ArticleJournal of the American College of Emergency Physicians open2022
Measuring without a ruler: Limited data to characterize the relationship between physician assistant/nurse practitioner staffing and emergency department performance.
Article in Journal of the American College of Emergency Physicians open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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Who cites it
1 citing paper in PubMed.
- Measuring without a ruler: Limited data to characterize the relationship between physician assistant/nurse practitioner staffing and emergency department performance.Journal of the American College of Emergency Physicians open · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivePhysician assistant (PA) and nurse practitioner (NP) staffing is increasingly common in emergency departments (EDs), with variable physician supervision. We examined the feasibility of using publicly reported metrics as a measure of ED performance by staffing model.
methodsWe classified a convenience sample of 915 EDs by staffing model using the National Emergency Department Inventory-USA 2016 and a follow-up survey. Staffing models included 24/7 attending coverage with PAs/NPs, 24/7 attending coverage without PAs/NPs, and PAs/NPs without 24/7 attending coverage. We linked EDs with Hospital Compare data to examine availability of metrics and compared metric performance by staffing model. We used regression modeling to examine the independent relationship between staffing model and ED performance after adjusting for ED characteristics.
resultsOf 915 EDs surveyed, 767 (83%) responded and 436 (48%) had complete staffing data and any Hospital Compare data. The 216 EDs without any Hospital Compare data more frequently had no 24/7 attending coverage, were smaller, and were more often rural. Of 5 clinical metrics, 3 had data from < 100 EDs (range: 2%-21%), and 2 had data from 0 EDs. Of the 5 clinical metrics, only median time-to-ECG had enough data for analysis and found no difference among staffing models. Among the 3 process metrics, only time to discharge was significantly faster in EDs with any PA/NP staffing.
conclusionMany EDs in our national sample lacked sufficient Hospital Compare data to evaluate performance, likely because of lower patient volumes for condition-specific metrics. Alternative strategies to measure quality of care delivery in these settings should be developed.
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