Jack M. Chapel PhD, Elizabeth Currid-Halkett PhD, Bryan Tysinger PhD
Purpose
Estimate health-quality-adjusted life expectancy (QALE) for Americans nearing retirement age and assess rural–urban disparities in QALE.
Methods
We used a dynamic microsimulation model based on Health and Retirement Study data to estimate the quantity and health quality of expected future life years for rural and urban Americans ages 59–60 in 2014–2020.
Findings
Cohort life expectancy at age 60 (LE) for urban and rural men was 22.9 and 20.9, respectively; for urban and rural women, LE was 25.6 and 25.0, respectively. Adjusting future life years to quality-adjusted life years, QALE was 17.5 versus 15.7 for urban versus rural men, and 19.3 versus 18.7 for women. Compared to a cohort in 1994–2000, the urban–rural QALE gap in 2014–2020 grew substantially for men; changes for women were smaller. Average QALE masked heterogeneity by race/ethnicity, education, and Census region. Counterfactual scenarios suggested eliminating smoking and managing obesity and prevalent heart conditions would be particularly beneficial for increasing rural QALE and reducing the urban–rural gap.
Conclusions
Expected health quality, in addition to longevity, is an important factor when assessing rural disparities in older Americans’ future life outcomes. Current chronic disease disparities are expected to translate to a widening urban–rural gap in QALE, particularly for men. Interventions earlier in life may be needed to fully address disparities in QALE at older ages.
{"title":"The urban–rural gap in older Americans’ healthy life expectancy","authors":"Jack M. Chapel PhD, Elizabeth Currid-Halkett PhD, Bryan Tysinger PhD","doi":"10.1111/jrh.12875","DOIUrl":"10.1111/jrh.12875","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>Estimate health-quality-adjusted life expectancy (QALE) for Americans nearing retirement age and assess rural–urban disparities in QALE.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We used a dynamic microsimulation model based on Health and Retirement Study data to estimate the quantity and health quality of expected future life years for rural and urban Americans ages 59–60 in 2014–2020.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Cohort life expectancy at age 60 (LE) for urban and rural men was 22.9 and 20.9, respectively; for urban and rural women, LE was 25.6 and 25.0, respectively. Adjusting future life years to quality-adjusted life years, QALE was 17.5 versus 15.7 for urban versus rural men, and 19.3 versus 18.7 for women. Compared to a cohort in 1994–2000, the urban–rural QALE gap in 2014–2020 grew substantially for men; changes for women were smaller. Average QALE masked heterogeneity by race/ethnicity, education, and Census region. Counterfactual scenarios suggested eliminating smoking and managing obesity and prevalent heart conditions would be particularly beneficial for increasing rural QALE and reducing the urban–rural gap.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Expected health quality, in addition to longevity, is an important factor when assessing rural disparities in older Americans’ future life outcomes. Current chronic disease disparities are expected to translate to a widening urban–rural gap in QALE, particularly for men. Interventions earlier in life may be needed to fully address disparities in QALE at older ages.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142308968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
April D. Kimmel PhD, Rose S. Bono MPH, Zhongzhe Pan PhD, Jessica S. Kiernan MSc, Faye Z. Belgrave PhD, Daniel E. Nixon DO, Lindsay Sabik PhD, Bassam Dahman PhD
Purpose
Less than 50% of people with HIV (PWH) in the United States are retained in care, a key step along the HIV care continuum. We examined the impact of geographic access to care on retention in care for urban and rural PWH.
Methods
We used Medicaid claims and clinician data (Medicaid Analytic eXtract and MAX Provider Characteristics, 2009–2012) for 13 Southern states plus the District of Columbia. We calculated drive time from the enrollees’ ZIP Code Tabulation Area to their usual source of care. We used generalized estimating equations to examine the association between drive time to care >30 min (versus ≤30 min) and retention in care, overall and stratified by rurality. In sensitivity analysis, we examined the definition of retention in care, states included in the analysis, and enrollee- and care-related characteristics.
