Objective: To understand why American Indian and Alaskan Native (AIAN) populations have had exceptionally high COVID-19 mortality, we compare patterns of healthcare utilization and outcomes for two serious infectious respiratory diseases-Influenza-like-illness (ILI) and coronavirus disease 2019 (COVID-19)-between American Indian and Alaskan Native (AIAN) populations (as identified in Medicaid data) and non-Hispanic Whites over the 2009-2021 period.
Study setting and design: We select all people under the age of 65 years identified as non-Hispanic White or AIAN in the New York State Medicaid claims data between 2009 and 2021. We analyze data across 10 ILI cohorts (between September 2009 and August 2020) and 4 COVID-19 cohorts (March-June 2020, July-September 2020, October-December 2020, and January-June 2021). We examine mortality and utilization rates using logistic regressions, adjusting for demographic characteristics, prior chronic conditions, and geographic location (including residence near a reservation). We stratify the analysis by rural vs. nonrural counties.
Data sources and analytic sample: We use the New York State Medicaid claims data for the analysis.
Principal findings: We find that even among Medicaid beneficiaries, who are similar in socioeconomic status and identical in health insurance coverage, AIAN populations have much lower rates of use of outpatient services and much higher rates of acute (inpatient and emergency room) service utilization for both ILI and COVID-19 than non-Hispanic Whites. Prior to COVID-19, demographic and health status-adjusted all-cause mortality rates, including from ILI, were lower among American Indians than among non-Hispanic Whites on New York State Medicaid, but this pattern reversed during the COVID-19 pandemic. Both findings are driven by nonrural counties. We did not observe significant differences in all-cause mortality and acute service utilization comparing AIAN to non-Hispanic Whites in rural areas.
Conclusion: The utilization and mortality disparities we identify within the Medicaid population highlight the need to move beyond insurance in addressing poor health outcomes in the American Indian population.
{"title":"Disparities in infectious disease-related health care utilization between Medicaid-enrolled American Indians and non-Hispanic Whites-Lessons from the first 16 months of coronavirus disease 2019 and a decade of flu seasons.","authors":"Scarlett Sijia Wang, Randall Akee, Emilia Simeonova, Sherry Glied","doi":"10.1111/1475-6773.14389","DOIUrl":"https://doi.org/10.1111/1475-6773.14389","url":null,"abstract":"<p><strong>Objective: </strong>To understand why American Indian and Alaskan Native (AIAN) populations have had exceptionally high COVID-19 mortality, we compare patterns of healthcare utilization and outcomes for two serious infectious respiratory diseases-Influenza-like-illness (ILI) and coronavirus disease 2019 (COVID-19)-between American Indian and Alaskan Native (AIAN) populations (as identified in Medicaid data) and non-Hispanic Whites over the 2009-2021 period.</p><p><strong>Study setting and design: </strong>We select all people under the age of 65 years identified as non-Hispanic White or AIAN in the New York State Medicaid claims data between 2009 and 2021. We analyze data across 10 ILI cohorts (between September 2009 and August 2020) and 4 COVID-19 cohorts (March-June 2020, July-September 2020, October-December 2020, and January-June 2021). We examine mortality and utilization rates using logistic regressions, adjusting for demographic characteristics, prior chronic conditions, and geographic location (including residence near a reservation). We stratify the analysis by rural vs. nonrural counties.</p><p><strong>Data sources and analytic sample: </strong>We use the New York State Medicaid claims data for the analysis.</p><p><strong>Principal findings: </strong>We find that even among Medicaid beneficiaries, who are similar in socioeconomic status and identical in health insurance coverage, AIAN populations have much lower rates of use of outpatient services and much higher rates of acute (inpatient and emergency room) service utilization for both ILI and COVID-19 than non-Hispanic Whites. Prior to COVID-19, demographic and health status-adjusted all-cause mortality rates, including from ILI, were lower among American Indians than among non-Hispanic Whites on New York State Medicaid, but this pattern reversed during the COVID-19 pandemic. Both findings are driven by nonrural counties. We did not observe significant differences in all-cause mortality and acute service utilization comparing AIAN to non-Hispanic Whites in rural areas.</p><p><strong>Conclusion: </strong>The utilization and mortality disparities we identify within the Medicaid population highlight the need to move beyond insurance in addressing poor health outcomes in the American Indian population.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142402054","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}
Sungchul Park, David J Meyers, Yubin Park, Amal N Trivedi
Objective: To examine differences in access to care and financial burden between Traditional Medicare (TM) and Medicare Advantage (MA) beneficiaries in rural and urban areas and then explore whether there were potential differences in MA benefits between urban and rural areas.
