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IMPLEMENTATION OF ELECTRONIC HEALTH RECORDS:

MODELING AND EVALUATING HEALTHCARE INFORMATION SYSTEMS FOR

QUALITY IMPROVEMENTS IN THE U.S.HEALTHCARE INDUSTRY

by

Vinata A. Kulkarni

A Dissertation Presented in Partial Fulfillment

Of the Requirements for the Degree

Doctor of Philosophy

Capella University

October 2006


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Vinata Kulkarni, 2006


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Abstract

In spite of several innovative measures in the United States (U.S.) healthcare industry, the

industry is not only lagging behind other industries in its technology adoption, but also in

ensuring basic safety and healthcare quality (Landro, 2001). The healthcare information systems

(HIS) can provide financial and qualitative benefits to the healthcare industry (Wickramasinghe,

Fadlalla, Geisler, & Schaffer, 2003). However, the HIS literature review has indicated a lack of

cost-effective HIS model with uniform healthcare information standards and quality measures, in

the U.S. healthcare information technology documentation. The purpose of this study was to

construct and evaluate the Electronic Health Record (EHR)-centric model to monitor a

predefined set of healthcare quality goals. The quantitative research methodology, strategic

contingency theory of organizational management, and economic value-added concepts of HIS

planning have been applied. Secondary survey data from 1999 to 2004, collected by the

American Hospital Association (AHA) annual survey of hospitals and the Dorenfest Integrated

Healthcare Delivery Systems (IHDS), have been used to determine statistical significance of the

proposed critical success factors of healthcare quality in small, medium, and large size healthcare

organizations. The findings have provided a planning structure for healthcare organizations and

new understanding in healthcare information technology management fields, for improving

quality of the healthcare services.


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Acknowledgments

I would like to express my sincere thanks to the members of my dissertation committee-

Dr. Tsun Chow, Dr. Edward Goldberg, and Dr. Sharlene Adams. They provided me a

constructive feedback, valuable suggestions, and have significantly contributed to the completion

of this dissertation. I am grateful to Dr. Tsun Chow, my mentor and the chairman of this

dissertation committee, for his insightful observations, advice and guidance in my research

study. Also, I am indebted to my teachers and colleagues, who made a positive influence on my

educational journey.

Finally, I would like to thank my husband- Arvind, and my children- son

Vainatey and daughter Anvita, for their patience and full support throughout my doctoral studies.

I also thank my son Vainatey, for his assistance in proofreading and editing my dissertation

document.


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Table of Contents

Acknowledgments iii

List of Tables vii

List of Figures xi

CHAPTER 1: INTRODUCTION 1

Introduction to the Problem 1

Background of the Study 2

Statement of the Problem 5

Purpose of the Study 6

Rationale 6

Research Questions 7

Significance of the Study 7

Definition of the Terms 8

Nature of the Study 12

Assumptions and Limitations 13

Organization of the Remainder of the Study 15

CHAPTER 2: LITERATURE REVIEW 17

The U.S. Healthcare Systems Background 17


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Review of the U.S. Healthcare Information Systems 18

Electronic Health Record through Healthcare Information Systems for Managed

Healthcare Delivery and Quality 22

Theoretical Development and Information Systems Models for Healthcare InformationSystems' Integrity and Quality 25

Healthcare Information Systems and Electronic Health Record Modeling 30

Summary of the Literature Review 36

CHAPTER 3: METHODOLOGY 38

Research Design with the Conceptual Model 39

Measurement of the Variables 49

Validity of the Secondary Survey Data Instrument 60

Hypothesis Testing 61

Log Transformed Linear and Logistic Regression Model 65

Possible Research Study Implications and Recommendations 69

CHAPTER 4: DATA COLLECTION AND ANALYSIS 72

Data Descriptives 73

Hypothesis Testing of Healthcare Quality Profiles 81

Hypothesis Testing of Critical Success Factors' Profiles 84

Log Transformed Linear and Logistic Regression Models 89

Summary of the Predictive and Significant Variables 104

CHAPTER 5: RESULTS, RECOMMENDATIONS, AND CONCLUSIONS 115

Results 116


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Practical Implications 118

Limitations 120

Recommendations for Further Study 121

Conclusions 123

REFERENCES 126

APPENDIXES 140

A. Definition and Description of the Data Variables 140

B. Output from Statistical Package for Social Sciences-Graduate Pack 144Version 13.0


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List of Tables

Table 1: Consolidated Balanced Scorecard and Critical Success Factors Analysis 45

Table 2: Secondary Survey Responses By Bed Size 77

Table 3: Healthcare Quality Descriptives for Small, Medium and Large Integrated Healthcare

Delivery Systems 78

Table 4: Descriptives of Electronic Health Record Centric Critical Success Factors of HealthcareQuality 79

Table 5: Analysis of Variance for Quality Profile Healthcare Information Systems AnnualOperating Cost per bed 83

Table 6: Discriminant Analysis for Quality Profile Health Insurance Portability andAccountability Act (HIPAA) Compliance 84

Table 7: Analysis of Variance for Electronic Health Record Centric Critical Success Factors of

Healthcare Quality 86

Table 8: Discriminant Analysis for Electronic Health Record Centric Critical Success Factors87

Table 9: Canonical Discriminant Functions for Electronic Health Record Centric Critical Success

Factors 88

Table 10: Log Transformed Linear Regression Model Summary 94

Table 11: Log Transformed Linear Regression Model for Small Size Integrated

Healthcare Delivery Systems Organizations 95

Table 12: Log Transformed Linear Regression Model for Medium Size Integrated

Healthcare Delivery Systems Organizations 96

Table 13: Log Transformed Linear Regression Model for Large Size IntegratedHealthcare Delivery Systems Organizations 97

Table 14: Logistic Regression Model Summary for Small Size Integrated Healthcare DeliverySystems Organizations 100


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Table 15: Logistic Regression Model Summary for Medium Size Integrated Healthcare DeliverySystems Organizations 101

Table 16: Logistic Regression Coefficients Summary for Large Size IntegratedHealthcare Delivery Systems Organizations 102

Table 16a: Logistic Regression Model Summary for Large Size Integrated Healthcare Delivery

Systems Organizations 103

Table 17: Summary of Predictive and Significant Factors of Healthcare Information Systems(HIS) Annual Operating Cost per Bed 105

Table 18: Summary of Predictive and Significant Factors of Health Insurance Portability andAccountability Act (HIPAA) Compliance 106

Table B1: Dependent Variable: Healthcare Information Systems (HIS) Annual Operating Costper Staffed Bed (1999-2003) 144

Table B2: Dependent Variable: Health Insurance Portability and Accountability Act (HIPAA)

Compliance (2002-2003) 144

Table B3: Dependent/Explanatory Variables: Descriptive Statistics 145

Table B4: Test of Homogeneity of Variances 147

Table B5: Discriminant Analysis: Health Insurance Portability and Accountability Act (HIPAA)Compliance 149

Table B6: Discriminant Analysis: Physicians' Usage of Healthcare Information Systems 150

Table B7: Discriminant Analysis: Affiliation Status 151

Table B8: Discriminant Analysis: Strategic Usage of Healthcare Information Systems 152

Table B9: Discriminant Analysis: Healthcare Information Systems Connectivity 153

Table B10: Discriminant Analysis: Electronic Health RecordSupporting TechnologyApplication Status 154

Table B11: Discriminant Analysis: Utilization of Patient Safety Software Applications 155


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Table B12: Discriminant Analysis: Status of Clinical data security issues 156

Table B13: Small Bed Size Model Summary 157

Table B14: Small Bed Size Model Summary After Removing Factors Information Systems Staffand Information Systems Servers 159

Table B15: Medium Bed Size Model Summary 161

Table B16: Large Bed Size Model Summary 163

Table B17: Large Bed Size Model Summary After Removing Information Systems Staff and

Information Systems Servers 163

Table B18: Large Bed Size Model SummaryUsing Stepwise Regression/BackwardRegression 165

Table B19: Small Bed Size: Health Insurance Portability and Accountability Act (HIPAA)Compliance Model Summary 167

