Resources allocation in healthcare for cancer: a case study using generalised additive mixed models

Geospat Health. 2012 Nov;7(1):83-9. doi: 10.4081/gh.2012.107.

Abstract

Our aim is to develop a method for helping resources re-allocation in healthcare linked to cancer, in order to replan the allocation of providers. Ageing of the population has a considerable impact on the use of health resources because aged people require more specialised medical care due notably to cancer. We propose a method useful to monitor changes of cancer incidence in space and time taking into account two age categories, according to healthcar general organisation. We use generalised additive mixed models with a Poisson response, according to the methodology presented in Wood, Generalised additive models: an introduction with R. Chapman and Hall/CRC, 2006. Besides one-dimensional smooth functions accounting for non-linear effects of covariates, the space-time interaction can be modelled using scale invariant smoothers. Incidence data collected by a general cancer registry between 1992 and 2007 in a specific area of France is studied. Our best model exhibits a strong increase of the incidence of cancer along time and an obvious spatial pattern for people more than 70 years with a higher incidence in the central band of the region. This is a strong argument for re-allocating resources for old people cancer care in this sub-region.

MeSH terms

  • Adult
  • Age Distribution
  • Aged
  • Aging
  • Female
  • France / epidemiology
  • Health Care Rationing / economics*
  • Health Care Rationing / standards
  • Health Priorities / economics*
  • Health Priorities / standards
  • Health Services for the Aged / economics*
  • Health Services for the Aged / standards
  • Humans
  • Incidence
  • Male
  • Middle Aged
  • Neoplasms / economics*
  • Neoplasms / epidemiology
  • Poisson Distribution
  • Population Dynamics / trends
  • Registries
  • Resource Allocation / methods
  • Resource Allocation / standards
  • Space-Time Clustering
  • Young Adult