Findings
The sample included 49,596 PWH. Overall, the association between drive time >30 min and retention was significant, but small (adjusted odds ratio [aOR] 1.01, 95% confidence interval [CI] 1.00, 1.01) and was not significant in urban areas; however, the significance and direction of the association differed in sensitivity analysis. In rural areas, driving >30 min to care was associated with 7% higher odds of retention in care (aOR 1.07, 95% CI 1.05, 1.08) and this association remained significant and positive in nearly all sensitivity analyses.
Conclusions
For PWH in rural areas, greater drive time is consistently associated with greater retention in care. Disentangling the mechanisms of this relationship is a future research priority.
{"title":"Drive time to care and retention in HIV care: Rural–urban differences among Medicaid enrollees in the United States South","authors":"April D. Kimmel PhD, Rose S. Bono MPH, Zhongzhe Pan PhD, Jessica S. Kiernan MSc, Faye Z. Belgrave PhD, Daniel E. Nixon DO, Lindsay Sabik PhD, Bassam Dahman PhD","doi":"10.1111/jrh.12877","DOIUrl":"10.1111/jrh.12877","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>Less than 50% of people with HIV (PWH) in the United States are retained in care, a key step along the HIV care continuum. We examined the impact of geographic access to care on retention in care for urban and rural PWH.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We used Medicaid claims and clinician data (Medicaid Analytic eXtract and MAX Provider Characteristics, 2009–2012) for 13 Southern states plus the District of Columbia. We calculated drive time from the enrollees’ ZIP Code Tabulation Area to their usual source of care. We used generalized estimating equations to examine the association between drive time to care >30 min (versus ≤30 min) and retention in care, overall and stratified by rurality. In sensitivity analysis, we examined the definition of retention in care, states included in the analysis, and enrollee- and care-related characteristics.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>The sample included 49,596 PWH. Overall, the association between drive time >30 min and retention was significant, but small (adjusted odds ratio [aOR] 1.01, 95% confidence interval [CI] 1.00, 1.01) and was not significant in urban areas; however, the significance and direction of the association differed in sensitivity analysis. In rural areas, driving >30 min to care was associated with 7% higher odds of retention in care (aOR 1.07, 95% CI 1.05, 1.08) and this association remained significant and positive in nearly all sensitivity analyses.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>For PWH in rural areas, greater drive time is consistently associated with greater retention in care. Disentangling the mechanisms of this relationship is a future research priority.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jrh.12877","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Steven Cohen DrPH, MPH, Emily Metcalf , Monique J. Brown PhD, MPH, FGSA, Neelam H. Ahmed MPH, Caitlin Nash MPH, RD, LDN, Mary L. Greaney PhD, MPH, CHES
Background
Racial health disparities are well documented and pervasive across the United States. Evidence suggests there is a “rural mortality penalty” whereby rural residents experience poorer health outcomes than their urban counterparts. However, whether this penalty is uniform across demographic groups and U.S. regions is unknown.
Objective
To assess how rural–urban differences in mortality differ by race (Black vs. White), U.S. region, poverty status, and how rural–urban status is measured.
Methods
Age-standardized mortality rates (ASMRs)/100,000 by U.S. county (2015–2019) were obtained by race (Black/White) from the CDC Wonder National Vital Statistics System (2015–2019) and were merged with county-level social determinants from the US Census Bureau and County Health Rankings. Multivariable generalized linear models assessed the associations between rurality (index of relative rurality [IRR] decile, rural–urban continuum codes, and population density) and race-specific ASMR, overall, and by Census region and poverty level.
Results
Overall, average ASMR was significantly higher in rural areas than urban areas for both Black (rural ASMR = 949.1 per 100,000 vs. urban ASMR = 857.7 per 100,000) and White (rural ASMR = 903.0 per 100,000 vs. urban ASMR = 791.6 per 100,000) populations. The Black-White difference was substantially higher (p < 0.001) in urban than in rural counties (65.1 per 100,000 vs. 46.1 per 100,000). Black–White differences and patterns in ASMR varied notably by poverty status and U.S. region.
