The effect of electronic medical record adoption on outcomes in US hospitals

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Abstract

Background

The electronic medical record (EMR) is one of the most promising components of health information technology. However, the overall impact of EMR adoption on outcomes at US hospitals remains unknown. This study examined the relationship between basic EMR adoption and 30-day rehospitalization, 30-day mortality, inpatient mortality and length of stay.

Methods

Our overall approach was to compare outcomes for the two years before and two years after the year of EMR adoption, at 708 acute-care hospitals in the US from 2000 to 2007. We looked at the effect of EMR on outcomes using two methods. First, we compared the outcomes by quarter for the period before and after EMR adoption among hospitals that adopted EMR. Second, we compared hospitals that adopted EMR to those that did not, before and after EMR adoption, using a generalized linear model.

Results

Hospitals adopting EMR experienced 0.11 (95% CI: -0.218 to −0.002) days’ shorter length of stay and 0.182 percent lower 30-day mortality, but a 0.19 (95% CI: 0.0006 to 0.0033) percent increase in 30-day rehospitalization in the two years after EMR adoption. The association of EMR adoption with outcomes also varied by type of admission (medical vs. surgical).

Conclusions

Previous studies using observational data from large samples of hospitals have produced conflicting results. However, using different methods, we found a small but statistically significant association of EMR adoption with outcomes of hospitalization.

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Most cited references 19

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Comorbidity measures for use with administrative data.

A Elixhauser, C. Steiner, D Harris … (1998)

This study attempts to develop a comprehensive set of comorbidity measures for use with large administrative inpatient datasets. The study involved clinical and empirical review of comorbidity measures, development of a framework that attempts to segregate comorbidities from other aspects of the patient's condition, development of a comorbidity algorithm, and testing on heterogeneous and homogeneous patient groups. Data were drawn from all adult, nonmaternal inpatients from 438 acute care hospitals in California in 1992 (n = 1,779,167). Outcome measures were those commonly available in administrative data: length of stay, hospital charges, and in-hospital death. A comprehensive set of 30 comorbidity measures was developed. The comorbidities were associated with substantial increases in length of stay, hospital charges, and mortality both for heterogeneous and homogeneous disease groups. Several comorbidities are described that are important predictors of outcomes, yet commonly are not measured. These include mental disorders, drug and alcohol abuse, obesity, coagulopathy, weight loss, and fluid and electrolyte disorders. The comorbidities had independent effects on outcomes and probably should not be simplified as an index because they affect outcomes differently among different patient groups. The present method addresses some of the limitations of previous measures. It is based on a comprehensive approach to identifying comorbidities and separates them from the primary reason for hospitalization, resulting in an expanded set of comorbidities that easily is applied without further refinement to administrative data for a wide range of diseases.

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Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review.

Amit X Garg, Neill K. J. Adhikari, Heather McDonald … (2005)

Developers of health care software have attributed improvements in patient care to these applications. As with any health care intervention, such claims require confirmation in clinical trials. To review controlled trials assessing the effects of computerized clinical decision support systems (CDSSs) and to identify study characteristics predicting benefit. We updated our earlier reviews by searching the MEDLINE, EMBASE, Cochrane Library, Inspec, and ISI databases and consulting reference lists through September 2004. Authors of 64 primary studies confirmed data or provided additional information. We included randomized and nonrandomized controlled trials that evaluated the effect of a CDSS compared with care provided without a CDSS on practitioner performance or patient outcomes. Teams of 2 reviewers independently abstracted data on methods, setting, CDSS and patient characteristics, and outcomes. One hundred studies met our inclusion criteria. The number and methodologic quality of studies improved over time. The CDSS improved practitioner performance in 62 (64%) of the 97 studies assessing this outcome, including 4 (40%) of 10 diagnostic systems, 16 (76%) of 21 reminder systems, 23 (62%) of 37 disease management systems, and 19 (66%) of 29 drug-dosing or prescribing systems. Fifty-two trials assessed 1 or more patient outcomes, of which 7 trials (13%) reported improvements. Improved practitioner performance was associated with CDSSs that automatically prompted users compared with requiring users to activate the system (success in 73% of trials vs 47%; P = .02) and studies in which the authors also developed the CDSS software compared with studies in which the authors were not the developers (74% success vs 28%; respectively, P = .001). Many CDSSs improve practitioner performance. To date, the effects on patient outcomes remain understudied and, when studied, inconsistent.

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Systematic review: impact of health information technology on quality, efficiency, and costs of medical care.

Basit Chaudhry, Jerome K Wang, Shinyi Wu … (2006)

Experts consider health information technology key to improving efficiency and quality of health care. To systematically review evidence on the effect of health information technology on quality, efficiency, and costs of health care. The authors systematically searched the English-language literature indexed in MEDLINE (1995 to January 2004), the Cochrane Central Register of Controlled Trials, the Cochrane Database of Abstracts of Reviews of Effects, and the Periodical Abstracts Database. We also added studies identified by experts up to April 2005. Descriptive and comparative studies and systematic reviews of health information technology. Two reviewers independently extracted information on system capabilities, design, effects on quality, system acquisition, implementation context, and costs. 257 studies met the inclusion criteria. Most studies addressed decision support systems or electronic health records. Approximately 25% of the studies were from 4 academic institutions that implemented internally developed systems; only 9 studies evaluated multifunctional, commercially developed systems. Three major benefits on quality were demonstrated: increased adherence to guideline-based care, enhanced surveillance and monitoring, and decreased medication errors. The primary domain of improvement was preventive health. The major efficiency benefit shown was decreased utilization of care. Data on another efficiency measure, time utilization, were mixed. Empirical cost data were limited. Available quantitative research was limited and was done by a small number of institutions. Systems were heterogeneous and sometimes incompletely described. Available financial and contextual data were limited. Four benchmark institutions have demonstrated the efficacy of health information technologies in improving quality and efficiency. Whether and how other institutions can achieve similar benefits, and at what costs, are unclear.

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Author and article information

Journal

Journal ID (nlm-ta): BMC Health Serv Res

Journal ID (iso-abbrev): BMC Health Serv Res

Title: BMC Health Services Research

Publisher: BioMed Central

ISSN (Electronic): 1472-6963

Publication date Collection: 2013

Publication date (Electronic): 1 February 2013

Volume: 13

Page: 39

Affiliations

[1 ]Department of Internal Medicine, University of Texas Medical Branch, Galveston, TX, 77555, USA

Article

Publisher ID: 1472-6963-13-39

DOI: 10.1186/1472-6963-13-39

PMC ID: 3568047

PubMed ID: 23375071

SO-VID: 3d194a20-9bf3-4425-bae0-d4a9aa963e4f

License:

This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

The effect of electronic medical record adoption on outcomes in US hospitals

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Abstract

Background

Methods

Results

Conclusions

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Most cited references 19

Comorbidity measures for use with administrative data.

Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review.

Systematic review: impact of health information technology on quality, efficiency, and costs of medical care.

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