Mary Christensen PhD, Stacey Culp PhD, John V. Campo MD, Jeffrey A. Bridge PhD, Lisa Horowitz PhD
Purpose
This study evaluated psychometric properties of the Ask Suicide-Screening Questions (ASQ) and Item Nine of the Patient Health Questionnaire (PHQ Item 9) to detect suicide risk in rural adult primary care and whether pain and opioid screening contributed to suicide risk detection.
Methods
A sample of adult rural primary care patients (N = 214) completed suicide risk, pain, and opioid screening measures electronically; 48% of participants also completed a follow-up survey. Using the Adult Suicidal Ideation Questionnaire (ASIQ) as the criterion measure, psychometric properties for the ASQ and the PHQ Item 9 were compared using McNemar's test for proportions. Bivariate and multivariable regression analyses explored associations between suicide risk, pain, opioid measures, and ASIQ results.
Findings
Approximately 4% (N = 8) of participants screened positive for suicide risk on the ASIQ relative to 11.7% (N = 25) on the ASQ and 3.7% (N = 8) on the PHQ Item 9. The ASQ had higher sensitivity (75.0%) than the PHQ Item 9 (50.0%); the difference was not statistically significant but may have clinical relevance. The PHQ Item 9 had significantly higher specificity (98.1%) than the full ASQ (91.0%, p < 0.001). The ASQ, PHQ Item 9, depression scores, and LGBTQ+ status were significant predictors of ASIQ scores. Pain and opioid misuse were not.
Conclusions
Findings from this small sample provide preliminary support for the ASQ and PHQ Item 9 as suicide risk screens in rural adult primary care, but psychometric studies in larger samples are needed.
{"title":"Evaluation of the Ask Suicide-Screening Questions (ASQ) tool, Item 9 of the Patient Health Questionnaire (PHQ), pain, and opioid screening to detect suicide risk among rural adult primary care patients","authors":"Mary Christensen PhD, Stacey Culp PhD, John V. Campo MD, Jeffrey A. Bridge PhD, Lisa Horowitz PhD","doi":"10.1111/jrh.70064","DOIUrl":"https://doi.org/10.1111/jrh.70064","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This study evaluated psychometric properties of the Ask Suicide-Screening Questions (ASQ) and Item Nine of the Patient Health Questionnaire (PHQ Item 9) to detect suicide risk in rural adult primary care and whether pain and opioid screening contributed to suicide risk detection.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A sample of adult rural primary care patients (<i>N</i> = 214) completed suicide risk, pain, and opioid screening measures electronically; 48% of participants also completed a follow-up survey. Using the Adult Suicidal Ideation Questionnaire (ASIQ) as the criterion measure, psychometric properties for the ASQ and the PHQ Item 9 were compared using McNemar's test for proportions. Bivariate and multivariable regression analyses explored associations between suicide risk, pain, opioid measures, and ASIQ results.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Approximately 4% (<i>N</i> = 8) of participants screened positive for suicide risk on the ASIQ relative to 11.7% (<i>N</i> = 25) on the ASQ and 3.7% (<i>N</i> = 8) on the PHQ Item 9. The ASQ had higher sensitivity (75.0%) than the PHQ Item 9 (50.0%); the difference was not statistically significant but may have clinical relevance. The PHQ Item 9 had significantly higher specificity (98.1%) than the full ASQ (91.0%, <i>p</i> < 0.001). The ASQ, PHQ Item 9, depression scores, and LGBTQ+ status were significant predictors of ASIQ scores. Pain and opioid misuse were not.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Findings from this small sample provide preliminary support for the ASQ and PHQ Item 9 as suicide risk screens in rural adult primary care, but psychometric studies in larger samples are needed.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144751527","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}
Micah A. Skeens PhD, Adelaide Booze BA, Mark Ranalli MD, Anna Olsavsky PhD
Purpose
Children with cancer experience significant symptom burden, worsened by social deprivation. This study examines social determinants of health, including Appalachian residency, influence on symptom burden.
Methods
Caregiver-child dyads were recruited within 1 year of cancer treatment. Addresses were coded for social determinants of health (SDOH) measures: Area Deprivation Index (ADI), rurality, medically underserved areas (MUA), and Appalachian residency. Total child symptom scores (0–31) were calculated for dyad reports using the Memorial Symptom Assessment Scale. Provider matching symptom reports were extracted from electronic medical records. Descriptive statistics and correlations examined associations between child, caregiver, and provider symptom reports and SDOH. Significant correlations informed three multiple linear regression models examining SDOH predictors of child symptoms by reporter.