Table B20: Small Bed Size Health Insurance Portability and Accountability Act (HIPAA)Compliance Model: Standardized Canonical Discriminant Function Coefficients 168

Table B21: Small Bed Size Health Insurance Portability and Accountability Act (HIPAA)

Compliance Model Summary Using Block One Backward Stepwise (Conditional)

Method 169

Table B22: Medium Bed Size Health Insurance Portability and Accountability Act (HIPAA)Compliance Model Summary 170

Table B23: Medium Bed Size Health Insurance Portability and Accountability Act (HIPAA)Compliance Model Using Block One and Backward Stepwise Likelihood Ratio

Method 171

Table B24: Medium Bed Size Health Insurance Portability and Accountability Act (HIPAA)Compliance Model if Terms Removed 175

Table B25: Medium Bed Size Health Insurance Portability and Accountability Act (HIPAA)Compliance Model: Standardized Canonical Discriminant Function

Coefficients 177


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Table B26: Large Bed Size Health Insurance Portability and Accountability Act (HIPAA)Compliance Model Summary 178

Table B27: Large Bed Size Health Insurance Portability and Accountability Act (HIPAA)Compliance Model Summary with Block One Backward Stepwise Likelihood RatioMethod 179

Table B28: Large Bed Size Health Insurance Portability and Accountability Act (HIPAA)Compliance Model if Terms Removed 180

Table B29: Large Bed Size Health Insurance Portability and Accountability Act (HIPAA)Compliance Model: Standardized Canonical Discriminant Function

Coefficients 183


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List of Figures

Figure 1: Electronic Health Record-centric building blocks of healthcare integration 42

Figure 2: The conceptual model of Electronic Health Record-centric healthcare quality 48

Figure 3: The number of beds and hospitals for American Hospital Association- registered

hospitals 73

Figure 4: The bed size category and patients' admissions for American Hospital Association-registered hospitals 74

Figure 5: The Out patients' visits & full time equivalent personnel for American HospitalAssociation- registered hospitals. 75

Figure 6: Total expenses and revenue for American Hospital Association- registeredhospitals 76

Figure 7: Normal approximation of log transformed healthcare information systems annual

operating cost per bed for small bed size healthcare organizations. 93


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CHAPTER 1. INTRODUCTION

Introduction to the Problem

The healthcare industry is an economically and socially significant portion of the United

States (U.S.) industry sector. The industry represents a fifth of the U.S. economy and carries

social significance due to its ongoing focus on quality of the services. However, the healthcare

industry is not only lagging behind other industries in its technology adoption, it is also behind

other high risk industries in ensuring basic safety and healthcare quality (Landro, 2001). While

the U.S. healthcare "absorbs more than $1.7 trillion per year--twice the Organization for

Economic Cooperation and Development (OECD), average-premature mortality in the country is

much higher than OECD averages" (Hillestad, Bigelow, Bower & Girosi, 2005, p. 1103).

The Institute of Medicine (IOM) committee on quality healthcare in America has taken

initiative steps on healthcare quality since 2000 (Sokol & Molzen, 2002). The IOM committee

presented a series of quality reports identifying gaps in healthcare quality in areas including

healthcare information systems (HIS) and patient safety (Swan, Lang & McGinley, 2004). As per

the IOM report, errors in the healthcare industry are due to failures in organizational systems and

various organizational factors. The IOM and the Joint Commission on the Accreditation of

Healthcare Organizations (JCAHO) are trying to implement error-reducing processes. In a series

of reports, IOM recommended implementing an electronic health record program (EHR) to

achieve effective coordination of clinical services and in turn to improve healthcare quality

(IOM, 2001, 2003b). At present, when several healthcare practitioners treat a patient, they often


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do not have complete information about the medicines prescribed or details about their patient's

illnesses.Most medical records are still stored on a paper, which makes it difficult to properly

coordinate care and provide detail information to the consumers about healthcare costs or quality

and to make informed decisions about their care (Hillestad, et al., 2005).

Healthcare literature indicates the existence of some healthcare errors due to scribbled

writing in medical records and prescriptions that resulted in administration of a drug for which

the patient had a known allergy. Lesar, Ben, and Henry (1997) pointed that if healthcare

providers have timely information about their patients and the prescribed medication with the use

of computerized systems and EHR, many of these errors could be avoided.Another important

current issue observed is that segments of the healthcare industry and individual providers have

adopted technology at different rates and a gap is widening between the most wired and the

least wired providers (Solovy, 2000).According to Hillestad et al. (2005, p. 1104), "the U.S.

trails a number of other countries in the use of EHR. Only 15-20 % of the U.S. physicians'

offices and 20-25 % of hospitals have adopted such systems." Thus, in spite of several innovative

measures in the U.S. healthcare industry, there are still many barriers in EHR implementation

that include high costs, a lack of certification and standardization of IT tools, and an inadequate

HIS infrastructure. HIS cost reduction and improvement in quality of services are two important

issues of the U.S. healthcare industry while implementing EHR.

Background of the Study

As per GAO Report (2004, para.1), from 1992 to 2002, the U.S. healthcare spending

"increased from $827 billion to about $1.6 trillion and it is expected to nearly double to $3.1

trillion in the subsequent decade." The Peirce (2004) analysis of cost and wages indicated a rapid


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increase in medical costs compared to that in wages, which is a threat to the global

competitiveness of the United States. Although the United States leads the world in per capita

medical spending, life expectancy of people in the U.S. is approximately same as Cuba's and

significantly behind nations such as France, New Zealand, Spain, and Singapore (Peirce, 2004).

High healthcare costs, errors in medical data recording systems, administrative inefficiencies,

and lack of system coordination are some of the concerning issues of the U.S. healthcare

industry. According to the estimates made by the IOM, there are some 44,000 losses of human

life in the U.S. hospitals each year, and there are more losses of life due to medical mistakes than

from highway accidents, breast cancer, or AIDS each year (Tickner, 1999). According to the

IOM report, the total national cost for adverse events is estimated to be between $37.6 and $50

billion. Also, at present, the application of health information technology (HIT) to clinical

records is quite slow.

Thus, at present, an integration of HIT into the nation's healthcare system seems quite

inadequate (White House Statement, 2004). There is variation in the healthcare quality within

and across communities, hospitals, practitioners, patients, delivery systems, geographic areas,

and health problems. Researchers have demonstrated that even for the same groups, healthcare

quality performance varies considerably at different times and situations, which makes it difficult

to develop programs to improve healthcare quality based on the current knowledge. Teisberg,

Porter, and Brown (1994, p. 131) suggested innovation as "the fundamental driver of continuous

quality improvement and cost reduction." Thus, considering the seriousness of medical errors

and the technology potentialto decrease medical errors, the healthcare industry needs a specific

guideline for reducing cost and improving quality of the healthcare.


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Many accreditation agencies, state governments, business coalitions, and U.S.

government agencies are proposing solutions to decrease the medication errors. The Agency for

Healthcare Research and Quality (AHRQ) designed the national healthcare disparity report

(NHDR) and national healthcare quality report (NHQR) to provide policy makers with snapshots

of disparities and quality of healthcare in the U.S. (Moy, Dayton, & Clancy, 2005). One of the

objectives of the IOM Report was to establish a national goal of reducing the number of medical

errors by 50% over 5 years (Kohn, Corrigan, & Donaldson, 2000). To accomplish this goal and

to reduce the medical mistakes, the healthcare advisers have created a four-tiered framework.

The framework includes establishing a national focus to create leadership, research, tools, and

protocols to enhance the knowledge base about safety; identifying and learning from medical

errors through mandatory and voluntary reporting systems; raising standards and expectations for

improvements in safetythrough the actions of oversight organizations, group purchasers, and

professional groups; and implementing safe practices at the delivery level.

