chapter 1 - T-Space - University of Toronto

Development of the Diabetes Complication Surveillance System (DCSS) by SHUO WANG

A thesis submitted in conformity with the requirements for the Degree of M.Sc. Health Services Research Graduate Department of Health Policy, Management and Evaluation Faculty of Medicine University of Toronto

Copyright 2010

© Copyright by Shuo Wang 2010

Development of Electronic Tool “DCSS” by Shuo Wang

Abstract

ABSTRACT Development of the Diabetes Complication Surveillance System (DCSS)

Shuo Wang Degree of M.Sc. Health Services Research

Graduate Department of Health Policy, Management and Evaluation University Of Toronto 2010

Abstract Information technology [IT] that enables electronic access to patient health records has been widely recognized as a promising means to improve the quality of care for patients with chronic diseases, and reduce health care costs through better health information delivery and encouragement of selfmanagement. IT applied to assist chronic disease management is inadequately studied in Canadian health care settings. This thesis describes the development and modest pilot implementation of an electronic tool, the Diabetes Complication Surveillance System [DCSS]. The DCSS was conceived as a self-monitoring tool that facilitates regular checks on conditions of diabetes patients, including acute and long-term complications. The DCSS is relatively unusual, as it facilitates glycemic control and also allows patients to address the long-term complications of diabetes. The development of the DCSS involved literature reviews and consultations with clinician experts. Questionnaire results from the pilot provided positive feedback.

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Acknowledgements

ACKNOWLEDGEMENTS Having successfully accomplished the study, I would like to express my gratitude to all the following people for their contribution to this research project: Ann Jones and Dr. Phil McFarlane from St. Michael’s Hospital and Dr. Matthew Oliver from Sunnybrook Health Sciences Centre.

Especially, I would like to express appreciation to my Supervisor, Dr. Sandra Donnelly, for her innovative idea of building such a system to improve diabetes care based on her many years of front line clinical experience, as well as her strong support to complete the entire project including the development of the DCSS, the questionnaire survey, and patient investigation.

Finally, my thanks to Dr. Whitney Berta, Associate Professor at the Department of Health Policy, Management and Evaluation in the Faculty of Medicine at the University of Toronto, for her contributions as a Committee Member.

NOTE: No specific grant was obtained for any of the project activities. The project was not funded by a funding agency. Dr. Sandra Donnelly made personal investments in hardware, software, and funded Web application development.

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Table of contents

TABLE OF CONTENTS ABSTRACT .............................................................................................................................................ii ACKNOWLEDGEMENTS.....................................................................................................................iii TABLE OF CONTENTS ........................................................................................................................ iv EXECUTIVE SUMMARY ....................................................................................................................vii CHAPTER 1:

INTRODUCTION ........................................................................................................ 1

1.1 Issues Relating to Chronic Disease in Canada ......................................................................... 1 1.2 The Burden of Diabetes ............................................................................................................ 2 1.3 Information Technology and Diabetes Management ............................................................... 3 1.4 Diabetes Surveillance to Support Self-Management................................................................ 6 1.5 Research Questions................................................................................................................... 6 CHAPTER 2: LITERATURE REVIEW ............................................................................................. 8 2.1 What Is Known about the Self-Management of Chronic Disease............................................ 8 2.2 Self-Management of Diabetes via Information Technology (IT)........................................... 11 2.2.1 Telemedicine................................................................................................................... 11 2.2.2 eTools Designed to Improve Diabetes Mellitus Management ....................................... 12 2.2.3 Linking Diabetes Guidelines to eTools .......................................................................... 14 2.3 Electronic Tools: Components and Factors That Impact Access ........................................... 15 2.4 Study Objectives..................................................................................................................... 18 CHAPTER 3: METHODS ................................................................................................................. 20 3.1 Overview................................................................................................................................. 20 3.1.1 Timeline.......................................................................................................................... 21 3.2 Initiation.................................................................................................................................. 21 3.3 Development and Implementation of Electronic Tool “DCSS”—Months 1–6...................... 21 3.3.1 System Overview............................................................................................................ 22 3.3.2 User Profile Data Fields Selection.................................................................................. 22 3.3.3 Surveillance Benchmarks Selection ............................................................................... 22 3.3.4 System Design ................................................................................................................ 25 3.3.5 DCSS Development / Implementation ........................................................................... 25 3.4 Pilot of DCSS—Months 7–12 ................................................................................................ 28 3.4.1 Development of Brief Questionnaire “Patients' Views of DCSS Utility”...................... 29 3.4.2 Participant Recruitment / Data Collection...................................................................... 30 3.4.3 Data Analysis.................................................................................................................. 30 3.4.4 Privacy and Confidentiality ............................................................................................ 31 CHAPTER 4: RESULTS ................................................................................................................... 32 4.1 Development of Electronic Tool “DCSS”.............................................................................. 32 4.1.1. User Profile Data Fields.................................................................................................. 32 4.1.2. Surveillance Benchmarks ............................................................................................... 32 4.1.3. Application Features....................................................................................................... 33 4.1.4. DCSS Development........................................................................................................ 35 • DCSS Workflow..................................................................................................................... 35 • DCSS Database Design .......................................................................................................... 37 • DCSS Screenshots (Details in Appendix) ............................................................................ 39 iv


Table of contents

4.1.5. System Implementation .................................................................................................. 40 4.2 Pilot of DCSS ......................................................................................................................... 41 4.2.1 DCSS Pilot Results ......................................................................................................... 41 CHAPTER 5: DISCUSSION............................................................................................................. 43 5.1 Development of the Electronic Tool "DCSS" ........................................................................ 43 5.1.1. User Profile Data Fields.................................................................................................. 43 5.1.2. Surveillance Benchmarks / Electronic Tool Indicators .................................................. 43 5.1.3. System Technology Selection......................................................................................... 45 5.1.4. System Functionality ...................................................................................................... 46 5.1.5. System Implementation .................................................................................................. 47 5.1.6. Maximizing Access to an Electronic Self-Management Tool........................................ 48 5.2 Pilot of DCSS ......................................................................................................................... 49 5.3 Limitations.............................................................................................................................. 51 5.4 Implications and Recommendations....................................................................................... 51 CHAPTER 6: CONCLUSIONS AND FUTURE DIRECTIONS ..................................................... 53 6.1 Development of the Electronic Tool "DCSS" ........................................................................ 53 6.2 Implications ............................................................................................................................ 54 6.3 Future Research ...................................................................................................................... 54 6.4 Summary................................................................................................................................. 55 REFERENCES ....................................................................................................................................... 57 APPENDICES ........................................................................................................................................ 63 APPENDIX 1: DCSS Database Design ............................................................................................. 63 APPENDIX 2: Diabetes Complication Surveillance System Questionnaire ..................................... 66 APPENDIX 3: Survey Detailed Results............................................................................................. 67 1. Subject enrollment and characteristics ................................................................................... 67 2. Internet and accessing health information on Internet............................................................ 67 3. Patient right to access health records...................................................................................... 68 4. Patient response to electronic health records.......................................................................... 68 5. Patient concern about security and privacy of EHR............................................................... 69 6. Patient issues around understanding & updating EHR, & errors ........................................... 70 7. Patient response to Diabetes Complication Surveillance System – usefulness...................... 70 APPENDIX 4: Acronyms................................................................................................................... 72 APPENDIX 5: Glossary Information Technology Terms ................................................................. 73

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Table of contents

Table Index Table 1 eTool Indicators and Best Accessed.................................................................................16 Table 2 DCSS Project Timeline ....................................................................................................21 Table 3 Surveillance Benchmarks and Sources.............................................................................22 Table 4 Demographic Information in DCSS .................................................................................32 Table 5 Clinical Benchmarks in Diabetes Complication Surveillance (based on data in 2005) ...33 Table 6 Patient Demographic Information (Age, Gender, Education, English as 1st language) ...41 Table 7 Study Results in Themes ..................................................................................................42

Figure Index Figure 1 Business Logic Workflow...............................................................................................26 Figure 2 DCSS Workflow Diagram ..............................................................................................36 Figure 3 Patient’s Demographics Modification Page....................................................................38 Figure 4 Add New Medical Record for Patients ...........................................................................39 Figure 5 DCSS Screenshot Sample – Patient List .........................................................................39

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Executive Summary

EXECUTIVE SUMMARY OBJECTIVE This study focused on the development of an evidence-based electronic tool, the Diabetes Complication Surveillance System [DCSS] and a modest implementation pilot of the tool. The DCSS was conceptualized as a surveillance tool that facilitates the management of a diabetes patient’s condition, including acute and long-term complications. Most programs for diabetes management have focused on achieving good glycemic control and managing the acute complications of diabetes. As an electronic tool, the DCSS is unique in that it helps achieve both purposes: it facilitates glycemic control while allowing patients to address the long-term diabetes complications.