Findings
Fifty-five caregiver-child dyads were recruited. Caregivers were 65.5% female and 87.3% White. Children were 50.9% male, 85% White, an average of 12 years old, 30.9% rural, and 20.0% Appalachian. ADI scores (M = 4.22) indicated moderate disadvantage, and 14.5% were medically underserved. On average, children reported 8.61 symptoms, while caregivers reported 7.15, and providers recorded 1.87 child symptoms. For children, a bivariate association and significant regression model revealed Appalachian children experienced a higher number of symptoms. For caregivers, bivariate associations indicated a higher ADI was associated with more symptoms. For providers, bivariate associations revealed higher symptoms were associated with rurality, MUA, and Appalachian residency, though only Appalachian residency remained significant in the regression model.
Conclusions
Results suggest Appalachian residency is associated with higher symptom burden for children with cancer. Findings support culturally sensitive care to minimize symptom burden.
{"title":"Understanding the influence of social determinants of health on symptom reporting in pediatric cancer","authors":"Micah A. Skeens PhD, Adelaide Booze BA, Mark Ranalli MD, Anna Olsavsky PhD","doi":"10.1111/jrh.70071","DOIUrl":"https://doi.org/10.1111/jrh.70071","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>Children with cancer experience significant symptom burden, worsened by social deprivation. This study examines social determinants of health, including Appalachian residency, influence on symptom burden.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Caregiver-child dyads were recruited within 1 year of cancer treatment. Addresses were coded for social determinants of health (SDOH) measures: Area Deprivation Index (ADI), rurality, medically underserved areas (MUA), and Appalachian residency. Total child symptom scores (0–31) were calculated for dyad reports using the Memorial Symptom Assessment Scale. Provider matching symptom reports were extracted from electronic medical records. Descriptive statistics and correlations examined associations between child, caregiver, and provider symptom reports and SDOH. Significant correlations informed three multiple linear regression models examining SDOH predictors of child symptoms by reporter.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Fifty-five caregiver-child dyads were recruited. Caregivers were 65.5% female and 87.3% White. Children were 50.9% male, 85% White, an average of 12 years old, 30.9% rural, and 20.0% Appalachian. ADI scores (<i>M</i> = 4.22) indicated moderate disadvantage, and 14.5% were medically underserved. On average, children reported 8.61 symptoms, while caregivers reported 7.15, and providers recorded 1.87 child symptoms. For children, a bivariate association and significant regression model revealed Appalachian children experienced a higher number of symptoms. For caregivers, bivariate associations indicated a higher ADI was associated with more symptoms. For providers, bivariate associations revealed higher symptoms were associated with rurality, MUA, and Appalachian residency, though only Appalachian residency remained significant in the regression model.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Results suggest Appalachian residency is associated with higher symptom burden for children with cancer. Findings support culturally sensitive care to minimize symptom burden.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jrh.70071","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758585","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}
Whitney E. Zahnd PhD, Jason T. Semprini PhD, MPP, Robin C. Vanderpool DrPH, Sarah H. Nash PhD, MPH, Erin L. Van Blarigan ScD, Mindy C. DeRouen PhD, MPH, Angela L. W. Meisner MPH, Chuck Wiggins PhD
Purpose
To evaluate pandemic-related changes in cancer-related care for cancer survivors residing in nonmetropolitan and metropolitan areas.
Methods
We used data from the Health Information National Trends-Surveillance Epidemiology End Results (HINTS-SEER) survey administered to cancer survivors from the Greater San Francisco Bay Area, Iowa, and New Mexico between January and August 2021. Respondents were queried on changes to their cancer-related care, including treatment, follow-up appointments, and routine cancer screening/preventive care. We calculated weighted percentages and Rao-Scott chi-square tests for reported differences between nonmetropolitan and metropolitan areas.
Findings
Compared to survivors residing in metropolitan areas, a higher proportion of those in nonmetropolitan areas reported that their cancer treatment or follow-up appointments were unaffected by the pandemic (38.6% vs 28.1%; P = .008). Survivors in metropolitan areas experienced more of a shift in cancer treatment or follow-up appointments to telehealth (12.5% vs 5.7%, P = .003), but there was no difference in appointment cancellations. More survivors residing in metropolitan versus nonmetropolitan areas reported shifts to telehealth for preventive care (8.2% vs 2.9%, P = .005). There was no difference across nonmetropolitan and metropolitan survivors reporting that cancer-related care was cancelled, that routine cancer screening or preventive care was unaffected by the pandemic, or that providers discussed COVID-19 risks.
Conclusions
Survivors in nonmetropolitan compared to metropolitan areas had less perceived change in cancer follow-up and treatment schedules. It will be important to assess whether shifts in follow-up and preventive care to telehealth for cancer survivors in need of care during the COVID-19 pandemic affect their long-term outcomes.
