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The role of Medicaid home- and community-based services in use of Medicare post-acute care 医疗补助家庭和社区服务在使用医疗保险急性期后护理中的作用。
IF 3.1 2区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Pub Date : 2024-05-28 DOI: 10.1111/1475-6773.14325
Sijiu Wang PhD, Rachel M. Werner MD, PhD, Norma B. Coe PhD, Rhys Chua MPH, MscA, Mingyu Qi MS, R. Tamara Konetzka PhD

Objective

Medicaid-funded long-term services and supports are increasingly provided through home- and community-based services (HCBS) to promote continued community living. While an emerging body of evidence examines the direct benefits and costs of HCBS, there may also be unexplored synergies with Medicare-funded post-acute care (PAC). This study aimed to provide empirical evidence on how the use of Medicaid HCBS influences Medicare PAC utilization among the dually enrolled.

Data Sources

National Medicare claims, Medicaid claims, nursing home assessment data, and home health assessment data from 2016 to 2018.

Study Design

We estimated the relationship between prior Medicaid HCBS use and PAC (skilled nursing facilities [SNF] or home health) utilization in a national sample of duals with qualifying index hospitalizations. We used inverse probability weights to create balanced samples on observed characteristics and estimated multivariable regression with hospital fixed effects and extensive controls. We also conducted stratified analyses for key subgroups.

Data Extraction Methods

The primary sample included 887,598 hospital discharges from community-dwelling duals who had an eligible index hospitalization between April 1, 2016, and September 30, 2018.

Principal Findings

We found HCBS use was associated with a 9 percentage-point increase in the use of home health relative to SNF, conditional on using PAC, and a meaningful reduction in length of stay for those using SNF. In addition, in our primary sample, we found HCBS use to be associated with an overall increase in PAC use, given that the absolute increase in home health use was larger than the absolute decrease in SNF use. In other words, the use of Medicaid-funded HCBS was associated with a shift in Medicare-funded PAC use toward home-based settings.

Conclusion

Our findings indicate potential synergies between Medicaid-funded HCBS and increased use of home-based PAC, suggesting policymakers should cautiously consider these dynamics in HCBS expansion efforts.

目标:医疗补助计划(Medicaid)资助的长期服务和支持越来越多地通过家庭和社区服务(HCBS)来提供,以促进持续的社区生活。虽然越来越多的证据研究了以家庭和社区为基础的服务的直接效益和成本,但其与医疗补助计划(Medicare)资助的急性期后护理(PAC)之间的协同作用可能还未被发掘。本研究旨在提供实证证据,说明在双重参保者中,医疗补助 HCBS 的使用如何影响医疗保险 PAC 的使用:2016年至2018年的全国医疗保险索赔、医疗补助索赔、养老院评估数据和家庭健康评估数据:我们估算了具有合格指数住院的双重参保者的全国样本中,之前医疗补助 HCBS 使用情况与 PAC(专业护理设施 [SNF] 或家庭保健)使用情况之间的关系。我们使用反概率加权法创建了观察特征的平衡样本,并利用医院固定效应和广泛的控制措施进行了多变量回归估计。我们还对关键亚组进行了分层分析:主要样本包括在 2016 年 4 月 1 日至 2018 年 9 月 30 日期间符合条件的指数住院的 887,598 例社区居住的双职工出院病例:我们发现,在使用 PAC 的条件下,使用 HCBS 与使用 SNF 相比,家庭医疗的使用率增加了 9 个百分点,使用 SNF 的患者住院时间显著缩短。此外,在我们的主要样本中,我们发现 HCBS 的使用与 PAC 使用的整体增加有关,因为家庭医疗使用的绝对增幅大于 SNF 使用的绝对降幅。换句话说,使用医疗补助计划资助的 HCBS 与医疗保险计划资助的 PAC 向居家环境的转移有关:我们的研究结果表明,医疗补助资助的 HCBS 与居家 PAC 使用量的增加之间存在潜在的协同作用,这表明政策制定者在扩大 HCBS 时应谨慎考虑这些动态因素。
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引用次数: 0
"You want people to listen to you": Patient experiences of women's healthcare within the Veterans Health Administration. "你希望人们倾听你的心声":退伍军人健康管理局内妇女医疗保健的患者体验。
IF 3.4 2区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Pub Date : 2024-05-28 DOI: 10.1111/1475-6773.14324
Ashley C Mog, Samantha K Benson, Vyshnika Sriskantharajah, P Adam Kelly, Kristen E Gray, Lisa S Callegari, Ernest M Moy, Jodie G Katon

Objective: To identify constructs that are critical in shaping Veterans' experiences with Veterans Health Administration (VA) women's healthcare, including any which have been underexplored or are not included in current VA surveys of patient experience.

Data sources and study setting: From June 2022 to January 2023, we conducted 28 semi-structured interviews with a diverse, national sample of Veterans who use VA women's healthcare.

Study design: Using VA data, we divided Veteran VA-users identified as female into four groups stratified by age (dichotomized at age 45) and race/ethnicity (non-Hispanic White vs. all other). We enrolled Veterans continuously from each recruitment strata until thematic saturation was reached.

Data collection/extraction methods: For this qualitative study, we asked Veterans about past VA healthcare experiences. Interview questions were guided by a priori domains identified from review of the literature, including trust, safety, respect, privacy, communication and discrimination. Analysis occurred concurrently with interviews, using inductive and deductive content analysis.

Principal findings: We identified five themes influencing Veterans' experiences of VA women's healthcare: feeling valued and supported, bodily autonomy, discrimination, past military experiences and trauma, and accessible care. Each emergent theme was associated with multiple of the a priori domains we asked about in the interview guide.

Conclusions: Our findings underscore the need for a measure of patient experience tailored to VA women's healthcare. Existing patient experience measures used within VA fail to address several aspects of experience highlighted by our study, including bodily autonomy, the influence of past military experiences and trauma on healthcare, and discrimination. Understanding distinct factors that influence women and gender-diverse Veterans' experiences with VA care is critical to advance efforts by VA to measure and improve the quality and equity of care for all Veterans.

目标:确定对塑造退伍军人在退伍军人健康管理局(VA)女性医疗保健方面的体验至关重要的构建因素,包括尚未得到充分探索或未被纳入当前退伍军人健康管理局患者体验调查中的构建因素:从 2022 年 6 月到 2023 年 1 月,我们对使用退伍军人管理局女性医疗保健服务的退伍军人进行了 28 次半结构化访谈,访谈样本来自全国各地:利用退伍军人事务部的数据,我们将退伍军人事务部的女性用户按年龄(以 45 岁为二分法)和种族/族裔(非西班牙裔白人与所有其他族裔)分为四组。我们从每个招募分层中不断招募退伍军人,直到达到主题饱和为止:在这项定性研究中,我们向退伍军人询问了他们过去的退伍军人医疗保健经历。访谈问题以文献综述中确定的先验领域为指导,包括信任、安全、尊重、隐私、沟通和歧视。分析与访谈同时进行,采用归纳和演绎内容分析:我们确定了影响退伍军人对退伍军人妇女医疗保健体验的五个主题:感觉被重视和支持、身体自主、歧视、过去的从军经历和创伤以及可获得的护理。每个新出现的主题都与我们在访谈指南中询问的多个先验领域相关:我们的研究结果表明,有必要为退伍军人事务部的妇女医疗保健量身定制患者体验测量方法。退伍军人事务部内使用的现有患者体验测量方法未能解决我们的研究中强调的体验的几个方面,包括身体自主性、过去的从军经历和创伤对医疗保健的影响以及歧视。了解影响女性和不同性别退伍军人在退伍军人医疗保健方面体验的独特因素,对于推动退伍军人事务部衡量和改善所有退伍军人的医疗保健质量和公平性至关重要。
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引用次数: 0
The impact of Medicaid expansion on state expenditures through the COVID-19 era 在 COVID-19 时代,医疗补助扩展对各州支出的影响。
IF 3.1 2区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Pub Date : 2024-05-28 DOI: 10.1111/1475-6773.14331
Jenny Markell BA, Mark Katz Meiselbach PhD

Objective

To investigate the impact of Medicaid expansion on state expenditures through the end of 2022.

Data Sources

We used data from the National Association of State Budget Officers (NASBO)'s State Expenditure Report, Kaiser Family Foundation (KFF)'s Medicaid expansion tracker, US Bureau of Labor Statistics data (BLS), US Bureau of Economic Analysis data (BEA), and Pandemic Response Accountability Committee Oversight (PRAC).

Study Design

We investigated spending per capita (by state population) across seven budget categories, including Medicaid spending, and four spending sources. We performed a difference-in-differences (DiD) analysis that compared within-state changes in spending over time in expansion and nonexpansion states to estimate the effect of Medicaid expansion on state budgets. We adjusted for annual state unemployment rate, annual state per capita personal income, and state spending of Coronavirus Relief Funds (CRF) from 2020 to 2022 and included state and year fixed effects.

Data Collection/Extraction Methods

We linked annual state-level data on state-reported fiscal year expenditures from NASBO with state-level characteristics from BLS and BEA data and with CRF state spending from PRAC.

Principal Findings

Medicaid expansion was associated with an average increase of 21% (95% confidence interval [CI]: 16%–25%) in per capita Medicaid spending after Medicaid expansion among states that expanded prior to 2020. After inclusion of an interaction term to separate between the coronavirus disease (COVID) era (2020–2022) and the prior period following expansion (2015–2019), we found that although Medicaid expansion led to an average increase of 33% (95% CI: 21%–45%) in federal funding of state expenditures in the post-COVID years, it was not significantly associated with increased state spending.

Conclusions

There was no evidence of crowding out of other state expenditure categories or a substantial impact on total state spending, even in the COVID-19 era. Increased federal expenditures may have shielded states from substantial budgetary impacts.

目标:调查到 2022 年底医疗补助扩展对各州支出的影响:我们使用的数据来自全美州预算官员协会(NASBO)的州支出报告、凯撒家庭基金会(KFF)的医疗补助扩展跟踪器、美国劳工统计局(BLS)数据、美国经济分析局(BEA)数据以及大流行病应对问责委员会监督(PRAC):我们调查了包括医疗补助支出在内的七个预算类别和四个支出来源的人均支出(按州人口计算)。我们进行了差异分析(DiD),比较了扩展州和未扩展州的州内支出随时间的变化,以估计医疗补助扩展对州预算的影响。我们调整了州年度失业率、州年度人均个人收入以及 2020 年至 2022 年各州的冠状病毒救助基金(CRF)支出,并纳入了州和年份固定效应:我们将 NASBO 提供的各州上报财政年度支出的年度州级数据与 BLS 和 BEA 数据中的州级特征以及 PRAC 提供的 CRF 州级支出联系起来:在 2020 年之前扩大医疗补助范围的州中,扩大医疗补助范围后人均医疗补助支出平均增加 21%(95% 置信区间 [CI]:16%-25%)。在加入交互项以区分冠状病毒病(COVID)时代(2020-2022 年)和扩军后的前一时期(2015-2019 年)后,我们发现,虽然医疗补助扩军导致后 COVID 年联邦对各州支出的资助平均增加了 33%(95% 置信区间:21%-45%),但它与各州支出的增加并无显著关联:即使在 COVID-19 时代,也没有证据表明其他州支出类别被挤出或对州支出总额产生重大影响。联邦支出的增加可能使各州免受实质性预算影响。
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引用次数: 0
Trends in hospital price transparency after implementation of the CMS Final Rule CMS Final Rule 实施后医院价格透明度的趋势。
IF 3.1 2区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Pub Date : 2024-05-28 DOI: 10.1111/1475-6773.14329
Aaron Brant MD, Patrick Lewicki MD, Stephen Rhodes PhD, Alec Zhu MD, Jonathan Shoag MD

Objective

To assess trends in hospital price disclosures after the Centers for Medicare & Medicaid Services (CMS) Final Rule went into effect.

