Definition and categorization of rural and assessment of realized access to care

Abstract

Objective To examine how three measures of realized access to care vary by definitions and categorizations of “rural”. Data sources Health Information National Trends Survey (HINTS) data, a nationally representative survey assessing knowledge of health‐related information, were used. Participants were categorized by county‐based Urban Influence Codes (UICs), Rural–Urban Continuum Codes (RUCCs), and census tract‐based Rural–Urban Commuting Area (RUCAs). Study design Three approaches were used across categories of UICs, RUCCs, and RUCAs: (1) non‐metropolitan/metropolitan, (2) three‐group categorization based upon population size, and (3) three‐group categorization based on adjacency to metropolitan areas. Wald Chi‐square tests evaluated differences in sociodemographic variables and three measures of realized access across three of Penchansky's “A's of access” and approaches. The three outcome measures included: having a regular provider (realized availability), self‐reported “excellent” quality of care (realized acceptability), and self‐report of the provider “always” spending enough time with you (provider attentiveness–realized accommodation). The average marginal effects corresponding to each outcome were calculated. Data collection/extraction methods N/A Principal findings All approaches indicated comparable variation in sociodemographics. In all approaches, RUCA‐based categorizations showed differences in having a regular provider (e.g., 68.9% of non‐metropolitan and 64.4% of metropolitan participants had a regular provider). This association was attenuated in multivariable analyses. No rural–urban differences in quality of care were seen in unadjusted or adjusted analyses regardless of approach. After adjustment for covariates, rural respondents reported greater provider attentiveness in some categorizations of rural compared with urban (e.g., non‐metropolitan respondents reported 6.03 percentage point increase in probability of having an attentive provider [CI = 0.76–11.31%] compared with metropolitan). Conclusions Our findings underscore the importance of considering multiple definitions of rural to understand access disparities and suggest that continued research is needed to examine the interplay between potential and realized access. These findings have implications for federal funding, resource allocation, and identifying health disparities.

Effect of rurality and travel distance on contralateral prophylactic mastectomy for unilateral breast cancer

“…We performed a secondary data analysis using the NCDB, a hospital-based cancer registry system maintained by the American College of Surgeons Commission on Cancer (CoC) [30]. The NCDB includes data from more than 1500 CoC-accredited facilities and represents an estimated 70% of incident cancer cases in the US [30].…”

“…We performed a secondary data analysis using the NCDB, a hospital-based cancer registry system maintained by the American College of Surgeons Commission on Cancer (CoC) [30]. The NCDB includes data from more than 1500 CoC-accredited facilities and represents an estimated 70% of incident cancer cases in the US [30]. We identified a cohort of women aged 40 + years (the NCDB suppresses data on patients < 40 years of age) who were diagnosed with stage I-III unilateral breast cancer between 2007 and 2017 and managed surgically.…”

Measuring rurality in health services research: a scoping review

“…Likewise, health services researchers use multiple geographic units and definitions to measure rurality, such as county [12][13][14], zip code or rural-urban commuting patterns [13][14][15][16][17]. Importantly, some key outcome measures, such as access to care estimates and the incidence of breast cancer were shown to be sensitive to the rural measurement method used [18]. Inconsistent usage of these definitions can influence policy decisions, as demonstrated by Kozhimannil et al, (2018) who documented loss of obstetric services in rural areas.…”

Eating disorder risk in rural US adolescents: What do we know and where do we go?

“…One population that may have elevated eating disorder risk is rural adolescents. While the definition of what constitutes a rural community varies, rural communities are generally characterized as areas with low population density located outside of metropolitan areas or cities (Long et al, 2021; Zahnd et al, 2022). Irrespective of the exact definition used, rural communities are shown to face mental (Fontanella et al, 2015; Monnat & Rigg, 2016; Reiss, 2013) and physical health disparities (Ng & Kaye, 2015; Valentine et al, 2022; Ziller et al, 2019).…”

“…One population that may have elevated eating disorder risk is rural adolescents. While the definition of what constitutes a rural community varies, rural communities are generally characterized as areas with low population density located outside of metropolitan areas or cities (Long et al, 2021;Zahnd et al, 2022).…”