目的评价居住在非大都市和大都市地区的癌症幸存者的癌症相关护理的大流行相关变化。方法：我们使用来自2021年1月至8月期间来自大旧金山湾区、爱荷华州和新墨西哥州的癌症幸存者的健康信息国家趋势监测流行病学最终结果（HINTS-SEER）调查的数据。受访者被问及他们癌症相关护理的变化，包括治疗、随访预约和常规癌症筛查/预防护理。我们计算加权百分比和Rao-Scott卡方检验非大都市和大都市地区之间报告的差异。与居住在大都市地区的幸存者相比，居住在非大都市地区的幸存者报告说，他们的癌症治疗或随访预约不受疫情影响的比例更高(38.6%比28.1%；P = .008)。大都市地区的幸存者在癌症治疗或随访预约方面更多地转向远程医疗（12.5% vs 5.7%, P = 0.003），但预约取消方面没有差异。居住在大都市地区的幸存者比居住在非大都市地区的幸存者报告转向远程医疗进行预防性护理（8.2%对2.9%,P = 0.005）。非大都市和大都市幸存者报告的癌症相关护理被取消、常规癌症筛查或预防性护理不受大流行影响、提供者讨论COVID-19风险的情况没有差异。结论：与大都市地区相比，非大都市地区的幸存者在癌症随访和治疗计划方面的变化较小。重要的是评估在COVID-19大流行期间需要护理的癌症幸存者的后续和预防性护理转向远程医疗是否会影响其长期预后。
{"title":"Metropolitan/nonmetropolitan differences of the impact of COVID-19 on cancer survivors' care","authors":"Whitney E. Zahnd PhD, Jason T. Semprini PhD, MPP, Robin C. Vanderpool DrPH, Sarah H. Nash PhD, MPH, Erin L. Van Blarigan ScD, Mindy C. DeRouen PhD, MPH, Angela L. W. Meisner MPH, Chuck Wiggins PhD","doi":"10.1111/jrh.70061","DOIUrl":"https://doi.org/10.1111/jrh.70061","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To evaluate pandemic-related changes in cancer-related care for cancer survivors residing in nonmetropolitan and metropolitan areas.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We used data from the Health Information National Trends-Surveillance Epidemiology End Results (HINTS-SEER) survey administered to cancer survivors from the Greater San Francisco Bay Area, Iowa, and New Mexico between January and August 2021. Respondents were queried on changes to their cancer-related care, including treatment, follow-up appointments, and routine cancer screening/preventive care. We calculated weighted percentages and Rao-Scott chi-square tests for reported differences between nonmetropolitan and metropolitan areas.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Compared to survivors residing in metropolitan areas, a higher proportion of those in nonmetropolitan areas reported that their cancer treatment or follow-up appointments were unaffected by the pandemic (38.6% vs 28.1%; <i>P</i> = .008). Survivors in metropolitan areas experienced more of a shift in cancer treatment or follow-up appointments to telehealth (12.5% vs 5.7%, <i>P</i> = .003), but there was no difference in appointment cancellations. More survivors residing in metropolitan versus nonmetropolitan areas reported shifts to telehealth for preventive care (8.2% vs 2.9%, <i>P</i> = .005). There was no difference across nonmetropolitan and metropolitan survivors reporting that cancer-related care was cancelled, that routine cancer screening or preventive care was unaffected by the pandemic, or that providers discussed COVID-19 risks.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Survivors in nonmetropolitan compared to metropolitan areas had less perceived change in cancer follow-up and treatment schedules. It will be important to assess whether shifts in follow-up and preventive care to telehealth for cancer survivors in need of care during the COVID-19 pandemic affect their long-term outcomes.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jrh.70061","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144740115","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}
Ryan J. Crowley MPhil, Jag S. Lally MPhil, David M. Kline PhD, Amanda M. Bunting PhD
Purpose
To assess county-level and specialty-level age differences between urban and rural physicians.
Methods
We linked the 2008–2021 Medicare Data on Provider Practice and Specialty (MD-PPAS) dataset with the 2024 Doctors and Clinicians national downloadable file. We assessed specialty-level differences in the age of rural versus urban physicians using Rural–Urban Continuum Codes (RUCC) with four groups: urban (RUCC 1–3), large rural (RUCC 4–5), small rural (RUCC 6–7), and isolated rural (RUCC 8–9). We analyzed the relationship between rurality and physician age using choropleth graphs, spatial clustering, and univariable regression.
Findings
Our final cohort comprised 571,886 physicians. The mean ages of physicians were higher in rural counties (large rural: 53.1 years; small rural: 53.3 years; isolated rural: 53.5 years) than urban counties (52.5 years; p value <0.001). Some specialties including medical oncology, palliative care, and thoracic surgery showed particularly large age differences with older physicians in more rural areas. There were clusters of older physicians in the South and clusters of younger physicians in the Mountain West and Midwest. Rurality was strongly associated with clusters of older physicians (odds ratio [OR]: 3.8; 95% confidence interval [CI], 2.6–5.5), and the percentage of households with broadband internet subscription was strongly associated with clusters of younger physicians (OR: 2.6; 95% CI, 2.2–3.0).
