• unlimited access with print and download
    $ 37 00
  • read full document, no print or download, expires after 72 hours
    $ 4 99
More info
Unlimited access including download and printing, plus availability for reading and annotating in your in your Udini library.
  • Access to this article in your Udini library for 72 hours from purchase.
  • The article will not be available for download or print.
  • Upgrade to the full version of this document at a reduced price.
  • Your trial access payment is credited when purchasing the full version.
Buy
Continue searching

A quantitative exploration of the relationship between patient health and electronic personal health records

ProQuest Dissertations and Theses, 2009
Dissertation
Author: Denise Williams Hines
Abstract:
The use of electronic personal health records is becoming increasingly more popular as healthcare providers, healthcare and government leaders, and patients are seeking ways to improve healthcare quality and to decrease costs (Abrahamsen, 2007). This quantitative, descriptive correlational study examined the relationship between the degree of use of electronic personal health records and patient health through the measurement of patient satisfaction among the patients at North Fulton Family Medicine. Analysis of the data indicated a statistically significant relationship between patient satisfaction and the degree of use of the electronic personal health record. The results of this study support the conclusion that the use of electronic personal health records improves patient satisfaction and overall patient health.

vi TABLE OF CONTENTS LIST OF TABLES.............................................................................................................ix LIST OF FIGURES..........................................................................................................xii CHAPTER 1: INTRODUCTION........................................................................................1 Background of the Problem.................................................................................................2 Statement of the Problem.....................................................................................................7 Purpose of the Study............................................................................................................9 Significance of the Study...................................................................................................10 Nature of the Study............................................................................................................14 Research Questions............................................................................................................16 Hypotheses.........................................................................................................................17 Theoretical Framework......................................................................................................17 Definition of Terms............................................................................................................21 Assumptions.......................................................................................................................25 Scope..................................................................................................................................26 Limitations.........................................................................................................................26 Delimitations......................................................................................................................27 Summary............................................................................................................................27 CHAPTER 2: REVIEW OF THE LITERATURE............................................................29 Documentation...................................................................................................................30 Literature Review………………………………………………………..............……….32 Historical Overview...........................................................................................................32 Theoretical Foundation……………………………………………………….............….35

vii Healthcare Quality……………………………………………………………….............37 Transformational Leadership…………………………………………………….............47 Technology in Healthcare………………………………………………….................….50 Quality and Treatment Outcomes and the use of Information Technology……...............56 Conclusion.........................................................................................................................59 Summary............................................................................................................................59 CHAPTER 3: METHOD...................................................................................................61 Research Design.................................................................................................................62 Appropriateness of Design.................................................................................................64 Population..........................................................................................................................66 Sampling Frame……………………………………………………………….................66 Informed Consent...............................................................................................................67 Confidentiality...................................................................................................................69 Geographic Location..........................................................................................................70 Instrumentation..................................................................................................................71 Data Collection..................................................................................................................73 Data Analysis.....................................................................................................................74 Validity and Reliability......................................................................................................75 Summary............................................................................................................................76 CHAPTER 4: PRESENTATION AND ANALYSIS OF DATA………………..............78 Data Collection…………………………………………………………………..............80 Demographics…………………………………………………………………................81 Patient Satisfaction and Patient Health……………………….……………….................86