Conclusion
Policies and interventions designed to reduce racial health disparities should consider and address key contextual factors associated with geographic location, including rural–urban status and socioeconomic status.
{"title":"A closer examination of the “rural mortality penalty”: Variability by race, region, and measurement","authors":"Steven Cohen DrPH, MPH, Emily Metcalf , Monique J. Brown PhD, MPH, FGSA, Neelam H. Ahmed MPH, Caitlin Nash MPH, RD, LDN, Mary L. Greaney PhD, MPH, CHES","doi":"10.1111/jrh.12876","DOIUrl":"10.1111/jrh.12876","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Racial health disparities are well documented and pervasive across the United States. Evidence suggests there is a “rural mortality penalty” whereby rural residents experience poorer health outcomes than their urban counterparts. However, whether this penalty is uniform across demographic groups and U.S. regions is unknown.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>To assess how rural–urban differences in mortality differ by race (Black vs. White), U.S. region, poverty status, and how rural–urban status is measured.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Age-standardized mortality rates (ASMRs)/100,000 by U.S. county (2015–2019) were obtained by race (Black/White) from the CDC Wonder National Vital Statistics System (2015–2019) and were merged with county-level social determinants from the US Census Bureau and County Health Rankings. Multivariable generalized linear models assessed the associations between rurality (index of relative rurality [IRR] decile, rural–urban continuum codes, and population density) and race-specific ASMR, overall, and by Census region and poverty level.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Overall, average ASMR was significantly higher in rural areas than urban areas for both Black (rural ASMR = 949.1 per 100,000 vs. urban ASMR = 857.7 per 100,000) and White (rural ASMR = 903.0 per 100,000 vs. urban ASMR = 791.6 per 100,000) populations. The Black-White difference was substantially higher (<i>p</i> < 0.001) in urban than in rural counties (65.1 per 100,000 vs. 46.1 per 100,000). Black–White differences and patterns in ASMR varied notably by poverty status and U.S. region.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Policies and interventions designed to reduce racial health disparities should consider and address key contextual factors associated with geographic location, including rural–urban status and socioeconomic status.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142094116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Daniel Jung PhD, Jeong Ha (Steph) Choi PhD, Kerstin Gerst Emerson PhD
Purpose
To examine the relationship between living arrangements and discharge disposition, and how this relationship differs by the rural or urban characteristics of the patient's residence among home health care patients with Alzheimer's disease and related dementia (ADRD).
Methods
This retrospective study used the 2019 Outcome and Assessment Information Set and the Master Beneficiary Summary File. Our study was based on 531,269 Medicare fee-for-service patients with ADRD. We used linear probability regression models to examine the relationship between discharge disposition (to the community vs. an institution) and living arrangements, including an interaction term for rural-urban residence.
Findings
Patients in rural areas (19.8%) were more likely to live alone than those in urban areas (15.2%). Our main results show that patients living at home with others (coefficient: –0.02, p-value < 0.001) or alone (coefficient: –0.03, p-value < 0.001) were less likely to be discharged to the community compared to patients who lived in congregate settings. Also, for patients with ADRD who lived in rural areas, living at home with others (rural*home with others; coefficient: –0.02, p-value < 0.001) or living alone (rural*home alone; coefficient: –0.03, p-value<0.001) were associated with additional lower probabilities of being discharged to their communities.
Conclusions
A multidimensional approach considering living arrangements to support home health care patients with ADRD could be critical to achieving better health outcomes. Furthermore, implementing area-specific target interventions could be important for improving the care and health of patients with ADRD as well as reducing rural-urban disparities in discharge disposition.