DESIGN AND MEASUREMENT The DCSS was designed as a Web-based system for providing opportunities for patients and providers to access patients’ records through the Internet. Under a defined timeline, the DCSS development and the pilot patient survey were completed.

DCSS development included two steps: data field selection and development procedures. Data field selection included choosing fields relating to two sections, the “user profile” and the “surveillance benchmark” sections. Four resources were used to guide the selections of data fields: Clinical Practice Guidelines [CPG] 2003 developed by an expert committee of the CDA’s clinical and scientific section, review of diabetes literature and other eTool publications related to diabetes, the input of clinical experts, and technical specifications of the system including MS Window Server 2000, MS Access 2000 Database, Java Server Page, and Tomcat as Web Server.

In the pilot, I engaged a few patients to view the DCSS, and asked them to provide their feedback via a questionnaire I developed. Data collected from the pilot included patient demographics. (i.e., age, gender, education, first language) and six additional domains including (1)use of the Internet to access health information; (2) patient’s right to access records; (3)response to EHR; (4)security and privacy concerns; (5)EHR help managing disease; and (6)DCSS usefulness.

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Executive Summary

RESULTS The DCSS ultimately contained the following data fields: Demographics

MRN /OHIP# + version /Name /Date of birth /Marital status /Gender /Address /Phone numbers /Email /Payment program

Surveillance

For acute care: HbA1C /Blood glucose /Lipids, LDL-C /Weight /Height /

Benchmarks

For complications: Urinary albumin /Blood pressure /Exam on eye, feet, heart

Application

Doctor profile / Patient profile / Patient medical record information in 9 key

Features

benchmarks. Actions: View /Add /Modify/Delete

In the pilot, I enrolled 12 patients to view the DCSS. I analyzed patient demographics on age, gender, education, and English as first language. I also analyzed patient feedback through 19 questions addressing the six domains. Overall, the feedback was positive.

DISCUSSION The user profile is an essential component of an eTool applied in a health care setting. This information can be used for many purposes: i.e., to identify an individual, to link doctors and patients, to link a patient to his/her medical record, and to provide contact information for message delivery. While seemingly straightforward, careful selection of the fields for this section of the DCSS, and any eTool, are important.

Similarly, judicious and parsimonious selection of surveillance benchmarks is important and challenging. These benchmarks provide key checking indicators for monitoring diabetes complications. Including excess benchmarks will mandate the investment of more resources for development than are really needed; including fewer may lead to a failure to collect key information. With careful consideration and research, and through consultation with clinical experts, I selected 9 benchmarks which have been demonstrated to be useful in diabetes complication surveillance: 4 benchmarks relate to the management of acute complications, and 5 relate to the management of longterm complications.

In addition, selecting the right technology will enable system scalability. Under a limited budget and timeline, I undertook an efficient approach to development of the DCSS, in terms of technology

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Executive Summary

applied and functions included. I concluded my study with a modest pilot involving 12 diabetes patients, and summarized success factors and challenges that emerged. Overall, patient reception of the DCSS was positive. The pilot was facilitated mainly by effective leadership, adequate knowledge in health informatics, cooperation from some clinic staff and good project management. The main challenges identified were lack of funding and lack of support from the hospital IT department.

CONCLUSION Applying the DCSS in practice may require a shift in procedure, extracting the surveillance of the long-term complications of diabetes from the current hospital-centered care model to one with additional self-management by patients. This innovation represents a reformatting of currently supported activities that create efficiencies for the health care system and conveniences for health care providers and patients.

Choosing appropriate technology and designing a useful system are the keys to designing adoptable systems for end users. Providing training and support to eTool users, including patients and clinicians, will increase users’ interest and ensure data quality in the system.

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Chapter 1 - Introduction

CHAPTER 1: INTRODUCTION This chapter introduces background information that led to the study. It describes issues in Canadian health care related to the prevalence and management of chronic disease, discusses the potential for information technology to assist in the management and self-management of chronic disease, and states the objective of the study.

1.1

Issues Relating to Chronic Disease in Canada

Since its founding in 1957, the Canadian Medicare system’s enduring purpose has been to ensure timely access to quality care, the sustainability of the system, and wellness for Canadians. While the health care system was designed to address acute diseases through hospital-based care delivery(Wagner et al. 01a), today’s health problems are predominantly chronic in nature and include heart disease, cancer and diabetes(Kirby, 02) [p243-246]. Thousands of Canadians die every year and tens of thousands are hospitalized because of complications related to their chronic illnesses(Rachlis M, 03).

The publicly funded Canadian health care system is based on the five principles of universality, accessibility, portability, comprehensiveness and public administration(Canada, 04;COACH, 03). The continued rise in health care expenditures(CIHI, 04b) has generally been attributed to the costs of caring for a growing elderly population and a growing proportion of the population suffering chronic disease, which certainly includes elderly Canadians(Gordon, 08;National Physician Survey, 08). In addition to costs incurred by hospitalization, doctor visits and medication, there are societal costs including those related to work absences and the provision of informal care. In light of these tensions, the sustainability of the current health care system has emerged as one of the most urgent national issues of the 21st century(COACH, 03).

According to a report released by the Canadian Institute for Health Information [CIHI], in 2003 Canada spent $121.4 billion on health care, or an average of $3,839 per person. After inflation, this is an increase of 30% from 1993 and 62% from 1983. Health care costs are now responsible for 10% of the nation’s total economy (gross domestic product), a historic high first reached in 1992. Hospitals, drugs, and doctors’ services account for the bulk of health spending(CIHI, 04a;CIHI, 04d;CIHI, 04b;CIHI, 04c). In terms of the cost of chronic disease to the Canadian economy, it differs depending 1



upon the disease. A study of eight types of chronic disease (cancer, musculoskeletal disease, cardiovascular diseases, diabetes, hypertension, neuropsychiatric diseases, respiratory diseases, and other miscellaneous diseases) compared costs across provinces. The authors found that, “In Canada, costs estimated in 1999 for diabetes were translated into $9.9 billion both direct and indirect costs in present 2005 $ value.”(Jayadeep Patra et al, 07).

1.2

The Burden of Diabetes

The increasing prevalence of chronic disease and multiple co-morbidities among Canadians and North Americans in general, is exerting unprecedented demands on the health care system(Debra Black, 05), and has led to concerns about the escalating costs of care. Increasingly, attention is given to mechanisms, structures, and systems that may reduce the costs of chronic care.

According to the Canadian Diabetes Association(Canadian Diabetes Association, 08), over two million Canadians have been diagnosed with diabetes, and one third of diabetes cases are not yet diagnosed. People with diabetes are at a greater risk of heart attacks than the general population(Catherine Zahn, 06). Diabetes is the leading cause of adult blindness and amputations, and is also the leading cause of kidney disease in Canada.

Black reported that 50% of Canadian Type 2 diabetes patients do not have historicized records of blood-sugar levels, indicating that their diabetes is not being controlled. As a result, they are increasingly susceptible to complications including heart attack, stroke, kidney disease and blindness. Furthermore, 600,000 Canadians are not aware that they have diabetes because they do not yet display symptoms(Debra Black, 05).

Diabetes is the seventh-leading cause of death in Canada. Over the next five to ten years, the number of Canadians affiliated with diabetes is expected to jump to three million, which will add to the already heavy burden of this disease on the Canadian health care system(Debra Black, 05).

