Journal of Advanced Nursing· 2026Q1· Review
Inpatient Patient‐ and Assignment‐Level Nursing Workload Measures: A Scoping Review
- 0citations
- Q1SCImago
- 2026year
Short summary
A scoping review of 36 articles (2004-2024) reveals varied approaches to measuring inpatient nursing workload, with patient classification tools being most prominent, though interest is growing in more objective, automated, and dynamic measures.
AI-generated from the title and abstract; the full text is not read.
Key points
- 36 articles published between 2004 and 2024 were included in the review.
- Workload measures were categorized by setting, patient/assignment factors, data sources, assessment method, and application.
- Patient classification tools were the most prominent measurement approach.
- There is increasing interest in objective, automated, and dynamic workload measures.
AI-generated from the title and abstract; the full text is not read.
Abstract
AIM: To review the scope of nursing workload measures that include patient and/or assignment characteristics. DESIGN: Scoping review. DATA SOURCES: In June 2024, articles published between 2004 and 2024 were gathered from Academic Search Complete, Business Source Complete, CINAHL, Medline, and IEEE Xplore. Articles describing formal approaches to assess nurses' patient- and/or assignment-level workload in inpatient settings were included. RESULTS: A total of 36 articles were included. Workload measures were categorized according to five attributes: intended care setting, patient-level and assignment-level workload factors assessed, data sources, assessment method, and intended application. Measurement approaches encompassed a range of workload factors, using data from nursing assessments, staffing and patient census data, electronic records, physical measurements, and proprietary systems. CONCLUSION: There are varied approaches to measure nursing workload with consideration for patient and assignment characteristics. Between 2004 and 2024, patient classification tools were the most prominent approach, but there is demonstrated interest in approaches that may provide more objective, automated, and dynamic workload measures. The complexity of workload measures and screening methodology may limit the completeness of this review. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: Formal workload measures can support more equitable patient assignments, improve communication and understanding of patient demands, and inform staffing decisions. More work is needed to develop comprehensive workload measures suited for specific care settings. IMPACT: There is a need to synthesize workload measures that consider more than unit-level and task-level factors. Nursing workload is shaped by the characteristics of their patients and assignments, commonly evaluated using patient classification tools. Findings can inform healthcare leaders, frontline staff, and workload researchers. REPORTING METHOD: This paper was guided and reported using PRISMA-Sc guidelines. PATIENT OR PUBLIC CONTRIBUTION: This study did not include patient or public involvement in its design, conduct, or reporting. TRIAL REGISTRATION: Open Science Framework (https://doi.org/10.17605/OSF.IO/5WK26).
The authors' abstract, as published at the source. Journal of Advanced Nursing, 2026 · DOI ↗
Continue with a free account
Ask the paper: 3 free questions a day about this paper; save it, get its citation, new summaries every day for your field. Takeaways are Premium.
Continue free on the webSign in with Google or Apple; no card needed. You come back to this paper.
On your phone:
Research and TheoryNursing