viii Adherence to Treatment Regimens…………………………………............……………95 Findings………………………………………………………………………................107 Research Questions and Hypothesis……………………………………………............109 ANOVA Analysis………………………………………………………………............122 Summary…………………………………………………………………………..........124 CHAPTER 5: CONCLUSIONS AND RECOMMENDATIONS………………...........127 Findings and Conclusions………………………………………………………............131 Implications……………………………………………………………………..............139 Significance to Leadership………………………………………………………...........143 Recommendations………………………………………………………………............147 Summary………………………………………………………………………..............149 REFERENCES …..........................................................................………….……... …151 APPENDIX A: PERMISSION TO USE PREMISES.....................................................169 APPENDIX B: INFORMED CONSENT FORM....................................................…...171 APPENDIX C: PERMISSION TO USE AN EXISTING SURVEY………….............. 174 APPENDIX D: COPY OF SURVEY INSTRUMENT…………………………...……176 APPENDIX E: DEMOGRAPHIC DATA FREQUENCY CHARTS………………….180 APPENDIX F: PATIENT SATISFACTION DATA FREQUENCY CHARTS………187 APPENDIX G: SCATTER PLOTS-DEMOGRAPHICS AND DEGREE OF USE…...195 APPENDIX H: SCATTER PLOTS-PATIENT SATISFACTION AND DEGREE OF USE……………………………………………………………………...208 APPENDIX I: ANOVA CALCULATIONS-LAST TIME LOGGED IN……...……...219 APPENDIX J: ANOVA CALCULATIONS: FREQUENCY LOGGING IN…………221

ix LIST OF TABLES Table 1 Summary of Literature Reviewed by Search…………………………………………31 Table 2 Participant Race/Ethnicity………………………………………………………82 Table 3 Participant Age………………………………………………………………….83 Table 4 Participant Gender……………………………………………………………...83 Table 5 Participant Educational Level…………………………………………………..84 Table 6 Participant Computer Skills……………………………………………………..85 Table 7 Participant Time Using the Internet…………………………………………….86 Table 8 When Was the Last Time You Logged into My Health Portfolio?........................88 Table 9 Demographics-Never Logged into My Health Portfolio………………………..89 Table 10 How Often Do You Log into My Health Portfolio?............................................90 Table 11 Demographics-Log into My Health Portfolio Rarely and Every Few Months................................................................................................................................91 Table 12 Demographics-Log into My Health Portfolio Every Few Weeks and Every Few Days……………………………………………………………………..…...92 Table 13 Helps Communication Between the Patient and the Provider………………...93 Table 14 Demographics-Strongly Disagree and Disagree-Helps Me Communicate with My Healthcare Professional………………………………………………………..94 Table 15 Demographics-Strongly Agree and Agree-Helps Me Communicate with My Healthcare Professional…………………………………………………………………95 Table 16 Helps Me Organize and Keep Track of My Healthcare Information.….……...96 Table 17 Demographics-Disagree-Helps Me Organize and Keep Track of My Healthcare Information…………….…………………………………………………....97

x Table 18 Demographics-Strongly Agree and Agree-Helps Me Organize and Keep Track of My Healthcare Information…………………………..………………………...98 Table 19 Helps Me Understand Choices and Make Better Decisions About My Health……………………………………………….…………………………………....99 Table 20 Demographics-Disagree-Helps Me Understand Choices and Make Better Decisions About My Health…………………………………………………………….100 Table 21 Demographics-Strongly Agree and Agree-Helps Me Understand Choices and Make Better Decisions About My Health……………………….………………….101 Table 22 Helps Me Follow My Treatment Plans……………………………………….102 Table 23 Demographics-Disagree-Helps Me Follow My Treatment Plans……………103 Table 24 Demographics-Strongly Agree and Agree-Helps Me Follow My Treatment Plans……………………………...…………………………………………104 Table 25 Helps Me Take a More Active Role in My Own Healthcare…………………105 Table 26 Demographics-Disagree-Helps Me Take a More Active Role in My Own Healthcare………………………………………………………………………………106 Table 27 Strongly Agree and Agree-Helps Me Take a More Active Role in My Own Healthcare………………………………………………………………………………107 Table 28 Descriptive Statistics of Demographic and Patient Satisfaction/Patient Health Items…………………………………………………………………………….108

xi Table 29 Pearson Coefficient for Research Question 1………………………………...113 Table 30 Pearson Coefficient for Research Question 2………………………………...117 Table 31 Pearson Coefficient for Research Question 3………………………………...121 Table 32 ANOVA Calculation for Age and Last Time Logged Into My Health Portfolio……………………….………………………………………………………..122 Table 33 ANOVA Calculation for Computer Skills and Last Time Logged Into My Health Portfolio.…………………………………………………………..………..123 Table 34 ANOVA Calculation for Race and Gender and Frequency Logging Into My Health Portfolio..………………………………………..……………………..123

