Rethinking Electronic Health Records to Better Achieve Quality and Safety Goals

Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee 37203, USA.
Annual Review of Medicine (Impact Factor: 12.93). 02/2007; 58(1):35-47. DOI: 10.1146/
Source: PubMed


Health care information technology changes the ecosystem of a practice. Human roles, process work flow, and technology infrastructure are tightly interrelated. Medical errors may increase if a change in one is not accommodated by a change in the others. Introduction of information technology should be approached as an iterative process of care improvement rather than as a one-time insertion of an information system into established practice. Information technology supports a family of technological approaches, each with distinct mechanisms of action, benefits, and side effects. By matching technological approach to task and staging introduction into practice, initial benefit can be obtained more quickly, at reduced cost, while managing risk of a misfit. A staged approach to turning direct access by patients to their health information into more effective care is presented as an example of this strategy.

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    • "A centralized transactional messaging engine called the Generic Interface Engine (GIE) manages communication and information exchange between systems. This early adoption and integration of electronic clinical information systems have had significant impact in the domains of clinical care, patient safety, provider accountability, and improved documentation [16] [17] [18] [19]. The end result of our early launch and continuously evolving clinical systems is an information-rich environment covering 2 million patients, with longitudinal records spanning more than a decade. "
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    ABSTRACT: The last decade has seen an exponential growth in the quantity of clinical data collected nationwide, triggering an increase in opportunities to reuse the data for biomedical research. The Vanderbilt research data warehouse framework consists of identified and de-identified clinical data repositories, fee-for-service custom services, and tools built atop the data layer to assist researchers across the enterprise. Providing resources dedicated to research initiatives benefits not only the research community, but also clinicians, patients and institutional leadership. This work provides a summary of our approach in the secondary use of clinical data for research domain, including a description of key components and a list of lessons learned, designed to assist others assembling similar services and infrastructure.
    Journal of Biomedical Informatics 02/2014; 52. DOI:10.1016/j.jbi.2014.02.003 · 2.19 Impact Factor
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    • "Stead wrote recently that improvements from information technology implementation "are difficult to quantify in a practice while changing people's roles, process, and technology at the same time. Most measures have an immediate impact on process whereas many of the expected benefits are in long-term clinical outcomes [8]." We had no a priori knowledge of time needed from initial EPR implementation to development of a measurable outcome, particularly when dependent on many underlying diseases, comorbid factors, care, and other variables. "
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    ABSTRACT: In chronic disease, health information technology promises but has yet to demonstrate improved outcomes and decreased costs. The main aim of the study was to determine the effects on mortality and cost of an electronic patient record used in daily patient care in a model chronic disease, End Stage Renal Disease, treated by chronic maintenance hemodialysis. Dialysis treatment is highly regulated, and near uniform in treatment modalities and drugs used. The particular electronic patient record, patient-centered and extensively coded, was used first in patient care in 3 dialysis units in New York, NY in 1998, 1999, and 2000. All data were stored "live"; none were archived. By December 31, 2006, the patients had been treated by maintenance hemodialysis for a total of 3924 years. A retrospective analysis was made using query tools embedded in the software. The United States Renal Data System dialysis population served as controls. In all there were 1790 patients, with many underlying primary diseases and multiple comorbid conditions affecting many organ systems. Year by year mortality, hospital admissions, and staffing were analyzed, and the data were compared with national data compiled by the United States Renal Data System. Analyzed by calendar year after electronic patient record implementation, mortality decreased strikingly. In years 3-9 mortality was lower than in years 1-2 by 23%, 48%, and 34% in the 3 units, and was 37%, 37%, and 35% less than that reported by the United States Renal Data System. Clinical staffing was 25% fewer per 100 patients than the national average, thereby lowering costs. To our knowledge, this is the first demonstration that an electronic patient record, albeit of particular design, can have a favorable effect on outcomes and cost in chronic disease. That the population studied has many underlying diseases affecting all organ systems suggests that the electronic patient record design may enable application to many fields of medical practice.
    BMC Medical Informatics and Decision Making 02/2007; 7(1):38. DOI:10.1186/1472-6947-7-38 · 1.83 Impact Factor
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