On January 27, 2005, the U.S President took an important step in the nation's health IT

plan by signing the electronic prescribing (e-prescribing) proposed regulation by the Centers for

Medicare and Medicaid Services (CMS) at the Department of Health and Human Services

(HHS). Also, recently the U.S. President signed the new Patient Safety and Quality Improvement

Act (White House, 2005) with an objective to create an incentive for healthcare providers to

report medical errors to a centralized database. By April 2006, "new healthcare information

security provisions designed to protect data transmitted and stored electronically will go into

effect under the Health Insurance Portability and Accountability Act (HIPAA) medical privacy

law"(Swartz, 2004, p.26). The U.S. national healthcare plan is to facilitate EHR to most


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Americans within the next 10 years.Consequently the objective of EHR implementation is to

achieve expected qualitative benefits, such as easy storage and access to medical information,

prompt response in medical services, elimination of errors and duplicative testing due to lost

laboratory reports, patient safety, and reduction in time and cost of the healthcare services.

Statement of the Problem

The problem in the U.S. healthcare industry, while emphasizing HIT documentation is a

lack of an EHR-centric, cost effective HIS model with uniform healthcare information standards

and pre-defined healthcare quality measures. Though several promising efforts and many

innovative measures are in progress for broader adoption of EHR across the entire U.S.

healthcare system, there are some barriers in attaining desired efficiency of services of the

healthcare systems while implementing EHR. Kibbe (2004, para. 5)evaluated key barriers to the

deployment of EHR at the national level such as "high prices, risk of implementation failure,

lack of connectivity and interoperability, confusion about the product and company reliability for

EHR, and variation in HIS and healthcare business practices." According to Maffei (1997),

though nature of the healthcare industry is basically customer service oriented, for the past

decade, focus of the U.S healthcare services is not only caring for the sick and injured, but also

preventing illness and injury, and reducing clinical errors in the healthcare practices Thus,

nationwide emphasis on HIT documentation and implementation of EHR has established a need

for an IT based model to help document, categorize, control, and transfer knowledge while

attaining the healthcare quality.


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Purpose of the Study

The purpose of this study was to construct and evaluate a conceptual HIS model for EHR

implementation and suggest outcome measures to monitor the healthcare quality. The underlying

key to gaining the healthcare quality improvement is identifying critical success factors for

strategic HIS management during EHR implementation (Baker & Pink, 1997; Zani, 1970). With

a focus on predefined healthcare quality goals, the model is built on strategic contingency theory

of organizational management and economic value added concepts of IS planning.

Rationale

One of the advantages of good information systems (IS) is that these systems facilitate

healthcare providers in creating a budget and accurately calculating the costs to treat a group of

patients (Montague, 1994). EHR is one of the useful repository sources for documentation of a

patients medical information and healthcare outcomes that can capture required data and display

it to make timely decisions on healthcare. Brailer and Von Horn (1993) suggested investment in

employee education because more and more employees are getting involved in the control of

healthcare delivery that implicitly involves providing consequential information and relevant

data. Porter and Teisberg (2004) recommended a collection and wide distribution of standardized

healthcare information about individual diseases and treatments that would facilitate patients to

make informed choices about their care. According to Porter & Teisberg (2004), setting up a

transparent billing and pricing mechanisms by payers, providers, and health plans would reduce

cost, confusion in data handling, pricing inequality, and other possible inefficiencies in the

system. Thus, effective development methodology and business processes with HIS architectural


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vision could be the key factors to implement and evaluate EHR in view of the associated costs,

benefits, risks, and predefined values.

Research Questions

While the U.S. healthcare costs are constantly escalating, there is also an increase in the

healthcare budget at the national level to expedite development and adoption of EHRs and

supporting technologies. As per the press release on October 13, 2004, The U.S. Department of

Health and Human Services announced $139 million in grants and contracts to promote a use of

health information technology (HIT)"(Anderson, 2004, p. 3).Consequently, as pointed by Al-

Faris (1995, p. 24), "the fundamental challenge to IS decision makers is how to sustain quality of

patient care delivery while earning profit." The implicit questions examined in the study are:

1. How can cost effective and value added healthcare quality be achieved through

strategic healthcare information management (HIM) while implementing EHR?

2. What are the critical success factors for achieving the healthcare quality while

implementing EHR?

Significance of the Study

Although the healthcare literature indicates varied strategies about classification of

medical errors, including types of healthcare services provided, severity of the resulting injury,

legal definition, type of setting, and type of the individual involved, to the best knowledge of this

author, those strategies lack a common framework. According to Borel and Rascati (1995),

researchers, healthcare providers, various healthcare agencies, and related businesses have tried

to develop their own solutions to decrease clinical errors. Kettelhut (1992, p. 18) suggested,

"Hospitals and clinics must upgrade feedback and control systems in order to track costs,


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Acute care hospital. As per the description in Dorenfest database, it is a healthcare

facility that "services individuals with less than chronic diseases on an inpatient basis."

Sub-acute care hospital. According to the description in Dorenfest database, a healthcare

facility that "services individuals with chronic diseases: long-term, skilled nursing, behavioral

health, psychiatric facilities, inpatient hospice."

Ambulatory care hospital. According to the description in Dorenfest database, it is a

healthcare organization that "offers preventive, diagnostic, therapeutic, and rehabilitative

services to individuals not classified as inpatients or residents. This category also includes

physician offices."

Information systems. Hirschheim, Klein, and Lyytinen (1995) described information

systems (IS) as "a technologically implemented medium for recording, storing, and

disseminating linguistic expressions, as well as for drawing conclusions from such expressions."

Information systems application. Ferrand and Lay (1994) described an IS application as

an integrated group of computer programs and associated data that support end-users in carrying

out one or more of their business functions.

Healthcare information systems. The National Library of Medicine (Medicare Payment

Advisory Committee, 2001) defined healthcare information systems (HIS) as integrated

computer-assisted systems to store, manipulate, and retrieve healthcare administrative and

clinical data.

Data and information. Though the term data and information are often used

interchangeably, as per Tan (1995),data are primary building blocks of HIS while information is


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Medicare HMO. This is"the HMO that has contracted with the federal government under

the Medicare Advantage program to provide health benefits to persons eligible for Medicare who

choose to enroll in the HMO, instead of receiving benefits and care through the traditional fee-

for-service Medicare program" (Medicare HMO, n.d.).

HIPAA. HIPAA is the acronym for the Health Insurance Portability and Accountability

Act of 1996. The Center for Medicare & Medicaid Services (CMS) is responsible for

implementing various unrelated provisions of HIPAA. The administrative simplification

provisions of the HIPAA of 1996 (HIPAA, n.d.) require the Department of Health and Human

Services to establish the national standards for electronic healthcare transactions and national

identifiers for providers, health plans, and employers. HIPAA also addresses patients' safety and

security and privacy of health data (CMS, 2005).

Nature of the Study

This study is based on quantitative research methodology. Robson (2002, p. 6) mentions

"there are some circumstances where quantitative designs are preferred, and others where

flexible qualitative ones are more appropriate." This research has included a set of explanatory

variables based on HIS, operational characteristics, and internal and external factors of the

healthcare organization, and the healthcare quality as a dependent variable. The data variables

are operationalized with quantitative measures. Based on the proposed conceptual research

model, the study used descriptive and inferential multivariate statistical analysis and statistical

tests of hypotheses to observe the casual relationship between dependent variable and

explanatory independent variables. Hence, with such analytic methodology, quantitative analysis

with fixed research design is a suitable research methodology (Robson, 2002).


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In this study, a non-experimental longitudinal design with multivariate data was

examined over an extended time series. As longitudinal data on some of the variables was not

available, cross sectional multivariate data was used in those situations. The individual

community hospital was considered a unit of analysis. Annual data containing information about

the hospital characteristics, predefined quality measures, and the healthcare information systems

and technology programs were collected from authentic secondary data sources. According to

Robson (2002), advantages associated with secondary data are as follows. It is possible to tap

into extensive data sets, often drawn from large representative samples well beyond the resources

of an individual researcher. It is an unobtrusive measure in a sense that any individual researcher

who is using it does not affect such data collection. Miles and Huberman (1994) mentioned that

pragmatic operationalization of research requires economy, convenience, and interpretability of

results. As discussed by Robson (2002), the secondary data records are in a permanent form,

which facilitates reanalysis, reliability checks, and replication studies, and provides a low cost

form of longitudinal multivariate statistical data analysis. In view of these advantages of

secondary data, longitudinal quantitative secondary data from 1999 through the most recent

available time period was collected from the American Hospital Association (AHA) annual

survey of hospitals and The Dorenfest Integrated Healthcare Delivery System Database (IHDS).