{"title":"Discharge disposition for home health care patients with Alzheimer's disease and related dementia: The role of living arrangements and rural living","authors":"Daniel Jung PhD, Jeong Ha (Steph) Choi PhD, Kerstin Gerst Emerson PhD","doi":"10.1111/jrh.12872","DOIUrl":"10.1111/jrh.12872","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To examine the relationship between living arrangements and discharge disposition, and how this relationship differs by the rural or urban characteristics of the patient's residence among home health care patients with Alzheimer's disease and related dementia (ADRD).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This retrospective study used the 2019 Outcome and Assessment Information Set and the Master Beneficiary Summary File. Our study was based on 531,269 Medicare fee-for-service patients with ADRD. We used linear probability regression models to examine the relationship between discharge disposition (to the community vs. an institution) and living arrangements, including an interaction term for rural-urban residence.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Patients in rural areas (19.8%) were more likely to live alone than those in urban areas (15.2%). Our main results show that patients living at home with others (coefficient: –0.02, <i>p</i>-value < 0.001) or alone (coefficient: –0.03, <i>p</i>-value < 0.001) were less likely to be discharged to the community compared to patients who lived in congregate settings. Also, for patients with ADRD who lived in rural areas, living at home with others (rural*home with others; coefficient: –0.02, <i>p</i>-value < 0.001) or living alone (rural*home alone; coefficient: –0.03, <i>p</i>-value<0.001) were associated with additional lower probabilities of being discharged to their communities.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>A multidimensional approach considering living arrangements to support home health care patients with ADRD could be critical to achieving better health outcomes. Furthermore, implementing area-specific target interventions could be important for improving the care and health of patients with ADRD as well as reducing rural-urban disparities in discharge disposition.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11635399/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142019368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Devon Noonan PhD, MPH, FNP-BC, Suzanne Frisbee PhD, Lorna Bittencourt PhD, Dana Rubenstein MD, F. Joseph McClernon PhD, Dana Mowls Carroll PhD
Purpose
There are significant rural/urban disparities that exist in cancer and chronic disease morbidity and mortality, many of which are attributed to increased tobacco use prevalence in rural populations compared to urban. Understanding differences in rural and urban tobacco use patterns is key to developing targeted interventions.
Methods
Using nationally representative data from Wave 5 of the Population Assessment of Tobacco Use and Health (PATH), we examined weighted frequencies and conducted multivariable logistic regression to examine the use of cessation supports in people who currently smoke with a quit attempt in the last 12 months (recent attempters) by rural and urban status and geographic region. Our second objective was to examine lifetime quitting in rural versus urban people who smoke and by geographic region.
Results
Rural people who recently attempted to quit were less likely to use any FDA-approved cessation aids, less likely to use Nicoctine Replacement Therapy (NRT), and less likely to be exposed to a home smoking ban in the adjusted analysis. The adjusted odds of quitting were lower in the rural Northeast, Midwest, and South compared to the urban regions.
Conclusions
Findings from this data can serve to inform the development of targeted interventions for rural communities.
{"title":"Rural–urban differences in smoking quit ratios and cessation-related factors: Results from a nationally representative sample","authors":"Devon Noonan PhD, MPH, FNP-BC, Suzanne Frisbee PhD, Lorna Bittencourt PhD, Dana Rubenstein MD, F. Joseph McClernon PhD, Dana Mowls Carroll PhD","doi":"10.1111/jrh.12870","DOIUrl":"10.1111/jrh.12870","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>There are significant rural/urban disparities that exist in cancer and chronic disease morbidity and mortality, many of which are attributed to increased tobacco use prevalence in rural populations compared to urban. Understanding differences in rural and urban tobacco use patterns is key to developing targeted interventions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Using nationally representative data from Wave 5 of the Population Assessment of Tobacco Use and Health (PATH), we examined weighted frequencies and conducted multivariable logistic regression to examine the use of cessation supports in people who currently smoke with a quit attempt in the last 12 months (recent attempters) by rural and urban status and geographic region. Our second objective was to examine lifetime quitting in rural versus urban people who smoke and by geographic region.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Rural people who recently attempted to quit were less likely to use any FDA-approved cessation aids, less likely to use Nicoctine Replacement Therapy (NRT), and less likely to be exposed to a home smoking ban in the adjusted analysis. The adjusted odds of quitting were lower in the rural Northeast, Midwest, and South compared to the urban regions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Findings from this data can serve to inform the development of targeted interventions for rural communities.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142005721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vashisht V. Madabhushi MD, Matthew Wright MD, Gabriel Orozco MD, Allison Murphy MPH, Antonio R. Garcia PhD, Natalie Pope PhD, Xiaonan Mei MS, Alexandra Cocca MD, Roberto Gedaly MD, Meera Gupta MD, MSCE
Purpose
In rural America, the road to obtaining a liver transplant (LTX) often starts at the primary care provider's (PCP's) office. Patients with end-stage liver disease (ESLD) in rural communities experience lower rates of wait-listing and higher mortality. This study identifies issues related to the knowledge and perceptions of ESLD and LTX referral among PCPs in rural Kentucky (KY).