Study setting and design: We conducted a cross-sectional study within the Medicare setting in the United States.
Data sources and analytical sample: Data from three distinct sources for 2017-2021: the Medicare Current Beneficiary Survey, the MA landscape data, and the Plan Benefit Package data. Our sample comprised 43,343 Medicare beneficiary-years, including TM and MA beneficiaries in urban and rural areas.
Principal findings: Our adjusted analysis showed that rural MA beneficiaries experienced higher rates of delayed care due to costs (10.0% [95% confidence interval (CI): 8.8-11.1]) compared with rural TM (9.5% [8.8-10.2]), urban MA (7.9% [7.4-8.4]), and urban TM (7.9% [7.5-8.2]) beneficiaries. Similarly, rural MA beneficiaries (11.4% [95% CI: 10.3-12.5]) reported more difficulty paying medical bills compared with rural TM (9.4% [8.7-10.1]), urban MA (8.1% [7.7-8.6]), and urban TM (7.8% [7.5-8.2]) beneficiaries. This disparity was associated with less generous financial structures in rural MA plans. Compared to urban MA plans, rural MA plans offered lower out-of-pocket maximums for in-network care ($5918 vs. $5439), but required higher copayments ($1686 vs. $1724 for a 5-day hospitalization, $37 vs. $41 for a specialist visit, and $35 vs. $38 for a mental health visit). However, differences in quality of care and provision of supplemental benefits were small.
Conclusion: Rural Medicare beneficiaries reported a greater financial burden of care than urban Medicare beneficiaries, but the most significant burden was observed among MA beneficiaries in rural areas. One possible mechanism could be the less generous financial structures offered by rural MA plans. These findings suggest the need for policies addressing the affordability of care for rural MA beneficiaries.
{"title":"Financial burden of care greatest among rural beneficiaries in Medicare advantage.","authors":"Sungchul Park, David J Meyers, Yubin Park, Amal N Trivedi","doi":"10.1111/1475-6773.14393","DOIUrl":"https://doi.org/10.1111/1475-6773.14393","url":null,"abstract":"<p><strong>Objective: </strong>To examine differences in access to care and financial burden between Traditional Medicare (TM) and Medicare Advantage (MA) beneficiaries in rural and urban areas and then explore whether there were potential differences in MA benefits between urban and rural areas.</p><p><strong>Study setting and design: </strong>We conducted a cross-sectional study within the Medicare setting in the United States.</p><p><strong>Data sources and analytical sample: </strong>Data from three distinct sources for 2017-2021: the Medicare Current Beneficiary Survey, the MA landscape data, and the Plan Benefit Package data. Our sample comprised 43,343 Medicare beneficiary-years, including TM and MA beneficiaries in urban and rural areas.</p><p><strong>Principal findings: </strong>Our adjusted analysis showed that rural MA beneficiaries experienced higher rates of delayed care due to costs (10.0% [95% confidence interval (CI): 8.8-11.1]) compared with rural TM (9.5% [8.8-10.2]), urban MA (7.9% [7.4-8.4]), and urban TM (7.9% [7.5-8.2]) beneficiaries. Similarly, rural MA beneficiaries (11.4% [95% CI: 10.3-12.5]) reported more difficulty paying medical bills compared with rural TM (9.4% [8.7-10.1]), urban MA (8.1% [7.7-8.6]), and urban TM (7.8% [7.5-8.2]) beneficiaries. This disparity was associated with less generous financial structures in rural MA plans. Compared to urban MA plans, rural MA plans offered lower out-of-pocket maximums for in-network care ($5918 vs. $5439), but required higher copayments ($1686 vs. $1724 for a 5-day hospitalization, $37 vs. $41 for a specialist visit, and $35 vs. $38 for a mental health visit). However, differences in quality of care and provision of supplemental benefits were small.</p><p><strong>Conclusion: </strong>Rural Medicare beneficiaries reported a greater financial burden of care than urban Medicare beneficiaries, but the most significant burden was observed among MA beneficiaries in rural areas. One possible mechanism could be the less generous financial structures offered by rural MA plans. These findings suggest the need for policies addressing the affordability of care for rural MA beneficiaries.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142395427","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}
Objective: To estimate differences in facility-level outcomes between nursing homes which reached Institutional Special Needs Plan (I-SNP) maturity and those which never cared for I-SNP enrollees.