Assumptions and Limitations

HIS is not the entire solution to tackling quality related issues of the healthcare industry.

This study concentrates on a limited focus of the healthcare quality through HIS to better

understand how EHR implementation with HIS can be one of the effective controlling and

driving factors to improve the healthcare quality. As per Stetson and Andrew (1996), focus of


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EHR is to improve the healthcare quality in terms of reducing the clinical processing time and

avoiding repetition of certain routine tasks, such as filling in the billing forms, writing

prescriptions, and requesting diagnostic studies. The healthcare literature indicates there are

several assumptions and characteristics of EHR, such as flexibility in information display format;

accessibility of information to the healthcare providers, administrators, and researchers; data

security; and authenticity in data access. Thus, this study has several assumptions including but

not limited to:

HIS-based healthcare quality evaluation is a comprehensive approach that includes not

only utilization of IS resources, financial indicators, and healthcare quality in terms of reduced

errors, increased safety measures, and cost reduction; but also should include patient satisfaction

of the services (Shortell, 2001). At present, EHR implementation is still in its developing stage at

macro level of the U.S. healthcare systems, and data to track EHR-related satisfaction of patients

and healthcare providers is not available to this writer. With widespread adoption of EHR

systems and robust HIS, her-related satisfaction of patients and healthcare providers should be

evaluated in future studies. Although this study used authentic data resources, such as AHA and

Dorenfest survey data, these data sets represent broad canvassing of only acute care hospitals,

chronic care facilities, and ambulatory practices on their adoption of and plans to adopt various

HIT components. The study did not include long-term care that should be considered for more

detailed analysis and conclusions in the future. Longitudinal data was not available for some of

the data variables described in this study. In those cases, the data analysis was based on cross

sectional data sets.


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Although a conceptual model in the methodology section of this study has provided a

comprehensive healthcare quality model through critical success factors of EHR implementation;

data on few of the proposed critical success factors: (a) IS management of patients records, (b)

patients' awareness of EHR functionality, (c) remote patients' data access and management, (d)

prevention of clinical negligence and adverse events through HIS were not available at the time

of the study. Also, data on some predefined quality goals, namely- reduction in clinical data

errors, patient waiting time for the healthcare/clinical services and patient satisfaction of the

healthcare services, were not available to this writer at present.

Thus, data analysis has focused on the predictive influence of several critical success

factors as challenges impacting on the design and management of HIS with two proposed

measures of quality goals: cost effectiveness and HIPAA compliance. The research framework

acknowledges the existence of other challenges in view of the quality goals of an increase in

patient satisfaction and reduction in a patient waiting time for the healthcare and clinical

services. These challenges are beyond the scope of data analysis of this study; however, they are

reflected in the proposed conceptual model for completeness.

Overall, the estimators from the conceptual model did not provide predictions of what

will happen, but of what could happen by capturing dominant strategic IS management themes,

critical success factors of environmental determinants, organizational determinants, and

innovational determinants of the healthcare quality while implementing EHR.

Organization of the Remainder of the Study

The research problem, background, purpose, and rationale of the study, the research

questions, significance and nature of the study, relevant definitions of key terms and concepts,


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and assumptions and limitations of the study are presented in Chapter 1. Chapter 2 presents the

literature review on HIS, EHR, and healthcare quality. Chapter 3 provides the research

methodology and develops the conceptual framework for modeling and evaluating HIS in view

of EHR implementation for healthcare quality. The research methodology contains quantitative

techniques for the conceptual research design, data sources, data variables and their measurement

criteria, and multivariate statistical techniques to examine and evaluate the relationships between

data variables involved in EHR implementation for improving the healthcare quality. Chapter 4

presents data collection tools and techniques and statistical data analysis. Chapter 5 provides the

evaluations of the research findings based on the statistical output of the tests of hypotheses.

Finally, implications, limitations and directions for future study are presented.


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CHAPTER 2. LITERATURE REVIEW

This chapter presents the literature review relevant to the U.S. healthcare system

background, the U.S. healthcare information systems (HIS), and implementation of EHR through

HIS for managed healthcare delivery and quality. Also reviewed are general theoretical

development and IS models in view of HIS integrity and quality and HIS modeling for the

healthcare quality while implementing EHR. Finally, conclusions of the literature review are

summarized. The discussion is built on several concepts presented in this author's unpublished

paper work at Capella University (Kulkarni, 2005a, 2005b, 2005c, 2005d) andon review of

published scholarly literature on HIS and the U.S. healthcare quality.

The U.S. Healthcare Systems Background

Before World War II, U.S. healthcare and health insurance was available through some

community institutions (Beach, 2005). During World War II, the main goal of the healthcare

plan was "to attract skilled workers that resulted in increased productivity and lots of corporate

loyalty"(Brailer & Von Horn, 1993, p. 126). The literature review indicates that since the 1970s,

instead of providing an attractive employee benefit, healthcare cost is continuously rising.

During the early 1980s, growing private industrialization and governmental concerns over rising

healthcare costs resulted in managed healthcare systems. A managed healthcare system is

defined as "Any system that manages healthcare delivery with the aim of controlling costs; these

systems typically rely on a primary care physician who acts as a gatekeeper through whom the

patient has to go to obtain other health services, such as specialty medical care, surgery, or


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physical therapy" (MedicineNet.com, n.d.). Since 1990, focus of managed healthcare is more on

operating procedures. The current healthcare infrastructure of the U.S. has significantly changed

to publicly provided healthcarecoverage, largely through Medicaid and Medicare, which may

have implications on total cost of the healthcare, and on the communication system between the

healthcare providers (doctors, nurses, healthcare administrators, and hospitals), and patients who

are in need of the healthcare.

Review of the U.S. Healthcare Information Systems (HIS)

Information technology (IT) has played a major role in the healthcare delivery. Use of

computers in the healthcare arena is dated back to the 1960s (Shortliffe, 2005). During the early

60s, leading IT companies such as International Business Machine Corporation (IBM), National

Cash Register Company (NCR), and Honeywell started offering healthcare application devices to

U.S. hospitals with a goal of improving healthcare and hospital productivity in terms of cost

effectiveness (Bekey & Schwartz, 1972). During the early 1970s, there was a small group of

hospitals that started adopting HIS (Hodge, Gostin & Jacobson, 1999). However, in the past, HIS

initiative was basically for automation of the business office and for the healthcare tools and

techniques related to diagnostic, therapeutic and surgical applications. During the 80s, with

innovations in database designs, HIS applications made some developments in planning and

administration of the healthcare data. During the same period, HIS also introduced low cost

financial systems for hospitals under 200 beds in size (Sneider, 1987). One of the goals of HIS

was to facilitate "the administration, processing of the centralized and distributed healthcare data,

and the development of effective system networking" (Mantas, 1992, p. 570). Over time, HIS

expanded to cover departments, clinics, and hospitals (Berger & Ciotti, 1993).


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As healthcare organizations grew in size and complexity of operational procedures,

"corporate philosophy focused more on core businesses and outsourced other activities"

(Sandrick, 1994, p. 60). As new trends emerged in the healthcare industry, it became more

challenging to incorporate innovation and competition into the risk-adverse healthcare industry

(Teisberg et al., 1994). These researchers suggested four categories of measures of the medical

outcomes that are adopted by the healthcare industry, as follows. These four measures of the

medical outcomes can provide a guideline to the healthcare providers for assuring quality of the

healthcare services.

1. Clinical health is described as traditional biomedical and physiological health

status.

2. Functional health is described as quality of life and general well-being is

considered in view of the subjective evaluation by the patient of himself.

3. Healthcare satisfaction is described as consumers' attitude and responses to the

experience of seeking and receiving care.

4. Healthcare cost is related to acquiring the desired level of health outcome.

Davenport (1994, p. 120) presented parallel views in his "human centered IT approach,"

pointing to the fact that the focus of corporations shifted from hardware and software to how

"people in an organization acquire, share, and make use of the information." As per Davenport

(1994), the objective of human centered IT is to employ adequate methodologies to enhance

usage of the information. These arguments are quite applicable to adoption of HIS to support

collection, processing, and dissemination of the healthcare data. Boynton (1993) also suggested

strategic management of the information while building long-term process capabilities.


