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Journal of the American Medical Informatics Association | 2006

Personal Health Records: Definitions, Benefits, and Strategies for Overcoming Barriers to Adoption

Paul C. Tang; Joan S. Ash; David W. Bates; J. Marc Overhage; Daniel Z. Sands

Recently there has been a remarkable upsurge in activity surrounding the adoption of personal health record (PHR) systems for patients and consumers. The biomedical literature does not yet adequately describe the potential capabilities and utility of PHR systems. In addition, the lack of a proven business case for widespread deployment hinders PHR adoption. In a 2005 working symposium, the American Medical Informatics Associations College of Medical Informatics discussed the issues surrounding personal health record systems and developed recommendations for PHR-promoting activities. Personal health record systems are more than just static repositories for patient data; they combine data, knowledge, and software tools, which help patients to become active participants in their own care. When PHRs are integrated with electronic health record systems, they provide greater benefits than would stand-alone systems for consumers. This paper summarizes the College Symposium discussions on PHR systems and provides definitions, system characteristics, technical architectures, benefits, barriers to adoption, and strategies for increasing adoption.


Journal of the American Medical Informatics Association | 2001

Reducing the Frequency of Errors in Medicine Using Information Technology

David W. Bates; Michael Cohen; Lucian L. Leape; J. Marc Overhage; M. Michael Shabot; Thomas Sheridan

BACKGROUND Increasing data suggest that error in medicine is frequent and results in substantial harm. The recent Institute of Medicine report (LT Kohn, JM Corrigan, MS Donaldson, eds: To Err Is Human: Building a Safer Health System. Washington, DC: National Academy Press, 1999) described the magnitude of the problem, and the public interest in this issue, which was already large, has grown. GOAL The goal of this white paper is to describe how the frequency and consequences of errors in medical care can be reduced (although in some instances they are potentiated) by the use of information technology in the provision of care, and to make general and specific recommendations regarding error reduction through the use of information technology. RESULTS General recommendations are to implement clinical decision support judiciously; to consider consequent actions when designing systems; to test existing systems to ensure they actually catch errors that injure patients; to promote adoption of standards for data and systems; to develop systems that communicate with each other; to use systems in new ways; to measure and prevent adverse consequences; to make existing quality structures meaningful; and to improve regulation and remove disincentives for vendors to provide clinical decision support. Specific recommendations are to implement provider order entry systems, especially computerized prescribing; to implement bar-coding for medications, blood, devices, and patients; and to utilize modern electronic systems to communicate key pieces of asynchronous data such as markedly abnormal laboratory values. CONCLUSIONS Appropriate increases in the use of information technology in health care- especially the introduction of clinical decision support and better linkages in and among systems, resulting in process simplification-could result in substantial improvement in patient safety.


International Journal of Medical Informatics | 1999

The Regenstrief Medical Record System: a quarter century experience

Clement J. McDonald; J. Marc Overhage; William M. Tierney; Paul R. Dexter; Douglas K. Martin; Jeffrey G. Suico; Atif Zafar; Gunther Schadow; Lonnie Blevins; Tull Glazener; Jim Meeks-Johnson; Larry Lemmon; Jill Warvel; Brian Porterfield; Jeff S. Warvel; Pat Cassidy; Don Lindbergh; Anne W. Belsito; Mark Tucker; Bruce Williams; Cheryl Wodniak

Entrusted with the records for more than 1.5 million patients, the Regenstrief Medical Record System (RMRS) has evolved into a fast and comprehensive data repository used extensively at three hospitals on the Indiana University Medical Center campus and more than 30 Indianapolis clinics. The RMRS routinely captures laboratory results, narrative reports, orders, medications, radiology reports, registration information, nursing assessments, vital signs, EKGs and other clinical data. In this paper, we describe the RMRS data model, file structures and architecture, as well as recent necessary changes to these as we coordinate a collaborative effort among all major Indianapolis hospital systems, improving patient care by capturing city-wide laboratory and encounter data. We believe that our success represents persistent efforts to build interfaces directly to multiple independent instruments and other data collection systems, using medical standards such as HL7, LOINC, and DICOM. Inpatient and outpatient order entry systems, instruments for visit notes and on-line questionnaires that replace hardcopy forms, and intelligent use of coded data entry supplement the RMRS. Physicians happily enter orders, problems, allergies, visit notes, and discharge summaries into our locally developed Gopher order entry system, as we provide them with convenient output forms, choice lists, defaults, templates, reminders, drug interaction information, charge information, and on-line articles and textbooks. To prepare for the future, we have begun wrapping our system in Web browser technology, testing voice dictation and understanding, and employing wireless technology.