The increasing prevalence of diabetes has been described as an epidemic, and its negative economic impact has been documented. Costs include those related to prescription drugs, lost productivity, direct health care services, and personal expenditures related to seeking care. It is estimated that in 1998, “diabetes accounted for $0.4 billion for hospital care and drugs, and $1.2 billion in indirect costs…”(Stewart, 05). 2



Health Canada reports spending over $9 billion annually on diabetes. Black estimated that the disease costs the health care system $13.2 billion per year, and that this number is rising exponentially. By 2020, the disease and its complications could cost the system as much as $19.2 billion annually(Debra Black, 05). Comparable statistics and estimates are cited for the United States, where diabetes is the fifth-leading cause of death.

1.3

Information Technology and Diabetes Management

Electronic access to patient health records has been widely recognized as a particularly promising way to reduce the costs of care. It is thought to provide better and more timely delivery of health information among care providers, and to enable the self-management of chronic care(Wagner et al. 01a;Kerkenbush and Lasome, 03;Goldberg, Ralston, Hirsch, Hoath, and Ahmed, 03;Bodenheimer, Lorig, Holman, and Grumbach, 02b;Bodenheimer, Wagner, and Grumbach, 02a). While selfmanagement eTools have caused a great deal of discussion, little has been done to date to develop and trial them.

This study focuses on the development of a technology-based management system to assist in the selfmanagement of diabetes among adults. Diabetes Mellitus [DM] is a serious chronic disease that is costly to affected individuals and society. If untreated or improperly managed, it can result in a variety of complications, which contribute to significant morbidity and early mortality. Diabetes is one of four chronic “Ambulatory Care Sensitive Conditions” [ACSC] associated with hospitalizations that are deemed avoidable when patients have timely access to high-quality care in their communities. Such care includes disease prevention programs and appropriate primary health care(CIHI, 03). As with other ACSC, the quality of care relating to these conditions is strongly influenced by the coordination of care and by the timeliness, appropriateness and quality of patient information that is brought to bear in care decision-making(Statistics Canada and CIHI, 03;Romanow RJ., 02). There appears to be significant potential for technology-facilitated information management to improve the quality and coordination of diabetes care. As noted in earlier sections, diabetes programs have mostly focused on achieving good glycemic control and managing the acute complications of diabetes. However, the importance of observing and monitoring long-term diabetes complications to decrease acute complications and associated mortalities should be recognized. Therefore, in this study, DCSS was designed as a self-management/monitoring tool to facilitate the tracking and monitoring of benchmarks associated with long-term complications, allowing for their timely treatment. 3



The Internet and Health Information Access Reliance on information technology requires that patients are somewhat comfortable with using the Internet. A survey conducted by the University Health Network [UHN] showed that 68% (693/1019) of UHN patients had Internet access. Of the patients who had Internet access, 75% (520/693) wanted access to medical information over the Internet(Chiu, Rizo, and Wang, 04). According to Statistics Canada(Stat Canada, 08), 73% of the population in 2007 used the Internet, compared with 68% in 2005. It is felt that citizen use of the Internet for gathering health information is increasing.

The Web is now widely accessed by diabetes patients seeking relevant health information. In a study by Dedell (2004), three criteria – usability, content, and reliability – were used to assess the medical information relevant to diabetes mellitus management available through Google, Yahoo and the Mendosa directory. Dedell studied 47 websites, giving only five a usability ranking of ‘high’. The remainder were cluttered or inundated with distracting information. Content was generally excellent, but limited by an absence of specific advice, and only 17% of the websites met all of the criteria for reliability.

Electronic Health Records [EHR] for Diabetes While the tool developed around the present study is not a full electronic health record, it is important to discuss the DCSS in the context of other electronic tools like the EHR that are used to manage patient information and chronic conditions.

According to HIMSS [The Healthcare Information and Management Systems Society], “The Electronic Health Record (EHR) is a longitudinal electronic record of patient health information generated by one or more encounters in any care delivery setting. Included in this information are patient demographics, progress notes, problems, medications, vital signs, past medical history, immunizations, laboratory data and radiology reports.” 1

Electronic Health Records [EHRs] have been seen as promising mechanisms by which to improve chronic care including diabetes by promoting health information delivery(Canada, 04;COACH, 03;Kirby, 02;Romanow RJ., 02). Electronic decision support promises to improve evidence-based

1

Definition of Electronic Health Record (EHR) - http://www.himss.org/ASP/topics_ehr.asp

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practice in chronic disease management. The role of information systems has become increasingly important in the evolution of new forms of medical records and communication structures. EHRs can provide visible monitoring for medical records and shareable data among doctors, nurses and patients in hospitals and primary care.

EHRs have been available to health care practitioners for over a decade. Different EHRs provide various functions in different formats, and are built for different purposes. Canada's Health Informatics Association discusses EHRs as part of the solution to Canada’s health care sustainability issues(COACH, 03). In particular, EHRs promise to facilitate quality and coordination of care, and the timeliness of patient information transfer in the area of chronic disease management(Romanow RJ., 02). EHRs are also recommended as a solution in three major provincial and national health reports to ensure accountability and sustainability, including the Romanow Commission (Romanow RJ., 02) and Kirby Committee reports(Kirby, 02). Mazankowski (2001) contends that EHRs stand to improve the health of individuals and the quality of our health care system through data sharing, more efficient data access(Mazankowski D., 01). Gorman et al. argue that EHRs represent a reduction of errors in record keeping(Gorman et al. 96). In the Kirby report, EHRs were depicted as the cornerstone of an efficient and responsive health care delivery system with improved quality and accountability(Kirby, 02). The Romanow report stated that EHRs are key to modernizing Canada's health system and to improving access and outcomes for Canadians. The Romanow report also cited improvements in diagnoses, treatment results, efficiency, security, and the accuracy of personal health records. In addition, EHR data can be used for health research and surveillance, as well as for tracking disease trends and monitoring health status(Romanow RJ., 02). The concept of applying electronic information technology in health care to improve the quality of care continues to be widely promoted by the Canadian government. Most recently, Canada Health Infoway CEO Richard Alvarez announced at the eHealth 2009 conference that the agency would spend $500 million funding physician EMR systems, interoperability among electronic solutions, and other eHealth initiatives(Jerry Zeidenberg, 09).

Despite widespread support for the concept, EHR implementation faces many challenges in terms of privacy, fragmented eHealth authorities, a lack of data standards, barriers to physician adoption, and knowledge barriers on the part of consumers relating to the use of Personal Health Records(COACH, 03). To some extent, challenges associated with standards and uptake relate to a general lack of rigorous consideration of content and consumer perspectives in the design of many systems.

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1.4


Diabetes Surveillance to Support Self-Management

With respect to diabetes care specifically, studies have shown that intensive diabetes monitoring with diet control and the maintenance of blood glucose, LDL, and urine albumin lead to a substantial reduction in the rate of complications (e.g. blindness, kidney failure, amputations and circulatory diseases), which can be difficult to achieve through conventional means(Hejlesen, Plougmann, and Cavan, 00).

Management of chronic disease by care providers and self-management by patients are increasingly emphasized as ways to address the emerging issues discussed above. Self-management stands to improve chronic disease outcomes by reducing complications through diabetes education or detecting issues early through the monitoring of key benchmarks(Stewart, 05).

Electronic access and sharing of patient (health/medical) information are seen as mechanisms to assist self-management, or through which a self-management program or regimen can be delivered. A Webbased approach allows patients to access their health care information through the Internet anytime and anywhere.

Prior studies show that patients consider home access to their records convenient(Canhealth, 08). Benefits to patients include reduced costs and time associated with travel, and possible improvements to the quality of care. Patients do not need to go to the hospital to get a lab result, but can access their records online. Further, patients may be able to obtain health care information prior to a routine scheduled visit to the doctor; clinic visits may be more efficient for patients who really need physician consultation.

With electronic self-management tools, extra care information available to doctors can lead to better monitoring. Patients can enter self-measured data into such tools from home. The tools can act as reminders to patients, leading to better self-management of diabetes.