Study setting and design: We used a difference-in-differences design to estimate the effect of I-SNP maturity, defined as having at least 33.75% of Medicare long-stayers in the nursing home enrolled in any I-SNP. Our main outcome was the hospitalization rate in each nursing home-year. Secondary outcomes included the share of residents with medication use, fall, urinary tract infection, catheter insertion, pressure ulcer, physical restraint use, increased need for help with activities of daily living (ADLs), and mortality.
Data sources and analytic sample: This repeated cross-sectional study used 100% Medicare claims, Minimum Data Set assessments, and publicly available Medicare Advantage (MA) plan characteristics data (2004-2021). We included all MA beneficiaries who resided in US nursing homes which reached I-SNP maturity and those without I-SNP enrollees.
Principal findings: We identified 2530 nursing homes which reached I-SNP maturity (treated) and 9830 nursing homes without I-SNP enrollees (untreated). There were some differences observed between these nursing homes, including shares of residents who were White (76.42% vs. 84.84%) and on Medicaid (66.94% vs. 55.45%). These nursing homes were also larger on average (141.76 beds vs. 87.56 beds). From the difference-in-differences model, nursing homes which reached I-SNP maturity experienced declines of 4.1 percentage points (pp) for hospitalizations, 1.0 pp for pressure ulcers, 1.3 pp for urinary tract infections (p < 0.001) alongside increases in the need for help with ADLs, use of antipsychotics, falls, and physical restraints.
Conclusions: Nursing homes which reached I-SNP maturity experienced fewer hospitalizations and pressure ulcers but a decline in function and increase in other negative outcomes. I-SNPs may be a promising model to improve care for long-stay residents, but more research is needed to understand potential adverse consequences.
{"title":"A model to increase care delivery in nursing homes: The role of Institutional Special Needs Plans.","authors":"Amanda C Chen, David C Grabowski","doi":"10.1111/1475-6773.14390","DOIUrl":"https://doi.org/10.1111/1475-6773.14390","url":null,"abstract":"<p><strong>Objective: </strong>To estimate differences in facility-level outcomes between nursing homes which reached Institutional Special Needs Plan (I-SNP) maturity and those which never cared for I-SNP enrollees.</p><p><strong>Study setting and design: </strong>We used a difference-in-differences design to estimate the effect of I-SNP maturity, defined as having at least 33.75% of Medicare long-stayers in the nursing home enrolled in any I-SNP. Our main outcome was the hospitalization rate in each nursing home-year. Secondary outcomes included the share of residents with medication use, fall, urinary tract infection, catheter insertion, pressure ulcer, physical restraint use, increased need for help with activities of daily living (ADLs), and mortality.</p><p><strong>Data sources and analytic sample: </strong>This repeated cross-sectional study used 100% Medicare claims, Minimum Data Set assessments, and publicly available Medicare Advantage (MA) plan characteristics data (2004-2021). We included all MA beneficiaries who resided in US nursing homes which reached I-SNP maturity and those without I-SNP enrollees.</p><p><strong>Principal findings: </strong>We identified 2530 nursing homes which reached I-SNP maturity (treated) and 9830 nursing homes without I-SNP enrollees (untreated). There were some differences observed between these nursing homes, including shares of residents who were White (76.42% vs. 84.84%) and on Medicaid (66.94% vs. 55.45%). These nursing homes were also larger on average (141.76 beds vs. 87.56 beds). From the difference-in-differences model, nursing homes which reached I-SNP maturity experienced declines of 4.1 percentage points (pp) for hospitalizations, 1.0 pp for pressure ulcers, 1.3 pp for urinary tract infections (p < 0.001) alongside increases in the need for help with ADLs, use of antipsychotics, falls, and physical restraints.</p><p><strong>Conclusions: </strong>Nursing homes which reached I-SNP maturity experienced fewer hospitalizations and pressure ulcers but a decline in function and increase in other negative outcomes. I-SNPs may be a promising model to improve care for long-stay residents, but more research is needed to understand potential adverse consequences.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142395426","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}
Rendelle E Bolton, Eduardo R Núñez, Jacqueline Boudreau, Lauren M Kearney, Samantha K Ryan, Abigail Herbst, Christopher Slatore, Renda Soylemez Wiener
Objective: To examine how lung cancer screening (LCS) is coordinated across healthcare systems, specifically Veterans Affairs (VA) and non-VA settings.
Data sources and study setting: We conducted primary qualitative data collection in six VA medical centers with established LCS programs from November 2020 to November 2021.
Study design and data collection methods: Semi-structured interviews were conducted with 48 primary care providers, LCS program coordinators and directors, and pulmonologists. Thematic analysis examined spontaneously raised narratives related to initiating and coordinating LCS for Veterans screened in non-VA settings. We mapped coordination challenges to each step of the LCS care continuum.
Principal findings: While non-VA options increased access to LCS for Veterans, VA medical centers lacked clear processes for initiating LCS referrals and tracking Veterans across the LCS continuum when screening occurred in non-VA settings. The responsibility of coordinating LCS with community providers often fell to VA primary care providers rather than LCS programs. Gaps in communication and data transfer contributed to delayed evaluation of potentially cancerous nodules post-screening, raising concerns about compromised care quality when LCS was shared with non-VA settings.
Conclusions: While policies expanding LCS for Veterans in non-VA settings increase access, lack of consistent processes to initiate referrals, obtain results, and promote timely downstream evaluation fragmented care and delayed evaluation of concerning nodules. These unintended consequences highlight a need to address cross-system coordination challenges. Strategies to better coordinate LCS between VA and non-VA settings are essential to achieve high quality LCS and prevent Veterans from falling through the cracks.
{"title":"\"We don't get that information right back to us unless it's a full-blown cancer\": Challenges coordinating lung cancer screening across healthcare systems.","authors":"Rendelle E Bolton, Eduardo R Núñez, Jacqueline Boudreau, Lauren M Kearney, Samantha K Ryan, Abigail Herbst, Christopher Slatore, Renda Soylemez Wiener","doi":"10.1111/1475-6773.14384","DOIUrl":"https://doi.org/10.1111/1475-6773.14384","url":null,"abstract":"<p><strong>Objective: </strong>To examine how lung cancer screening (LCS) is coordinated across healthcare systems, specifically Veterans Affairs (VA) and non-VA settings.</p><p><strong>Data sources and study setting: </strong>We conducted primary qualitative data collection in six VA medical centers with established LCS programs from November 2020 to November 2021.</p><p><strong>Study design and data collection methods: </strong>Semi-structured interviews were conducted with 48 primary care providers, LCS program coordinators and directors, and pulmonologists. Thematic analysis examined spontaneously raised narratives related to initiating and coordinating LCS for Veterans screened in non-VA settings. We mapped coordination challenges to each step of the LCS care continuum.</p><p><strong>Principal findings: </strong>While non-VA options increased access to LCS for Veterans, VA medical centers lacked clear processes for initiating LCS referrals and tracking Veterans across the LCS continuum when screening occurred in non-VA settings. The responsibility of coordinating LCS with community providers often fell to VA primary care providers rather than LCS programs. Gaps in communication and data transfer contributed to delayed evaluation of potentially cancerous nodules post-screening, raising concerns about compromised care quality when LCS was shared with non-VA settings.</p><p><strong>Conclusions: </strong>While policies expanding LCS for Veterans in non-VA settings increase access, lack of consistent processes to initiate referrals, obtain results, and promote timely downstream evaluation fragmented care and delayed evaluation of concerning nodules. These unintended consequences highlight a need to address cross-system coordination challenges. Strategies to better coordinate LCS between VA and non-VA settings are essential to achieve high quality LCS and prevent Veterans from falling through the cracks.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142395425","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}
Nicholas Bowden, Aaron Hedquist, Dannie Dai, Olukorede Abiona, Enrique Bernal-Delgado, Carl Rudolf Blankart, Julie Cartailler, Francisco Estupiñán-Romero, Philip Haywood, Zeynep Or, Irene Papanicolas, Mai Stafford, Steven Wyatt, Reijo Sund, Jean Pierre Uwitonze, Walter P Wodchis, Robin Gauld, Hien Vu, Tania Sawaya, Jose F Figueroa
