The Association between Nursing Skill Mix and Mortality for Adult Medical and Surgical Patients: Protocol for a Systematic Review

Int J Environ Res Public Health. 2020 Nov 19;17(22):8604. doi: 10.3390/ijerph17228604.

Abstract

Skill mix refers to the number and educational experience of nurses working in clinical settings. Authors have used several measures to determine the skill mix, which includes nurse-to-patient ratio and the proportion of baccalaureate-prepared nurses. Observational studies have tested the association between nursing skill mix and patient outcomes (mortality). To date, this body of research has not been subject to systematic review or meta-analysis. The aim of this study is to systematically review and meta-analyse observational and experimental research that tests the association between nursing skill mix and patient mortality in medical and surgical settings. We will search four key electronic databases-MEDLINE [OVID], EMBASE [OVID], CINAHL [EBSCOhost], and ProQuest Central (five databases)-from inception. Title, abstract, and full-text screening will be undertaken independently by at least two researchers using COVIDENCE review management software. We will include studies where the authors report an association between nursing skill mix and outcomes in adult medical and surgical inpatients. Extracted data from included studies will consist measures of nursing skill mix and inpatient mortality outcomes. A meta-analysis will be undertaken if there are at least two studies with similar designs, exposures, and outcomes. The findings will inform future research and workforce planning in health systems internationally.

Keywords: inpatient; mortality; nurse-to-patient ratio; observational research; protocol; skill mix; systematic review.

Publication types

  • Meta-Analysis
  • Systematic Review

MeSH terms

  • Adult
  • Databases, Factual
  • General Surgery / statistics & numerical data
  • Humans
  • Nursing Staff, Hospital* / standards
  • Nursing Staff, Hospital* / statistics & numerical data
  • Patients* / statistics & numerical data
  • Personnel Staffing and Scheduling / statistics & numerical data
  • Workforce / statistics & numerical data