1.5

Research Questions

Research Questions While work done to date on EHRs and self-management tools consistently supports the concept of EHRs improving self-management, few studies rigorously combine considerations of the content of self-management eTools and adherence to the principles of IT development. 6



This paper describes the development of an evidence-informed self-management tool, the DCSS, for adults with diabetes mellitus. The principles of IT development were applied in the development of the DCSS. The following questions were addressed during the tool’s development and implementation: -

What are the key components and design features that should be included in a self-management tool intended to facilitate surveillance of diabetes complications, such as clinical indicators, workflow, and functionalities?

-

What are potential facilitators of, and challenges to the use of electronic self-management tools from the perspective of patients?

The design of the DCSS was informed by extant literature, reviewed in Chapter 2, on chronic disease management models and information technology including telemedicine and EHR. Chapter 3 describes the process of developing the tool, including the involvement of clinical experts.

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Chapter 2 – Literature Review

CHAPTER 2: LITERATURE REVIEW This chapter describes literature review on Chronic Disease Management models and chronic disease self-management, as well as related topics involving information technology in chronic disease management. The literature review guided us with respect to the content of the DCSS, and in the minutiae of the development process.

2.1

What Is Known about the Self-Management of Chronic Disease

Self-management programs have been widely reported as successful in assisting patients in managing their chronic conditions(Foster, Taylor, Eldridge, Ramsay, and Griffiths, 07;Lorig et al. 99;Lorig, Sobel, Ritter, Laurent, and Hobbs, 01;Lorig, Ritter, Laurent, and Plant, 06). In late of the 20th century2, new concepts have been introduced, including the Chronic Care Model [CCM], Chronic Disease Management, Chronic Illness Management, and Chronic Condition Improvement.

It is important to achieve optimum therapy goals through educating and supporting patients in managing their chronic diseases. Self-management is an essential component for clinical outcomes of diabetes. Planned care is recommended as a redesigned model for chronic disease care that involves utilizing clinical information systems and implementing guidelines to support of self-management.

In a 2001 publication, Wagner et al. developed a guide to improve chronic care, called the Chronic Care Model. Their study indicated that chronic disease patients have difficulties managing their condition, due to the mismatch that exists between the encouragement given patients to undertake self-management and the traditional approach of the medical system. “Our care systems were organized historically to respond rapidly and efficiently to any acute illness or injury that came through the door. The focus was on the immediate problem, its rapid definition and exclusion of more serious alternative diagnoses, and the initiation of professional treatment.”

Elements of CCM include health care organization, community resources, self-management support, delivery system design, decision support, and a clinical information system(Wagner et al. 01a). A subsequent study conducted by Wagner et al. examined the impact of organized periodic primary care sessions in meeting the complex needs of diabetic patients, and improving

2

Chronic Care Model - http://en.wikipedia.org/wiki/Chronic_care_management

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diabetes care and outcomes. The results of the study showed improved outcomes for diabetes care, including more recommendations on preventive procedures and helpful education, fewer visits to specialty and emergency rooms, and better HbA1c levels among intervention group participants(Wagner et al. 01b).

Published in 2001 as well, Glasgow et al. conducted a research study focusing on the chronic care model and diabetes. In the study, the authors identified key characteristics of effective diabetes management programs, such as using a population-based systems approach, incorporating active patient participation, and using patient-centered collaborative goal setting. The paper also mentioned using clinical information systems to improve quality of care, such as diabetes registries and electronic medical records. Seven top-rated barriers (from a total of 37 submitted) to establishing a chronic care model for diabetes care were identified, including a lack of appropriate health care policies, poor understanding of population-based chronic disease management, and inadequate integration of information systems to enable the sharing of information across providers(Glasgow et al. 01). In addition, the authors concluded that barriers are generally due to systems issues arising from the acute illness model of care, where the “vast majority of physicians have been trained, and most of our health care systems have been established, to treat acute illness.” Finally, the paper suggested that future research is needed to overcome these barriers, including “research on the Internet and other interactive technologies to inform patient-provider interactions, deliver self-management support, and coordinate health care team efforts.”(Glasgow et al. 01).

In 2002, a systematic review of studies of chronic disease management confirmed the utility of the CCM for improving chronic care (using diabetes as an example) and reducing health care costs. The majority of studies included in the review (32 out of 39) showed positive clinical outcomes. Further, 18 of 27 studies focused on 3 chronic conditions (congestive heart failure, asthma, and diabetes) and demonstrated reductions in health care costs(Bodenheimer et al. 02a).

In 2004, based on reviewing 71 trials of self-management education programs, Warsi’s study found that “self-management education programs resulted in small to moderate effects for selected chronic diseases.” Diabetes patients demonstrated reductions in glycosylated hemoglobin levels and improvement in systolic blood pressure. Asthmatic patients experienced fewer attacks, but no statistically significant effects were observed for arthritis (Warsi, Wang, LaValley, Avorn, and Solomon, 04). 9



Another study by Bodenheimer and colleagues encouraged the partnership between patients and providers through collaborative care and self-management education. The paper indicated that, by providing problem-solving skills, self-management education supports better quality of life for patients with chronic conditions. Compared with traditional patient education which offers information and technical skills, self-management education programs may improve clinical outcomes and reduce costs. In the paper, the authors indicated that a central concept in self-management is self-efficacy, where patients believe in their abilities to solve problems and to reach a desired goal through changes in their behaviour (Bodenheimer et al. 02b).

With 791 participants enrolled, Meyer studied the concept that “technology was to improve health status, increase program efficiency, and decrease resource utilization” when suitable technology was chosen to enhance the care coordinator role. The evaluation data showed positive results. There were reductions of emergency room visits (40%), hospital admissions (63%), hospital bed days of care (60%), VHA nursing home admissions (64%), and nursing home bed days of care (88%). These results found that long-term care services requests (nursing care) decreased more than acute care services (ER visits). Finally, the research concluded: “All performance improvement outcomes reached or exceeded the targeted goals.”(Meyer, Kobb, and Ryan, 02).

Under the domain of redesigning the health care delivery system to support patient self-management by using clinical information and decision support systems, a study by Rothman indicated that chronic diseases patients do not receive effective therapy and do not have optimal disease control. Therefore, chronic care is shifted to specialists or disease management programs. “The future of primary care may depend on its ability to successfully redesign care systems that can meet the needs of a growing population of chronically ill patients”(Rothman and Wagner, 03).

Concerning self-management of chronic kidney disease, one of the possible complications of diabetes, a study by Costantini discussed the impact of its patient self-management experiences on the level of support needed. This qualitative study identified themes, such as searching for evidence, taking care of the self and the need for disease-specific information(Costantini et al. 08).

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2.2


Self-Management of Diabetes via Information Technology (IT)

Integrated clinical management systems can facilitate the management of clients with chronic diseases and provide an efficient way to integrate consultations and client education with monitoring, followup, and support(White and etc, 01). Diabetes has been the focus of telemedicine and medical information technology for years(Lahtela and Lamminen, 02). In this section, I describe published studies on applying IT to facilitate diabetes self-management.

First, at the earliest stage, many studies discussed using telemedicine to improve diabetes care. These studies are reviewed in the first subsection below. Later, in tandem with IT development, electronic tools were applied in diabetes management. Studies of those applications, discussed in the second subsection, have mainly focused on clinical evaluation. After those studies, some researchers introduced more functionality to eTools—for example, adding “Clinical Decision Support” by including diabetes guidelines in applications (third subsection below).

2.2.1 Telemedicine Successful telemedicine projects have demonstrated that information and communication technologies facilitate the improvement and efficiency of the quality of health care. A number of telemedicine systems have addressed the needs of clients with DM. For example, the home care system for Type 1 diabetes clients was discussed by Bellazzi et al. with the goal of: (i) providing clients with an effective insulin treatment, (ii) obtaining an appropriate level of continuous and intensive care at home through tele-monitoring and tele-consultation services, (iii) allowing for cost-effective monitoring, (iv) supporting continuing education of clients through tele-consultation(Bellazzi, Montani, Riva, and Stefanelli, 01).

The Diabetes Education and Telemedicine (IDEATel) project was recently conducted to evaluate the feasibility, acceptability, effectiveness, and cost-effectiveness of telemedicine. The focal point of this intervention was the home telemedicine unit, which provided four functions: (i) synchronous videoconferencing over standard telephone lines, (ii) electronic transmission for glucose and blood pressure readings, (iii) secure Web-based messaging and clinical data review, and (iv) access to Web-based educational materials(Starren et al. 02).