Conclusions
Rural physicians were older than urban physicians with certain specialties and regions demonstrating large age disparities. The aging of rural physicians could worsen existing urban–rural health care disparities. Initiatives focusing on recruiting and retaining rural physicians should target specific regions and specialties to ameliorate these inequities.
{"title":"Urban–rural differences in the age of US physicians","authors":"Ryan J. Crowley MPhil, Jag S. Lally MPhil, David M. Kline PhD, Amanda M. Bunting PhD","doi":"10.1111/jrh.70054","DOIUrl":"https://doi.org/10.1111/jrh.70054","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To assess county-level and specialty-level age differences between urban and rural physicians.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We linked the 2008–2021 Medicare Data on Provider Practice and Specialty (MD-PPAS) dataset with the 2024 Doctors and Clinicians national downloadable file. We assessed specialty-level differences in the age of rural versus urban physicians using Rural–Urban Continuum Codes (RUCC) with four groups: urban (RUCC 1–3), large rural (RUCC 4–5), small rural (RUCC 6–7), and isolated rural (RUCC 8–9). We analyzed the relationship between rurality and physician age using choropleth graphs, spatial clustering, and univariable regression.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Our final cohort comprised 571,886 physicians. The mean ages of physicians were higher in rural counties (large rural: 53.1 years; small rural: 53.3 years; isolated rural: 53.5 years) than urban counties (52.5 years; <i>p</i> value <0.001). Some specialties including medical oncology, palliative care, and thoracic surgery showed particularly large age differences with older physicians in more rural areas. There were clusters of older physicians in the South and clusters of younger physicians in the Mountain West and Midwest. Rurality was strongly associated with clusters of older physicians (odds ratio [OR]: 3.8; 95% confidence interval [CI], 2.6–5.5), and the percentage of households with broadband internet subscription was strongly associated with clusters of younger physicians (OR: 2.6; 95% CI, 2.2–3.0).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Rural physicians were older than urban physicians with certain specialties and regions demonstrating large age disparities. The aging of rural physicians could worsen existing urban–rural health care disparities. Initiatives focusing on recruiting and retaining rural physicians should target specific regions and specialties to ameliorate these inequities.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144725611","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}
Saleema A. Karim MHA, MBA, PhD, Nathan W. Carroll PhD, Paula H. Song PhD, Adam Atherly PhD
Purpose
Rural hospitals struggling with prepandemic financial instability faced heightened challenges during COVID-19. While Provider Relief Funds (PRFs) offered essential support, their impact varied, highlighting the need to examine how prepandemic financial health influenced rural hospitals’ financial performance during the pandemic. This study evaluates PRF's role across three hospital categories: financially strained (low operating margin), financially vulnerable (midrange operating margin), and financially strong (high operating margin).
Methods
A cohort study with a pre–post research design analyzed 2243 US rural hospitals from 2017 to 2022. The sample included short-term general acute nonfederal hospitals and Critical Access Hospitals in nonmetropolitan counties and rural tracts within metropolitan counties. Financial health was assessed using operating margin measures and total margins with and without PRF across four time periods: pre-COVID-19 (2017–2019), COVID-19 Year 1 (2020), Year 2 (2021), and Year 3 (2022).
Findings
Financially strained and vulnerable hospitals represented 85% of rural hospitals. Financially strained hospitals had the lowest average operating margins from patient services (−17.36%), trailing financially vulnerable (−3.09%), and financially strong (8.04%). In COVID-19 Year 1, operating margins declined across all categories. PRF increased total margins for financially strained hospitals to 8.39% in 2021 before dropping to 0.76% in 2022. Financially vulnerable hospitals also benefited, while financially strong hospitals remained profitable even without PRF.
Conclusion
PRF played a critical role in stabilizing rural hospitals, mitigating financial declines, and preventing closures. Its expiration leaves many hospitals facing renewed financial pressures. Addressing long-term financial challenges through sustainable funding strategies and operational adaptations will be essential to preserving health care access in rural communities.