xii LIST OF FIGURES Figure 1. Frequency for Race/Ethnicity………………………………………………..181 Figure 2. Frequency for Age…………………………………………………………...182 Figure 3. Frequency for Gender………………………………………………………..183 Figure 4. Frequency for Education Level………………………………………………184 Figure 5. Frequency for Computer Skills………………………………………………185 Figure 6. Frequency for Internet Usage………………………………………………...186 Figure 7. Frequency for Last Time Logged into My Health Portfolio…………………188 Figure 8. Frequency for Logging into My Health Portfolio……………………………189 Figure 9. Frequency for My Health Portfolio Helps Me Communicate with My Healthcare Professionals………………………………………………………………..190 Figure 10. Frequency for My Health Portfolio Helps Me Organize and Keep Track of My Healthcare Information……………………..…………………...………………191 Figure11. Frequency for My Health Portfolio Helps Me Understand My Choices……192 Figure 12. My Health Portfolio Helps Me Follow My Treatment Plan………………..193 Figure 13. Frequency for My Health Portfolio Helps Me Take a More Active Role in My Own Healthcare……………………………………..………………..........194 Figure 14. Scatter plot of Race/Ethnicity as compared to Frequency Logging into My Health Portfolio……………………………………………………………….....…196 Figure 15. Scatter plot of Race/Ethnicity as compared to Last Time Logged into My Health Portfolio…………………………………………………………………………197 Figure 16. Scatter plot of Age as compared to Frequency Logging into My Health Portfolio………………………………………………………………………………...198

xiii Figure 17. Scatter plot of Age as compared to Last Time Logged into My Health Portfolio………………………………………………………………………………...199 Figure 18. Scatter plot of Gender as compared to Frequency Logging into My Health Portfolio…………….…………………………………………………………...200 Figure 19. Scatter plot of Gender as compared to Last Time Logged into My Health Portfolio………………………………………………………………………………...201 Figure 20. Scatter plot of Education Level as compared to Frequency Logging into My Health Portfolio…………………………………….………………………………202 Figure 21. Scatter plot of Education Level as compared to Last Time Logged into My Health Portfolio…………………………………………………………….………203 Figure 22. Scatter plot of Computer Skills as compared to Frequency Logging into My Health Portfolio……………………………………………………………….……204 Figure 23. Scatter plot of Computer Skills as compared to Last Time Logged into My Health Portfolio………………………………………………………………….…205 Figure 24. Scatter plot of Internet Usage as compared to Frequency Logging into My Health Portfolio……………………………………………………………….……206 Figure 25. Scatter plot of Internet Usage as compared to Last Time Logged into My Health Portfolio……………….……………………………………………….…...207 Figure 26. My Health Portfolio Helps Me Communication With My Healthcare Professionals as compared to Frequency Logging into My Health Portfolio….………209 Figure 27. My Health Portfolio Helps Me Communication With My Healthcare Professionals as compared to Last Time Logged into My Health Portfolio…….…….210

xiv Figure 28. Scatter plot of Helps Me Organize and Keep Track of My Healthcare Information as compared to Frequency Logging into My Health Portfolio……………211 Figure 29. Scatter plot of Helps Me Organize and Keep Track of My Healthcare Information as compared to Last Time Logged into My Health Portfolio……………..212 Figure 30. Scatter plot of Helps Me Understand My Choices as compared to Frequency Logging into My Health Portfolio……………………………………..…...213 Figure 31. Scatter plot of Helps Me Understand My Choices as compared to Last Time Logged into My Health Portfolio………………………………..……………….214 Figure 32. Scatter plot of Helps Me Follow My Treatment Plan as compared to Frequency Logging into My Health Portfolio………………………………………….215 Figure 33. Scatter plot of Helps Me Follow My Treatment Plans as compared to Last Time Logged into My Health Portfolio………………………………………………...216 Figure 34. Scatter plot of Helps Me Take a More Active Role in My Healthcare as compared to Frequency Logging into My Health Portfolio…………………………….217 Figure 35. Scatter plot of Helps Me Take a More Active Role in My Healthcare as compared to Last Time Logged into My Health Portfolio……………………………..218