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According to the literature review, since the mid 1980s, different hospitals used varied

systems from different vendors in their departments. However, in spite of increase in the HIS

costs, there was inadequate HIS interface and communication, and overall, HIS integration

became a major issue in the process of improving healthcare services (Sneider, 1987). Since

then, HIS has played an important role in the structure of the healthcare systems.

Several researchers have proposed frameworks with various perspectives to examine HIS

integrity. Based on the sample survey analysis of hospitals, Longo, Bohr, Miller, and Miller

(1990) concluded there was an increased need for the healthcare information data. Griffith,

Smith, and Wheeler (1994) demonstrated the evolution of strategic governance of IS in the

hospitals. MacLeod (1995) emphasized strategic management of the healthcare information

systems.As pointed byKongstvedt and Plocher (1995), the transition from fee-for-service to the

managed healthcare systems with a goal of cost minimization and quality improvement further

led to developments of an integrated HIS. Merlo and Freundl (1999) analyzed the factors

responsible for inefficient HIS in the healthcare organizations. These researchers concluded that

a lack of data integration is a barrier to the effective data analysis. Norrie and Blackwell (2000)

conducted a case-based study and concluded that a computerized patient data management

system can save administrative time and cost and can increase performance of the healthcare

organization. Ma (2003) analyzed the cross sectional sample survey data and reviewed HIS

applications on two dimensions, namely, basic functionality of HIS in administration and patient

care, and the global nature of the HIS application across and beyond the healthcare organization.

Based on his study, Ma (2003) concluded that HIS integrity is one of the driving factors of the

healthcare organization's performance.


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Several IT developments evolved in the U.S. healthcare system through government,

professional, and research environments (Shortliffe, 2005).At present, the National Library of

Medicine (NLM), the National Center for Research Resources (NCRR), the Agency for

Healthcare Research and Quality (AHRQ), the American Medical Informatics Association

(AMIA), and the Healthcare Information and Management Systems Society (HIMSS), are some

leading agencies that are conducting research programs and making recommendations for

development of IT projects in the healthcare industry. Additionally, federal advisory groups such

as the National Committee on Vital and Health Statistics (NCVHS), National Research Council

(NRC), and the Institute of Medicine (IOM) are "educating the public, the health professions,

and policymakers regarding health IT topics" (Shortliffe, 2005, p. 27). He pointed out that

culture, the business case, and structural realities such as poor appreciation of IT as a strategic

asset; lack of structured knowledge and criteria in determining IS capabilities and

implementation processes; poor coordination; and a lack of generally accepted standards in

decision making regarding IT investment are the major barriers in successful implementation of

integrated HIS within the U.S. healthcare system (Shortliffe, 2005).

The literature review indicates an exponential increase in the use of the Internet during

the last decade, which made it possible to have easily accessible information on health

promotion, disease prevention, and disease management. Clinicians, politicians, and researchers

all have an increased recognizition of the inevitable role of IT in healthcare delivery. However,

as per Fadlalla and Wickramasinghe (2004, p. 65), along with cost reduction and quality

improvement, the U.S. healthcare industry is facing a challenge to meet a "stringent timeline to

become compliant with the health insurance portability and accountability act (HIPAA)


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regulatory requirements." These researchers emphasized a need for robust HIS so that the

"information that is captured, generated and disseminated by HIS can be of the highest possible

integrity and quality, as well as compliant with regulatory requirements" (p. 65). Medicare's

recent pay-for-performance initiative encourages improved quality of care through approaches

requiring forms of monitoring and data management. However, these approaches are difficult to

implement due to the current lack of robust health information systems (CMS, 2005).

Electronic Health Record through Healthcare Information Systems for

Managed Healthcare Delivery and Quality

The literature review indicates a need for effective IS implementation, not only with a

cost-centric approach, but also with a healthcare quality focus. Although HIS is not the only

avenue to addressing all the quality issues of the healthcare industry, it can be one of the

controlling and driving factors to improve healthcare delivery. Austin (1989) commented that

quality information is the result of quality information systems. Many researchers emphasized a

need for strategic HIS developments and evaluations prior to the selection of an operation model

and linking HIS to improvement in the organization's performance (Cerne, 1993; Halverson,

1996; Martin, 1996; Teisberg et al., 1994; Ummel, 1997). Austin and Boxerman (1997)

demonstrated some qualitative benefits of HIS in clinical and administrative applications. Prince

and Sullivan (2000) presented the conceptual framework for HIS integration and suggested

implementation of EHR at various medical services to enhance HIM capabilities. The U.S.

Department of Health and Human Services estimated about $140 billion annual savingabout

10% of total U.S. health spending through implementation of EHR-centric nationwide health

information network, resulting in improved healthcare and reduction in duplication of medical


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tests (Brailer, 2004).Thus, as pointed by the Institute of Medicine (2001), EHR could be one of

the potential key elements to improving healthcare quality through integrated and interoperable

healthcare information systems.

At present, when several healthcare practitioners treat a patient, they often do not have

complete information about their patient's illnesses or the medicines previously prescribed to the

patients.The IOM (2001) report mentioned that a majority of the clinical errors are not due to

carelessness of an individual, but due to errors in organization and management of the healthcare

systems. Independent studies have cited many situations of medical practices that do not meet

the required norms and result in healthcare errors that take several lives every year (Peirce,

2004). The research literature indicates that the healthcare and the non-health care organizations

are not different in maturity of quality management. As per Hartman, Fok, Fok, and Li (2002),

an increasing maturity in quality management appears to be related to at least some of the

changes in the information systems. HIS implicitly involves technology implications in the

organizational system.Technology has a potential to improve quality of the healthcare, safety,

effectiveness, patient-centered care, timeliness, and efficiency (Kohn, Corrigan, & Donaldson,

2000; Sokol & Molzen, 2002). Several healthcare studies indicated that archaic information

systems of the U.S. hospitals and clinics could have a negative effect on quality of patient care

(Swartz, 2004). Some of the reported causes of medical errors include "multiple physicians

treating the same patients without all having access to all the patients' medical records and with

each storing different, incomplete medical records in different places" (Swartz, 2004, p. 20).

Researchers have suggested integrated HIS for quality improvement in the healthcare

delivery. According to Swartz (2004), there is consensus among the healthcare industry experts


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that EHR based HIS would provide more coordination and higher quality of healthcare and

would reduce errors due to hand written prescriptions. Werder and Deng (1999) pointed that, in

the past, HIS were mostly proprietary solutions, acquired in separate modules and tightly

coupled through ad hoc means. Such HIS resulted into the stovepipe systems: each collected

patient-care data differently and many had duplicated large amounts of data and non-

interoperable functions. Today's HIS have to link together hospitals, clinics, physician offices,

and other business units that are mutually dependent, yet located at different places, each with

distinct business functions (Werder & Deng, 1999).

Today's HIS are quite complex and critical enterprise systems. As per the opinion of

Werder and Deng (1999), a transition from the earlier stovepipe systems to the next generation of

open HIS with interoperability and maintenance is a real challenge to healthcare information

management. Based on their case study, these researchers concluded that adoption of standard

architecture andinfrastructure is the best approach to achieve interoperable, extensible, and

cohesive HIS. While suggesting HIS reforms, Porter and Teisberg (2004) recommended the

collection and wide distribution of standardized healthcare information about individual diseases

and treatments that would facilitate patients to make informed choices about their care.

According to Porter and Teisberg (2004), setting up transparent billing and pricing mechanisms

by payers, providers, and health plans would reduce cost, confusion in data handling, inequality

in pricing, and other inefficiencies in the system.

Thus, the literature review indicates that effective IS development methodology and

supporting business processes with HIS architectural vision could be some of the key factors

while implementing EHR. Also, the literature suggests to evaluation of IT project in terms of


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associated costs, benefits, risks, and values. Researchers have described various approaches to

evaluate HIS and have constructed healthcare models based on different evaluation criteria of

decision making, durable products, financial benefits, and integration for optimal application of

IT in the healthcare industry, as well as using cost benefit analysis as evaluation tool (Maffei,

1997). The following section explores relevant theoretical background and conceptual models in

IT literature applicable to EHR implementation for healthcare quality improvement.

