that are easy to read
and interpret for use in informed patient care or related decision making.
IV. HMIS Cultures
Why do HMIS cultures matter? A health information system exists as part of a larger system to
support one or more of a combination of administrative, financial, clinical, research, or managerial activities occurring within a health organization. Yet, it is the culture of the health services
organization that largely determines the appropriate product mix, roll out, and use of HMIS
solutions within the organization. More likely than not, existing and traditional HMIS applications often tend to be disintegrated so that critical information embedded in the different parts
of the organization is not going to be transparent among employees of the organization.
In terms of HMIS cultures, based on what we now know about successful and effective
IS/IT (information systems/information technology) leadership, a healthcare services organization may intentionally or unintentionally adopt and nurture one of four types of cultures: an
information-functional culture, an information-sharing culture, an information-inquiring culture, and an information-discovery culture.8 Understanding the different characteristics of each
of these cultures is important to guide managers, administrators, and systems analysts in generating appropriate HMIS solutions for the organization.
An information-functional culture essentially takes the traditional view that information is
power and that giving up information means giving up the power of controlling others. It also
follows that as most organizations are structured functionally, information-functional culture
therefore limits the flow of information within a functional area such as human resources, accounting and finance, sales and marketing, and IT. For example, nurses in an emergency department of a healthcare services organization adopting an information-functional culture will
attempt to safeguard their own use of patient-gathered information as well as limit the sharing
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of patient records as a way of exerting power over nurses in other departments. Thus, whenever
nurses from the acute care units or other departments need to schedule a care routine of a discharged patient from the emergency department, they would have to involve the emergency department nurses.
In contrast, an information-sharing culture promotes trust among employees of different
departments within the same organization. While needing to be sensitive as to the privacy,
confidentiality, and security of particular information under his or her safeguard, it is important that nurses, physicians, and others be able to share certain types of information with fellow employees for the benefit of the entire organization. For example, the chief medical officer
(CMO) of a hospital who wants to see that his or her direct reports work collaboratively to
benefit the efficient and effective running of the entire hospital must not only encourage sharing of information among individual physicians, but he or she should also focus on making information—especially on procedural problems and patient care process failures—transparent
among the individual physicians in the hospital.
An information-inquiring culture essentially makes transparent the core values, beliefs, and
purpose of the organization and ensures that critical information about the due processes, procedures, and functioning of the organization is easily accessible for all employees throughout
the organization. Employees are also encouraged and trained to actively monitor such information and to align their daily actions and behaviors with the trends and new leadership directions
of the organization. For instance, all nurses and doctors of a healthcare provider organization
could be asked to greet and politely interact with incoming and discharged patients to promote
its reputation as an organization focused on patient care and customer satisfaction. All employees are also clear about how conflicts should and can be resolved quickly and the due procedures
for attending to patient complaints.
Finally, an information-discovery culture entails that the organization is able to share insights freely and encourages its employees to collaborate in offering new products and/or services that meet the needs of existing and new clients. Employees throughout the organization
are also provided with a comprehensive view of how the organization functions and how it will
support them in their attempt to deal with crises and radical changes and/or finding ways to
achieve competitive advantages against its competitors. For healthcare organizations, it is difficult to imagine the adoption of an information-discovery culture, especially among the physicians, because of these organizations’ strong traditional roots in which physicians are
accustomed to make their decisions independently about the patients under their care, even
though they are affiliated with the organizations in which they practice.
Understanding HMIS applications begins with having an appreciation of how health organizations function and how IT is used in these organizations. The complexity of healthcare organizations and the intricacy of its myriad processes often is the root cause of IT failures in
health care. Many health executives thought that slapping a complex HMIS on top of the problems encountered in a healthcare organization would resolve its woes when, in many cases, it
not only worsens it, but adds unnecessary expenses when the root causes of these problems are
not well understood. It is far more important to map out the processes, simplify the complexity,
consolidate the needs, and identify the core IT requirements. From here, management has to
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nurture, cultivate, and respect the working of the HMIS culture and implement appropriate
HMIS solutions accordingly.
V. Conclusion
This chapter started out with a real-world scenario describing the challenge of HMIS integration within a healthcare organization. It briefly highlighted the roots and evolution of HMIS
discipline. The basic components and functions of a health management information system
were further contemplated. It is clear that in order to understand HMIS, students should appreciate the functioning of a healthcare organization, such as the HMIS cultures, before HMIS
solutions can be efficiently and effectively deployed in the organization and used to their full
capacity.