Journal of the American Medical Informatics Association | 1997

A Randomized Trial of “Corollary Orders” to Prevent Errors of Omission

J. Marc Overhage; William M. Tierney; Xiao Hua Zhou; Clement J. McDonald

OBJECTIVE Errors of omission are a common cause of systems failures. Physicians often fail to order tests or treatments needed to monitor/ameliorate the effects of other tests or treatments. The authors hypothesized that automated, guideline-based reminders to physicians, provided as they wrote orders, could reduce these omissions. DESIGN The study was performed on the inpatient general medicine ward of a public teaching hospital. Faculty and housestaff from the Indiana University School of Medicine, who used computer workstations to write orders, were randomized to intervention and control groups. As intervention physicians wrote orders for 1 of 87 selected tests or treatments, the computer suggested corollary orders needed to detect or ameliorate adverse reactions to the trigger orders. The physicians could accept or reject these suggestions. RESULTS During the 6-month trial, reminders about corollary orders were presented to 48 intervention physicians and withheld from 41 control physicians. Intervention physicians ordered the suggested corollary orders in 46.3% of instances when they received a reminder, compared with 21.9% compliance by control physicians (p < 0.0001). Physicians discriminated in their acceptance of suggested orders, readily accepting some while rejecting others. There were one third fewer interventions initiated by pharmacists with physicians in the intervention than control groups. CONCLUSION This study demonstrates that physician workstations, linked to a comprehensive electronic medical record, can be an efficient means for decreasing errors of omissions and improving adherence to practice guidelines.


Journal of the American Medical Informatics Association | 2003

Implementing Syndromic Surveillance: A Practical Guide Informed by the Early Experience

Kenneth D. Mandl; J. Marc Overhage; Michael M. Wagner; William B. Lober; Paola Sebastiani; Farzad Mostashari; Julie A. Pavlin; Per H. Gesteland; Tracee A. Treadwell; Eileen Koski; Lori Hutwagner; David L. Buckeridge; Raymond D. Aller; Shaun J. Grannis

Syndromic surveillance refers to methods relying on detection of individual and population health indicators that are discernible before confirmed diagnoses are made. In particular, prior to the laboratory confirmation of an infectious disease, ill persons may exhibit behavioral patterns, symptoms, signs, or laboratory findings that can be tracked through a variety of data sources. Syndromic surveillance systems are being developed locally, regionally, and nationally. The efforts have been largely directed at facilitating the early detection of a covert bioterrorist attack, but the technology may also be useful for general public health, clinical medicine, quality improvement, patient safety, and research. This report, authored by developers and methodologists involved in the design and deployment of the first wave of syndromic surveillance systems, is intended to serve as a guide for informaticians, public health managers, and practitioners who are currently planning deployment of such systems in their regions.


Annals of Internal Medicine | 2010

Advancing the Science for Active Surveillance: Rationale and Design for the Observational Medical Outcomes Partnership

Paul E. Stang; Patrick B. Ryan; Judith A. Racoosin; J. Marc Overhage; Abraham G. Hartzema; Christian G. Reich; Emily Welebob; Thomas Scarnecchia; Janet Woodcock

The U.S. Food and Drug Administration (FDA) Amendments Act of 2007 mandated that the FDA develop a system for using automated health care data to identify risks of marketed drugs and other medical products. The Observational Medical Outcomes Partnership is a public-private partnership among the FDA, academia, data owners, and the pharmaceutical industry that is responding to the need to advance the science of active medical product safety surveillance by using existing observational databases. The Observational Medical Outcomes Partnerships transparent, open innovation approach is designed to systematically and empirically study critical governance, data resource, and methodological issues and their interrelationships in establishing a viable national program of active drug safety surveillance by using observational data. This article describes the governance structure, data-access model, methods-testing approach, and technology development of this effort, as well as the work that has been initiated.


Journal of General Internal Medicine | 2003

Effects of computerized guidelines for managing heart disease in primary care.

William M. Tierney; J. Marc Overhage; Michael D. Murray; Lisa E. Harris; Xiao Hua Zhou; George J. Eckert; Faye Smith; Nancy A. Nienaber; Clement J. McDonald; Fredric D. Wolinsky

BACKGROUND: Electronic information systems have been proposed as one means to reduce medical errors of commission (doing the wrong thing) and omission (not providing indicated care).OBJECTIVE: To assess the effects of computer-based cardiac care suggestions.DESIGN: A randomized, controlled trial targeting primary care physicians and pharmacists.SUBJECTS: A total of 706 outpatients with heart failure and/or ischemic heart disease.INTERVENTIONS: Evidence-based cardiac care suggestions, approved by a panel of local cardiologists and general internists, were displayed to physicians and pharmacists as they cared for enrolled patients.MEASUREMENTS: Adherence with the care suggestions, generic and condition-specific quality of life, acute exacerbations of their cardiac disease, medication compliance, health care costs, satisfaction with care, and physicians’ attitudes toward guidelines.RESULTS: Subjects were followed for 1 year during which they made 3,419 primary care visits and were eligible for 2,609 separate cardiac care suggestions. The intervention had no effect on physicians’ adherence to the care suggestions (23% for intervention patients vs 22% for controls). There were no intervention-control differences in quality of life, medication compliance, health care utilization, costs, or satisfaction with care. Physicians viewed guidelines as providing helpful information but constraining their practice and not helpful in making decisions for individual patients.CONCLUSIONS: Care suggestions generated by a sophisticated electronic medical record system failed to improve adherence to accepted practice guidelines or outcomes for patients with heart disease. Future studies must weigh the benefits and costs of different (and perhaps more Draconian) methods of affecting clinician behavior.


