Recorded presentation

Charles Townsend, MA, Strategic Planning, Dartmouth-Hitchcock Alliance, One Medical Center Drive, Lebanon, NH 03756, 603-653-1923, charles.townsend@DARTMOUTH.EDU and David Bott, PhD, Center for Evaluative Clinical Sciences, Dartmouth Medical School, 7251 Strasenburgh Hall, Hanover, NH 03755.

Research Objective: Developing methods that identify vulnerable populations efficiently in states that are not representative of the US as a whole is an important goal in efforts to improve vulnerable populations’ access to primary health care resources. We sought to adapt existing datasets to develop indicators that measure barriers to access of primary health resources in regions with small populations, e.g., rural and low population urban areas.

Study Design: We used existing data available from New Hampshire DHHS, the Census, and the Primary Care Service Area (PCSA) project to develop markers indicating the presence of barriers to primary care access. We used these markers to compute scores characterizing difficulties accessing primary care by the population within a given PCSA.

Population Studied: Vulnerable populations within New Hampshire—a state with rural and urban populations atypical compared to US as a whole.

Principal Findings: New Hampshire contains 48 PCSAs (median population 12,225 per PCSA). We were able to successfully compute 19 indicators of geographic, socio-cultural and economic barriers to primary care access and identify several regions with substantial barriers to primary care access.

Conclusions: This study demonstrates the feasibility of using surrogate measures to identify barriers to primary care access, even in areas with low population density, i.e., rural and low-population urban regions, where standard access indicators may fail.

Implications for Policy:  Health policy makers can learn how to use existing datasets within PCSAs to identify primary care access barriers even when virtually the entire region under study contains low population densities rendering many typical national indicators or larger units of analysis less useful.

Learning Objectives: