Why Public Health Needs GIS: A Methodological Overview

Abstract

The short paper provides an overview on how geographic issues have become increasingly relevant to public health research and policy, particularly through the lens of geographic information systems (GIS). It covers six themes with an emphasis on methodological issues. (1) Our health-related behavior varies across geographic settings, so should public health policy. (2) Facilities (supply) and patients (demand) in a health care market interact with each other across geopolitical borders, and measures of health care accessibility need to capture that. (3) Our health outcome is the result of joint effects of individual attributes and neighborhood characteristics, and an adequate definition of neighborhood is critical for assessing neighborhood effect. (4) Disease rates in areas of small population are unreliable, and one effective way to mitigate the problem is to construct a larger, internally-homogenous and comparable area unit. (5) Defining a scientific geographic unit for health care market is critical for researchers, practitioners, and policy makers to evaluate health care delivery, and GIS enables us to define the unit (e.g., primary care service areas, hospital service areas, and cancer service areas) automatically, efficiently and optimally. (6) Aside from various optimization objectives around "efficiency", it is as important to plan the location and allocation of health care resources toward maximum equality in health care access. Case studies are cited to illustrate each theme.

Keywords: GIS; health care accessibility; hospital service areas; location-allocation optimization; maximum equality; multilevel modeling; neighborhood effect; public health; regionalization methods; spatial heterogeneity.

Figure 1.

Most influential local determinants of household energy expenditure (Source: Mashhoodi et al. 2019: 28)

Figure 2.

Hospital potential crowdedness vs. zip code area accessibility (Source: Wang 2018: 257)

Figure 3.

Dynamic exposure assessments based on (A) person’s daily path (B) person’s residential trajectory (Source: Helbich, 2018: 132)

Figure 4.

Late-stage breast cancer rates in Chicago region in 2000: (a) ZIP code areas, (b) REDCAP-constructed areas (Source: Wang, 2015:206&210)

Figure 5.

Network-based delineations of HSAs/HRRs in Florida: (a) HSAs with ≥200 inpatient discharge, and (b) HRRs with ≥50 inpatient discharge (Source: Hu et al., 2018: 250)