Methods
The study protocol involved relying upon a semistructured outline to explore the knowledge, attitude, and perceptions of PCPs toward ESLD and LTX referral among PCPs in rural KY. Inductive thematic analysis was utilized to identify, analyze, and report themes.
Findings
From the focus group interviews, three themes were identified: medical culture, gaps in knowledge, and bias against those with self-induced causes of ESLD. Each theme illuminated barriers to referral for transplant evaluation.
Conclusions
Knowledge gaps, attitudes in medical culture, and biases surrounding ESLD and LTX referral exist in community medicine practice. This highlights the importance of education, resources, and facilitation of LTX referral processes for PCPs.
{"title":"A qualitative study of end-stage liver disease and liver transplant referral practices among primary care providers in nonurban America","authors":"Vashisht V. Madabhushi MD, Matthew Wright MD, Gabriel Orozco MD, Allison Murphy MPH, Antonio R. Garcia PhD, Natalie Pope PhD, Xiaonan Mei MS, Alexandra Cocca MD, Roberto Gedaly MD, Meera Gupta MD, MSCE","doi":"10.1111/jrh.12871","DOIUrl":"10.1111/jrh.12871","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>In rural America, the road to obtaining a liver transplant (LTX) often starts at the primary care provider's (PCP's) office. Patients with end-stage liver disease (ESLD) in rural communities experience lower rates of wait-listing and higher mortality. This study identifies issues related to the knowledge and perceptions of ESLD and LTX referral among PCPs in rural Kentucky (KY).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The study protocol involved relying upon a semistructured outline to explore the knowledge, attitude, and perceptions of PCPs toward ESLD and LTX referral among PCPs in rural KY. Inductive thematic analysis was utilized to identify, analyze, and report themes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>From the focus group interviews, three themes were identified: medical culture, gaps in knowledge, and bias against those with self-induced causes of ESLD. Each theme illuminated barriers to referral for transplant evaluation.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Knowledge gaps, attitudes in medical culture, and biases surrounding ESLD and LTX referral exist in community medicine practice. This highlights the importance of education, resources, and facilitation of LTX referral processes for PCPs.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142005720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ahlia Sekkarie PhD, Rebecca C. Woodruff PhD, Michele Casper PhD, Angela-Thompson Paul PhD, Adam S. Vaughan PhD
Purpose
To examine rural and urban disparities in cardiovascular disease (CVD) death rates by poverty level and region.
Methods
Using 2021 county-level population and mortality data for CVD deaths listed as the underlying cause among adults aged 35–64 years, we calculated age-standardized CVD death rates and rate ratios (RR) for 4 categories of counties: high-poverty rural, high-poverty urban, low-poverty rural, and low-poverty urban (referent). Results are presented nationally and by US Census region.
Findings
Rural and urban disparities in CVD mortality varied markedly by poverty and region. Nationally, the CVD death rate was highest among high-poverty rural areas (191 deaths per 100,000, RR: 1.76, CI: 1.73–1.78). By region, Southern high-poverty rural areas had the highest CVD death rate (256 deaths per 100,000) and largest disparity relative to low-poverty urban areas (RR: 2.05; CI: 2.01–2.09). In the Midwest and West, CVD death rates among high-poverty areas were higher than low-poverty areas, regardless of rural or urban classification.
