Javascript must be enabled to continue!
Salient Measures of Hospitalist Workload
View through CrossRef
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.
American Medical Association (AMA)
Title: Salient Measures of Hospitalist Workload
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.
Related Results
Effects of a hospitalist care model on mortality of elderly patients with hip fractures
Effects of a hospitalist care model on mortality of elderly patients with hip fractures
AbstractBACKGROUNDWe previously demonstrated that a hospitalist service created to medically manage patients with hip fracture reduced time to surgery and length of hospital stay, ...
Storage Workload Identification
Storage Workload Identification
Storage workload identification is the task of characterizing a workload in a storage system (more specifically, network storage system—NAS or SAN) and matching it with the previou...
COMPREHENSIVE METHOD OF ENERGY-EFFICIENT WORKLOAD PROCESSING IN THE INFORMATION AND COMMUNICATION NETWORK
COMPREHENSIVE METHOD OF ENERGY-EFFICIENT WORKLOAD PROCESSING IN THE INFORMATION AND COMMUNICATION NETWORK
Background. Peculiarities of the workload in a modern information and communication network (ICN) determine specific requirements for energy efficiency, performance and availabilit...
Workload of diagnostic radiologists in the foreseeable future based on recent scientific advances: growth expectations and role of artificial intelligence
Workload of diagnostic radiologists in the foreseeable future based on recent scientific advances: growth expectations and role of artificial intelligence
Abstract
Objective
To determine the anticipated contribution of recently published medical imaging literature, including artificial intelligence (AI...
Depth-aware salient object segmentation
Depth-aware salient object segmentation
Object segmentation is an important task which is widely employed in many computer vision applications such as object detection, tracking, recognition, and ret...
Staffing and Workload in Primary Care Facilities of Selected Geographically Isolated and Disadvantaged Communities in the Philippines
Staffing and Workload in Primary Care Facilities of Selected Geographically Isolated and Disadvantaged Communities in the Philippines
Background and Objective. Staffing shortages and health inequities are persistent barriers in the Philippines toward achieving universal health care. To ensure an adequate and resp...
A Hospitalist-Led Fracture Liaison Service Improves Care of Hip Fracture Patients
A Hospitalist-Led Fracture Liaison Service Improves Care of Hip Fracture Patients
Abstract
Background: Osteoporosis care traditionally falls to outpatient primary care providers despite the fact that over 300,000 elderly patients are hospitalized ...
THE WORKLOAD ANALYSIS OF EMPLOYEE BY USING NATIONAL AERONAUTICS AND SPACE ADMINISTRATION-TASK LOAD INDEX METHOD (NASA-TLX)
THE WORKLOAD ANALYSIS OF EMPLOYEE BY USING NATIONAL AERONAUTICS AND SPACE ADMINISTRATION-TASK LOAD INDEX METHOD (NASA-TLX)
Development of manufacturing and service institutions can not be separated from the role of human resources. Human resources have an important role in fulfilling vision and mission...