<p><strong>Objective: </strong>To explore variation in rates of acute care utilization for mental health conditions, including hospitalizations and emergency department (ED) visits, across high-income countries before and during the COVID-19 pandemic.</p><p><strong>Data sources and study setting: </strong>Administrative patient-level data between 2017 and 2020 of eight high-income countries: Canada, England, Finland, France, New Zealand, Spain, Switzerland, and the United States (US).</p><p><strong>Study design: </strong>Multi-country retrospective observational study using a federated data approach that evaluated age-sex standardized rates of hospitalizations and ED visits for mental health conditions.</p><p><strong>Principal findings: </strong>There was significant variation in rates of acute mental health care utilization across countries. Among the subset of four countries with both hospitalization and ED data, the US had the highest pre-COVID-19 combined average annual acute care rate of 1613 episodes/100,000 people (95% CI: 1428, 1797). Finland had the lowest rate of 776 (686, 866). When examining hospitalization rates only, France had the highest rate of inpatient hospitalizations of 988/100,000 (95% CI 858, 1118) while Spain had the lowest at 87/100,000 (95% CI 76, 99). For ED rates for mental health conditions, the US had the highest rate of 958/100,000 (95% CI 861, 1055) while France had the lowest rate with 241/100,000 (95% CI 216, 265). Notable shifts coinciding with the onset of the COVID-19 pandemic were observed including a substitution of care setting in the US from ED to inpatient care, and overall declines in acute care utilization in Canada and France.</p><p><strong>Conclusion: </strong>The study underscores the importance of understanding and addressing variation in acute care utilization for mental health conditions, including the differential effect of COVID-19, across different health care systems. Further research is needed to elucidate the extent to which factors such as workforce capacity, access barriers, financial incentives, COVID-19 preparedness, and community-based care may contribute to these variations.</p><p><strong>What is known on this topic: </strong>Approximately one billion people globally live with a mental health condition, with significant consequences for individuals and societies. Rates of mental health diagnoses vary across high-income countries, with substantial differences in access to effective care. The COVID-19 pandemic has exacerbated mental health challenges globally, with varying impacts across countries.</p><p><strong>What this study adds: </strong>This study provides a comprehensive international comparison of hospitalization and emergency department visit rates for mental health conditions across eight high-income countries. It highlights significant variations in acute care utilization patterns, particularly in countries that are more likely to care for people with mental health conditions
{"title":"International comparison of hospitalizations and emergency department visits related to mental health conditions across high-income countries before and during the COVID-19 pandemic.","authors":"Nicholas Bowden, Aaron Hedquist, Dannie Dai, Olukorede Abiona, Enrique Bernal-Delgado, Carl Rudolf Blankart, Julie Cartailler, Francisco Estupiñán-Romero, Philip Haywood, Zeynep Or, Irene Papanicolas, Mai Stafford, Steven Wyatt, Reijo Sund, Jean Pierre Uwitonze, Walter P Wodchis, Robin Gauld, Hien Vu, Tania Sawaya, Jose F Figueroa","doi":"10.1111/1475-6773.14386","DOIUrl":"10.1111/1475-6773.14386","url":null,"abstract":"<p><strong>Objective: </strong>To explore variation in rates of acute care utilization for mental health conditions, including hospitalizations and emergency department (ED) visits, across high-income countries before and during the COVID-19 pandemic.</p><p><strong>Data sources and study setting: </strong>Administrative patient-level data between 2017 and 2020 of eight high-income countries: Canada, England, Finland, France, New Zealand, Spain, Switzerland, and the United States (US).</p><p><strong>Study design: </strong>Multi-country retrospective observational study using a federated data approach that evaluated age-sex standardized rates of hospitalizations and ED visits for mental health conditions.</p><p><strong>Principal findings: </strong>There was significant variation in rates of acute mental health care utilization across countries. Among the subset of four countries with both hospitalization and ED data, the US had the highest pre-COVID-19 combined average annual acute care rate of 1613 episodes/100,000 people (95% CI: 1428, 1797). Finland had the lowest rate of 776 (686, 866). When examining hospitalization rates only, France had the highest rate of inpatient hospitalizations of 988/100,000 (95% CI 858, 1118) while Spain had the lowest at 87/100,000 (95% CI 76, 99). For ED rates for mental health conditions, the US had the highest rate of 958/100,000 (95% CI 861, 1055) while France had the lowest rate with 241/100,000 (95% CI 216, 265). Notable shifts coinciding with the onset of the COVID-19 pandemic were observed including a substitution of care setting in the US from ED to inpatient care, and overall declines in acute care utilization in Canada and France.</p><p><strong>Conclusion: </strong>The study underscores the importance of understanding and addressing variation in acute care utilization for mental health conditions, including the differential effect of COVID-19, across different health care systems. Further research is needed to elucidate the extent to which factors such as workforce capacity, access barriers, financial incentives, COVID-19 preparedness, and community-based care may contribute to these variations.