Theoretical Development and Information Systems Models for

Healthcare Information Systems Integrity and Quality

The information systems literature in general, and HIS literature in particular, contain

various organizational theories of performing HIS management and provide guidelines to

improve performance of the organization. The classical approach of the universalistic theories

focused on IS management and how it could be improved. However, as per Galliers and Leidner

(2003), the classical approach is narrow because it assumes that organizations have the same

structure, and the approach does not provide integrative perspectives of IS management.

According to the contingency theory, "organization design decisions are contingent (depend) on

environmental conditions" (Scott, 2003, p. 97). The contingency theory suggests the possibility

of alternative ways to organize and variation in the effectiveness of such alternative strategies;

and thus the theory provides an integrative strategic perspective of IS management (Galbraith,

1973).

Some researchers opposed the conventional contingency approach that considers

organizational environment as the determinant of its structure. Many researchers proposed a

strategic contingency theory that assumes several internal and external factors, such as


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organizational size, resources, managerial perspectives, technological developments and

adaptiveness, market and regulatory constraints during organizational decision-making, IS

planning, and its strategic management, to achieve goals of the organization (Miller, 1992; Scott,

2003;Van de Ven, 1986). Several IS researchers (Chan, Barclay & Copeland, 1997; Sabherwal &

Kirs, 1994; Sambamurthy & Zmud, 1992) supported such a strategic contingency theory

approach. These researchers empirically demonstrated that there is improvement in the

organizational performance through greater alignment and coordination between IS and business

units.

Young, Parker, and Charns (2001) examined the value of the contingency theory for

guiding empirical studies on healthcare provider integration. In the opinion of these researchers,

healthcare organizations should match their information processing capabilities with information

processing requirements in order to achieve optimal performance. Young et al. (2001, p. 77)

argued that the value of the "contingency theory depends on its ability to withstand rigorous

empirical testing." Young et al. (2001) pointed to the challenge to assess whether healthcare

providers have achieved optimal fit "between their organization's operating environment and

organization's internal design" (p.79). Thus, the Young et al. (2001) conclusions imply that,

unlike a manufacturing industry that generally has only one-dimensional performance indicators,

such as return-on-investment or profit margin, the current healthcare environment has multiple

performance measures of interest, including profit margin, operating costs, and various

healthcare quality criteria such as patient satisfaction and reduction in documented errors.

Many researchers emphasized the importance of information systems for healthcare

quality improvement (Griffith, 1994; Ummel, 1997). Through their survey based study, Bajwa,


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Rai, and Ramaprasad (1998) evaluated the associated structural factors of organizations and

concluded that executives in larger hospitals implemented HIS more than those in smaller

hospitals. Krohn and Broffman (1998) suggested integrated HIS for reliable financial and clinical

data. Killian (1999) demonstrated that healthcare organizations that have some system affiliation

often incline to adopt HIS. Ferrant, Lederer, Hall, and Krella (1998) conducted a survey based

study of HIS in seven community hospitals that shared patient healthcare information through a

common network. Through a questionnaire-based survey, these researchers collected and

analyzed data on perceived benefits of HIS in the views of physicians, medical record personnel,

and IS personnel. Ferrant et al. (1998) concluded that physicians' use of IS was quite low due to

less user friendly systems and due to doctors having inadequate time for handling such electronic

data. Also, conclusions of Ferrant et al. (1998) indicate that both physicians and IS personnel

considered use of electronic data as an essential technological requirement of the healthcare

services.

Lin and Wan (1999) conducted quantitative, cross sectional, secondary data analysis of

the structural design and performance of the top 100 integrated healthcare network services

(IHNS). The study concluded that IS integration indicates structural integration of the healthcare

organizations. Wan and Wang (2003) also examined the effects of integration on performance

ratings of the top 100 IHNS in the United States. The results of their cross-sectional data analysis

indicated high performance rated IHNS is related to more sophisticated HIS with managerial and

executive decision support systems. However, these researchers mentioned that clinical

integration is not yet well developed and needs to prove its efficiency. Wan and Wang (2003, p.

123) recommended use of "longitudinal data on the quality of healthcare network services and


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time varying data to serve as predictors of network performance" for further study. Later, Begun,

Kaissi, and Sweetland (2005) conducted an exploratory study through interviews of leaders in 20

healthcare organizations in the metropolitan areas of Minneapolis/St. Paul, MN, and San

Antonio, TX. These researchers showed that strategic planning is a common and valued function

in the healthcare organizations.

Young et al. (2001) pointed that most of the empirical studies of the contingency theory

performed cross-sectional data analysis and measured environmental uncertainty of the

organization. However, as per the opinion of Young et al. (2001), these empirical studies of the

contingency theory lack rigorous testing and they do not include a variable for measuring

information processing capabilities. Hence it is "important for the contingency theory to be

tested further and for the healthcare managers to participate in these research efforts" (p. 79).

Some researchers have conducted studies on the status of electronic health information

systems and their usage by healthcare providers. Kralewski, Hammons, and Dowd (2005)

conducted a sample survey analysis of medical group practices to assess their current use of

information technology and concluded there is inadequate use of IT in the healthcare systems.

Gans et al. (2005) concluded that at present, EHR adoption is significantly slow. These

researchers highlighted complexity and variation in the process of choosing and implementing

EHR and also pointed to a need for greater technological support to smaller healthcare practices.

Through an interview based survey, Weber (2005) conducted an exploratory study to present the

current state of electronic health information systems among perceptions of the U.S. physicians

in the 2005. Webers (2005) results indicate that less than 40 % of respondents mentioned usage

of EHR and identified cost as the major obstruction for EHR implementation. According to


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Weber (2005) results, the physicians believe that return on investment (ROI) through EHR is a

progressive benefit, which involves HIS project management with effective investment and

learning technology focus.

Miller and Sim (2004), in their exploratory study on physician's use of EHR technology,

commented that EHR has a potential to generate quality improvements in physician practices.

Kilo (2005), in his case based research study, explored aspects of the transformative changes

under way in an ambulatory care from the information technology perspective. The study

concluded that EHR as a knowledge-management tool is still in its development stage, which is

justifiable because the healthcare marketplace is not yet ready for such advanced products. Kilo

(2005, p. 1301) pointed that "funding sources--namely venture capitalists--are generally skeptical

of healthcare IT because of their adverse experiences in this sector in recent years". As per Kilo

(2005), while implementing EHR, it is essential to use the right technology in the right way so as

to improve healthcare quality. In his opinion, healthcare performance improvement efforts

require HIS intelligent system design through integration, connectivity, and the incorporation of

IT into the system.

Thus, while there is consensus amongst the researchers on IT as an enabling technology

for physician practices to pursue healthcare quality improvement, the research literature review

does not provide a specific solution to accelerate EHR adoption to advance healthcare quality.

However, in order to integrate and evaluate IS applications, researchers have proposed several

models based on the strategic contingency theory, as discussed in the following section.


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Healthcare Information Systems and Electronic Health Record Modeling

With management perspectives for EHR implementation, healthcare information system

evaluation needs to establish the quantitative and qualitative benefits of IS to the healthcare

organization. According to Galliers & Leidner (2003), such HIS evaluation involves notions of

costs, benefits, risks, and values, and it involves organizational processes to assess these factors.

Information economics models can provide one of the approaches to evaluate both quantitative

and qualitative benefits of EHR implementation to the healthcare industry, as discussed below.