Data Sources and Study Setting

The Turquoise Health Price Transparency Dataset was used to identify all US hospitals that publicly displayed pricing from 2021 to 2023.

Study Design

Price-disclosing versus nondisclosing hospitals were compared using Pearson's Chi-squared and Wilcoxon rank sum tests. Bayesian structural time-series modeling was used to determine if enforcement of increased penalties for nondisclosure was associated with a change in the trend of hospital disclosures.

Data Collection/Extraction Methods

Not applicable.

Principal Findings

As of January 2023, 5162 of 6692 (77.1%) US hospitals disclosed pricing of their services, with the majority (2794 of 5162 [54.1%]) reporting their pricing within the first 6 months of the final rule going into effect in January 2021. An increase in hospital disclosures was observed after penalties for nondisclosure were enforced in January 2022 (relative effect size 20%, p = 0.002). Compared with nondisclosing hospitals, disclosing hospitals had higher annual revenue, bed number, and were more likely to be have nonprofit ownership, academic affiliation, provide emergency services, and be in highly concentrated markets (p < 0.001).

Conclusions

Hospital pricing disclosures are continuously in flux and influenced by regulatory and market factors.

目标:评估医疗保险与医疗补助服务中心(CMS)最终规则生效后医院价格披露的趋势:研究设计:使用皮尔逊卡方检验和Wilcoxon秩和检验对价格公开医院和不公开医院进行比较。贝叶斯结构时间序列模型用于确定对不披露行为加大处罚力度是否与医院披露趋势的变化有关:主要发现截至 2023 年 1 月,6692 家美国医院中有 5162 家(77.1%)披露了其服务定价,其中大多数医院(5162 家医院中有 2794 家[54.1%])在最终规则于 2021 年 1 月生效后的前 6 个月内报告了其定价。在 2022 年 1 月对未披露信息的医院实施处罚后,医院披露信息的数量有所增加(相对效应大小为 20%,P = 0.002)。与未披露信息的医院相比,披露信息的医院年收入更高、床位数更多,而且更有可能拥有非营利性所有权、与学术机构有关联、提供急诊服务并位于高度集中的市场中(P 结论):医院定价披露一直在变化,并受到监管和市场因素的影响。
{"title":"Trends in hospital price transparency after implementation of the CMS Final Rule","authors":"Aaron Brant MD,&nbsp;Patrick Lewicki MD,&nbsp;Stephen Rhodes PhD,&nbsp;Alec Zhu MD,&nbsp;Jonathan Shoag MD","doi":"10.1111/1475-6773.14329","DOIUrl":"10.1111/1475-6773.14329","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>To assess trends in hospital price disclosures after the Centers for Medicare &amp; Medicaid Services (CMS) Final Rule went into effect.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Data Sources and Study Setting</h3>\u0000 \u0000 <p>The Turquoise Health Price Transparency Dataset was used to identify all US hospitals that publicly displayed pricing from 2021 to 2023.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Study Design</h3>\u0000 \u0000 <p>Price-disclosing versus nondisclosing hospitals were compared using Pearson's Chi-squared and Wilcoxon rank sum tests. Bayesian structural time-series modeling was used to determine if enforcement of increased penalties for nondisclosure was associated with a change in the trend of hospital disclosures.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Data Collection/Extraction Methods</h3>\u0000 \u0000 <p>Not applicable.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Principal Findings</h3>\u0000 \u0000 <p>As of January 2023, 5162 of 6692 (77.1%) US hospitals disclosed pricing of their services, with the majority (2794 of 5162 [54.1%]) reporting their pricing within the first 6 months of the final rule going into effect in January 2021. An increase in hospital disclosures was observed after penalties for nondisclosure were enforced in January 2022 (relative effect size 20%, <i>p</i> = 0.002). Compared with nondisclosing hospitals, disclosing hospitals had higher annual revenue, bed number, and were more likely to be have nonprofit ownership, academic affiliation, provide emergency services, and be in highly concentrated markets (<i>p</i> &lt; 0.001).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Hospital pricing disclosures are continuously in flux and influenced by regulatory and market factors.</p>\u0000 </section>\u0000 </div>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":"59 4","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141157972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Association between claims-based setting of diagnosis and treatment initiation among Medicare patients with hepatitis C 医疗保险丙型肝炎患者中基于索赔的诊断与开始治疗之间的关系。
IF 3.1 2区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Pub Date : 2024-05-21 DOI: 10.1111/1475-6773.14330
Hao Zhang PhD, Yuhua Bao PhD, Kayla Hutchings MPH, Martin F. Shapiro MD PhD, Shashi N. Kapadia MD

Objective

To develop a claims-based algorithm to determine the setting of a disease diagnosis.

Data Sources and Study Setting

Medicare enrollment and claims data from 2014 to 2019.

Study Design

We developed a claims-based algorithm using facility indicators, revenue center codes, and place of service codes to identify settings where HCV diagnosis first appeared. When the first appearance was in a laboratory, we attempted to associate HCV diagnoses with subsequent clinical visits. Face validity was assessed by examining association of claims-based diagnostic settings with treatment initiation.

Data Collection/Extraction Methods

Patients newly diagnosed with HCV and continuously enrolled in traditional Medicare Parts A, B, and D (12 months before and 6 months after index diagnosis) were included.

Principal Findings

Among 104,454 patients aged 18–64 and 66,726 aged ≥65, 70.1% and 69%, respectively, were diagnosed in outpatient settings, and 20.2% and 22.7%, respectively in laboratory or unknown settings. Logistic regression revealed significantly lower odds of treatment initiation after diagnosis in emergency departments/urgent cares, hospitals, laboratories, or unclassified settings, than in outpatient visits.

Conclusions

The algorithm identified the setting of HCV diagnosis in most cases, and found significant associations with treatment initiation, suggesting an approach that can be adapted for future claims-based studies.

目的:开发一种基于索赔的算法,以确定疾病诊断的环境:开发一种基于理赔的算法,以确定疾病诊断的环境:研究设计:我们利用设施指标、收入中心代码和服务场所代码开发了一种基于理赔的算法,以确定首次出现 HCV 诊断的场所。当首次出现在实验室时,我们尝试将 HCV 诊断与随后的临床就诊联系起来。数据收集/提取方法:数据收集/提取方法:纳入新诊断为丙型肝炎病毒并连续参加传统医疗保险 A、B 和 D 部分的患者(诊断前 12 个月和诊断后 6 个月):在 104,454 名 18-64 岁和 66,726 名≥65 岁的患者中,分别有 70.1% 和 69% 是在门诊确诊的,20.2% 和 22.7% 是在实验室或未知场所确诊的。逻辑回归显示,在急诊科/急诊室、医院、实验室或未分类场所确诊后开始治疗的几率明显低于在门诊就诊的几率:该算法确定了大多数病例的 HCV 诊断环境,并发现了与开始治疗之间的重要关联,表明这种方法可用于未来基于索赔的研究。
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引用次数: 0
A structured approach to modifying an implementation package while scaling up a complex evidence-based practice 在推广复杂的循证实践的同时修改一揽子实施方案的结构化方法。
IF 3.1 2区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Pub Date : 2024-05-15 DOI: 10.1111/1475-6773.14313
Kristina M. Cordasco MD, MPH, MSHS, Sonya E. Gabrielian MD, MPH, Jenny Barnard BA, Taylor Harris PhD, MA, Erin P. Finley PhD, MPH
<div> <section> <h3> Objective</h3> <p>To describe <i>a</i> structured, iterative, data-driven approach for modifying implementation strategies for a complex evidence-based practice during a nationwide scale-up initiative.</p> </section> <section> <h3> Data Sources and Study Setting</h3> <p>We scaled-up implementation of Critical Time Intervention (CTI)—an evidence-based case management model—across 32 diverse community-based Veterans Affairs (VA) “Grant and Per Diem” case management (GPD-CM) agencies that serve homeless-experienced Veterans transitioning to independent living. Primary data were collected using qualitative methods.</p> </section> <section> <h3> Study Design</h3> <p>We embarked on a scale-up initiative while conducting a pragmatic randomized evaluation using a roll-out design, comparing two versions of a CTI implementation package tailored to VA's GPD-CM program. We iteratively assessed contextual factors and implementation outcomes (e.g., acceptability); findings informed package modifications that were characterized using the Framework for Reporting Adaptations and Modifications to Evidence-based Implementation Strategies.</p> </section> <section> <h3> Data Collection Methods</h3> <p>We conducted semi-structured interviews with Veterans, GPD-CM staff, and liaising VA clinicians; periodic reflections with liaising VA clinicians and implementation team members; and drew upon detailed meeting notes. We used rapid qualitative methods and content analysis to integrate data and characterize modifications.</p> </section> <section> <h3> Principal Findings</h3> <p>After each scale-up wave—in response to variations in agency-level characteristics— we made iterative modifications to the implementation package to increase CTI adoption and fidelity across the diverse contexts of our scale-up sites. Modifications included adding, deleting, integrating, and altering the package; core package components were preserved.</p> </section> <section> <h3> Conclusions</h3> <p>Implementation packages for complex evidence-based practices undergoing scale-up in diverse contexts may benefit from iterative modifications to optimize practice adoption with fidelity. We offer a structured, pragmatic approach for iteratively identifying data-driven, midstream implementation package adjustments, for use in both VA and non-VA scale-up initiatives. Our project demon
目的描述一种结构化的、迭代的、数据驱动的方法,用于在全国范围内推广一项复杂的循证实践时修改实施策略:我们在 32 个不同社区的退伍军人事务(VA)"补助金和按日补贴 "个案管理(GPD-CM)机构中扩大了关键时刻干预(CTI)--一种循证个案管理模式--的实施范围,这些机构为无家可归的退伍军人提供服务,帮助他们过渡到独立生活。研究设计:研究设计:我们开始了一项扩大规模的计划,同时采用推广设计进行了一项务实的随机评估,比较了为退伍军人事务部 GPD-CM 计划量身定制的两个版本的 CTI 实施方案。我们对背景因素和实施结果(如可接受性)进行了反复评估;评估结果为软件包的修改提供了依据,这些修改采用了 "基于证据的实施策略调整和修改报告框架":我们对退伍军人、GPD-CM 工作人员和负责联络的退伍军人事务部临床医生进行了半结构化访谈;与负责联络的退伍军人事务部临床医生和实施团队成员进行了定期反思;并参考了详细的会议记录。我们使用快速定性方法和内容分析来整合数据并描述修改的特点:在每一轮推广之后,我们都会根据机构层面的不同特点对实施方案进行反复修改,以提高 CTI 在推广地点不同环境中的采用率和忠实度。修改包括增加、删除、整合和改变一揽子方案;保留一揽子方案的核心内容:结论:在不同环境中推广复杂的循证实践的实施包可能会受益于反复的修改,以优化实践的忠实采用。我们提供了一种结构化的实用方法,用于迭代识别数据驱动的中游实施包调整,既可用于退伍军人事务部,也可用于非退伍军人事务部的推广计划。我们的项目证明了在推广计划中进行评估和修改的重要性,以及同时进行形成性评估和总结性评估的项目的利弊权衡。
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引用次数: 0
Connecting unstably housed veterans living in rural areas to health care: Perspectives from Health Care Navigators 将居住在农村地区、住房条件不稳定的退伍军人与医疗保健联系起来:医疗保健导航员的观点。
IF 3.1 2区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Pub Date : 2024-05-10 DOI: 10.1111/1475-6773.14316
Kalea Jones MS/SLP, MPH, CBIS, Meagan Cusack PhD, Gala True PhD, Taylor E. Harris PhD, Jill S. Roncarati ScD, MPH, PA-C, Christel Antonellis MSW, Tatiana Brecht BS, Ann Elizabeth Montgomery PhD
<div> <section> <h3> Objective</h3> <p>To understand existing care practices and policies, and potential enhancements, to improve the effectiveness of the US Department of Veterans Affairs (VA) Supportive Services for Veteran Families (SSVF) Health Care Navigators (HCN) in linking Veterans experiencing housing instability in rural areas with health care services.</p> </section> <section> <h3> Data Sources and Study Setting</h3> <p>We used primary data collected during semistructured interviews with HCNs (n = 21) serving rural areas across the United States during Spring 2022.</p> </section> <section> <h3> Study Design</h3> <p>We applied the Consolidated Framework for Implementation Research (CFIR) 2009 and the Social Ecological Model (SEM) to the collection and analysis of qualitative data to understand how HCNs administer services within SSVF and the larger community.</p> </section> <section> <h3> Data Collection/Extraction Methods</h3> <p>We used rapid qualitative methods to summarize and analyze data. Templated matrix summaries identified facilitators and barriers to linking Veterans with health care services and policy and practice implications.</p> </section> <section> <h3> Principal Findings</h3> <p>Using CFIR 2009, we identified contextual factors affecting successful implementation of HCN services within SSVF; we offer a crosswalk between CFIR 2009 and the version updated in 2022. Framing facilitators and barriers within the SEM provided insight into whether implementation strategies should be addressed at a community, interpersonal, or intrapersonal level within the SEM. Facilitators included sufficient knowledge, training, and mentorship opportunities for HCNs and their capacity to collaborate within their organization and with other community-based organizations. Barriers included lack of local technology and housing resources, inadequate understanding of Veterans' service eligibilities and pathways to access those services, and deficient collaboration with the VA.</p> </section> <section> <h3> Conclusions</h3> <p>Understanding facilitators and barriers experienced by HCN when linking unstably housed Veterans in rural areas with health care services can inform future strategies, including policy changes such as increased training to support HCNs' understanding of eligibility, benefits, and entitlements as well as improving communication
目标:了解现有的护理实践和政策以及潜在的改进措施,以提高美国退伍军人事务部(VA)退伍军人家庭支持服务(SSVF)医疗保健导航员(HCN)在将农村地区住房不稳定的退伍军人与医疗保健服务联系起来方面的有效性:我们使用了在 2022 年春季对服务于美国农村地区的 HCN(n = 21)进行半结构式访谈时收集的原始数据:研究设计:我们将 2009 年实施研究综合框架(CFIR)和社会生态模型(SEM)应用于定性数据的收集和分析,以了解 HCN 如何在 SSVF 和更大的社区内管理服务:我们采用快速定性方法总结和分析数据。模板矩阵摘要确定了退伍军人与医疗保健服务联系的促进因素和障碍,以及政策和实践影响:通过使用 2009 年退伍军人医疗保健信息报告,我们确定了影响在 SSVF 内成功实施 HCN 服务的背景因素;我们提供了 2009 年退伍军人医疗保健信息报告与 2022 年更新版本之间的对照表。将促进因素和障碍纳入 SEM,有助于深入了解实施策略应在 SEM 内的社区、人际或个人层面加以解决。促进因素包括为社区医疗网络提供充足的知识、培训和指导机会,以及他们在组织内部和与其他社区组织合作的能力。障碍包括缺乏当地技术和住房资源、对退伍军人的服务资格和获得这些服务的途径了解不足,以及与退伍军人事务部的合作不力:了解社区医疗网络在将农村地区住房不稳定的退伍军人与医疗保健服务联系起来时遇到的促进因素和障碍,可以为未来的策略提供参考,包括政策变化,如增加培训以支持社区医疗网络了解资格、福利和权利,以及改善退伍军人事务部和社区合作伙伴之间的沟通与合作。
{"title":"Connecting unstably housed veterans living in rural areas to health care: Perspectives from Health Care Navigators","authors":"Kalea Jones MS/SLP, MPH, CBIS,&nbsp;Meagan Cusack PhD,&nbsp;Gala True PhD,&nbsp;Taylor E. Harris PhD,&nbsp;Jill S. Roncarati ScD, MPH, PA-C,&nbsp;Christel Antonellis MSW,&nbsp;Tatiana Brecht BS,&nbsp;Ann Elizabeth Montgomery PhD","doi":"10.1111/1475-6773.14316","DOIUrl":"10.1111/1475-6773.14316","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Objective&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;To understand existing care practices and policies, and potential enhancements, to improve the effectiveness of the US Department of Veterans Affairs (VA) Supportive Services for Veteran Families (SSVF) Health Care Navigators (HCN) in linking Veterans experiencing housing instability in rural areas with health care services.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Data Sources and Study Setting&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;We used primary data collected during semistructured interviews with HCNs (n = 21) serving rural areas across the United States during Spring 2022.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Study Design&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;We applied the Consolidated Framework for Implementation Research (CFIR) 2009 and the Social Ecological Model (SEM) to the collection and analysis of qualitative data to understand how HCNs administer services within SSVF and the larger community.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Data Collection/Extraction Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;We used rapid qualitative methods to summarize and analyze data. Templated matrix summaries identified facilitators and barriers to linking Veterans with health care services and policy and practice implications.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Principal Findings&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Using CFIR 2009, we identified contextual factors affecting successful implementation of HCN services within SSVF; we offer a crosswalk between CFIR 2009 and the version updated in 2022. Framing facilitators and barriers within the SEM provided insight into whether implementation strategies should be addressed at a community, interpersonal, or intrapersonal level within the SEM. Facilitators included sufficient knowledge, training, and mentorship opportunities for HCNs and their capacity to collaborate within their organization and with other community-based organizations. Barriers included lack of local technology and housing resources, inadequate understanding of Veterans' service eligibilities and pathways to access those services, and deficient collaboration with the VA.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Conclusions&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Understanding facilitators and barriers experienced by HCN when linking unstably housed Veterans in rural areas with health care services can inform future strategies, including policy changes such as increased training to support HCNs' understanding of eligibility, benefits, and entitlements as well as improving communication ","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":"59 S2","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540570/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140900416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Quality improvement lessons learned from National Implementation of the “Patient Safety Events in Community Care: Reporting, Investigation, and Improvement Guidebook” 从全国实施 "社区医疗患者安全事件 "中吸取的质量改进经验教训:报告、调查和改进指南》。
