Dataset Information

Associations between hospitalist physician workload, length of stay, and return to the hospital.

ABSTRACT:

Background

Hospitalist physicians' workload-the total number of patients they care for daily-is rising in the U.S. Hospitalists report that increased workload negatively affects patients care.

Objective

Measure the associations between hospitalist physicians' workload and clinical outcomes.

Design, settings, and participants

Observational study, using electronic health record (EHR) data, of adults hospitalized on the hospitalist service at Yale-New Haven Hospital from 2015-2018.

Main outcome and measures

We defined hospitalists' workload as the number of patients they cared for on the first full hospital day of a given patient's encounter. We used multilevel Poisson and logistic regression to examine associations between workload and length of stay (LOS), return to the Emergency Department (ED), and readmission. We adjusted for sociodemographic factors, patient complexity and severity of illness, and weekend admission (for LOS) or discharge (for ED visits or readmission).

Results

We analyzed 38,141 hospitalizations. Median patient age was 64 years (IQR 51-78 years), 53% were female, and 34% were nonwhite. Mean workload was 15 patients (SD 3 patients; range 10-34 patients). LOS was prolonged by 0.05 days (95% CI 0.02, 0.08; p(0.001) when comparing the 75th workload percentile (16 patients) to the 25th workload percentile (13 patients). There were no associations between workload and ED visits or readmission within 7 and 30 days.

Conclusions

There was a statistically significant but modest relationship between workload and LOS; workload was not associated with ED visits or readmissions.Given clinical reports of the deleterious effects of increased hospitalist workload, there is a need for prospective research assessing a range of outcomes, beyond those measurable in contemporary EHR data.

SUBMITTER: Djulbegovic M

PROVIDER: S-EPMC9248905 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Publications

Associations between hospitalist physician workload, length of stay, and return to the hospital.

Djulbegovic Mia M Chen Kevin K Cohen Andrew B AB Heacock Daniel D Canavan Maureen M Cushing William W Agarwal Ritu R Simonov Michael M Chaudhry Sarwat I SI

Journal of hospital medicine 20220606 6

<h4>Background</h4>Hospitalist physicians' workload-the total number of patients they care for daily-is rising in the U.S. Hospitalists report that increased workload negatively affects patients care.<h4>Objective</h4>Measure the associations between hospitalist physicians' workload and clinical outcomes.<h4>Design, settings, and participants</h4>Observational study, using electronic health record (EHR) data, of adults hospitalized on the hospitalist service at Yale-New Haven Hospital from 2015- ...[more]

PMID: 35662410

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Project description:ImportanceThe ideal hospitalist workload and optimal way to measure it are not well understood.ObjectiveTo obtain expert consensus on the salient measures of hospitalist workload.Design, setting, and participantsThis qualitative study used a 3-round Delphi technique between April 5 and July 13, 2022, involving national experts within and external to the field. Experts included hospitalist clinicians, leaders, and administrators, as well as researchers with expertise in human factors engineering and cognitive load theory.Main outcomes and measuresThree rounds of surveys were conducted, during which participants provided input on the salient measures of hospitalist workload across various domains. In the first round, free-text data collected from the surveys were analyzed using a directed qualitative content approach. In the second and third rounds, participants rated each measure's relevance on a Likert scale, and consensus was evaluated using the IQR. Percentage agreement was also calculated.ResultsSeventeen individuals from 14 organizations, encompassing clinicians, leaders, administrators, and researchers, participated in 3 rounds of surveys. In round 1, participants provided 135 unique qualitative comments across 10 domains, with 192 unique measures identified. Of the 192 measures presented in the second round, 6 (3%) were considered highly relevant, and 25 (13%) were considered moderately relevant. In round 3, 161 measures not meeting consensus were evaluated, with 25 (16%) considered highly relevant and 95 (59%) considered moderately relevant. Examples of measures considered highly relevant included a patient complexity score and outcome measures such as savings from hospital days avoided and clinician turnover.Conclusions and relevanceIn this qualitative study measuring hospitalist workload, multiple measures, including those quantifying work demands and the association of those demands with outcomes, were considered relevant for measuring and understanding workloads. The findings suggest that relying on traditional measures, such as productivity-related measures and financial measures, may offer an incomplete understanding of workloads and their association with key outcomes. By embracing a broader range of measures, organizations may be able to better capture the complexity and nuances of hospitalist work demands and their outcomes on clinicians, patients, and organizations.

Project description:Backgroung and objectivesUnder the Affordable Care Act, the US Centers for Medicare & Medicaid Services created the Physician Value-Based Payment Modifier Program and its successor, the Merit-Based Incentive Payment System, to tie physician payments to quality and cost. The addition of hospital length of stay (LOS) to these value-based physician payment models reflects its increasing importance as a metric of health care cost and efficiency and its association with adverse health outcomes. This study compared the Centers for Medicare & Medicaid Services-endorsed LOS risk-adjustment methodology with a novel methodology that accounts for pre-hospitalization clinical, socioeconomic status (SES), and admission-related factors as influential factors of hospital LOS.MethodsUsing the 2014 New York, Florida, and New Jersey State Inpatient Database, we compared the observed-to-expected LOS of 2373102 adult admissions for 742 medical and surgical diagnosis-related groups (DRGs) by 3 models: ( a ) current risk-adjustment model (CRM), which adjusted for age, sex, number of chronic conditions, Elixhauser comorbidity score, and DRG severity weight, ( b ) CRM but modeling LOS using a generalized linear model (C-GLM), and (c) novel risk-adjustment model (NRM), which added to the C-GLM covariates for race/ethnicity, SES, discharge destination, weekend admission, and individual intercepts for DRGs instead of severity weights.ResultsThe NRM disadvantaged physicians for fewer medical and surgical DRGs, compared with both the C-GLM and CRM models (medical DRGs: 0.49% vs 13.17% and 10.89%, respectively; surgical DRGs: 0.30% vs 13.17% and 10.98%, respectively). In subgroup analysis, the NRM reduced the proportion of physician-penalizing DRGs across all racial/ethnic and socioeconomic groups, with the highest reduction among Whites, followed by low SES patients, and the lowest reduction among Hispanic patients.ConclusionsAfter accounting for pre-hospitalization socioeconomic and clinical factors, the adjusted LOS using the NRM was lower than estimates from the current Centers for Medicare & Medicaid Services-endorsed model. The current model may disadvantage physicians serving communities with higher socioeconomic risks.

Dataset Information

Associations between hospitalist physician workload, length of stay, and return to the hospital.

Background

Objective

Design, settings, and participants

Main outcome and measures

Results

Conclusions

Publications

Associations between hospitalist physician workload, length of stay, and return to the hospital.

Similar Datasets

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