Black Clouds vs Random Variation in Hospital Admissions

Luei Wern Ong; Jeffrey D Dawson; John W Ely

doi:10.22454/FamMed.2018.555558

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Black Clouds vs Random Variation in Hospital Admissions

Journal article

Open access

Peer reviewed

Black Clouds vs Random Variation in Hospital Admissions

Luei Wern Ong, Jeffrey D Dawson and John W Ely

Family medicine, Vol.50(6), pp.444-449

06/2018

DOI: 10.22454/FamMed.2018.555558

PMID: 29933444

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https://doi.org/10.22454/FamMed.2018.555558View

Published (Version of record) Open Access

Abstract

Physicians often accuse their peers of being "black clouds" if they repeatedly have more than the average number of hospital admissions while on call. Our purpose was to determine whether the black-cloud phenomenon is real or explainable by random variation. We analyzed hospital admissions to the University of Iowa family medicine service from July 1, 2010 to June 30, 2015. Analyses were stratified by peer group (eg, night shift attending physicians, day shift senior residents). We analyzed admission numbers to find evidence of black-cloud physicians (those with significantly more admissions than their peers) and white-cloud physicians (those with significantly fewer admissions). The statistical significance of whether there were actual differences across physicians was tested with mixed-effects negative binomial regression. The 5-year study included 96 physicians and 6,194 admissions. The number of daytime admissions ranged from 0 to 10 (mean 2.17, SD 1.63). Night admissions ranged from 0 to 11 (mean 1.23, SD 1.22). Admissions increased from 1,016 in the first year to 1,523 in the fifth year. We found 18 white-cloud and 16 black-cloud physicians in simple regression models that did not control for this upward trend. After including study year and other potential confounding variables in the regression models, there were no significant associations between physicians and admission numbers and therefore no true black or white clouds. In this study, apparent black-cloud and white-cloud physicians could be explained by random variation in hospital admissions. However, this randomness incorporated a wide range in workload among physicians, with potential impact on resident education at the low end and patient safety at the high end.

Data Collection

Hospitalization

Humans

Internship and Residency

Medical Staff, Hospital - statistics & numerical data

Models, Statistical

Patient Admission - statistics & numerical data

Physicians

Retrospective Studies

Workload - statistics & numerical data

Details

Title: Subtitle: Black Clouds vs Random Variation in Hospital Admissions
Creators: Luei Wern Ong - Carver College of Medicine, Department of Family Medicine, University of Iowa, Iowa City, IA
Jeffrey D Dawson - College of Public Health, University of Iowa, Iowa City, IA
John W Ely - Carver College of Medicine, Department of Family Medicine, Iowa City, IA
Resource Type: Journal article
Publication Details: Family medicine, Vol.50(6), pp.444-449
DOI: 10.22454/FamMed.2018.555558
PMID: 29933444
NLM abbreviation: Fam Med
ISSN: 0742-3225
eISSN: 1938-3800
Publisher: Society of Teachers of Family Medicine
Language: English
Date published: 06/2018
Academic Unit: Public Health Administration; Biostatistics; Family and Community Medicine
Record Identifier: 9984214956102771

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