A randomized control study was conducted by Montori et al. to determine the efficacy of telecare (modem transmission of glucometer data followed by nurse-mediated feedback and clinician feedback) 11



to support intensive insulin therapy in 31 clients with Type 1 diabetes and inadequate glycemic control. The results indicated that telecare which augmented usual care among clients with Type 1 diabetes and inadequate glycemic control had a small effect on glycemic control compared with the transmission of glucometer data without feedback in the context of usual care(Montori et al. 04).

2.2.2

eTools Designed to Improve Diabetes Mellitus Management

Chronic disease management programs that use Web-based communication offer an opportunity to shift the focus of health care away from clinicians’ offices and towards clients’ daily lives at home(Ralston, Revere, Robins, and Goldberg, 04).

A study conducted in 1998 by Smith et al. first introduced the concept of applying electronic management tools to improve the management of diabetes mellitus. Smith et al. measured the number of exams, such as foot, blood pressure, and glycated hemoglobins documented by providers using an electronic management tool. This study indicated the number of foot exams and blood pressure readings were greater (P < 0.01) for providers using the system(Smith et al. 98).

Two additional papers describe a similar approach. Meigs et al. (Meigs et al. 03) reported on a randomized controlled trial conducted to assess the impact of a Web-based EMR system on quality of diabetes care at a teaching practice for outpatients. Physicians using the EMR ordered significantly more HbA(1c) and LDL cholesterol tests for diabetes patients. Because of this, the authors concluded that EMR use led to better quality of diabetes care. Another controlled study of the impact of an EMR system on outpatient diabetes outcomes also found increased rates of test ordering such as HbA(1c), lipids, microalbuminuria, or blood pressure levels(Montori et al. 02).

A study of the implementation of a Web-based diabetes care management support system was carried out in the Henry Ford Health System by Baker et al.(Baker, Lafata, Ward, Whitehouse, and Divine, 01). The study included 13,325 diabetes patients aligned to 190 primary care providers practicing in 31 primary care clinics. Three features were provided as part of the support system: clinical practice guidelines, patient registries, and performance reports. The application was available via a corporate intranet. Because it was hosted on an intranet instead of the Internet, patients were not able to access their records from home, but had to be on site to get access. This study documented the frequency with which clinical benchmarks testing was performed, treating this frequency data as its outcome measure. The results indicated an increase in the frequency with which patients received lipid profile testing and 12



retinal exams if their tests were ordered by physicians who used the system more often. The authors concluded that frequent use of the system by caregivers improved the rate of routine testing among patients with diabetes. No relationship was found, however, between system usage and glycated hemoglobin testing.

As O'Connor pointed out, there is a drawback relating to studies like those above, “Increased test frequency did not translate into better A1C or LDL levels in the patients of physicians with access to the EMRs compared with patients of physicians without access to the EMRs…While it is encouraging that EMR use led to increased frequency of testing, it is disappointing that key care outcomes such as A1C and LDL levels did not improve” (O'Connor, 03). Thus, it deviates from the principle of diabetes management because it only measures the test rate instead of measuring the improvement in metabolic parameters levels.

Conversely, a randomized clinical trial involving 110 patients in Korea demonstrated the impact of using the Internet to improve blood glucose monitoring. With 12-week follow-up examination, HbA(1c) levels were significantly decreased from 7.59 to 6.94% in the intervention group (P < 0.001). Moreover, HbA(1c) levels in the intervention group were significantly lower than in the control group (6.94 vs. 7.62%; P < 0.001, respectively) (Kwon et al. 04).

Conducted at the University of Washington, Goldberg et al.’s study introduced a Web-based application as a co-management module between physicians and their patients to improve the quality of chronic disease care, which mainly focused on diabetes. In this Web-based disease management program, the services included: (i) access to an electronic medical record (EMR) over the Internet, (ii) secure email communication between doctors and clients, (iii) ability to upload blood glucose readings via the phone line, (iv) an education site with endorsed content, and (v) an interactive online diary for entering exercise, diet, and medication. Three pilot participants were in the study. One patient achieved control (glycohemoglobin [HbA1c] from 8.0% to 6.1%) in diabetes management. While the result was positive, the study was severely limited by the small sample size (Goldberg et al. 03). Based on the same Web-based EHR application, Ralston and colleagues published a qualitative study of patients' experiences with this diabetes support program. Six themes emerged, three of which had particular relevance to the design and use of Web-based tools for care of patients with diabetes: 1) a feeling that non-acute concerns were uniquely valued; 2) an enhanced sense of security about health and health care; 3) frustration with unmet expectations. The study concluded that qualitative analysis supported 13



further study of open access to the EMR and online communication between clients and their caregivers(Ralston et al. 04).

A more recent study conducted by Cho et al. in Korean found information technology-based diabetes management system reduced complications on subjects with Type 2 Diabetes. They are mainly “microangiopathic complications, including diabetic retinopathy, diabetic neuropathy, diabetic nephropathy, and diabetic foot ulcer” (Cho et al. 08).

2.2.3

Linking Diabetes Guidelines to eTools

Some EHRs have integrated clinical guidelines, decision support and workflow into their systems (Montori and Smith, 01) in the interest of promoting evidence-based practice. Barretto et al. report a case study of guideline-compliant treatment of hypertension in diabetes (Barretto et al. 03).

Tang et al. report using a personalized portal combined with workflow management tools to improve diabetes care. The Web service technologies applied Microsoft .Net Environment, plus MS SQL Server as its backend. The results of this descriptive study were positive; however, no control group was included(Tang, Li, Chang, and Chang, 03).

Plougmann et al. reported on a diabetes advisory system (DiasNet) implemented for communication and education via the Internet between clinicians and patients. Patients could experiment with their own data, adjusting insulin doses or meal sizes. The system was developed by Java based on a client/server model (Plougmann, Hejlesen, and Cavan, 01).

Without discussing clinical benchmarks in the paper, De Clercq et al. reported on another Web-based system for diabetes patients. The system had two main functionalities: 1) Both care providers and patients could enter data; 2) The system downloaded the data from a glucose meter and provided feedback to patients based on the data entered and incorporated guidelines(De Clercq, Hasman, and Wolffenbuttel, 03).

The section following this one (Section 2.3) summarizes publications focusing on eTools and factors associated with access.

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2.3


Electronic Tools: Components and Factors That Impact Access

Prior to developing the DCSS, I reviewed the literature focusing on information-technology-based chronic disease management tools associated specifically with the self-management of diabetes. In this section, I summarize the components of existing eTools, and the research to date that has identified factors that influence access, including patients’ views.

The table below summarizes the key elements of these electronic tools, both those that were included and those that were missed (the latter most often being benchmarks for long-term diabetes complication surveillance).

15



Table 1 Existing eTool Components and Access Indicators included in eTools

Comments on Applications

References

Home Telemedicine Unit: glucose meter,

This paper was based on a plan for

(Starren et al. 02)

automated BP meter.

system development, but did not

Case Management Software (CommuniHealth

involve a real implemented

product by Siemens): patients’ view: glucose,

application. It intended to create a

glycosylated hemoglobin, blood pressure, treatment

Web-based guideline messaging

plan, weight, diet, and lipid levels; graphical

system with videoconferencing.

longitudinal displays.

It did not include benchmarks for long-term complications such as: eye and foot exam, albumin.

Glucose, blood pressure, diet, weight

This paper comes from the same

(Shea et al. 02)

research group as the above (Starren et al), and was based on same project. Similarly, it did not include such longterm complication benchmarks as albumin, eye exam, foot exam.

Lab: blood glucose, glycated hemoglobin, urinary

This study included most long-term

microalbumin, lipid profile (total cholesterol,

complication indicators but did not

triglyceride, and HDL cholesterol);

include cardiac measurement.

