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Objective measures of workload in healthcare: a narrative review

Daniela Fishbein (Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, Pennsylvania, USA)
Siddhartha Nambiar (Edward P. Fitts Department of Industrial and Systems Engineering, North Carolina State University, Raleigh, North Carolina, USA)
Kendall McKenzie (Edward P. Fitts Department of Industrial and Systems Engineering, North Carolina State University, Raleigh, North Carolina, USA)
Maria Mayorga (Edward P. Fitts Department of Industrial and Systems Engineering, North Carolina State University, Raleigh, North Carolina, USA)
Kristen Miller (National Center for Human Factors in Healthcare, MedStar Health, Washington, District of Columbia, USA)
Kevin Tran (LeBow College of Business, Drexel University, Philadelphia, Pennsylvania, USA)
Laura Schubel (National Center for Human Factors in Healthcare, MedStar Health, Washington, District of Columbia, USA)
Joseph Agor (School of Mechanical, Industrial and Manufacturing Engineering, Oregon State University, Corvallis, Oregon, USA)
Tracy Kim (National Center for Human Factors in Healthcare, MedStar Health, Washington, District of Columbia, USA)
Muge Capan (LeBow College of Business, Drexel University, Philadelphia, Pennsylvania, USA)

International Journal of Health Care Quality Assurance

ISSN: 0952-6862

Article publication date: 30 December 2019

Issue publication date: 15 January 2020

1597

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.

Keywords

Acknowledgements

The authors would like to acknowledge the SEPSIS (Sepsis Early Prediction Support Implementation System) Collaborative and research team members at North Carolina State University, Mayo Clinic and Drexel University. This work was supported by the National Science Foundation Smart and Connected Health (Award Numbers: 1522072, 1522106 and 1833538).

Citation

Fishbein, D., Nambiar, S., McKenzie, K., Mayorga, M., Miller, K., Tran, K., Schubel, L., Agor, J., Kim, T. and Capan, M. (2020), "Objective measures of workload in healthcare: a narrative review", International Journal of Health Care Quality Assurance, Vol. 33 No. 1, pp. 1-17. https://doi.org/10.1108/IJHCQA-12-2018-0288

Publisher

:

Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited

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