ArticleCritical care explorations2024
Using Electronic Health Records to Identify the Daily Primary Provider During Hospitalization.
Article in Critical care explorations, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- A Descriptive Overview of Deviations From an Institutional Peripheral Vasopressor Protocol and Its Effects on Safety Across an Academic Health System.Critical care explorations · 2026Observational
- Algorithmic Identification of the Daily Primary Frontline Clinician during Inpatient Medicine Encounters Using EHR Audit Log Data.Applied clinical informatics · 2026Article
- Overview of Peripheral Vasopressor Use in an Academic Health System.Annals of the American Thoracic Society · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
objectivesProviders vary in their impact on clinical outcomes, but this is rarely accounted for in healthcare research. By failing to identify the provider responsible for a patient's care, investigators miss an opportunity to account for nonrandom variation in outcomes. Prior methods of identifying responsible providers have relied on manual chart review, which is time-consuming and expensive, or analysis of claims data, which has been demonstrated to be inaccurate. To address these gaps, we sought to develop an algorithm using electronic health record (EHR) data to identify the responsible provider for each day of a patient's hospitalization.
designA multicenter retrospective cohort study.
settingMidwest healthcare system. PATIENTS: Hospitalized patients and their providers.
interventionsNone. MEASUREMENTS AND MAIN
resultsWe first confirmed high inter-rater reliability of manual chart review to identify the responsible provider. Using manual chart review as the gold standard, we then assessed the accuracy of an automated algorithm in a set of randomly selected patients. The agreement between two independent physicians in their determination of the responsible provider by chart review was 100%. Among 200 randomly selected patients, the algorithm identified the same responsible provider as the physician chart reviewer on 93% (3372/3626; 95% CI, 92-94%) of patient-days.
conclusionsReadily available EHR data can be used to assign patients to providers daily with a high degree of accuracy. This methodology could be applied in healthcare research to identify sources of variation other than the intervention being studied.
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Registered trials
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