The Relationship between Electronic Health Record Use and Quality of Care over Time
Open accessAbstract
OBJECTIVE Electronic health records (EHRs) have the potential to advance the quality of care, but studies have shown mixed results. The authors sought to examine the extent of EHR usage and how the quality of care delivered in ambulatory care practices varied according to duration of EHR availability. METHODS The study linked two data sources: a statewide survey of physicians' adoption and use of EHR and claims data reflecting quality of care as indicated by physicians' performance on widely used quality measures. Using four years of measurement, we combined 18 quality measures into 6 clinical condition categories. While the survey of physicians was cross-sectional, respondents indicated the year in which they adopted EHR. In an analysis accounting for duration of EHR use, we examined the relationship between EHR adoption and quality of care. RESULTS The percent of physicians reporting adoption of EHR and availability of EHR core functions more than doubled between 2000 and 2005. Among EHR users in 2005, the average duration of EHR use was 4.8 years. For all 6 clinical conditions, there was no difference in performance between EHR users and non-users. In addition, for these 6 clinical conditions, there was no consistent pattern between length of time using an EHR and physicians performance on quality measures in both bivariate and multivariate analyses. CONCLUSIONS In this cross-sectional study, we found no association between duration of using an EHR and performance with respect to quality of care, although power was limited. Intensifying the use of key EHR features, such as clinical decision support, may be needed to realize quality improvement from EHRs. Future studies should examine the relationship between the extent to which physicians use key EHR functions and their performance on quality measures over time.
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Simply having an electronic health record appears to have little impact on quality by itself.
“Simply having an electronic health record appears to have little impact on quality by itself.3 4”
From Overrides of medication-related clinical decision support alerts in outpatients (2014) · cites this paper as [4]
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- Authors
- Zhou, L., Soran, C. S., Jenter, C. A., Volk, L. A., Orav, E. J., Bates, D. W., & Simon, S. R.
- Affiliations
- Brigham and Women's Hospital (US)
- Harvard University (US)
- Venue
- Journal of the American Medical Informatics Association
- Publisher
- Oxford University Press (OUP)
- Published
- 2009-07-01
- Volume
- 16
- Issue
- 4
- Pages
- 457-464
- ISSN
- 1067-5027 (ISSN-L)
- 1527-974X
- PMC
- PMC2705247
- OpenAlex
- W2096325224
- Cited by
- 194
- References
- 41
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 5 · 2023: 2 · 2022: 12 · 2021: 8 · 2020: 5 · 2019: 8 · 2018: 8 · 2017: 12 · 2016: 13 · 2015: 19 · 2014: 16 · 2013: 22 · 2012: 18
- FWCI
- 41.51
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of the American Medical Informatics Association (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Agency for Healthcare Research and Quality (1uc1hs015397-01, UC1 HS015397)
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
- Health Sciences › Health Professions › General Health Professions › Primary Care and Health Outcomes
- Keywords
- electronic health records, EHR adoption, quality of care, outpatient care, physician performance, quality metrics, clinical decision support, health information technology
- MeSH terms
- Adult, Ambulatory Care, Clinical Competence, Cross-Sectional Studies, Diffusion of Innovation, Female, Humans, Male, Massachusetts, Middle Aged, Practice Patterns, Physicians', Quality of Health Care, Surveys and Questionnaires, Medical Records Systems, Computerized, Health Care Surveys
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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