1 CHAPTER 1: INTRODUCTION Electronic personal health records are an Internet-based application that enables patients or care providers to create, review, or maintain a record of aspects of received medical care (Flores, 2005). Electronic personal health records are designed to help patients record, store, and electronically transmit their medical information to doctors and hospitals (Brown, 2007). Some electronic personal health records allow patients to store information entered by the individual and offer the ability to incorporate information directly from physician practices, hospitals, and laboratories (Brown). Since 2005, electronic personal health records have received heightened interest from healthcare industry leaders, advocacy groups, and patients (Ball, Bakalar, & Smith, 2006). The use of electronic personal health records enables patients to become engaged in their own care. In a national online survey, 68% of the respondents said they would use electronic personal health records to get health information, check and fill prescriptions, get test results over the Internet, and to conduct private email communication with their physicians. Electronic personal health records can offer patients education about their personal conditions, streamline administrative information, and help to protect patients from medical errors. Increased communication exchanges between patient and physician can lead to improved care, better clinical outcomes, and greater patient satisfaction (Denton, 2001). According to a national survey, 83% of primary care physicians in the U.S. support the concept of sharing medical records with their patients yet only 14% of physician offices have electronic medical records (Ball, Bakalar, & Smith, 2006). The intent of this quantitative correlation research study was to explore the relationship between the degree of use of electronic personal health records and patient

2 health. Patient health was reported through the measurement of patient satisfaction. This study adds to the body of literature to support the national adoption of electronic personal health records. Electronic personal health records integrated with electronic health records supports greater access to credible health information, data, and knowledge promoting improved health and disease management (Ash, Bates, Overhage, Sands, & Tang, 2006). Improved health and disease management leads to lower chronic disease management costs, lower medication costs, and lower wellness program costs. This chapter outlines the context of the research study, provides an overview of the theoretical framework upon which this study builds, and describes the significance and limitations of the study. Background of the Problem On April 24, 2004, former President George W. Bush issued an executive order supporting the use of health information technology. The executive order acknowledged the need to establish a national healthcare information technology infrastructure to improve the quality and efficiency of healthcare (Goldschmidt, 2005). The executive order also established the national health information technology coordinator position. As defined in the executive order, the role of the national health information technology coordinator is to facilitate the adoption of electronic health records with consistent and uniform technology standards by the year 2014 (Bush, 2004). In 2005, David Brailer, the national coordinator for health information technology, announced support of unified, consumer-oriented electronic personal health records with guaranteed privacy and security for all Americans in the national health information technology infrastructure (Horan, Lafky, & Tulu, 2006).

3 A national health information technology infrastructure will help to (1) ensure appropriate information is available to guide physicians when making medical decisions, (2) promote a more effective healthcare marketplace, greater competition, and increased consumer choices through the availability of health information, and (3) protect and secure patient health information (Bush, 2004). Health information technology combined with the Internet is projected to foster patient-focused care to enable consumers to drive the transformation of the U.S. healthcare system (Goldschmidt, 2005). Relating patient outcomes to care processes and having the ability to measure providers’ performances are expected to reduce medical errors and improve quality. A national health information technology infrastructure may help to automate the sharing of information among patients and providers, resulting in a decrease of duplicative tests, decreased office visits, and decreased hospital admissions. For physicians, a national health information technology infrastructure may decrease the risk of malpractice suits. Other primary benefits of a national health information technology infrastructure include improved clinical outcomes through access to patient and diagnostic data for physicians and caregivers (Goldschmidt, 2005). Direct access and instant updates to records as well as remote access for physicians to patient records are available through the use of technology. Greater provider productivity may result through the automation of routine data collection using more complete, more accurate, and more organized clinical data and documentation (Goldschmidt). Reduced laboratory and radiology test ordering by providers who use information technology improved productivity by 14% (Powner, 2005). Fewer medical mistakes resulting from poor handwriting and higher quality patient care through the acceleration of care evaluation using decision support tools and