{"title":"Financial resilience of rural hospitals: Prepandemic vulnerabilities and Provider Relief Funds’ role during COVID-19","authors":"Saleema A. Karim MHA, MBA, PhD, Nathan W. Carroll PhD, Paula H. Song PhD, Adam Atherly PhD","doi":"10.1111/jrh.70060","DOIUrl":"https://doi.org/10.1111/jrh.70060","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>Rural hospitals struggling with prepandemic financial instability faced heightened challenges during COVID-19. While Provider Relief Funds (PRFs) offered essential support, their impact varied, highlighting the need to examine how prepandemic financial health influenced rural hospitals’ financial performance during the pandemic. This study evaluates PRF's role across three hospital categories: financially strained (low operating margin), financially vulnerable (midrange operating margin), and financially strong (high operating margin).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A cohort study with a pre–post research design analyzed 2243 US rural hospitals from 2017 to 2022. The sample included short-term general acute nonfederal hospitals and Critical Access Hospitals in nonmetropolitan counties and rural tracts within metropolitan counties. Financial health was assessed using operating margin measures and total margins with and without PRF across four time periods: pre-COVID-19 (2017–2019), COVID-19 Year 1 (2020), Year 2 (2021), and Year 3 (2022).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Financially strained and vulnerable hospitals represented 85% of rural hospitals. Financially strained hospitals had the lowest average operating margins from patient services (−17.36%), trailing financially vulnerable (−3.09%), and financially strong (8.04%). In COVID-19 Year 1, operating margins declined across all categories. PRF increased total margins for financially strained hospitals to 8.39% in 2021 before dropping to 0.76% in 2022. Financially vulnerable hospitals also benefited, while financially strong hospitals remained profitable even without PRF.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>PRF played a critical role in stabilizing rural hospitals, mitigating financial declines, and preventing closures. Its expiration leaves many hospitals facing renewed financial pressures. Addressing long-term financial challenges through sustainable funding strategies and operational adaptations will be essential to preserving health care access in rural communities.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 3","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144687986","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}
Gregory N. Orewa PhD, MBA, MSc, Rohit Pradhan PhD, MPA, Akbar Ghiasi PhD, Shivani Gupta PhD, MBA, Robert Weech-Maldonado PhD, MBA
Purpose
The financial sustainability of nursing homes is increasingly critical as the aging US population continues to grow. Rural facilities often encounter more significant economic challenges than urban counterparts. This study investigates the disparities in financial performance between rural and urban nursing homes in the United States, emphasizing the influence of organizational and environmental factors. A comprehensive understanding of these differences is necessary for the implementation of effective policy and management interventions.
Methods
The study used a longitudinal dataset (2018–2022) comprising 66,056 nursing home-year observations. Data sources included Centers for Medicare and Medicaid Services (CMS) Cost Reports, Payroll-Based Journal, Care Compare, LTCFocus, and the Area Health Resource File. The dependent variable was the operating margin. The primary independent variable, geographic location, was classified using Rural–Urban Commuting Area (RUCA) codes. We conducted multivariable linear regression with facility-level random effects and two-way fixed effects (state and year) to assess rural–urban financial disparities while controlling for organizational and environmental factors and the impact of COVID-19.
Findings
Rural nursing homes had lower operating margins than urban facilities in unadjusted models. However, after adjusting for organizational factors such as size, occupancy, and payer mix, the rural–urban difference was no longer significant. Environmental factors, including population demographics and income levels, contributed to financial disparities. COVID-19 exacerbated financial challenges, disproportionately affecting rural facilities.
Conclusions
Financial disparities between rural and urban nursing homes are not solely due to geographical location, but also stem from structural challenges. These insights have significant policy implications suggesting that addressing reimbursement rates, operational efficiency, and resource allocation is crucial to ensure the financial sustainability and quality care for aging populations.
{"title":"Financial performance of rural and urban nursing homes: A comparative analysis","authors":"Gregory N. Orewa PhD, MBA, MSc, Rohit Pradhan PhD, MPA, Akbar Ghiasi PhD, Shivani Gupta PhD, MBA, Robert Weech-Maldonado PhD, MBA","doi":"10.1111/jrh.70053","DOIUrl":"https://doi.org/10.1111/jrh.70053","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>The financial sustainability of nursing homes is increasingly critical as the aging US population continues to grow. Rural facilities often encounter more significant economic challenges than urban counterparts. This study investigates the disparities in financial performance between rural and urban nursing homes in the United States, emphasizing the influence of organizational and environmental factors. A comprehensive understanding of these differences is necessary for the implementation of effective policy and management interventions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The study used a longitudinal dataset (2018–2022) comprising 66,056 nursing home-year observations. Data sources included Centers for Medicare and Medicaid Services (CMS) Cost Reports, Payroll-Based Journal, Care Compare, LTCFocus, and the Area Health Resource File. The dependent variable was the operating margin. The primary independent variable, geographic location, was classified using Rural–Urban Commuting Area (RUCA) codes. We conducted multivariable linear regression with facility-level random effects and two-way fixed effects (state and year) to assess rural–urban financial disparities while controlling for organizational and environmental factors and the impact of COVID-19.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Rural nursing homes had lower operating margins than urban facilities in unadjusted models. However, after adjusting for organizational factors such as size, occupancy, and payer mix, the rural–urban difference was no longer significant. Environmental factors, including population demographics and income levels, contributed to financial disparities. COVID-19 exacerbated financial challenges, disproportionately affecting rural facilities.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Financial disparities between rural and urban nursing homes are not solely due to geographical location, but also stem from structural challenges. These insights have significant policy implications suggesting that addressing reimbursement rates, operational efficiency, and resource allocation is crucial to ensure the financial sustainability and quality care for aging populations.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 3","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jrh.70053","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144681156","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}
Tara Stiller PhD, MPH, Anna Charlotta Kihlstrom MPH, Nishat Sultana , Grace Njau PhD, Matthew Schmidt MPH, Anastasia Stepanov , Andrew D. Williams PhD, MPH
Background
In North Dakota (ND), American Indian (AI) women face a persistent disparity in prenatal care (PNC) access compared to other women. During the COVID pandemic, the expansion of telehealth emerged as a potential solution to disparate access to health care. We examined whether telehealth use mitigated disparities in PNC in ND.