Information Economics Model

Parker, Benson, and Trainor (1988)proposed a broader concept of the effect of IT

investment on business performance of the organization. The model considers traditional cost

benefit analysis through four lenses of ROI. This approach could be applicable to assess the ROI

of EHR by considering the traditional cost-benefit analysis, along with a certain set of predefined

qualitative measures of EHR, such as patient data linking, reduction in patient's data processing

time, and documented errors .The approach is useful to assess how equipped the healthcare

industry organization is to implement EHR in view of new technological challenges and required

skills. The model seems quite adaptable to an organization's HIS framework and circumstances

and can enhance cost-benefit analysis through business and technology domain assessments

(Galliers & Leidner, 2003). The model can be evaluated through established goals of connecting

EHR directly to the patient care provision, such as providing, consuming, managing, reviewing,

and reimbursing for patient care services. Such assessment of business value of IS processes in

the Parker et al. (1988) information economics model involves top level management. However,

the model does not focus much on users of IS at lower levels during assessment of the process


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(Galliers & Leidner, 2003).Goldsteins (1995) generic integrated model provides comparatively

more comprehensive ROI perspectives. Goldsteins (1995) model identifies causes of lower

quality performance and accordingly conducts effective quality improvement interventions to

eliminate those shortcomings.

Generic Integrated Model

Goldstein (1995) suggested three main targets of intervention: "The health professional,

the patient, and the health service delivery system and further suggested even the combinations

of these targets" (p. 55). The generic integration model has the widest perspective of modeling,

i.e., clinical practices, value evaluations and organizational studies. As per Goldstein (1995), the

focus of the generic integration model is to develop evolutionary structures and processes. This

approach allows "physicians and managers to learn to share information and clinical

perspectives, and to set financially directed performance criteria" (p. 56). Goldstein (1995)

formulated an 11 block and 4 level model based on his theory of high quality of healthcare

administered by an error free healthcare delivery system, as described in the Figure 1.

As described by Goldstein (1995), level one (L1) contains the fundamental blocks of any

healthcare system. In this model, a physician's decisions account for almost 80% of healthcare

costs. Primary care networks are primary care providers. The IS management is responsible for

collecting dispersed clinical data. Reengineering and continuous quality improvement (CQI) of

care are enablers of an efficient and comparatively less costly delivery system. Also, according

to the model, continuum of care requires effective coordination within the system modules.

Level two (L2) identifies blocks that improve access and quality of the delivered care. Level

three (L3) blocks support the patient and the provider, while level four (L4) is "the empowering


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of the people responsible for restructuring the healthcare system" (p. 62). Thus Goldstein (1995)

model encompasses structural, technical and managerial issues of the healthcare organization

that can be used as a framework for useful collaborative systems while implementing EHR. The

model emphasizes leadership of healthcare managers and providers for transformation of the

healthcare delivery to function in a proactive manner and involvement of users at various levels,

while controlling cost and improving healthcare quality. As pointed by Maffei (1997), the

generic integrated model suggests major enhancement and collaboration of existing healthcare

information systems and healthcare information management.

Linking the HIS Integrity Model with Consolidated BSC & CSF Analysis

While the information economics model goes beyond costbenefit to value, Goldsteins

(1995) generic integrated model provides a wider perspective by linking HIS evaluation across

various stages of the healthcare delivery system in view of internal and external components of

the organization. As per the opinion of Ward and Peppard (2002), for a successful IT project in

general and EHR implementation in particular, it is essential to understand the current HIS

processes that are in place. Maffei (1997) argued that these HIS processes include several

interlinked activities that involve patients, as well as the roles of those who deliver healthcare,

such as doctors, nurses, pharmacy, laboratory, and healthcare administrators. According to

Maffei (1997), evaluation of an integrated HIS model requires fact-finding, analysis, and

interpretations. According to a GAO Report (2004), with an expected increase in the U.S.

healthcare spending in the subsequent decade, and with important stakes such as encouraging

high-quality clinical services while implementing EHR, the healthcare organizations need to

improve accountability. In this sense, unless healthcare delivery system performance indicators


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are linked to the drivers of EHR effectiveness in a meaningful way, desired improvements in

healthcare quality are unlikely to occur.

Thus, as described by Ward and Peppard (2002), the real challenge for the healthcare

organizations while implementing EHR is to create meaningful systems for strategic

organizational assessment and then use that information in internal policy and strategic decision-

making. The challenge can be achieved by the critical success factors analysis that has its roots

nearly 40 years back. The critical success factors analysis is a cumulative research approach

about decision-making, IS planning, and identifying the organization's important performance

objectives (Cleland & King, 1968; Zani, 1970). In their study, Baker and Pink (1997),

Castaneda-Mendez, Mangan, and Lavery (1998) pointed the relevance of the balanced score card

(BSC) and critical success factors (CSF) analysis to the healthcare organizations. These

researchers suggested BSC and CSF analysis to link healthcare practices with outcome, value,

and cost of the healthcare services and related projects. Thus, while Goldsteins (1995) model is

a collaborative framework of structural, technical, and managerial issues of the healthcare

organization systems, consolidated balanced scorecard and identification and analysis of the

critical success factors of the generic integrated healthcare system could provide a

comprehensive integrated view of EHR project in view of healthcare quality performance as

discussed below.

Consolidated Balanced Scorecard and Critical Success Factors Analysis

Kaplan and Norton (1992) introduced the balanced scorecard (BSC) as a set of measures

used to facilitate a holistic, integrated view of the business performance. Initially, Kaplan &

Norton (1996, p. 75) created the scorecard to supplement "the traditional financial measures with


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the criteria that measured performance from additional perspectives such as those of customers,

internal business processes, and learning and growth. Later, organizations developed BSC as a

strategic management system linking organizational long-term strategy to its short-term goals. In

view of the limitation of financial measures to display only past decisions, BSC emphasizes

identification of a certain balanced set of objectives and measures for managing the performance

of an organization or the industry. As per Ward and Peppard (2002, p. 208), the BSC approach

can provide a structured methodology for "monitoring current performance of the healthcare

industry/organization with four perspectives of finance, patient satisfaction and quality issues,

internal business, and innovative and learning perspectives." This approach suggests identifying

objectives for each of these perspectives and assigning relevant measures to these objectives as

"key performance indicators"(p. 208). Thus, the BSC approach can provide information needed

to measure the performance of healthcare business process results, as well as to improve the

processes and to motivate and educate the healthcare employees.

According to Ward and Peppard (2002), CSF analysis is helpful in identifying critical

factors in achieving the objectives set by BSC. The technique involves identifying structural,

managerial needs and performing strengths, weaknesses, opportunities and threats (SWOT)

analysis of existing systems against CSF in view of each objective. The consolidated BSC and

CSF technique supports the economic value model and provides a rigorous assessment of

"prioritized" IS opportunities, given the "current business strategy" (Ward & Peppard, 2002, p.

213).

Thus, Goldsteins (1995) HIS integrity model supplemented with consolidated BSC and

CSF analysis can provide a conceptual framework for EHR implementation. The approach can


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provide a comprehensive understanding of current performance of the organization (Ward &

Peppard, 2002). The technique can be applied to examine the healthcare organizations in the U.S.

healthcare industry (p. 213). The approach can assist in prioritizing healthcare activities, HIS

requirements, and evaluation of predefined variables of healthcare quality, such as reduction in

medical and medication errors, time and cost factors, meeting the regulations' requirement, and

improvement in patient safety. Therefore, using the balanced scorecard, healthcare organization

can construct a scorecard of objectives and associated measures for the previously described four

perspectives of finance, patient satisfaction and quality issues, internal business, and innovative

and learning perspectives of the organization. The literature review indicates use of such a BSC

approach to evaluate hospital performance.

During the 1998 system-wide report on Ontario, Canada, hospitals, researchers adapted

the BSC approach and provided information on the performance of Ontario's acute care hospitals

(Pink et al., 2001). Later, during 1999, the same team of researchers utilized BSC to extend the

information on the performance of Ontario's acute care hospitals at two levels, namely at

aggregate and subgroups of small, community, and teaching hospitals (Pink et al., 2001). These

researchers developed indicators of Canadian hospitals' healthcare performance in four areas:

system integration and change, financial conditions, patients' satisfaction, and clinical

deployment and outcomes. Such a BSC and CSF approach can be extended and adopted to

evaluate the U.S. hospitals' healthcare performance by analyzing the relationships among EHR

related HIS integration, as well as healthcare quality in terms of financial indicators, clinical

outcomes, and patient security and privacy issues. As pointed by Zelman, Pink, and Matthias

(2003), the consolidated BSC and CSF approach in healthcare is in its growth stage. Hence it is


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essential to have appropriate modifications in the approach to reflect the U.S. healthcare

organization's perspectives that include healthcare quality goals with some predefined measures

of healthcare quality.