4 predictive modeling are other benefits of a national health information technology infrastructure (Goldschmidt, 2005). In addition, the use of information technology by physicians reduced medication usage for patients by 11% (Powner, 2005). Greater provider productivity and fewer mistakes could save the nation $140 billion annually in healthcare spending as described by the Secretary of the U. S. Department of Health and Human Services in the document, The Decade of Health Information Technology: Delivering Consumer-centric and Information-rich Healthcare (Powner). Cost savings are based on (1) electronically sharing healthcare data between providers and stakeholders, saving time and avoiding duplicate tests and (2) avoiding unnecessary outpatient visits and hospital admissions, and (3) more cost-effective medication, radiology, and lab ordering (2005). In the report, Crossing the Quality Chasm: A New Health System for the 21 st Century issued by the Institute of Medicine, the use of information technology by healthcare professionals was recommended to support patient-centered care (Suri, 2002). Patient-centered care encourages the partnership between patient and physician to allow the patient to enjoy a better quality of life. Patient-centered technology such as electronic personal health records offer the mechanism for increased physician and patient communication and information sharing (Beauregard, Giuse, Ing, & Koonce, 2007). Without a national health information technology infrastructure, the standards for providers to adopt electronic medical records which offer an electronic personal health record component for patients are not nationally supported (Colorafi, Endsley, Kibbe, & Linares, 2006). WebMD Health Corporation introduced electronic personal health records in 1999 (Brown, 2007). Since 1999, a number of insurance companies have

5 begun to offer electronic personal health records. Some electronic personal health records store information entered by the individual and incorporate the information provided directly by physician practices, hospitals, and labs. In 2006, less than 1% of healthcare consumers were using a fully functional electronic personal health record (Lufky, Horan, & Tulu, 2006). The number of patients currently using an electronic personal health record remains relatively small (Colorafi, Endsley, Kibbe, & Linares, 2006). One electronic personal health record implementation that has gained national attention is the implementation of the U. S. Department of Veterans Affairs (VA) online personal health record system called myHealtheVet. The VA has been installing the system since 2003. The web-based system currently offers patients a complete one-screen portal to comprehensive personal health history, appointment scheduling and history, wellness reminders, prescriptions, hospital admissions, active health problems, and outpatient history, and the ability to access online health education materials (Horan, Lafky, & Tulu, 2006). The VA is the largest delivery system in the United States and has been recognized as a leader in developing a more coordinated system of care. In the 1990s, VA leadership instituted an electronic medical record system and a quality measurement approach to hold managers accountable for processes in preventive care and the management of chronic diseases (Adams, 2004). The VA serves over 5.3 million patients and VA performance now surpasses that of other health systems on standardized quality measurements. The advances in quality care are contributed in part to the VA’s use and development of electronic health records (Francis et al., 2007). The VA system is considered the most sophisticated electronic health record system in use. MyHealtheVet