(Smith et al. 98)

Vital signs: Blood pressure (diastolic and systolic pressure), foot exam, eye exam; Lifestyle: smoking status; Education: on diet & diabetes management

Frequency of foot/eye check, lipids exam;

This paper was published by same

Metabolic outcomes: HbA1c, microalbuminuria,

research group as Smith (above). It

lipids (LDL cholesterol, total cholesterol,

did not include a cardiac surveillance

triglycerides), blood pressure, exercise/smoke

indicator.

(Montori et al. 02)

advice, diet, immunization

HbA1c, LDL cholesterol, blood pressure, eye and

This paper is based on third-party

foot exam

software: COSTAR. For long-term complication measurement, it did not

16

(Meigs et al. 03)


Indicators included in eTools


Comments on Applications

References

include albumin and cardiac indictors. Glucose, HbA1c (glycated hemoglobin),

This study did not include blood

microalbumin, LDL, and retinal (eye/foot exam)

pressure and cardiac measurement for

(Baker et al. 01)

long-term complications. Glucose meter date upload, Glycohemoglobin

This study did not include: lipids,

[HbA1c], daily diary, clinical email.

albumin, blood pressure, eye/foot

(Goldberg et al. 03)

exam, cardiac measurement. Blood glucose, blood pressure or weight, drug

This study did not include: eye/foot

information (types and dosages of insulin, oral

exam, cardiac, albumin measurement.

(Kwon et al. 04)

antidiabetic medication), diet, exercise.

From information in the above table, I found that most eTools were for managing acute diabetes complications. Some included long-term components, but since they were missing key benchmarks they were not effective for long-term diabetes complications surveillance.

Patient's self-management is highly encouraged in chronic disease management. To optimize access to eTools, some researchers have investigated the factors that impact patients’ use of IT when managing chronic disease. It was found that some people are unwilling to use the Internet as a health tool for several reasons(Gimenez-Perez et al. 02): “Lack of IT training; anxiety and stress; derived information from different sources; lack of time; poor readability; concerns about quality of information; lack of a specifically-designed and professionally-moderated Web page.”

Another study of an Internet-based diabetes management system found that proactive outreach and patient tracking are critical success factors. Personalization is important for chronic disease management, such as a self-management plan, as individuals are ultimately responsible for its success. “Consequently, an Internet-based diabetes management system must allow patients to tailor the intervention to their specific needs”(Mazzi and Kidd, 02).

Patients hold particular views about accessing their electronic records. These are important to consider when designing electronic tools (like DCSS). Pyper and colleagues conducted a descriptive study to discover patients’ attitudes to EHRs in a primary care setting in Oxfordshire, UK. The author analyzed data by stratifying it by age and sex. Patients used private EHR viewing booths with a computer. The

17



results showed: 1) 86% thought that patients should have the right to see their records, 2) 72% knew that they had the right to see their records, and 3) 4% had done so. Of the 100 patients who saw their online EHR, 99% found the session useful and 84% found their records easy to understand(Pyper, Amery, Watson, Crook, and Thomas, 02).

Honeyman’s study revealed “the interest and expectations of patients having access to their electronic care records.” This qualitative study applied “semi-structured prospective interviews” in a community setting in London. A booth was provided to patients to access their electronic records in the waiting room. Overall, the results for this qualitative study were positive. “Patients were more interested in seeing their electronic than their paper record; they felt it would improve their relationship with their clinician; they generally trusted in the security of their records; they anticipated that there would be some mistakes; they were enthusiastic about the idea of adding to the record themselves, but were divided about having access over the Internet. Patients are confident in and anticipate the value of having access to their electronic records”(Honeyman, Cox, and Fisher, 05).

Hassol’s study was based on a setting of “an integrated provider network located in 31 counties of north central Pennsylvania” including clinic sites, hospitals, and 1.5 million outpatient visits per year. The research group applied a commercial EHR from Epic Systems Corporation, called EpiCare. “The application is Web based and it allows patients to view selected portions of their EHR.” It was a descriptive study conducted over a six-month period. The author conducted “an online survey of active MyChart users who had registered, [and] activated their account.” For the online survey, “responses were based on a continuous scale, which ranged from 1 (hard to use or strongly disagree, depending on the question) to 100 (easy to use or strongly agree)”(Hassol et al. 04).

2.4

Study Objectives

Under the Chronic Care Model framework, a number of studies have attempted to illustrate its value in improving chronic disease management. Several studies focused on DM, showing that CCM can improve clinic outcomes and reduce costs(Bodenheimer et al. 02a;Glasgow et al. 01;Wagner et al. 01b;Warsi et al. 04). Providing appropriate information and teaching problem-solving skills are important determinants of self-management in CCM(Bodenheimer et al. 02b).

There are numerous examples of the development of Web-based information technology for improving diabetes management. Most of these studies have focused on the evaluation of clinical outcomes. A 18



few reported on the system development approach, such as the selection of patient demographic indicators, clinical benchmarks, and disclosure of the development process.

In response to the self-management imperative, I developed the DCSS, embedding appropriate, evidence-based information and data fields supported by research evidence into the tool. The literature does not offer a self-management tool specifically designed for diabetes complication surveillance. Therefore, the use of a Web-based electronic system to address the surveillance of the complications per se has not been developed or piloted until this study. Thus, this study is novel and unique: first, it presents an electronic tool for diabetes mellitus patients to assist with self-surveillance, including acute and long-term complications. Second, the tool is predicated on the best available clinical research evidence, the Canadian Diabetes Association’s Clinical Practice Guidelines.

19


Chapter 3 – Methods

CHAPTER 3: METHODS This section describes the study design, the development process relating to the DCSS, and the project timelines, as well as a modest pilot of the DCSS that administered survey questionnaires, recruited participants, collected data, and measured outcomes.

I was responsible for all stages of this project. I communicated with doctors, nurses, patients, and IT staff, and also provided consultation for the study design, questionnaire design, data analysis and report writing. In addition, I worked on the tasks of preparing and distributing questionnaires, recruiting patients, supporting patient Web access, and collecting, entering, analyzing and reporting data. I translated the medical requirements into IT language and instructed developers to develop a two-way, real-time, Web-based DCSS application. I also worked on the eTool implementation and technical support, such as system installation, configuration, and maintenance.

3.1

Overview

The DCSS is an electronic tool designed to facilitate the self-management of diabetes complication surveillance. This electronic tool was designed for regularly monitoring key benchmarks for diabetes complication surveillance. This is an important attribute of this electronic tool. As indicated in the previous chapter, as controlling diabetes complications becomes more serious, key benchmarks should be on target, e.g., periodic eye/foot checks should be done; lab results should remain under certain recommended values. This eTool provides functions that monitor the process and the outcomes on those benchmarks for various diabetes complications.

The DCSS prototype can display interactive patient-specific clinical data through the Internet. It is possible for patients to access their diabetes medical information from anywhere and at any time. The Website was developed as a demonstration site for the pilot study; it allowed patients to walk through the application to get some experience. In the pilot study, some outpatients with diabetes were selected for utilizing the DCSS and providing feedback via questionnaire. They were diagnosed as having diabetes and had Internet access to the Web-based DCSS prototype.

20


3.1.1


Timeline

In this project, the key steps included system design, development, implementation, evaluation, and reporting writing. The key activities, milestones, and time frames are summarized in Table 2 below. Subsections that follow the table describe each phase in detail. Table 2 DCSS Project Timeline Section Timeline 3.2 Initiation (Nov. – Dec. 2004) 3.3 Month 1–6 (Jan. – Jun. 2005)

Tasks Project scope and IT approach Development & Implementation (3.3) • • •

3.4

Month 7–12 (Jul. – Dec. 2005)

Pilot of DCSS (3.4) • •

3.2

Data fields definition (3.3.2~3.3.3) System design (3.3.4) Development / Implementation (3.3.5)

Data collection (3.4.1~3.4.2) Data analysis and knowledge dissemination (3.4.3~3.4.4)

Initiation

During this period, through consulting with my study supervisor, I determined the topic of the project based on the following information: -

What I had learned about the principles of health informatics, which includes applying IT in health care to improve quality of care;

-

My study supervisor’s expertise, and her opinion about the needs in clinical practice;

-

Results of a literature review regarding a suitable topic within the eHealth field;

-

The importance and value of a research topic dealing with one type of chronic disease.