</p><p><strong>What is known on this topic: </strong>Approximately one billion people globally live with a mental health condition, with significant consequences for individuals and societies. Rates of mental health diagnoses vary across high-income countries, with substantial differences in access to effective care. The COVID-19 pandemic has exacerbated mental health challenges globally, with varying impacts across countries.</p><p><strong>What this study adds: </strong>This study provides a comprehensive international comparison of hospitalization and emergency department visit rates for mental health conditions across eight high-income countries. It highlights significant variations in acute care utilization patterns, particularly in countries that are more likely to care for people with mental health conditions ","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142332737","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}
Kara L. Beck PhD, Amy M. Kilbourne PhD, MPH, Stefanie I. Gidmark MPH, Melissa Z. Braganza MPH
<p>Timely generation and use of research evidence and methods to benefit patients, providers, and health systems continues to be a challenge for many health systems. The Quality Enhancement Research Initiative (QUERI) was established under the Office of Research and Development to help close this gap in the Department of Veterans Affairs (VA) health care system, the largest national integrated health system in the United States, by accelerating the uptake of research findings into health care practice and policy.<span><sup>1, 2</sup></span> QUERI funds investigators embedded in VA health care facilities to partner with multilevel leaders, providers and other frontline staff, managers, and Veterans to scale-up, spread, and sustain promising and evidence-based practices that address the needs of Veterans and the health system.</p><p>Each year, QUERI identifies its funding priorities through a systematic process that is grounded in the Learning Health System Framework.<span><sup>3</sup></span> The development and implementation of this priority-setting process to guide QUERI implementation, evaluation, and quality improvement investments has been described previously.<span><sup>3</sup></span> Briefly, the QUERI priority-setting process involves engaging leaders across the VA to identify their top priorities, funding initiatives to address these priorities, and communicating the results and impacts of these initiatives to VA leaders and other interested/impacted groups. The success of the QUERI priority-setting process is evidenced by its adaptation by the VA Office of Research and Development, which uses QUERI's process to identify VA research priorities with the goal of ensuring VA research is aligned with health system and Veteran needs.</p><p>The goal of this commentary is to describe the application of QUERI's priority-setting process to identify Veteran-centered research priorities for chronic pain and opioid use disorder (OUD). The four-step process involves identifying research gaps and priorities through an environmental scan, incorporating input from various interested parties and impacted groups, finalizing priorities through an executive committee, and integrating the priorities into funding announcements.</p><p>The first step involved assessing the current state of research on OUD and chronic pain through reviewing reports, journal articles, strategic plans, and websites. This rapid environmental scan included evidence from across the research translation spectrum and was conducted over a period of 1 week in February 2023. A list of research gaps and priorities were identified based on evidence needs documented in VA (e.g., FY2022-FY2028 VA Strategic Plan,<span><sup>4</sup></span> VA Health Systems Consortium of Research focused on pain/OUD [VA Pain/Opioid CoRE]<span><sup>5</sup></span>) and other agency reports (e.g., Surgeon General's Report on Alcohol, Drugs, and Health<span><sup>6</sup></span>; National Institute of Health's Early-Ph
{"title":"Aligning quality improvement, research, and health system goals using the QUERI priority-setting process: A step forward in creating a learning health system","authors":"Kara L. Beck PhD, Amy M. Kilbourne PhD, MPH, Stefanie I. Gidmark MPH, Melissa Z. Braganza MPH","doi":"10.1111/1475-6773.14388","DOIUrl":"10.1111/1475-6773.14388","url":null,"abstract":"<p>Timely generation and use of research evidence and methods to benefit patients, providers, and health systems continues to be a challenge for many health systems. The Quality Enhancement Research Initiative (QUERI) was established under the Office of Research and Development to help close this gap in the Department of Veterans Affairs (VA) health care system, the largest national integrated health system in the United States, by accelerating the uptake of research findings into health care practice and policy.<span><sup>1, 2</sup></span> QUERI funds investigators embedded in VA health care facilities to partner with multilevel leaders, providers and other frontline staff, managers, and Veterans to scale-up, spread, and sustain promising and evidence-based practices that address the needs of Veterans and the health system.