6 is an adjunct to veterans’ control over their health and supports possibilities for research. The VA system serves as the national model for integrated care involving patients and physicians (Francis et al., 2007). Support for electronic health records continues to mature nationally. In September 2006, the eHealth Initiative released the results of its third annual survey of health information technology use among 49 states, the District of Columbia, and Puerto Rico (Healthcare Financial Management, 2007). The level of policy activity and leadership at the state level has increased significantly in the past year. Thirty-six bills that call for the use of health information technology were passed in 24 states during 2005 and 2006 and 10 state governors passed executive orders related to the use of health information technology to improve healthcare. Specifically, the use of electronic personal health records has gained increased support from legislators such as Representative Patrick Kennedy of Rhode Island (American Academy of Family Physicians, 2007). In 2007, Patrick Kennedy introduced a health information technology bill that offers financial incentives to create qualifying health records for Medicare patients and their physicians. The bill is co-sponsored by Representatives Dave Reichert and Adam Smith, both of Washington State. The bill is known as the Personalized Health Information Act, H.R. 1368. The bill focuses on the physician-patient relationship by giving patients access to and control of their health data while providing physicians with a more accurate minimum data set of information. The bill also includes a provision to provide physicians $3 annually for each patient who uses a qualified electronic personal health record.

7 The use of electronic personal health records supports the Joint Commission’s patient safety goal to reconcile medications accurately and completely across the continuum of care (Thielst, 2007). The use of an electronic personal health record involving the patient provides a process for obtaining and documenting a complete list of the patient’s current medications upon the patient’s admission into the healthcare organization. The provider can then compare the patient’s list of medications to the list maintained by the provider organization’s records. The use of electronic personal health records helps the referral or transfer of care processes by facilitating the communication of the complete medication list for the patient. Furthermore, as one of the standards for Stroke Specialty, The Commission on Accreditation of Rehabilitation Facilities mandated the implementation of electronic personal health records for all stroke patients in the rehabilitation setting (Kupchunas, 2007). The electronic personal health record must contain specific health information including allergies, medications, health events, advanced directives information, and insurance provider information. The patient education process used by the orthopedic nurse includes teaching patients how to maintain their health record and health promotion (Kupchunas). Statement of the Problem The general problem is although the use of electronic health records reduces turnaround times for clinical results and resolves issues of lost and missing paper results (Boerner, 2004), only about 10% of all healthcare systems in the United States use computerization to support the healthcare delivery process (Boerner). Investigators with the Rand Corporation conducted a study that supports the financial benefits of

8 computerization in healthcare. In the study, the investigators identified that achieving a 90% rate of adoption of electronic health records in hospitals and physician practices would require capital expenditures of $121 billion over a period of 15 years but would yield net savings of $531 billion over the same period (Blumenthal & Glaser, 2007). Paper processing in healthcare creates poor availability of data, illegible patient information, and lack of data recovery (Bleeker et al., 2006). The need for electronic personal health records became critically evident during Hurricane Katrina. Paper files in doctors’ offices were lost to flood waters and local computer systems with patient files were unrecoverable (Kupchunas, 2007). The Katrina evacuees lacked even the most basic personal health information such as medication and dosage information. Patients are unlikely to recall health information under normal circumstances and are even less likely to recall important health information under extremely stressful circumstances (Kupchunas). The current process in healthcare requires patients and caregivers to complete, at each different provider, the necessary paper forms that ask for the same demographic information and medical history of the patient (Thielst, 2007). The more complicated the care, the more time patients and caregivers spend completing repetitive paperwork. The rewriting, reviewing, and confirming processes contribute to the inaccuracy and incompleteness of the medical information of the patient. In a July 2004 Harris Interactive online poll of 2,242 U.S. adults, 42% of the respondents said they kept personal medical records. Of the 42% who kept personal medical records, 86% did so on paper (Colorafi, Endsley, Kibbe, & Linares, 2006).

