Exploring measurement tools to optimise hospital physician distribution.

Equitable healthcare delivery is essential and requires resources to be distributed, which include assets and healthcare workers. To date, there is no gold standard for measuring the correct number of physicians to meet healthcare needs. This rapid review aims to explore measurement tools employed to optimise the distribution of hospital physicians, with a focus on ensuring fair resource allocation for equitable healthcare delivery. A literature search was performed across PubMed, EMBASE, Emerald Insight and grey literature sources. The key terms used in the search include 'distribution', 'method', and 'physician', focusing on research articles published in English from 2002 to 2022 that described methods or tools to measure hospital-based physicians' distribution. Relevant articles were selected through a two-level screening process and critically appraised. The primary outcome is the measurement tools used to assess the distribution of hospital-based physicians. Study characteristics, tool advantages and limitations were also extracted. The extracted data were synthesised narratively. Out of 7,199 identified articles, 13 met the inclusion criteria. Among the selected articles, 12 were from Asia and one from Africa. The review identified eight measurement tools: Gini coefficients and Lorenz curve, Robin Hood index, Theil index, concentration index, Workload Indicator of Staffing Need method, spatial autocorrelation analysis, mixed integer linear programming model and cohortcomponent model. These tools rely on fundamental data concerning population and physician numbers to generate outputs. Additionally, five studies employed a combination of these tools to gain a comprehensive understanding of physician distribution dynamics. Measurement tools can be used to assess physician distribution according to population needs. Nevertheless, each tool has its own merits and limitations, underscoring the importance of employing a combination of tools. The choice of measuring tool should be tailored to the specific context and research objectives.