</p><p>Each year, QUERI identifies its funding priorities through a systematic process that is grounded in the Learning Health System Framework.<span><sup>3</sup></span> The development and implementation of this priority-setting process to guide QUERI implementation, evaluation, and quality improvement investments has been described previously.<span><sup>3</sup></span> Briefly, the QUERI priority-setting process involves engaging leaders across the VA to identify their top priorities, funding initiatives to address these priorities, and communicating the results and impacts of these initiatives to VA leaders and other interested/impacted groups. The success of the QUERI priority-setting process is evidenced by its adaptation by the VA Office of Research and Development, which uses QUERI's process to identify VA research priorities with the goal of ensuring VA research is aligned with health system and Veteran needs.</p><p>The goal of this commentary is to describe the application of QUERI's priority-setting process to identify Veteran-centered research priorities for chronic pain and opioid use disorder (OUD). The four-step process involves identifying research gaps and priorities through an environmental scan, incorporating input from various interested parties and impacted groups, finalizing priorities through an executive committee, and integrating the priorities into funding announcements.</p><p>The first step involved assessing the current state of research on OUD and chronic pain through reviewing reports, journal articles, strategic plans, and websites. This rapid environmental scan included evidence from across the research translation spectrum and was conducted over a period of 1 week in February 2023. A list of research gaps and priorities were identified based on evidence needs documented in VA (e.g., FY2022-FY2028 VA Strategic Plan,<span><sup>4</sup></span> VA Health Systems Consortium of Research focused on pain/OUD [VA Pain/Opioid CoRE]<span><sup>5</sup></span>) and other agency reports (e.g., Surgeon General's Report on Alcohol, Drugs, and Health<span><sup>6</sup></span>; National Institute of Health's Early-Ph","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":"59 S2","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540569/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142332735","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}
Nicholas Bowden, Jose F Figueroa, Irene Papanicolas
{"title":"Bridging borders: Current trends and future directions in comparative health systems research.","authors":"Nicholas Bowden, Jose F Figueroa, Irene Papanicolas","doi":"10.1111/1475-6773.14385","DOIUrl":"https://doi.org/10.1111/1475-6773.14385","url":null,"abstract":"","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142332736","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}
Brady Post, Aliya Kitsakos, Farbod Alinezhad, Gary Young
<p><strong>Objective: </strong>To examine the association between hospital-cardiologist integration and Medicare spending for stable angina patients.</p><p><strong>Data sources and study setting: </strong>This study used Medicare Standard Analytic Files from 2013 to 2020 and the Centers for Medicare and Medicaid Services National Downloadable File for accompanying physician data.</p><p><strong>Study design: </strong>This was a retrospective cohort study of Medicare beneficiaries with a new diagnosis of stable angina between 2013 and 2020.</p><p><strong>Data collection/extraction methods: </strong>Patients with a new diagnosis of stable angina were categorized by whether they received care from an independent or a hospital-integrated cardiologist.</p><p><strong>Principal findings: </strong>Total spending for this sample was high: an average of $103,946 per patient over 12 months. Adjusted for covariates, patients of integrated cardiologists did not spend significantly more or less than clinically comparable patients of independent cardiologists (-$3856, 95% CI: -$8631 to 920, p = 0.11). This was true for overall inpatient (-$2622, 95% CI: -6069 to 825, p = 0.14) and outpatient (-1162, 95% CI: -$3510 to 1185, p = 0.33) spending as well as cardiology-specific inpatient and outpatient spending. Among high-risk patients, overall spending between the integrated and independent groups was comparable, though patients of integrated cardiologists incurred lower spending than those of their independent counterparts in inpatient care (-$13,589; 95% CI: -24,432 to -2746, p = 0.01). In a supplemental analysis, findings suggested that site-neutral payments would have resulted in lower spending among patients of integrated physicians.</p><p><strong>Conclusions: </strong>Specific clinical settings may lend themselves to efficiencies created by integration for certain complex patients, though we do not test a causal mechanism here. Adoption of site-neutral payment policy may also lead to lower spending among patients of integrated physicians.</p><p><strong>What is known on this topic: </strong>Hospital-physician integration has increased significantly in the United States. Policymakers and health policy experts have expressed concerns that hospital-physician integration leads to increased health spending and may threaten healthcare affordability. While some studies link integration to greater spending, many use incomplete measures of spending, do not consider the potential benefits of care coordination, or rely on outdated data.</p><p><strong>What this study adds: </strong>Spending among patients with stable angina, a common cardiovascular condition, was nearly equal, on average, across patients of integrated and independent cardiologists. Inpatient spending on high-risk patients was somewhat lower for those under the care of integrated cardiologists. Overall, patients of integrated cardiologists incurred largely comparable spending relative to patients of indepen
