ArticleMedical care2013
Improving the reliability of physician "report cards".
Article in Medical care, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 16 citations in OpenAlex.
- Physician Characteristics Associated With Ordering 4 Low-Value Screening Tests in Primary Care.JAMA network open · 2018Article
- Should interventions to reduce variation in care quality target doctors or hospitals?Health policy (Amsterdam, Netherlands) · 2018Article
- Diabetes care improvement in pharmacist- versus nurse-supported patient-centered medical homes.The American journal of managed care · 2017Article
- Misclassification Risk of Tier-Based Physician Quality Performance Systems.Health services research · 2017Article
- Resident dashboards: helping your clinical competency committee visualize trainees' key performance indicators.Medical education online · 2016Article
- Variation in Patient-reported Outcomes Across Hospitals Following Surgery.Medical care · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 4 institutions in 2 countries.
Funding
Abstract
backgroundPerformance measures are widely used to profile primary care physicians (PCPs) but their reliability is often limited by small sample sizes. We evaluated the reliability of individual PCP profiles and whether they can be improved by combining measures into composites or by profiling practice groups.
methodsWe performed a cross-sectional analysis of electronic health record data for patients with diabetes (DM), congestive heart failure (CHF), ischemic vascular disease (IVD), or eligible for preventive care services seen by a PCP within a large, integrated health care system between April 2009 and May 2010. We evaluated performance on 14 measures of DM care, 9 of CHF, 7 of IVD, and 4 of preventive care.
resultsThere were 51,771 patients observed by 163 physicians in 17 clinics. Few PCPs (0%-60%) could be profiled with 80% reliability using single process or intermediate-outcome measures. Combining measures into single-disease composites improved reliability for DM and preventive care with 74.5% and 76.7% of PCPs having sufficient panel sizes, but composites remained unreliable for CHF and IVD. A total of 85.3% of PCPs could be reliably profiled using a single overall composite. Aggregating PCPs into practice groups (3 to 21 PCPs per group) did not improve reliability in most cases because of little between-group practice variation.
conclusionsSingle measures rarely differentiate between individual PCPs or groups of PCPs reliably. Combining measures into single-disease or multidisease composites can improve reliability for some common conditions, but not all. Assessing PCP practice groups within a single health care system, rather than individual PCPs, did not substantially improve reliability.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.