Based on the purpose and goal of the study, I determined the scope of the project, which included developing a Web-based eTool focusing on patients with diabetes complications, and carrying out a pilot study of the eTool. The resources and budget needed to accomplish the project were also considered. The timeline was determined as well.

3.3

Development and Implementation of Electronic Tool “DCSS”—Months 1–6

The DCSS provides patients with a live environment to apply a Web-based program to enhance the self-surveillance of diabetes complications. The DCSS includes 9 evidence-informed clinical benchmarks based on CPG as well as on consultations with clinical experts.

21


3.3.1


System Overview

The online DCSS prototype was designed and developed by medical and IT professionals. The DCSS application worked as a Web-based portal that allowed health care providers and clients to access patients’ information online. Medical information can be entered into the DCSS electronically from home, lab, hospital, or point of care. Patients can view their information from multiple places (i.e., health care sites, including doctors’ offices and their own homes) at anytime.

3.3.2

User Profile Data Fields Selection

The data fields for patient demographic information were derived from the paper-based form records that were used in the clinic. The author also made use of his other EMR application experience in selecting the data fields. This demographic information conformed to the specifications of the Ontario Provincial Enterprise Master Patient Index project for client registry data fields. Data fields like medical records (ID) number, OHIP number, last name, first name, date of birth, address, and phone number are the key patient identifiers in an EMR system.

3.3.3 Surveillance Benchmarks Selection The essential benchmarks for the DCSS were identified from: 1) “Clinical Practice Guidelines [CPG] 2003,” published by Canadian Diabetes Association [CDA](Canadian Diabetes Association, 03); 2) a literature review on diabetes(Votey and Peters, 05); 3) other eTool publications related to diabetes; and 4) the recommendations of clinical experts. Table 3 summarizes the benchmarks, their sources, and the main rationale for their inclusion in the DCSS.

Table 3 Surveillance Benchmarks and Sources Benchmarks CPG

1

3

Acute Complication HbA1c X (Hemoglobin A1C)

Sources (2) DM Ref eTool Ref (3)

Rationale for Inclusion3 (4) Expert

X

X

X

It is mainly used to track average blood glucose levels based on average lifetime of red blood cells which contain hemoglobin.

2

FBG (Fasting Blood Glucose)

X

X

X

X

It is a key indicator to monitor diabetes. Glucose accumulated in the blood will lead to various complications.

3

Lipids, LDLC

X

X

X

X

High blood lipid levels lead to vascular damage, which will increase diabetes complications.

http://en.wikipedia.org/wiki/Diabetes_mellitus

22


4

Body Mass Index (BMI)(1)

X

X

5

Blood Pressure (Systolic / Diastolic )

X

X

7

Long-term Complication Urinary X X Albumin Excretion Rate Eye Exam X X

8

Feet Exam

9

Heart Exam (ECG)

6

X

X


X

Weight should be evaluated in relation to height, rather than on its own.

X

X

Blood pressure control, and lifestyle factors such as maintaining a healthy body weight, may reduce the risk for most of the chronic complications.

X

X

To detect a serious diabetes long-term complication, chronic renal failure

X

X

To monitor a serious diabetes long-term complication, retinal damage, which can lead to blindness

X

X

To monitor a serious diabetes long-term complication, microvascular damage; poor wound healing, particularly of the feet, can lead to gangrene.

X

To detect a serious diabetes long-term complication, cardiovascular disease

X

* notes: (1). BMI (calculated by weight and height) is related to physical activity/exercise, which is indicated by CPG, diabetes Ref. (2). “X” above means that sources recommended this benchmark. (3). For details, refer to Table 1. (4). According to 2003 Clinical Practice Guidelines [CPG] published by Canadian Diabetes Association [CDA] and related literature, to stop diabetes from progressing and prevent diabetes complications, HbA1C, blood glucose, lipids, and BMI levels should be under the target values, and the checking period should be on schedule. Comparing with an updated CPG from CDA, there is no major difference between version 2008 and 2003, such as benchmarks, target values, and checking period.

Details of Information Source 1. Clinic Practice Guide on Diabetes Diabetes can cause many complications. To control diabetes complications, related indicators to be monitored are: hypertension (blood pressure), hyperlipidemia (lipid, LDL, and HDL), nephropathy (urinary albumin), neuropathy (10-g Semmes-Weinstein monofilament), retinopathy, erectile dysfunction, and macrovascular complications (foot ulcers). 23



2. Literature on Diabetes Search criteria: terms included diabetes mellitus, diabetes, diabetes complications, blood glucose, HbA1c, nephropathy, neuropathy, retinopathy, diabetes control, hypertension, cardiovascular disease. Language is English, without restriction on the timeframe.

According to “Diabetes Mellitus, Type 2—A Review”(Votey et al. 05), indicators to be monitored are: blood glucose, HbA1c, diet or exercise. Microvascular complications include: retinopathy (eye examination) and nephropathy (urine protein and serum creatinine). Macrovascular complications include: hypertension (BP, ACE taken), coronary artery disease (ECG), peripheral vascular disease, cerebrovascular disease (transient ischemic attack), and hyperlipidemia (lipid levels). Other complications includes: neuropathy, diabetic foot (foot ulcers). Physical indicators include: vital signs, funduscopic examination, and foot examination.

3. Literature on eTool -related Diabetes Another source for determining indicators is other publications that are relevant to using eTools for managing diabetes (see Table 1). Through reviewing those papers which discussed using EMRs in managing diabetes, I determined what indicators other researchers had employed in their applications. Since those indicators should be useful in managing DM, I included them in our application as well.

4. Consultation with Clinical Experts Having identified a number of diabetes complication surveillance indicators through the criteria noted above, I asked four clinical experts (mentioned in Acknowledgement section, mainly nephrology specialists) to provide feedback regarding the indicators they preferred for diabetes self-management and complication surveillance.

All of this yielded three criteria for selecting indicators to include in the DCSS: frequency of use in the field, as documented by the literature and the clinical practice guide; suggestions from the experts I had consulted; and suitability for patients’ self-monitoring at home by themselves.

24


3.3.4


System Design

To build this Web-based DCSS, two major design steps were taken. The first, the medical design step, was to select key medical benchmarks which can represent the status and progress of diabetes, as well as indicate the risk of diabetes complications. This step also involved designing flow charts for the DCSS. The second, technological step was to choose an IT approach that could develop such an application within budget.

The system design had to be patient-oriented. Applying the theory from Knowledge Media Design, the principal investigator combined the concepts of human and machine, society and technique in developing this application to be used for diabetes patients and providers. Because most of the diabetes patients were elderly people, the design process had to consider their special requirements. For instance, the font should be large enough, and the layout should be simple and follow a simple business flow (unlike some media Websites which have lots of fancy stuff that could confuse users).

3.3.5

DCSS Development / Implementation

1) Steps First of all, I established a system development environment. It included installation and configuration of hardware, network, and software. I also needed to configure the Web server [Tomcat5.0], database, ODBC [Open Database Connectivity], and network TCP/IP.

Prior to the programming, I identified the application requirements. It included Web page layouts, workflow from one page to another, and the linkage between tables in the database.

During the programming stages, following the technical design, the development team created each Web page under the DCSS prototype. After I got the prototype, I reviewed it and discussed if anything needed to be improved. If I was satisfied with the application based on the functional requirements, I finalized the application. During the testing that followed, I found certain minor problems in the application, and then I requested that the developer solve the problems and ensure the system worked properly. After repeating these debugging processes several times, I concluded that the system was okay to use.

After I got the completed application, I implemented it on another testing server where the Internet was accessible. Later, I provided this application to pilot study users. 25



Figure 1 Business Logic Workflow system requirements code and debug software requirements test and preoperations preliminary design operations and maintenance detailed design

Application Development

There were other important aspects considered within the IT scope: •

Advanced information technology was used for the system development. System performance, capability and scalability were determined. To get the optimal performance, I considered all related factors, such as hardware device (server, network connection, etc), software (operating system, database system, etc), Web server, back-end and front-end programming languages, database architecture, system workflow, etc.

•

Security and privacy were critically considered with reference to the Personal Health Information Protection Act 2004 by the Ontario Ministry of Health and Long-Term Care4—for instance, who can access what.