IF 3.1 2区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Pub Date : 2024-05-08 DOI: 10.1111/1475-6773.14317
Jennifer L. Sullivan PhD, Marlena H. Shin JD, MPH, Jeffrey Chan BS, Michael Shwartz PhD, Edward J. Miech EdD, Ann M. Borzecki MD, MPH, Edward Yackel DNP, Sachin Yende MD, Amy K. Rosen PhD
<div> <section> <h3> Objective</h3> <p>To evaluate nationwide implementation of a Guidebook designed to standardize safety practices across VA-delivered and VA-purchased care (i.e., Community Care) and identify lessons learned and strategies to improve them.</p> </section> <section> <h3> Data Sources and Study Setting</h3> <p>Qualitative data collected from key informants at 18 geographically diverse VA facilities across 17 Veterans Integrated Services Networks (VISNs).</p> </section> <section> <h3> Study Design</h3> <p>We conducted semi-structured interviews from 2019 to 2022 with VISN Patient Safety Officers (PSOs) and VA facility patient safety and quality managers (PSMs and QMs) and VA Facility Community Care (CC) staff to assess lessons learned by examining organizational contextual factors affecting Guidebook implementation based on the Consolidated Framework for Implementation Research (CFIR).</p> </section> <section> <h3> Data Collection/Extraction Methods</h3> <p>Interviews were conducted virtually with 45 facility staff and 10 VISN PSOs. Using directed content analysis, we identified CFIR factors affecting implementation. These factors were mapped to the Expert Recommendations for Implementing Change (ERIC) strategy compilation to identify lessons learned that could be useful to our operational partners in improving implementation processes. We met frequently with our partners to discuss findings and plan next steps.</p> </section> <section> <h3> Principal Findings</h3> <p>Six CFIR constructs were identified as both facilitators and barriers to Guidebook implementation: (1) planning for implementation; (2) engaging key knowledge holders; (3) available resources; (4) networks and communications; (5) culture; and (6) external policies. The two CFIR constructs that were only barriers included: (1) cosmopolitanism and (2) executing implementation.</p> </section> <section> <h3> Conclusions</h3> <p>Our findings suggest several important lessons: (1) engage all collaborators involved in implementation; (2) ensure end-users have opportunities to provide feedback; (3) describe collaborators' purpose and roles/responsibilities clearly at the start; (4) communicate information widely and repeatedly; and (5) identify how multiple high priorities can be synergistic. This evaluation will help our partners and key VA leadership to determine next steps a
目标:评估《指南》在全国范围内的实施情况,该《指南》旨在规范退伍军人事务部提供的和退伍军人事务部购买的护理(即社区护理)的安全实践,并找出经验教训和改进策略:研究设计:研究设计:2019 年至 2022 年,我们对退伍军人综合服务网络(VISN)患者安全官员(PSO)、退伍军人设施患者安全和质量管理人员(PSM 和 QM)以及退伍军人设施社区护理(CC)工作人员进行了半结构化访谈,根据实施研究综合框架(CFIR)研究影响《指南》实施的组织背景因素,从而评估经验教训:我们与 45 名机构员工和 10 名 VISN PSO 进行了虚拟访谈。通过定向内容分析,我们确定了影响实施的 CFIR 因素。我们将这些因素与《实施变革的专家建议》(ERIC)战略汇编进行了映射,以确定可为我们的业务合作伙伴改进实施流程提供帮助的经验教训。我们经常与合作伙伴会面,讨论研究结果并计划下一步行动:我们确定了六个 CFIR 结构,它们既是《指南手册》实施的促进因素,也是障碍:(1) 实施规 划;(2) 关键知识持有者的参与;(3) 可用资源;(4) 网络和沟通;(5) 文化;(6) 外部政策。仅构成障碍的两个 CFIR 概念包括(结论:我们的研究结果提出了几条重要经验:(1) 让所有合作者参与实施工作;(2) 确保最终用户有机会提供反馈意见;(3) 在一开始就明确说明合作者的目的和作用/责任;(4) 广泛、反复地交流信息;(5) 确定多个高度优先事项如何能够协同增效。这项评估将帮助我们的合作伙伴和退伍军人事务部的主要领导层确定下一步措施和未来战略,以便通过与退伍军人事务部工作人员的合作改进《指南手册》的实施。
{"title":"Quality improvement lessons learned from National Implementation of the “Patient Safety Events in Community Care: Reporting, Investigation, and Improvement Guidebook”","authors":"Jennifer L. Sullivan PhD,&nbsp;Marlena H. Shin JD, MPH,&nbsp;Jeffrey Chan BS,&nbsp;Michael Shwartz PhD,&nbsp;Edward J. Miech EdD,&nbsp;Ann M. Borzecki MD, MPH,&nbsp;Edward Yackel DNP,&nbsp;Sachin Yende MD,&nbsp;Amy K. Rosen PhD","doi":"10.1111/1475-6773.14317","DOIUrl":"10.1111/1475-6773.14317","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Objective&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;To evaluate nationwide implementation of a Guidebook designed to standardize safety practices across VA-delivered and VA-purchased care (i.e., Community Care) and identify lessons learned and strategies to improve them.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Data Sources and Study Setting&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Qualitative data collected from key informants at 18 geographically diverse VA facilities across 17 Veterans Integrated Services Networks (VISNs).&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Study Design&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;We conducted semi-structured interviews from 2019 to 2022 with VISN Patient Safety Officers (PSOs) and VA facility patient safety and quality managers (PSMs and QMs) and VA Facility Community Care (CC) staff to assess lessons learned by examining organizational contextual factors affecting Guidebook implementation based on the Consolidated Framework for Implementation Research (CFIR).