Methods
Data were drawn from the 2020 to 2021 ND Pregnancy Risk Assessment Monitoring System (weighted n = 10,189). PNC initiation >13 weeks gestation or not receiving PNC was considered “late/no PNC.” Maternal race/ethnicity was self-reported. Use of telehealth for prenatal visits was self-reported and categorized as “any telehealth use” versus “no telehealth use.” Those not using telehealth self-reported eight barriers to telehealth (e.g., lacking internet, no appointments). Logistic regression estimated odds ratios (ORs) and 95% confidence intervals (CIs) for late/no PNC among AI and other race/ethnicity women compared to White women. Models included maternal sociodemographic and health factors. Chi-square was used to examine prevalence of telehealth barriers by race/ethnicity.
Results
Compared to White women, AI/AN women were twice as likely to receive late/no PNC (OR: 2.40; 95% CI, 1.08, 5.35). When telehealth was accounted for, the AI–White disparity was lowered by only 2% (OR: 2.35; 95% CI, 1.05, 5.26). Compared to White and other race/ethnicity women, a higher prevalence of AI/AN women reported a lack of telehealth appointments (p < 0.01), no computers (p < 0.01), no phones (p < 0.01), and no physical space (p < 0.01) as barriers to telehealth.
Discussion
The use of telehealth did not mitigate PNC disparities in ND. Infrastructure investments and culturally safe initiatives are needed to improve PNC access for AI/AN women.
{"title":"Use of telehealth did not mitigate persistent disparities in prenatal care access among American Indian women in North Dakota","authors":"Tara Stiller PhD, MPH, Anna Charlotta Kihlstrom MPH, Nishat Sultana , Grace Njau PhD, Matthew Schmidt MPH, Anastasia Stepanov , Andrew D. Williams PhD, MPH","doi":"10.1111/jrh.70056","DOIUrl":"https://doi.org/10.1111/jrh.70056","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>In North Dakota (ND), American Indian (AI) women face a persistent disparity in prenatal care (PNC) access compared to other women. During the COVID pandemic, the expansion of telehealth emerged as a potential solution to disparate access to health care. We examined whether telehealth use mitigated disparities in PNC in ND.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Data were drawn from the 2020 to 2021 ND Pregnancy Risk Assessment Monitoring System (weighted <i>n</i> = 10,189). PNC initiation >13 weeks gestation or not receiving PNC was considered “late/no PNC.” Maternal race/ethnicity was self-reported. Use of telehealth for prenatal visits was self-reported and categorized as “any telehealth use” versus “no telehealth use.” Those not using telehealth self-reported eight barriers to telehealth (e.g., lacking internet, no appointments). Logistic regression estimated odds ratios (ORs) and 95% confidence intervals (CIs) for late/no PNC among AI and other race/ethnicity women compared to White women. Models included maternal sociodemographic and health factors. Chi-square was used to examine prevalence of telehealth barriers by race/ethnicity.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Compared to White women, AI/AN women were twice as likely to receive late/no PNC (OR: 2.40; 95% CI, 1.08, 5.35). When telehealth was accounted for, the AI–White disparity was lowered by only 2% (OR: 2.35; 95% CI, 1.05, 5.26). Compared to White and other race/ethnicity women, a higher prevalence of AI/AN women reported a lack of telehealth appointments (<i>p</i> < 0.01), no computers (<i>p</i> < 0.01), no phones (<i>p</i> < 0.01), and no physical space (<i>p</i> < 0.01) as barriers to telehealth.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>The use of telehealth did not mitigate PNC disparities in ND. Infrastructure investments and culturally safe initiatives are needed to improve PNC access for AI/AN women.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 3","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144673028","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}
Maxime Inghels PhD, David Nelson PhD, Ros Kane PhD, Mark Gussy PhD, Carl Deaney MD
Purpose
To investigate how rurality shapes individual care pathways and health outcomes for depression and to investigate the sociodemographic and economic relationships with urban-rural variations.