Conclusions
Results reinforce the importance of prioritizing high-poverty rural areas, especially in the South, in efforts to reduce CVD mortality. These efforts may need to consider socioeconomic conditions and region, in addition to rural and urban disparities.
{"title":"Rural–urban disparities in cardiovascular disease mortality vary by poverty level and region","authors":"Ahlia Sekkarie PhD, Rebecca C. Woodruff PhD, Michele Casper PhD, Angela-Thompson Paul PhD, Adam S. Vaughan PhD","doi":"10.1111/jrh.12874","DOIUrl":"10.1111/jrh.12874","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To examine rural and urban disparities in cardiovascular disease (CVD) death rates by poverty level and region.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Using 2021 county-level population and mortality data for CVD deaths listed as the underlying cause among adults aged 35–64 years, we calculated age-standardized CVD death rates and rate ratios (RR) for 4 categories of counties: high-poverty rural, high-poverty urban, low-poverty rural, and low-poverty urban (referent). Results are presented nationally and by US Census region.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Rural and urban disparities in CVD mortality varied markedly by poverty and region. Nationally, the CVD death rate was highest among high-poverty rural areas (191 deaths per 100,000, RR: 1.76, CI: 1.73–1.78). By region, Southern high-poverty rural areas had the highest CVD death rate (256 deaths per 100,000) and largest disparity relative to low-poverty urban areas (RR: 2.05; CI: 2.01–2.09). In the Midwest and West, CVD death rates among high-poverty areas were higher than low-poverty areas, regardless of rural or urban classification.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Results reinforce the importance of prioritizing high-poverty rural areas, especially in the South, in efforts to reduce CVD mortality. These efforts may need to consider socioeconomic conditions and region, in addition to rural and urban disparities.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141996773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Removing Caps for rural graduate medical education: A policy recommendation to eliminate GME Caps of less than 16 for rurally located hospitals","authors":"Randall Longenecker MD","doi":"10.1111/jrh.12873","DOIUrl":"10.1111/jrh.12873","url":null,"abstract":"","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141989324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Janessa M. Graves PhD, Demetrius A. Abshire PhD, Jessica L. Mackelprang PhD, Tracy A. Klein PhD, Carmen Gonzalez PhD, Kailee Parrott AS, Deborah U. Eti PhD, Jordan G. Ferris MSN, Christina M. Chacon DNP, Ashley D. Beck PhD
Purpose
To explore adult community members’ perspectives concerning barriers to mental health care that confront rural-dwelling youth.
Methods
Group concept mapping, a participatory community-engaged research method, was used. Adult community members brainstormed and sorted statements describing barriers rural youth encounter in accessing mental health services. Point and cluster maps were created to visualize conceptual similarities between statements. Statements were rated according to their commonness and importance (1: low commonness/importance, 5: high commonness/importance).
Findings
Thirty-five adults sorted and/or rated 71 barriers facing rural youth in accessing mental health services. Seven conceptual clusters were identified: system-level barriers, knowledge and communication, youth concerns, parent/guardian concerns, parent/guardian barriers, costs and convenience, and school-level barriers. Within youth concerns, community members also identified a subcluster focused on stigma. Common and important statements related to limited after-school programs and community mental health support initiatives.
Conclusions
Group concept mapping methodology provides structure for conceptualizing challenges facing rural youth in accessing mental health services. Policies should be informed by rural community concerns and priorities. After-school and support programs may align with mental health needs identified by rural communities.