Summary of the Literature Review

The literature review explored historical developments of healthcare information systems

and identified several methodological problems and approaches in current HIS management. At

present, hospitals are motivated by a need to increase healthcare quality through reduction in

medical and medication errors and cost, improvement in patient safety, and creation of effective

IS processes. Healthcare organizations are looking at and drawing from quality management

processes used by manufacturers and other industries, such as the International Organization for

Standardization (ISO) 9000 series quality management systems standards, six sigma rigorous

data driven processes, and failure mode effect analysis: a systematic way to identify and prevent

product and process problems before they occur (Rossow & Grimes, 2003; Swan & Boruch,

2004).

While there exist several IT/IS press articles on EHR implementation and healthcare

quality through HIS that are accessible through the Internet, at present, academic research in this

area seems quite limited. For example, for 1995-2005, Google search engine returned 4,710,000

hits for information systems and healthcare quality, of which 920 hits for information systems,

healthcare quality, and EHR. However, for 1995-2005, the academic search through Business

Source Premier search engine returned only 84 research articles on information systems and

healthcare quality; of these hits, 21 are academic. There were 644 hits on EHR, of which 87are

academic papers and fewer than 15 are academic articles on EHR that focus on healthcare


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quality. Thus, in the opinion of this writer, a very limited number of empirical studies on HIS

and EHR implementation for healthcare quality have been conducted. Some of the academic

studies were exploratory and descriptive in nature andwere case based studies or adopted cross-

sectional data analysis. These studies lack comparability and generalizability of the results and

derived conclusions.

So far, most academic literature for EHR implementation and healthcare quality in the

HIS literature seems discrete in nature, and hence, difficult to quantify and research. With regard

to the strategic contingency theory approach, a healthcare organization needs to bring strategy,

structure, and context into natural alignment while building unique solutions to the problems

(Miller, 1987; Mintzberg, 1991). This requires building a comprehensive conceptual framework

and evaluating HIS projects of EHR implementation in view of the predefined healthcare quality

goals. The generic integrated model with a foundation of the strategic contingency theory and

evaluation tool of consolidated BSC and CSF analysis for quality performance of healthcare

industry was the basis of construction of EHR-centric conceptual model in this study. Emphasis

of the conceptual model was on the integrative analysis for predefined set of healthcare quality

goals by looking at critical success factors as drivers of successful EHR implementation at both

methodology and process level, which involved healthcare providers, HIS integrity, and

associated internal and external factors of the healthcare organization.


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CHAPTER 3. METHODOLOGY

The two research questions described in Chapter 1 are:

1. How can cost effective and value added healthcare quality be achieved through

strategic healthcare information management (HIM) while implementing EHR?

2. What are the critical success factors for healthcare quality while implementing EHR?

To address these two research questions, a conceptual model is presented in this study. The

model is based on the strategic contingency theory, Goldsteins (1995) integrated healthcare

systems model, and the consolidated balanced scorecard and critical success factors analysis

approaches. Quantitative methods are suggested to examine the critical success factors in terms

of HIS integrity, environmental factors, basic functionalities, operational characteristics, and

innovation and learning perspectives of the healthcare organization for healthcare quality

improvement during EHR implementation. The proposed model, data sources, measurement of

data variables, and statistical methods to test the hypotheses are presented.

In view of to the two research questions described above, the research objectives of this

study were to: (a) Perform an exploratory research into a series of proposed relationships

between organizational internal and external factors considering the two important systems for

successful EHR implementation and enhancing healthcare organizations; namely, healthcare

information systems (HIS) and healthcare quality. (b) Identify the critical success factors (CSF)

and quantify the perceived importance of each CSF during EHR implementation for the

healthcare quality goals. (c) Construct a regression analysis based predictive model using the


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proposed critical success factors for healthcare quality improvement during EHR

implementation, and compare and contrast the results of (a), (b) and (c) for small, medium, and

large size healthcare organizations to better understand how critical success factors and EHR

implementation decisions vary with size of the healthcare organization.

Research Design with the Conceptual Model

With a foundation of the strategic contingency theory, the generic integrated model

(Goldstein, 1995), and an evaluation tool of consolidated BSC and CSF analysis, the EHR

centric conceptual model is developed in this study to achieve healthcare quality goals. The

approach attempted to make a theoretical case to extend CSF to facilitate HIS planning in view

of the relationships between organization's internal and external attributes and goals. The model

considered healthcare organizations' context, structure and quality variable. Goldstein (2001)

explained the four fundamental blocks of the healthcare system as follows. Physicians decisions

account for almost 80% of healthcare costs. Primary healthcare providers constitute the primary

care network in the healthcare system. IS management is responsible for collecting dispersed

clinical data. Finally, reengineering and CQI of care is essential for a cost effective, efficient

healthcare delivery system. Adapting and restructuring these fundamental blocks of the

healthcare system of the Goldstein (1995) model, an EHR centric conceptual model for

healthcare quality is derived as follows.

In view of the level one building blocks of the healthcare systems in the Goldstein (1995)

model, in the conceptual model, physician's responses to HIS systems and technology represent

the physician's decisions block of the Goldstein (1995) model. Such approach during EHR

implementation would facilitate timely information and retrieval of specific information,


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particularly daily operational information for monitoring the organizational performance

(Galliers & Leidner, 2003; Huber & MacDaniel, 1986).

To represent the level one primary care network block of the Goldstein (1995) model, the

conceptual model used the healthcare organization's environmental factors and basic

functionality such as hospital bed size, healthcare facilities' affiliation status, managed healthcare

status, and HIS structural functionality. This approach supports Scotts (2003) suggestions to

consider the contingent control variables that relate toan organization's environment, mission,

technology, firm, and industry variables.

In view of the EHR mission of management of patients' record, the conceptual model

used EHR related structural functionality and connectivity of HIS with effective database

management of patients electronic records to represent the level one IS management block of

Goldstein (1995) model. According to Galliers and Leidner (2003), HIS management around the

healthcare business processes allows greater focus on the goals of the healthcare organization,

rather than just operationalizing organization's objectives around existing activities. Also,

researchers (Wickramasinghe, 2000; Wickramasinghe & Mills, 2001), suggested that HIS

management around the healthcare business processes can effectively link the key players within

the basic EHR system to facilitate patient information data management properly, with a cost

effective value added outcomes. To represent the building block of reengineering and CQI of

care of Goldsteins (1995) model,the conceptual model used strategic application of HIS with

learning perspectives, responses to new IT tools, and the executive decision support

functionality. Such approach considered process reengineering strategies, change, and quality

management, which is essential to build flexible systems and continuous improvement of


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management processes while adapting dynamic software technology and medicine. The

approach supports Lams (1995) views that "process reengineering requires characteristics of a

learning organization that has continuous capacity to adapt and change" (Kulkarni, 2005a, p. 30).

Also, the Continuum of care Network is the level-one building block of the Goldstein (1995)

model, which requires effective coordination within system modules. Hence, the conceptual

model represented this building block in terms of HIS connectivity aspect of facilitation of

communication and coordination.

Level two building blocks of healthcare systems in the Goldstein (1995) model are to

improve access and quality of the delivered care. Fadlalla and Wickramasinghe (2004) suggest

that new technologies and techniques in the healthcare organization could be driving forces of

cost effective healthcare quality. Hence, the conceptual model represented this building block in

terms of supplementary technology applications and EHR supporting systems, applications of

patient safety and data security tools, and remote patient data access and management.

Level three building blocks of healthcare systems in the Goldstein (1995) model support

patients and healthcare providers. As per IOM (2001), high quality healthcare initiative involves

patient centered healthcare services that are responsive to patient preferences, needs and safety.

Hence, the conceptual model considered the level three building blocks of Goldsteins (1995)

model in terms of patients' awareness to EHR functionality and applications to reduce clinical

negligence and adverse events. Finally, the level four building

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