9 The specific problem is without the adoption of electronic health records by providers that includes an electronic personal health record component, the only way to document and manage clinical outcomes is to review manually a sample of the paper patient charts, discharge data, and claims reviews according to predetermined measurements of quality (McAdams, 2005). With the use of electronic personal health records, both the physician and patient become responsible for managing and supporting treatment outcomes. The goal of this quantitative correlational research study was to explore the effectiveness of electronic personal health records in supporting improved patient health through the measurement of patient satisfaction. To fulfill this purpose, a research study was used to survey the satisfaction of patients and their degree of use of the North Fulton Family Medicine’s electronic personal health record. The patients from the Johns Creek, Georgia location of North Fulton Family Medicine were surveyed. Purpose of the Study The purpose of this quantitative correlational research study was to examine the relationship between the degree of use of electronic personal health records and patient health through the measurement of patient satisfaction among the patients at North Fulton Family Medicine. The independent variable, electronic personal health records use, is defined as the use of computer based health records controlled by consumers to exchange electronically clinical data between the patient and the physician (Goldschmidt, 2005). The dependent variable, patient satisfaction is defined as patients’ judgments and expectations regarding the quality of care received in a medical setting (Albrecht et al., 2004). Patient satisfaction as a measurement of compliance with using the electronic personal health record as a tool to support treatment plans may improve patient and

10 treatment outcomes (Cherrington et al., 2005). Patient satisfaction was explored based on the following variables: (a) communication between patient and physician, (b) the availability of information accessed through the electronic personal health record, (c) the patient-provider relationship, (d) the degree of electronic personal health record use, and (e) the degree of adherence to treatment regimens (Hacker, Manco-Johnson, & Primeaux, 2006). North Fulton Family Medicine has four sites located in Alpharetta, Cumming, Woodstock, and Johns Creek, Georgia. North Fulton Family Medicine locations are approximately 40-50 miles north of Atlanta, Georgia and the Hartsfield-Jackson Atlanta International Airport. North Fulton Family Medicine currently has 39,000 or 34% of its patient population enrolled to use the electronic personal health record. Participants from the Johns Creek location were invited to complete voluntarily a Likert-type patient satisfaction survey either on paper or in an electronic format. The Johns Creek location sees approximately 1674 patients per month. Paper surveys were available at the checkout desk for patients who were non-users or low degree users of the electronic personal health record. The link to the online survey was posted on the login screen of the electronic personal health record. Significance of the Study In a study of the U.S. ecology of medical care, the authors found that 80% of patients experienced medical concerns at home, yet only 30% sought care (Colorafi, Endsley, Kibbe, & Linares, 2006). Outdated information systems and current paper-based record keeping systems are barriers to improving the quality of care (Suri, 2002). For patients to receive coordinated evidence-based care, patients need access to health

11 information systems on a 24-hour-per day basis to allow them greater access to their healthcare information to make informed decisions. The use of electronic personal health records offers a number of benefits to patients, physicians, and the U.S. healthcare system: 1. Patients can verify and monitor the information in their medical record themselves. Patients can also schedule and receive reminders for health maintenance services. 2. Improved communication between provider and physician can occur through the documentation of interaction with patients and timely explanation of diagnostic test results. 3. Electronic personal health records can provide drug alerts and help identify missing procedures and services. 4. Electronic personal health records help to avoid duplicative testing and unnecessary services (Colorafi, Endsley, Kibbe, & Linares, 2006). Published data on the effects of electronic personal health records on patient outcomes are limited (Suri, 2002). The results of this proposed study may be used to support the identified benefits of electronic personal health records in the healthcare delivery process for patients. By using a locally established family practice such as at North Fulton Family Medicine to conduct the study, the results from the study can assist in supporting the additional adoption of electronic personal health records within the practice, within the state of Georgia, and nationally.

12 Significance of the Study to Leadership Healthcare leaders seek to harness information technology as the solution for cost containment and cost reduction in healthcare delivery (Killingsworth, Newkirk, & Seeman, 2006). Former President George W. Bush announced that the adoption of electronic health systems can reduce healthcare costs caused by inefficiency, medical errors, inappropriate care, and incomplete information by 20% per year (Sidorov, 2006). North Fulton Family Medicine implemented an electronic health record in 1998 and added the electronic personal health record component in 2003. The practice identified opportunities for financial return on investment through money spent on administrative functions such as transcription, supplies, medical record storage fees, and lost reimbursements due to miscoded procedures and charges. The practice also identified improvements in efficiencies by reduced wait times for laboratory results, decreased time searching for paper patient charts, and increased opportunities for communicating with patients through the electronic personal health record. Through the use of an electronic health record, the practice saved $934 per day and $253,978 per year in chart pulls, new patient chart generation, missing chart searches, transcription, lab result handling, referral letters, and medical chart supplies (North Fulton Family Medicine, 2005). Quality improvement through the use of electronic health records and the electronic personal health record have also been noted. Through the reporting functions of the electronic health record, physicians are able to identify at-risk patient populations, compare patients with similar conditions and treatment plans, and evaluate the practice with nationally published quality standards. Through the electronic personal health record, patients are able to view results, make appointments, request prescription refills,

