Purpose: Bypass, or utilizing healthcare outside of one's community rather than local healthcare, can have serious consequences on rural healthcare availability, quality, and outcomes. Previous studies of the likelihood of healthcare bypass used various individual and community characteristics. This study includes measures for individuals and communities, as well as place-based characteristics. We introduce the social vulnerability of place index (SoVI)—a well-established measure in disaster literature—into healthcare studies to further explain the impact of place on healthcare selection behavior. Additionally, with the use of open-ended questions, this study explains why people choose to bypass. By including each of these measures, this study provides a more nuanced and detailed understanding of how individual healthcare selection is affected by the privilege of the individual, community ties, place of residence, and primary motivator for bypass.
Procedure: A systematic random sample of residents from 25 rural towns in the western US state of Utah were surveyed in 2017 in the Rural Utah Community Survey (RUCS). After accounting for missing data, the total sample size was 1,061. This study used logistic regression to better predict the likelihood of rural healthcare bypass behavior. Measures associated with community push factors (dissatisfaction with various local amenities), community pull factors (friends in community and length of residence), individual ability (demographics, self-reported health, and distance to a hospital), and social vulnerability of place (SoVI), were added to the models to examine their impact on the likelihood of bypass. The SoVI was made using census data with variables that measure both social and place inequality. Each town in the study received a SoVI score and was then categorized as having low, mean, or high social vulnerability. Qualitative open-ended responses about healthcare selection were coded for explanations given for bypassing.
Main findings: The pooled model (Table 2) showed that bypass was more likely amongst residents who are dissatisfied with local healthcare and more likely for females. Breaking bypass down, according to SoVI (Table 3), provides a more nuanced understanding of bypass. For people living in low socially vulnerable areas, privileges such as graduating college made them more likely to bypass. For high socially vulnerable areas, privilege did not help people bypass, but disadvantages such as aging made residents less likely to bypass. Thus, by introducing the SoVI into healthcare literature, this study can compare healthcare selection behaviors of residents in low vulnerable towns, average vulnerable towns, and highly vulnerable towns. Additionally, the analysis of open-ended responses showed patterns explaining why people bypass.
Main conclusions: Policymakers and public health workers can use the SoVI to better target their healthcare outreach. Reasons for bypass include quality, selection, consistency, cost of insurance, one-stop-shop, and confidentiality. Rural clinics can help residents avoid the need to bypass by improving in these areas and thus gaining patients and minimizing the risk of closure. Healthcare policymakers should focus resources on high socially vulnerable places as well as underprivileged people in low socially vulnerable places.