American Journal of Public Health | 2008

A Comparison of the Completeness and Timeliness of Automated Electronic Laboratory Reporting and Spontaneous Reporting of Notifiable Conditions

J. Marc Overhage; Shaun J. Grannis; Clement J. McDonald

OBJECTIVES We examined whether automated electronic laboratory reporting of notifiable-diseases results in information being delivered to public health departments more completely and quickly than is the case with spontaneous, paper-based reporting. METHODS We used data from a local public health department, hospital infection control departments, and a community-wide health information exchange to identify all potential cases of notifiable conditions that occurred in Marion County, Ind, during the first quarter of 2001. We compared traditional spontaneous reporting to the health department with automated electronic laboratory reporting through the health information exchange. RESULTS After reports obtained using the 2 methods had been matched, there were 4785 unique reports for 53 different conditions during the study period. Chlamydia was the most common condition, followed by hepatitis B, hepatitis C, and gonorrhea. Automated electronic laboratory reporting identified 4.4 times as many cases as traditional spontaneous, paper-based methods and identified those cases 7.9 days earlier than spontaneous reporting. CONCLUSIONS Automated electronic laboratory reporting improves the completeness and timeliness of disease surveillance, which will enhance public health awareness and reporting efficiency.


Statistics in Medicine | 2012

Empirical assessment of methods for risk identification in healthcare data: results from the experiments of the Observational Medical Outcomes Partnership.

Patrick B. Ryan; David Madigan; Paul E. Stang; J. Marc Overhage; Judith A. Racoosin; Abraham G. Hartzema

BACKGROUND Expanded availability of observational healthcare data (both administrative claims and electronic health records) has prompted the development of statistical methods for identifying adverse events associated with medical products, but the operating characteristics of these methods when applied to the real-world data are unknown. METHODS We studied the performance of eight analytic methods for estimating of the strength of association-relative risk (RR) and associated standard error of 53 drug-adverse event outcome pairs, both positive and negative controls. The methods were applied to a network of ten observational healthcare databases, comprising over 130 million lives. Performance measures included sensitivity, specificity, and positive predictive value of methods at RR thresholds achieving statistical significance of p < 0.05 or p < 0.001 and with absolute threshold RR > 1.5, as well as threshold-free measures such as area under receiver operating characteristic curve (AUC). RESULTS Although no specific method demonstrated superior performance, the aggregate results provide a benchmark and baseline expectation for risk identification method performance. At traditional levels of statistical significance (RR > 1, p < 0.05), all methods have a false positive rate >18%, with positive predictive value <38%. The best predictive model, high-dimensional propensity score, achieved an AUC  =  0.77. At 50% sensitivity, false positive rate ranged from 16% to 30%. At 10% false positive rate, sensitivity of the methods ranged from 9% to 33%. CONCLUSIONS Systematic processes for risk identification can provide useful information to supplement an overall safety assessment, but assessment of methods performance suggests a substantial chance of identifying false positive associations.


Journal of the American Medical Informatics Association | 2005

Communities' Readiness for Health Information Exchange: The National Landscape in 2004

J. Marc Overhage; Lori Evans; Janet Marchibroda

BACKGROUND The Secretary of Health and Human Services recently released a report calling for the nation to create a national health information network (NHIN) that would interconnect Regional Health Information Organizations (RHIOs). These RHIOs, which others have called Local or Regional Health Information Infrastructures (LHII), would in turn interconnect local as well as national health information resources. Little data exist about the activities taking place in communities to create LHIIs. APPROACH The authors analyzed data that communities submitted in response to a request for capabilities issued by the Foundation for eHealth as part of their Connecting Communities for Better Health program using descriptive statistics and subjective evaluation. IMPRESSION The authors analyzed data from 134 responses from communities in 42 states and the District of Columbia. Communities are enthusiastic about moving forward with health information exchange to create LHIIs to improve the efficiency, quality, and safety of care. They have identified significant local sources of investment and plan to use some clinical data standards but not as broadly as was expected. The communities have not yet developed the specific technical approaches or the sustainable business models that will be required. Many communities are interested in creating an LHII and are developing the leadership commitment needed to translate that interest into an operational reality. Clinical information standards can be incorporated into a communitys plans as often as they need to be. Communities have to overcome funding issues, develop deeper understanding of the technical and organizational issues, and aggressively share their learning to succeed within their community and to help other communities succeed.

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Clement J. McDonald

National Institutes of Health

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William M. Tierney

University of Oklahoma Health Sciences Center

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Kenneth D. Mandl

Boston Children's Hospital

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