Contextually appropriate nurse staffing models: a realist review protocol.

ABSTRACT

INTRODUCTION: Decisions about nurse staffing models are a concern for health systems globally due to workforce retention and well-being challenges. Nurse staffing models range from all Registered Nurse workforce to a mix of differentially educated nurses and aides (regulated and unregulated), such as Licensed Practical or Vocational Nurses and Health Care Aides. Systematic reviews have examined relationships between specific nurse staffing models and client, staff and health system outcomes (eg, mortality, adverse events, retention, healthcare costs), with inconclusive or contradictory results. No evidence has been synthesised and consolidated on how, why and under what contexts certain staffing models produce different outcomes. We aim to describe how we will (1) conduct a realist review to determine how nurse staffing models produce different client, staff and health system outcomes, in which contexts and through what mechanisms and (2) coproduce recommendations with decision-makers to guide future research and implementation of nurse staffing models. METHODS AND ANALYSIS: Using an integrated knowledge translation approach with researchers and decision-makers as partners, we are conducting a three-phase realist review. In this protocol, we report on the final two phases of this realist review. We will use Citation tracking, tracing Lead authors, identifying Unpublished materials, Google Scholar searching, Theory tracking, ancestry searching for Early examples, and follow-up of Related projects (CLUSTER) searching, specifically designed for realist searches as the review progresses. We will search empirical evidence to test identified programme theories and engage stakeholders to contextualise findings, finalise programme theories document our search processes as per established realist review methods. ETHICS AND DISSEMINATION Ethical approval for this study was provided by the Health Research Ethics Board of the University of Alberta (Study ID Pro00100425). We will disseminate the findings through peer-reviewed publications, national and international conference presentations, regional briefing sessions, webinars and lay summary.