In the next chapter, we highlight the roles of the chief information officer/chief executive
officer for healthcare services organizations. Understanding these roles is critical for managing
and designing future HMIS. Following this, we close Part I of this text with a chapter on how
users are individually seeking health information on the Internet, selecting the best healthcare
providers, and learning to become better-informed consumers. It is hoped that instructors will
find these three foundational chapters in Part I helpful in encouraging students to become excited about the world of HMIS. The scenario at the beginning of each chapter and the minicases, Research Briefs, Technology Briefs, Policy Briefs, additional readings, and discussion questions
that are offered at the end of the chapters are ways to motivate the students’ learning—as well as
to help them seek answers to many more new questions about HMIS—as new knowledge
and technological breakthroughs in HMIS-related fields continue to emerge in a rapidly
changing world.
Notes
1. http://www.digitalhcp.com/2008/05/27/dc-rhio-sets-ambitious-plans.html, accessed May 27,
2008.
2. T. L. Lincoln and R. A. Korpman, “Computers, Healthcare, and Medical Information
Science,” Science 210, no. 4467 (1980): 257–263.
3. ICD-9 is a U.S. Public Health Service official adaptation of a system for the classification of
diseases and operations. The original system was developed and updated periodically by the
World Health Organization for indexing hospital records. See T. C. Timmreck, Dictionary
of Health Services Management (Owings Mills, MD: National Health Publishing, 1987):
306.
4. ICD-10-PCS is purported to be a replacement code set for ICD-9-CM. See http://www
.inhcc.com/Standardization/coding _systems.htm, accessed June 1, 2008.
5. T. Crowe and D. E. Avison, Management Information from Data Bases (New York: Macmillan
Press, 1980).
6. J. K. H. Tan and I. Benbasat, “Processing Graphical Information: A Decomposition
Taxonomy to Match Data Extraction Tasks and Graphical Representation,” Information
Systems Research 1, no. 4 (1990): 416–439.
7. J. K. H. Tan, “Graphics-Based Health Decision Support Systems: Conjugating Theoretical
Perspectives to Guide the Design of Graphics and Redundant Codes in HDSS Interfaces.”
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In J. K. H. Tan with S. Sheps, Health Decision Support Systems (Gaithersburg, MD: Aspen
Publishers, 1998): 153–173.
8. Booz Allen Hamilton, Information Sharing (New York: HarperCollins, 2006). See also www
.boozallen.com.
Chapter Questions
1–1. How does HMIS affect or influence the different departments within a healthcare services organization?
1–2. Why is it difficult to integrate IT and medicine? Discuss the need for an integrated management perspective of HMIS.
1–3. List the five major components of integrated HMIS. Discuss which component deserves
the most attention in today’s HIT environment and why. Provide specific examples of
each component in the context of your work.
1–4. If you were a CIO, which of the four types of IT cultures would you pursue, and why?
1–5. List and illustrate the basic functions of an HMIS. How may these basic functions be extended to accommodate complex health information processing tasks such as medical diagnosis and teleconsultation?
Mini-Case: MinuteClinic
MinuteClinic, owned by pharmacy giant CVS, is a retail healthcare provider with more than
500 locations established throughout the country. The centers are designed to treat patients
with minor injuries or sicknesses, and more than 1.8 million patient visits have been documented since the company’s inception in 2000. By creating a healthcare delivery model that responds to consumer demand, MinuteClinic makes access to high-quality medical treatment
easier for more Americans.
As more patients used MinuteClinic resources, one issue the company faced was how to pass
medical information to primary care physicians. As Cris Ross, chief information officer of
MinuteClinic, explains, “There are a number of things we do very well with physicians, except
connect electronically. We’ve been looking for a business-to-business exchange.”
As a solution to this problem, MinuteClinic recently turned to ePrescribing connectivity
network SureScripts to facilitate this exchange. It is the first time the SureScripts network has
been used for anything other than pharmacy orders and related transactions.
“The idea is that we already have pharmacies connected,” acting SureScripts CEO Rick
Ratliff told Digital Healthcare & Productivity by telephone. “We have an ability to identify a
physician uniquely on the network.”
As part of this connection, MinuteClinic will convert records from its proprietary electronic
medical records system into Continuity of Care Record (CCR) standard format. Ratliff adds
that this record “can be moved around almost like a piece of mail” from provider to provider,
and into personal health records (PHR).
Now with every visit, MinuteClinic practitioners stress the importance of maintaining a
medical home for each patient by making information accessible to primary care providers. If a
patient doesn’t have a primary care provider, MinuteClinic provides a list of physicians in the
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area who are accepting new patients. Practitioners are then able to use a multipurpose softwarebased approach at the conclusion of each visit that generates educational material, an invoice,
and a prescription (when clinically appropriate) for the patient, as well as a diagnostic record
that is automatically sent to the patient’s primary care provider’s office (with the patient’s consent) to facilitate continuity of care.
Mini-Case Questions
1. How might embracing the CCR standard benefit and/or damage MinuteClinic’s overall
profitability?
2. Why does MinuteClinic choose to promote the patient/primary care provider relationship?
3. What patient issues might MinuteClinic face in implementing an electronic record that can
be easily transferred from clinic to physician?
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