Methods
A retrospective cohort study using routinely collected data from adult patients diagnosed for depression and registered at a general practice in Lincolnshire in the UK. Access and time to access from the onset of depression symptoms to the following care pathway states were described (ie, access to a depression screening tool, confirmed diagnosis, access to treatment and outcomes). Multistate survival analyses were conducted to investigate the effect of the patient's living environment (rural/urban, index of multiple deprivation) on progression through their care pathway for depression.
Findings
Overall, 1,111 patients with depression were included. While access to depression services were lower for patients living in rural areas, they were more likely to experience positive depression outcomes, and more quickly, compared to their urban counterparts. Controlled depression and relapse rates were, respectively, 29% lower and 31% higher among urban residents. The level of deprivation was found to have a limited effect on care access, as well as on depression outcomes.
Conclusion
While accessing care services remains a challenge in rural areas, our study highlights the potential benefits of the rural context in improving depression outcomes and lowering relapse risk. Area-based deprivation had minimal impact on both care access and depression outcomes. Future mental health programs must tailor their strategies to the unique challenges of urban and rural environments to facilitate more effective interventions.
{"title":"Impact of rural-urban residence and deprivation on care pathways for depression disorders among adults in the UK","authors":"Maxime Inghels PhD, David Nelson PhD, Ros Kane PhD, Mark Gussy PhD, Carl Deaney MD","doi":"10.1111/jrh.70055","DOIUrl":"https://doi.org/10.1111/jrh.70055","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To investigate how rurality shapes individual care pathways and health outcomes for depression and to investigate the sociodemographic and economic relationships with urban-rural variations.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A retrospective cohort study using routinely collected data from adult patients diagnosed for depression and registered at a general practice in Lincolnshire in the UK. Access and time to access from the onset of depression symptoms to the following care pathway states were described (ie, access to a depression screening tool, confirmed diagnosis, access to treatment and outcomes). Multistate survival analyses were conducted to investigate the effect of the patient's living environment (rural/urban, index of multiple deprivation) on progression through their care pathway for depression.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Overall, 1,111 patients with depression were included. While access to depression services were lower for patients living in rural areas, they were more likely to experience positive depression outcomes, and more quickly, compared to their urban counterparts. Controlled depression and relapse rates were, respectively, 29% lower and 31% higher among urban residents. The level of deprivation was found to have a limited effect on care access, as well as on depression outcomes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>While accessing care services remains a challenge in rural areas, our study highlights the potential benefits of the rural context in improving depression outcomes and lowering relapse risk. Area-based deprivation had minimal impact on both care access and depression outcomes. Future mental health programs must tailor their strategies to the unique challenges of urban and rural environments to facilitate more effective interventions.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 3","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jrh.70055","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144666289","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}
Casey P Balio PhD, Olivia A Sullivan DrPH, MPH, EMT, E Grace Petty BBA, Benjamin Pelton MPH, RT(R), Nathan Dockery MPH, Kate E Beatty PhD, MPH
Purpose
Area-level vulnerability and resilience indices combine multiple dimensions of demographic, economic, and environmental factors into a single measure of area-level risk. These indices are widely used to allocate resources in health care and public health. We investigated how commonly used, existing area-level indices correlate with each other, and how they differ by geography, comparing rural and urban areas.
Methods
Seven publicly available indices were selected for inclusion. Rurality was defined by Rural-Urban Continuum Codes and/or Rural-Urban Commuting Areas, depending on the geographic level of each index. Percentiles were obtained or calculated for each index and compared by rurality.
Findings
We find that these area-level indices are not substitutes for each other, and they differ significantly across the rural-urban continuum in conflicting ways. Three different patterns generally emerged from analysis: indices that increase as geography becomes more rural; indices that decrease as geography becomes more rural; and indices with the greatest values among middle levels of geography.
Conclusions
Findings from this work underscore the importance of better understanding how area-level indices may differ across the United States and by specific populations. When using area-level indices in policy and resource allocation, strategic selection and implementation considering differences by rurality may be warranted.
