Unbiased Analysis of Today's Healthcare Issues

Defining a Hospital Catchment Area

Written By: Jason Shafrin - Nov• 23•10

From what areas does a hospital draw on to fill its beds?  There have been many attempts to define a hospital’s catchment area.  The Dartmouth Atlas Group uses hospital referral regions (HRRs) and hospital service areas (HSAs). One method is to determine a minimum admission rate for a given geographic unit (e.g., county, census tract, zip code).  For instance, a given zip code would be placed in a hospital’s catchment area if that zip code made up at least 0.5% of hospital admissions.  Conversely, one could include all areas where at least a certain percent of resident admissions were to the hospital in question.

A paper by Gilmour (2010) examines how to create a hospital catchment area using K-means clustering.  The goal of this process is to assign local authority districts to hospitals based on the how likely the individuals are to visit a certain hospital.  K-means clustering is used to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean. The author applies the standard K-means clustering algorithm as follows:

  1. Two cluster centers are chosen arbitrarily,
  2. Each observation is assigned into the cluster whose center it lies closest to,
  3. The center of the cluster formed by this assignment is recalculated, and
  4. The process is repeated until the cluster assignments cease to change.

Gilmour uses a multivariate approach to estimate “closeness.”  He uses principal components analysis to incorporate additional information such as the size and distribution of the hospital’s activity.

Although the K-means clustering captures a larger share of the hospital’s admissions, the catchment areas are generally much larger than is the case using the marginal methods.

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