{"title":"Adult perceptions of mental health access barriers facing youth in rural Washington State: A group concept mapping study","authors":"Janessa M. Graves PhD, Demetrius A. Abshire PhD, Jessica L. Mackelprang PhD, Tracy A. Klein PhD, Carmen Gonzalez PhD, Kailee Parrott AS, Deborah U. Eti PhD, Jordan G. Ferris MSN, Christina M. Chacon DNP, Ashley D. Beck PhD","doi":"10.1111/jrh.12866","DOIUrl":"10.1111/jrh.12866","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To explore adult community members’ perspectives concerning barriers to mental health care that confront rural-dwelling youth.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Group concept mapping, a participatory community-engaged research method, was used. Adult community members brainstormed and sorted statements describing barriers rural youth encounter in accessing mental health services. Point and cluster maps were created to visualize conceptual similarities between statements. Statements were rated according to their commonness and importance (1: low commonness/importance, 5: high commonness/importance).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Thirty-five adults sorted and/or rated 71 barriers facing rural youth in accessing mental health services. Seven conceptual clusters were identified: system-level barriers, knowledge and communication, youth concerns, parent/guardian concerns, parent/guardian barriers, costs and convenience, and school-level barriers. Within youth concerns, community members also identified a subcluster focused on stigma. Common and important statements related to limited after-school programs and community mental health support initiatives.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Group concept mapping methodology provides structure for conceptualizing challenges facing rural youth in accessing mental health services. Policies should be informed by rural community concerns and priorities. After-school and support programs may align with mental health needs identified by rural communities.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141977131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Laura McFadyen BS, Susie Gurzenda MS, George Pink PhD, Tyler Malone PhD, Kristin Reiter PhD
Introduction
There are long-standing differences in profitability between rural and urban hospitals. Prior to the COVID-19 Public Health Emergency (PHE), rural hospital profitability was decreasing, while urban hospital profitability was increasing. During the PHE, the Federal Government provided billions of dollars of support to hospitals. Given the prepandemic differences in trends in profitability, it is likely that the PHE funding had different effects on rural hospitals and urban hospitals.
Methods
This study uses 2015–2023 Medicare cost report data from acute-care hospitals to assess the impact of COVID-19 PHE funding on hospital profitability. We employ descriptive Kruskal–Wallis and chi-square tests and an interrupted time series analysis to evaluate the effect of PHE funding on operating margins for a stratified sample of rural prospective payment system (PPS), urban PPS, and critical access hospitals (CAHs).
Results
We found that the PHE funding was associated with significant increases in operating margins, with rural PPS hospitals experiencing similar increases compared to urban PPS hospitals, and CAHs surpassing both rural and urban PPS hospitals in their margin values. However, if PHE funding had not been provided, our evidence suggests operating margins for all hospitals in 2022–2023 would have been below prepandemic levels.
Discussion
This preliminary analysis portrays the importance of the PHE government funding in supporting hospitals during the pandemic, and shows declining profitability trends without the funds. Rural PPS hospitals fare the worst suggesting continued need for financial support if the trend continues.
{"title":"The effects of the COVID-19 pandemic on urban and rural hospital profitability","authors":"Laura McFadyen BS, Susie Gurzenda MS, George Pink PhD, Tyler Malone PhD, Kristin Reiter PhD","doi":"10.1111/jrh.12864","DOIUrl":"10.1111/jrh.12864","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>There are long-standing differences in profitability between rural and urban hospitals. Prior to the COVID-19 Public Health Emergency (PHE), rural hospital profitability was decreasing, while urban hospital profitability was increasing. During the PHE, the Federal Government provided billions of dollars of support to hospitals. Given the prepandemic differences in trends in profitability, it is likely that the PHE funding had different effects on rural hospitals and urban hospitals.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This study uses 2015–2023 Medicare cost report data from acute-care hospitals to assess the impact of COVID-19 PHE funding on hospital profitability. We employ descriptive Kruskal–Wallis and chi-square tests and an interrupted time series analysis to evaluate the effect of PHE funding on operating margins for a stratified sample of rural prospective payment system (PPS), urban PPS, and critical access hospitals (CAHs).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We found that the PHE funding was associated with significant increases in operating margins, with rural PPS hospitals experiencing similar increases compared to urban PPS hospitals, and CAHs surpassing both rural and urban PPS hospitals in their margin values. However, if PHE funding had not been provided, our evidence suggests operating margins for all hospitals in 2022–2023 would have been below prepandemic levels.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>This preliminary analysis portrays the importance of the PHE government funding in supporting hospitals during the pandemic, and shows declining profitability trends without the funds. Rural PPS hospitals fare the worst suggesting continued need for financial support if the trend continues.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141857001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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