&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Data Collection/Extraction Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Interviews were conducted virtually with 45 facility staff and 10 VISN PSOs. Using directed content analysis, we identified CFIR factors affecting implementation. These factors were mapped to the Expert Recommendations for Implementing Change (ERIC) strategy compilation to identify lessons learned that could be useful to our operational partners in improving implementation processes. We met frequently with our partners to discuss findings and plan next steps.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Principal Findings&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Six CFIR constructs were identified as both facilitators and barriers to Guidebook implementation: (1) planning for implementation; (2) engaging key knowledge holders; (3) available resources; (4) networks and communications; (5) culture; and (6) external policies. The two CFIR constructs that were only barriers included: (1) cosmopolitanism and (2) executing implementation.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Conclusions&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Our findings suggest several important lessons: (1) engage all collaborators involved in implementation; (2) ensure end-users have opportunities to provide feedback; (3) describe collaborators' purpose and roles/responsibilities clearly at the start; (4) communicate information widely and repeatedly; and (5) identify how multiple high priorities can be synergistic. This evaluation will help our partners and key VA leadership to determine next steps a","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":"59 S2","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540575/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140892939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Impact of the Affordable Care Act on access to accredited facilities for cancer treatment 平价医疗法案》对使用经认证的癌症治疗设施的影响
IF 3.4 2区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Pub Date : 2024-05-03 DOI: 10.1111/1475-6773.14315
Lindsay M. Sabik, Youngmin Kwon, Coleman Drake, Jonathan Yabes, Manisha Bhattacharya, Zhaojun Sun, Cathy J. Bradley, Bruce L. Jacobs
ObjectiveTo examine differential changes in receipt of surgery at National Cancer Institute (NCI)‐designated comprehensive cancer centers (NCI‐CCC) and Commission on Cancer (CoC) accredited hospitals for patients with cancer more likely to be newly eligible for coverage under Affordable Care Act (ACA) insurance expansions, relative to those less likely to have been impacted by the ACA.Data Sources and Study SettingPennsylvania Cancer Registry (PCR) for 2010–2019 linked with discharge records from the Pennsylvania Health Care Cost Containment Council (PHC4).Study DesignOutcomes include whether cancer surgery was performed at an NCI‐CCC or a CoC‐accredited hospital. We conducted a difference‐in‐differences analysis, estimating linear probability models for each outcome that control for residence in a county with above median county‐level pre‐ACA uninsurance and the interaction between county‐level baseline uninsurance and cancer treatment post‐ACA to capture differential changes in access between those more and less likely to become newly eligible for insurance coverage (based on area‐level proxy). All models control for age, sex, race and ethnicity, cancer site and stage, census‐tract level urban/rural residence, Area Deprivation Index, and year‐ and county‐fixed effects.Data Collection/Extraction MethodsWe identified adults aged 26–64 in PCR with prostate, lung, or colorectal cancer who received cancer‐directed surgery and had a corresponding surgery discharge record in PHC4.Principal FindingsWe observe a differential increase in receiving care at an NCI‐CCC of 6.2 percentage points (95% CI: 2.6–9.8; baseline mean = 9.8%) among patients in high baseline uninsurance areas (p = 0.001). Our estimate of the differential change in care at the larger set of CoC hospitals is positive (3.9 percentage points [95% CI: −0.5‐8.2; baseline mean = 73.7%]) but not statistically significant (p = 0.079).ConclusionsOur findings suggest that insurance expansions under the ACA were associated with increased access to NCI‐CCCs.
目的研究在美国国家癌症研究所(NCI)指定的综合癌症中心(NCI-CCC)和癌症委员会(CoC)认可的医院接受手术的癌症患者与那些不太可能受到《可负担医疗法案》(ACA)影响的癌症患者之间的差异变化。数据来源和研究设置2010-2019 年宾夕法尼亚州癌症登记处(PCR)与宾夕法尼亚州医疗成本控制委员会(PHC4)的出院记录相链接。研究设计结果包括癌症手术是否在 NCI-CCC 或 CoC 认证医院进行。我们进行了差异分析,对每项结果的线性概率模型进行了估算,这些模型控制了居住在《美国反垄断法》实施前未参保县级中位数以上的县,以及县级基线未参保与《美国反垄断法》实施后癌症治疗之间的交互作用,以捕捉那些更有可能和更不可能获得新的保险覆盖资格(基于地区级代理)的人在获得保险覆盖方面的不同变化。所有模型都控制了年龄、性别、种族和民族、癌症部位和分期、人口普查区级城市/农村居住地、地区贫困指数以及年份和县固定效应。数据收集/提取方法我们在 PCR 中识别了 26-64 岁患有前列腺癌、肺癌或结直肠癌的成年人,他们接受了癌症导向手术,并且在 PHC4 中有相应的手术出院记录。主要研究结果我们发现,在基线未参保率较高地区的患者中,接受 NCI-CCC 治疗的患者人数增加了 6.2 个百分点(95% CI:2.6-9.8;基线平均值 = 9.8%)(p = 0.001)。我们对较大的 CoC 医院护理差异变化的估计为正值(3.9 个百分点 [95% CI:-0.5-8.2;基线平均值 = 73.7%]),但在统计上并不显著(p = 0.079)。
