Whitney E Zahnd1, Natalie Del Vecchio2, Natoshia Askelson3, Jan M Eberth4, Robin C Vanderpool5, Linda Overholser6, Purnima Madhivanan7, Rachel Hirschey8, Jean Edward9. 1. Department of Health Management and Policy, College of Public Health, University of Iowa, Iowa City, Iowa, USA. 2. Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA. 3. Department of Community and Behavioral Health, College of Public Health, University of Iowa, Iowa City, Iowa, USA. 4. Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, South Carolina, USA. 5. Health Communication and Informatics Research Branch, National Cancer Institute, Bethesda, Maryland, USA. 6. Department of Internal Medicine, University of Colorado, Denver, Colorado, USA. 7. Health Promotion Sciences Department, Mel & Enid Zuckerman College of Public Health, University of Arizona, Tucson, Arizona, USA. 8. School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. 9. College of Nursing, University of Kentucky, Lexington, Kentucky, USA.
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.
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.
Authors: Peiyin Hung; Songyuan Deng; Whitney E Zahnd; Swann A Adams; Bankole Olatosi; Elizabeth L Crouch; Jan M Eberth Journal: Cancer Date: 2019-11-08 Impact factor: 6.860
Authors: Scott R Sanders; Lance D Erickson; Vaughn R A Call; Matthew L McKnight; Dawson W Hedges Journal: J Rural Health Date: 2014-09-12 Impact factor: 4.333
Authors: Kevin J Bennett; Tyrone F Borders; George M Holmes; Katy Backes Kozhimannil; Erika Ziller Journal: Health Aff (Millwood) Date: 2019-12 Impact factor: 6.301
Authors: Whitney E Zahnd; Natalie Del Vecchio; Natoshia Askelson; Jan M Eberth; Robin C Vanderpool; Linda Overholser; Purnima Madhivanan; Rachel Hirschey; Jean Edward Journal: Health Serv Res Date: 2022-03-07 Impact factor: 3.734