Doctors, nurses, and the optimal scale size in the Portuguese public hospitals

Health Policy. 2018 Oct;122(10):1093-1100. doi: 10.1016/j.healthpol.2018.06.009. Epub 2018 Jul 4.

Abstract

This study analyses the scale efficiency, optimal scale for hospital clinical staff, and the exogenous dimensions that can be associated with them. They offer useful insights for health policy design, particularly when human resources need to be reallocated across the country due to uneven distributions. Initial data considered a sample of 27 Portuguese general/acute-care public hospitals belonging to the National Health Service, observed between 2013 and 2016. This resulted into a sample of 108 hospitals-year. Data Envelopment Analysis was employed to assess scale efficiency and optimal scale associated with the workforce and at the overall hospital level. Quality and access to health care services adjusted the measures of scale efficiency and optimal size. A multiple regression analysis was carried out to associate optimal scale and scale efficiency to demographics. Optimal scale centred on 274 full-time equivalent (FTE) doctors and 475 FTE nurses. Overall, there is an excess of FTE doctors and FTE nurses, even after potential reallocations. There is an uneven distribution of health workforce, with excess of staff located in urban areas. Hospitals productivity would increase if they reduced their operational scale. Drivers of potential change include population size, childhood mortality rate, birth rate, and purchasing power parity. Health policies are required, not to hire more staff, but rather to promote the reallocation of employees to deprived regions.

Keywords: Efficiency; Hospital administration; Hospital economics; Nurses; Physicians; Productivity.

MeSH terms

  • Demography
  • Efficiency, Organizational / statistics & numerical data
  • Health Workforce / statistics & numerical data*
  • Hospitals, Public
  • Humans
  • Medical Staff, Hospital / statistics & numerical data*
  • Nursing Staff, Hospital / statistics & numerical data*
  • Portugal