{"title":"An assessment of area-level vulnerability and resilience indices by geography: A rural-urban comparison","authors":"Casey P Balio PhD, Olivia A Sullivan DrPH, MPH, EMT, E Grace Petty BBA, Benjamin Pelton MPH, RT(R), Nathan Dockery MPH, Kate E Beatty PhD, MPH","doi":"10.1111/jrh.70059","DOIUrl":"https://doi.org/10.1111/jrh.70059","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>Area-level vulnerability and resilience indices combine multiple dimensions of demographic, economic, and environmental factors into a single measure of area-level risk. These indices are widely used to allocate resources in health care and public health. We investigated how commonly used, existing area-level indices correlate with each other, and how they differ by geography, comparing rural and urban areas.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Seven publicly available indices were selected for inclusion. Rurality was defined by Rural-Urban Continuum Codes and/or Rural-Urban Commuting Areas, depending on the geographic level of each index. Percentiles were obtained or calculated for each index and compared by rurality.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>We find that these area-level indices are not substitutes for each other, and they differ significantly across the rural-urban continuum in conflicting ways. Three different patterns generally emerged from analysis: indices that increase as geography becomes more rural; indices that decrease as geography becomes more rural; and indices with the greatest values among middle levels of geography.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Findings from this work underscore the importance of better understanding how area-level indices may differ across the United States and by specific populations. When using area-level indices in policy and resource allocation, strategic selection and implementation considering differences by rurality may be warranted.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 3","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144666290","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}
This systematic review examines the profound impact of health information technology (HIT) on critical access hospitals (CAHs), focusing on the persistent challenges hindering effective implementation and utilization, and their consequences for rural health care.
Methods
Following Primary Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, we systematically searched ProQuest, Web of Science, Scopus, and MEDLINE (2000–2024) for peer-reviewed articles, screening titles, abstracts, and full texts.
Results
Forty-five studies were included, with a majority (n = 31) published post-Health Information Technology for Economic and Clinical Health (HITECH) Act. Analysis revealed recurring challenges: crippling financial constraints, persistent staffing shortages, and frustrating interoperability failures. Diverse methodologies, including statistical analyses, surveys, case studies, and interviews, underscored the pervasive nature of these issues.
Discussion
Beyond financial, human, and interoperability barriers, our review identified key themes related to organizational dynamics and network effects. We discuss critical policy implications, offer actionable recommendations, acknowledge study limitations, and highlight crucial directions for future research.
Conclusion
This review provides compelling evidence of the urgent need to address the unique HIT adoption challenges facing CAHs. By understanding these barriers and leveraging HIT's potential, we can significantly improve patient care and health equity in vulnerable rural communities. These findings are critical for policymakers, health care leaders, and researchers striving to strengthen rural health care delivery.
目的本系统综述探讨了卫生信息技术（HIT）对关键通道医院（CAHs）的深远影响，重点关注阻碍有效实施和利用的持续挑战及其对农村卫生保健的影响。方法按照PRISMA （Primary Reporting Items for Systematic Reviews and Meta-Analysis）指南，系统检索ProQuest、Web of Science、Scopus和MEDLINE(2000-2024)，检索同行评议文章、筛选标题、摘要和全文。结果纳入45项研究，其中大多数（n = 31）发表了《卫生信息技术促进经济和临床健康（HITECH）法案》。分析揭示了反复出现的挑战：严重的财务限制、持续的人员短缺和令人沮丧的互操作性失败。各种方法，包括统计分析、调查、案例研究和访谈，都强调了这些问题的普遍性。除了财务、人力和互操作性障碍之外，我们的综述确定了与组织动力学和网络效应相关的关键主题。我们讨论关键的政策影响，提供可行的建议，承认研究的局限性，并强调未来研究的关键方向。本综述提供了令人信服的证据，表明迫切需要解决卫生保健机构面临的独特的采用卫生保健技术的挑战。通过了解这些障碍并利用HIT的潜力，我们可以显著改善脆弱农村社区的患者护理和卫生公平。这些发现对决策者、卫生保健领导者和努力加强农村卫生保健服务的研究人员至关重要。
{"title":"Health information technology in rural health care: A systematic review of its impact on critical access hospitals","authors":"Dinesh R. Pai PhD","doi":"10.1111/jrh.70052","DOIUrl":"https://doi.org/10.1111/jrh.70052","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>This systematic review examines the profound impact of health information technology (HIT) on critical access hospitals (CAHs), focusing on the persistent challenges hindering effective implementation and utilization, and their consequences for rural health care.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Following Primary Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, we systematically searched ProQuest, Web of Science, Scopus, and MEDLINE (2000–2024) for peer-reviewed articles, screening titles, abstracts, and full texts.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Forty-five studies were included, with a majority (<i>n</i> = 31) published post-Health Information Technology for Economic and Clinical Health (HITECH) Act. Analysis revealed recurring challenges: crippling financial constraints, persistent staffing shortages, and frustrating interoperability failures. Diverse methodologies, including statistical analyses, surveys, case studies, and interviews, underscored the pervasive nature of these issues.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>Beyond financial, human, and interoperability barriers, our review identified key themes related to organizational dynamics and network effects. We discuss critical policy implications, offer actionable recommendations, acknowledge study limitations, and highlight crucial directions for future research.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>This review provides compelling evidence of the urgent need to address the unique HIT adoption challenges facing CAHs. By understanding these barriers and leveraging HIT's potential, we can significantly improve patient care and health equity in vulnerable rural communities. These findings are critical for policymakers, health care leaders, and researchers striving to strengthen rural health care delivery.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"41 3","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144647651","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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