{"title":"Impact of the Affordable Care Act on access to accredited facilities for cancer treatment","authors":"Lindsay M. Sabik, Youngmin Kwon, Coleman Drake, Jonathan Yabes, Manisha Bhattacharya, Zhaojun Sun, Cathy J. Bradley, Bruce L. Jacobs","doi":"10.1111/1475-6773.14315","DOIUrl":"https://doi.org/10.1111/1475-6773.14315","url":null,"abstract":"ObjectiveTo examine differential changes in receipt of surgery at National Cancer Institute (NCI)‐designated comprehensive cancer centers (NCI‐CCC) and Commission on Cancer (CoC) accredited hospitals for patients with cancer more likely to be newly eligible for coverage under Affordable Care Act (ACA) insurance expansions, relative to those less likely to have been impacted by the ACA.Data Sources and Study SettingPennsylvania Cancer Registry (PCR) for 2010–2019 linked with discharge records from the Pennsylvania Health Care Cost Containment Council (PHC4).Study DesignOutcomes include whether cancer surgery was performed at an NCI‐CCC or a CoC‐accredited hospital. We conducted a difference‐in‐differences analysis, estimating linear probability models for each outcome that control for residence in a county with above median county‐level pre‐ACA uninsurance and the interaction between county‐level baseline uninsurance and cancer treatment post‐ACA to capture differential changes in access between those more and less likely to become newly eligible for insurance coverage (based on area‐level proxy). All models control for age, sex, race and ethnicity, cancer site and stage, census‐tract level urban/rural residence, Area Deprivation Index, and year‐ and county‐fixed effects.Data Collection/Extraction MethodsWe identified adults aged 26–64 in PCR with prostate, lung, or colorectal cancer who received cancer‐directed surgery and had a corresponding surgery discharge record in PHC4.Principal FindingsWe observe a differential increase in receiving care at an NCI‐CCC of 6.2 percentage points (95% CI: 2.6–9.8; baseline mean = 9.8%) among patients in high baseline uninsurance areas (<jats:italic>p</jats:italic> = 0.001). Our estimate of the differential change in care at the larger set of CoC hospitals is positive (3.9 percentage points [95% CI: −0.5‐8.2; baseline mean = 73.7%]) but not statistically significant (<jats:italic>p</jats:italic> = 0.079).ConclusionsOur findings suggest that insurance expansions under the ACA were associated with increased access to NCI‐CCCs.","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":"38 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140837958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Performance of health care service area definitions for capturing variation in inpatient care and social determinants of health 医疗保健服务区域定义在捕捉住院护理和健康社会决定因素差异方面的表现
IF 3.1 2区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Pub Date : 2024-05-02 DOI: 10.1111/1475-6773.14312
Hannah Crook BSPH, Manuel Horta MEd, Kenneth A. Michelson MD, MPH, John A. Graves PhD
<div> <section> <h3> Objective</h3> <p>To quantify the degree to which health care service area (HCSA) definitions captured hospitalizations and heterogeneity in social determinants of health (SDOH).</p> </section> <section> <h3> Data Sources and Study Setting</h3> <p>Geospatial data from the Centers for Medicare and Medicaid Services, the Census Bureau, and the Dartmouth Institute. Drive-time isochrones from MapBox. Area Deprivation Index (ADI) data. 2017 inpatient discharge data from Arizona, Florida, Iowa, Maryland, Nebraska, New Jersey, New York, and Wisconsin, State Emergency Department Databases and State Inpatient Databases, Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality; and Fee-For-Service Medicare data in 48 states.</p> </section> <section> <h3> Study Design</h3> <p>Cross-sectional, descriptive analysis.</p> </section> <section> <h3> Data Collection/Extraction Methods</h3> <p>The capture rate was the percentage of inpatient discharges occurring in the same HCSA as the hospital. We compared capture rates for each HCSA definition for different populations and by hospital type. We measured SDOH heterogeneity using the coefficient of variation of the ADI among ZIP codes within each HCSA.</p> </section> <section> <h3> Principal Findings</h3> <p>HCSA definitions captured a wide range of inpatient discharges, ranging from 20% to 50% for Public Use Microdata Areas (PUMAs) to 93%–97% for Metropolitan Statistical Areas (MSAs). Three-quarters of inpatient discharges were from facilities within the same county as the patient's residential ZIP code, while nearly two-thirds were within the same Hospital Service Area. From the hospital perspective, 74.7% of inpatient discharges originated from within a 30-min drive and 90.1% within a 60-min drive. Capture rates were the lowest for teaching hospitals. PUMAs and drive-time-based HCSAs encompassed more homogenous populations while MSAs, Commuting Zones, and Hospital Referral Regions captured the most variation.</p> </section> <section> <h3> Conclusions</h3> <p>The proportion of hospital discharges captured by each HCSA varied, with MSAs capturing the highest proportion of discharges and PUMAs capturing the lowest. Additionally, researchers face a trade-off between capture rate and population homogeneity when deciding which HCSA to use.</p> </section>
目标量化医疗保健服务区 (HCSA) 的定义在多大程度上反映了住院情况以及健康的社会决定因素 (SDOH) 的异质性。数据来源和研究背景地理空间数据来自医疗保险和医疗补助服务中心、人口普查局和达特茅斯研究所。驾车时间等时线来自 MapBox。地区贫困指数(ADI)数据。来自亚利桑那州、佛罗里达州、爱荷华州、马里兰州、内布拉斯加州、新泽西州、纽约州和威斯康星州的 2017 年住院病人出院数据、州急诊科数据库和州住院病人数据库、医疗保健成本与利用项目、医疗保健研究与质量局;以及 48 个州的收费服务医疗保险数据。我们比较了不同人群和不同医院类型的每种 HCSA 定义的捕获率。我们使用每个 HCSA 内各邮政编码之间 ADI 的变异系数来衡量 SDOH 的异质性。主要研究结果HCSA 定义捕获的住院病人出院率范围很广,从公共使用微数据区 (PUMA) 的 20% 到 50% 到大都会统计区 (MSA) 的 93% 到 97%。四分之三的住院病人出院来自与病人居住地邮政编码相同的县内机构,近三分之二的住院病人出院来自相同的医院服务区。从医院角度来看,74.7% 的住院病人出院来自 30 分钟车程内的医院,90.1% 来自 60 分钟车程内的医院。教学医院的捕获率最低。PUMAs和基于车程的HCSAs涵盖的人口更为单一,而MSAs、通勤区和医院转诊区捕获的差异最大。此外,研究人员在决定使用哪个 HCSA 时,需要在捕获率和人口同质性之间进行权衡。
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Health Services Research
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