Dataset Information

Measures of electronic health record use in outpatient settings across vendors.

ABSTRACT: Electronic health record (EHR) log data capture clinical workflows and are a rich source of information to understand variation in practice patterns. Variation in how EHRs are used to document and support care delivery is associated with clinical and operational outcomes, including measures of provider well-being and burnout. Standardized measures that describe EHR use would facilitate generalizability and cross-institution, cross-vendor research. Here, we describe the current state of outpatient EHR use measures offered by various EHR vendors, guided by our prior conceptual work that proposed seven core measures to describe EHR use. We evaluate these measures and other reporting options provided by vendors for maturity and similarity to previously proposed standardized measures. Working toward improved standardization of EHR use measures can enable and accelerate high-impact research on physician burnout and job satisfaction as well as organizational efficiency and patient health.

SUBMITTER: Baxter SL

PROVIDER: S-EPMC8068413 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

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Measures of electronic health record use in outpatient settings across vendors.

Baxter Sally L SL Apathy Nate C NC Cross Dori A DA Sinsky Christine C Hribar Michelle R MR

Journal of the American Medical Informatics Association : JAMIA 20210401 5

Electronic health record (EHR) log data capture clinical workflows and are a rich source of information to understand variation in practice patterns. Variation in how EHRs are used to document and support care delivery is associated with clinical and operational outcomes, including measures of provider well-being and burnout. Standardized measures that describe EHR use would facilitate generalizability and cross-institution, cross-vendor research. Here, we describe the current state of outpatien ...[more]

PMID: 33211862

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Project description:BackgroundThe Meaningful Use (MU) program has increased the national emphasis on electronic measurement of hospital quality.ObjectiveTo evaluate stroke MU and one VHA stroke electronic clinical quality measure (eCQM) in national VHA data and determine sources of error in using centralized electronic health record (EHR) data.DesignOur study is a retrospective cross-sectional study of stroke quality measure eCQMs vs. chart review in a national EHR. We developed local SQL algorithms to generate the eCQMs, then modified them to run on VHA Central Data Warehouse (CDW) data. eCQM results were generated from CDW data in 2130 ischemic stroke admissions in 11 VHA hospitals. Local and CDW results were compared to chart review.Main measuresWe calculated the raw proportion of matching cases, sensitivity/specificity, and positive/negative predictive values (PPV/NPV) for the numerators and denominators of each eCQM. To assess overall agreement for each eCQM, we calculated a weighted kappa and prevalence-adjusted bias-adjusted kappa statistic for a three-level outcome: ineligible, eligible-passed, or eligible-failed.Key resultsIn five eCQMs, the proportion of matched cases between CDW and chart ranged from 95.4 %-99.7 % (denominators) and 87.7 %-97.9 % (numerators). PPVs tended to be higher (range 96.8 %-100 % in CDW) with NPVs less stable and lower. Prevalence-adjusted bias-adjusted kappas for overall agreement ranged from 0.73-0.95. Common errors included difficulty in identifying: (1) mechanical VTE prophylaxis devices, (2) hospice and other specific discharge disposition, and (3) contraindications to receiving care processes.ConclusionsStroke MU indicators can be relatively accurately generated from existing EHR systems (nearly 90 % match to chart review), but accuracy decreases slightly in central compared to local data sources. To improve stroke MU measure accuracy, EHRs should include standardized data elements for devices, discharge disposition (including hospice and comfort care status), and recording contraindications.

Dataset Information

Measures of electronic health record use in outpatient settings across vendors.

Publications

Measures of electronic health record use in outpatient settings across vendors.

Similar Datasets

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