13 and send/receive communication directly to and from their physician through email and participate actively in their care. One study conducted in two large medical practices identified that patient visits to physician offices decreased 9% after electronic health record implementation (Powner, 2005). This study is relevant to national leaders, physicians, administrators of hospitals, and healthcare organizations because it may provide a framework for supporting the national responsibility to have electronic health records with personal health record components implemented by 2014. By examining the improvement in healthcare quality and treatment outcomes caused by the use of electronic personal health records, the results of this study may be used to support the business case for the purchase and implementation of electronic health records with electronic personal health records components. According to a 2003 National Healthcare Survey, electronic health records were available in 17% of physicians’ offices, 31% of emergency rooms, and 29% of hospital outpatient departments (Sidorov, 2006). The implementation of electronic personal health records is dependent upon the implementation of electronic health records in care delivery settings. The results of this study may be used to expedite the adoption of the national health information technology infrastructure and electronic personal health records. Healthcare leaders must measure the impact of quality not just by quality efforts but also with reductions in healthcare costs (Potthoff, 2004). Healthcare spending increases dramatically for patients with chronic diseases such as cancer and diabetes. Older persons who suffer from chronic and disabling conditions are the heaviest users of healthcare resources (Fineman & Rice, 2004). Kerr (2004) found that care for diabetes

14 was better in the VA system than in any other commercially managed care program (Adams et al., 2004). The VA was an early leader in using electronic medical records with electronic personal health records components. Through the VA’s use of electronic clinical information, diabetes and related complications such as chronic kidney disease and potential amputations are identified, tracked, and managed. Electronic records have been critical in evaluating the safety and effectiveness of treatments by identifying gaps in medication refills and the lack of medication titration (Sachs, 2006). Integrated information systems, systematic performance monitoring, and coordination of care with the patient are essential requirements to improving quality (Adams, et al., 2004). The results of this study may be useful for other healthcare stakeholders such patients, insurance companies, and employers. Healthcare administrators, patients, insurance companies, and employers are all seeking ways to improve the quality of healthcare and to decrease costs. Major employers such as BP America Inc., Pitney Bowes Inc., Intel Corporation, Applied Materials, Inc., and Wal-Mart are investing funding into an electronic personal health record system to allow employees to manage their healthcare more easily and to improve data sharing among healthcare providers (Managing Benefits Plans, 2007). Nature of the Study A non-experimental, correlational descriptive quantitative survey research design was used to respond to the research questions. The design for this research study was quantitative. Quantitative research describes trends, explores relationships, and predicts results (Creswell, 2004). The hypothesis included in this study plan was used to predict the outcome of the research based on the relationship between the variables. The

Full document contains 238 pages
Abstract: The use of electronic personal health records is becoming increasingly more popular as healthcare providers, healthcare and government leaders, and patients are seeking ways to improve healthcare quality and to decrease costs (Abrahamsen, 2007). This quantitative, descriptive correlational study examined the relationship between the degree of use of electronic personal health records and patient health through the measurement of patient satisfaction among the patients at North Fulton Family Medicine. Analysis of the data indicated a statistically significant relationship between patient satisfaction and the degree of use of the electronic personal health record. The results of this study support the conclusion that the use of electronic personal health records improves patient satisfaction and overall patient health.