•

System user interface design: layout, button, text, font size, etc. This design focused on the system's usability from the perspective of the seniors who would make up the bulk of the research subjects.

Through analyzing the scope of the project, I determined the content of the DCSS Website and programming architecture. An outline detailing the creative content of each section of the Website was developed, along with a comprehensive site flow chart mapping out the relationship and links required

4

Health Information Protection Act, 2004 http://www.health.gov.on.ca/english/providers/legislation/priv_legislation/priv_legislation.html

26



in the initial roll-out. Before programming, I reviewed the outline and the flow chart. Upon the completion of the first cycle of development, I tested the application and communicated our comments to developers for debugging. Finally, when I was satisfied with the application, I implemented the application and finalized the deployment.

To illustrate how the system works, artificial patient records were presented on the demo Website. The Website could be accessed through the Internet from anywhere via a Web browser that used HTTP protocol, i.e., Internet Explore [IE]. In my pilot study, I recruited 12 outpatients with diabetes receiving care from a hemodialysis unit and diabetes clinic at a university-based facility, St. Michael’s Hospital in Toronto, Ontario. These patients were diagnosed as having diabetes with related symptoms and laboratory test results. Each patient was given a unique login ID and password to access the demo Website and get experience using the entire application.

2) DCSS Technical Specification System capacity, network protocol, and future scalability were carefully considered in the project.

Computer Hardware •

I selected a Dell computer system to host the Website after comparing the price and performance of different brand names, i.e., Dell, IBM, and HP. After testing, I confirmed that the Central Processing Unit [CPU], memory, and hard drive of a Dell machine were sufficient to process the data access.

Computer Software •

Operating system: Microsoft Windows Server 2000 was used to host the Website.

•

Database: Microsoft Access 2000 was selected to store the surveillance medical benchmark data.

•

Development software: HomeSite 4.5 for programming, and PhotoShop 6.0 for image processing.

•

Other software, i.e., File Transfer Protocol [FTP], was used for file uploading and downloading if working remotely.

Network

27


•


I managed the Internet connectivity independently via a Netgear router as a firewall device. It was installed to protect the system by port filtering.

•

I used Rogers Cable Network for Wide-Area Network (WAN) access.

•

To ensure the security of Internet data transfer, I closed all other ports, only opening the port for Hypertext Transfer Protocol [HTTP].

Other Devices: •

Uninterrupted Power Supply [UPS] and external hard drive for data backup were implemented as well.

Programming Language •

Java, a new generation Web-based programming language, was used for this Internet-based application development. The Web pages are called Java Server Pages [JSP].

Web Server •

Jakarta-Tomcat-5.0.12

Backup Plan •

A scheduled backup plan was created for data backup and disaster restoration. The entire Website is backed up on another computer hard drive. Thus, two copies of the source code and data were stored.

Data Security •

Besides using a firewall, clients (doctors and patients) needed login ID and password to access the demo Website and get experience of how the system works.

•

A routine of login authentication was carried out. Through user accounts setup, I controlled the permission of user access level.

•

3.4

I authorized patients to access by an email notification.

Pilot of DCSS—Months 7–12

This was a modest attempt to gauge patient perspectives on the utility of accessing EHRs and, more specifically, accessing a tool like the DCSS. The approach was first to introduce diabetes patients to an

28



interactive Web-based DCSS, then to evaluate patients’ attitude to accessing the DCSS prototype through a questionnaire that I developed (see Appendix 2). Originally, I had planned to apply DCSS to real patients visiting a haematology clinic situated in a hospital. Privacy and confidentiality concerns were raised by hospital authorities (i.e. privacy councilor, IT department), however, which necessitated using hypothetical data in my study.

3.4.1 Development of Brief Questionnaire “Patients' Views of DCSS Utility” Using a survey questionnaire, I collected patient evaluation data on the DCSS. Due to the fact that I could not find an applicable existing questionnaire, I developed one based on relevant literature and referred to literature on survey development. 1) My draft questionnaire included questions on usefulness and ease of use(Mazzoleni et al. 96). Other questions related to patient satisfaction, their knowledge of having the right to access their records, Internet usage behaviour, improved interactions with health professionals, and improved understanding of health and illness(Pyper, Amery, Watson, and Crook, 04;Cimino, Patel, and Kushniruk, 02).

2) I invited nephrologists, nurses and patients (from the hemodialysis unit) to review the draft questionnaire for face validity(Al Windi, 03). I modified the questionnaires based on this feedback. Specifically, I made the following revisions: •

Simplified the language to facilitate patients understanding;

•

Used a bigger font (14 pt. font on questionnaires);

•

Shortened the pages by eliminating some titles;

•

Worded the questions in a more easily understandable way.

The final version of the questionnaire is provided in Appendix 2. There were several domains covered in the survey: •

General information on subject enrollment and characteristics, i.e., age, gender, education, first language.

•

Internet usage, and accessing health information on the Internet

•

Patient knowledge of having the right to access their health record.

•

Patient response to electronic health records in terms of pros and cons, and whether they would like to access their EHR.

29


•


Patient concern about security and privacy of their EHR, and patient awareness of having the right to decide who can see what from their records.

•

Patient response to whether an EHR will help them to better understand and manage disease, as well as to reduce errors.

•

Patient response to the usefulness of the DCSS, such as improving diabetes management and communication with health care providers.

3.4.2

Participant Recruitment / Data Collection

Study participants were recruited from a diabetes clinic and hemodialysis clinic at St. Michael’s Hospital. Most patients had been given requisitions to complete parts of a diabetes complication surveillance screen. The recruitment period was June to August 2005. To access the DCSS, patients were requested to access the Internet (i.e., from home, or a relative’s house, or a public place—library, etc). Otherwise they could not access the DCSS.

I would like to note that although this study was conducted in a hospital based primary care setting, it could realistically have applied to any clinical setting associated with chronic care. The DCSS system was not developed exclusively for application in hospitals; it can be more generally applied to settings including non- acute care settings, i.e. primary care, and long term care.

In total, I talked to 75 patients. Of these, 43 were interested in participating in the study, and they got the questionnaire. Of those 43 patients, 35 gave me back completed questionnaires, but 23 of those 35 had no access to the DCSS. The remaining12, who did have access to the DCSS, became my enrolled participants for pilot testing the DCSS.

After patients agreed to participate in the study, they had to read through the survey package and sign an informed consent form. Subsequent to accessing the DCSS, patients completed the questionnaire, and returned it to the clinic office within two weeks.

3.4.3

Data Analysis

The purpose of the pilot was to discover patient views regarding accessing the Web-based DCSS, which can potentially facilitate diabetes self-management. I collected the following domain information:

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•

Patient behaviour and frequency of using the Internet;

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Patient knowledge about accessing their medical records;

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Patient perceptions of using a Web-based EHR, such as satisfaction, expectations, privacy considerations, recommendations, etc.

For each question, I analyzed the frequency ratios of patient “Yes/No/Don’t know” responses using SPSS software.

3.4.4

Privacy and Confidentiality

To protect patients’ privacy, patient identification was removed during data analysis. All information obtained in this study was kept confidential and used only for research purposes. Any future published results of the study will not discuss individual patients.

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Chapter 4 – Results

CHAPTER 4: RESULTS This section presents the functionalities of the DCSS and the results of the small pilot that assessed patient feedback regarding the tool.

4.1

Development of Electronic Tool “DCSS” 4.1.1.

User Profile Data Fields

The following table lists fields containing demographic information on patients that were used in my study. It is suitable for both doctor and patient profiles. Table 4 Demographic Information in the DCSS Fields MRN OHIP# and version Name Date of birth Marital status Gender Street address City Province Postal code Phone numbers office phone home phone cell phone pager Email address Payment program

Description medical record number used for patient only last name, first name, middle name

4.1.2. Surveillance Benchmarks The key benchmarks used for the DCSS are included in Table 5.

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Chapter 4 – Results

Table 5 Clinical Benchmarks in Diabetes Complication Surveillance (based on data in 2005) Domain

Benchmark

Clinical

Lab Test

Frequency of review

Targets/Desirable Findings Control 1

HbA1c