Journal article
Objective measures of workload in healthcare: a narrative review
International journal of health care quality assurance, v 33(1), pp 1-17
20 Dec 2019
PMID: 31940153
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Purpose Workload is a critical concept in the evaluation of performance and quality in healthcare systems, but its definition relies on the perspective (e.g. individual clinician-level vs unit-level workload) and type of available metrics (e.g. objective vs subjective measures). The purpose of this paper is to provide an overview of objective measures of workload associated with direct care delivery in tertiary healthcare settings, with a focus on measures that can be obtained from electronic records to inform operationalization of workload measurement. Design/methodology/approach Relevant papers published between January 2008 and July 2018 were identified through a search in Pubmed and Compendex databases using the Sample, Phenomenon of Interest, Design, Evaluation, Research Type framework. Identified measures were classified into four levels of workload: task, patient, clinician and unit. Findings Of 30 papers reviewed, 9 used task-level metrics, 14 used patient-level metrics, 7 used clinician-level metrics and 20 used unit-level metrics. Key objective measures of workload include: patient turnover (n=9), volume of patients (n=6), acuity (n=6), nurse-to-patient ratios (n=5) and direct care time (n=5). Several methods for operationalization of these metrics into measurement tools were identified. Originality/value This review highlights the key objective workload measures available in electronic records that can be utilized to develop an operational approach for quantifying workload. Insights gained from this review can inform the design of processes to track workload and mitigate the effects of increased workload on patient outcomes and clinician performance.
Metrics
Details
- Title
- Objective measures of workload in healthcare: a narrative review
- Creators
- Daniela Fishbein - Thomas Jefferson UniversitySiddhartha Nambiar - North Carolina State UniversityKendall McKenzie - North Carolina State UniversityMaria Mayorga - North Carolina State UniversityKristen Miller - MedStar HealthKevin Tran - Drexel UniversityLaura Schubel - MedStar HealthJoseph Agor - Oregon State UniversityTracy Kim - MedStar HealthMuge Capan - Drexel University
- Publication Details
- International journal of health care quality assurance, v 33(1), pp 1-17
- Publisher
- Emerald Group Publishing
- Number of pages
- 17
- Grant note
- 1522072; 1522106; 1833538 / National Science Foundation Smart and Connected Health
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Decision Sciences (and Management Information Systems); Physical Therapy (and Rehabilitation Sciences)
- Web of Science ID
- WOS:000505880500001
- Scopus ID
- 2-s2.0-85077284434
- Other Identifier
- 991019168759504721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Health Policy & Services