{"title":"Hospital-physician integration and Medicare spending: Evidence from stable angina.","authors":"Brady Post, Aliya Kitsakos, Farbod Alinezhad, Gary Young","doi":"10.1111/1475-6773.14383","DOIUrl":"https://doi.org/10.1111/1475-6773.14383","url":null,"abstract":"<p><strong>Objective: </strong>To examine the association between hospital-cardiologist integration and Medicare spending for stable angina patients.</p><p><strong>Data sources and study setting: </strong>This study used Medicare Standard Analytic Files from 2013 to 2020 and the Centers for Medicare and Medicaid Services National Downloadable File for accompanying physician data.</p><p><strong>Study design: </strong>This was a retrospective cohort study of Medicare beneficiaries with a new diagnosis of stable angina between 2013 and 2020.</p><p><strong>Data collection/extraction methods: </strong>Patients with a new diagnosis of stable angina were categorized by whether they received care from an independent or a hospital-integrated cardiologist.</p><p><strong>Principal findings: </strong>Total spending for this sample was high: an average of $103,946 per patient over 12 months. Adjusted for covariates, patients of integrated cardiologists did not spend significantly more or less than clinically comparable patients of independent cardiologists (-$3856, 95% CI: -$8631 to 920, p = 0.11). This was true for overall inpatient (-$2622, 95% CI: -6069 to 825, p = 0.14) and outpatient (-1162, 95% CI: -$3510 to 1185, p = 0.33) spending as well as cardiology-specific inpatient and outpatient spending. Among high-risk patients, overall spending between the integrated and independent groups was comparable, though patients of integrated cardiologists incurred lower spending than those of their independent counterparts in inpatient care (-$13,589; 95% CI: -24,432 to -2746, p = 0.01). In a supplemental analysis, findings suggested that site-neutral payments would have resulted in lower spending among patients of integrated physicians.</p><p><strong>Conclusions: </strong>Specific clinical settings may lend themselves to efficiencies created by integration for certain complex patients, though we do not test a causal mechanism here. Adoption of site-neutral payment policy may also lead to lower spending among patients of integrated physicians.</p><p><strong>What is known on this topic: </strong>Hospital-physician integration has increased significantly in the United States. Policymakers and health policy experts have expressed concerns that hospital-physician integration leads to increased health spending and may threaten healthcare affordability. While some studies link integration to greater spending, many use incomplete measures of spending, do not consider the potential benefits of care coordination, or rely on outdated data.</p><p><strong>What this study adds: </strong>Spending among patients with stable angina, a common cardiovascular condition, was nearly equal, on average, across patients of integrated and independent cardiologists. Inpatient spending on high-risk patients was somewhat lower for those under the care of integrated cardiologists. Overall, patients of integrated cardiologists incurred largely comparable spending relative to patients of indepen","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142301390","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}
Jorge R Ledesma,Stavroula A Chrysanthopoulou,Mark N Lurie,Jennifer B Nuzzo,Irene Papanicolas
OBJECTIVETo quantify disruptions in hospitalization and ambulatory care throughout the coronavirus disease 2019 (COVID-19) pandemic for 32 countries, and examine associations of health system characteristics and COVID-19 response strategies on disruptions.DATA SOURCESWe utilized aggregated inpatient hospitalization and surgical procedure data from the Organization for Economic Co-operation and Development Health Database from 2010 to 2021. Covariate data were extracted from the Organization for Economic Co-operation and Development Health Database, World Health Organization, and Oxford COVID-19 Government Response Tracker.STUDY DESIGNThis is a descriptive study using time-series analyses to quantify the annual effect of the COVID-19 pandemic on non-COVID-19 hospitalizations for 20 diagnostic categories and 15 surgical procedures. We compared expected hospitalizations had the pandemic never occurred in 2020-2021, estimated using autoregressive integrated moving average modeling with data from 2010 to 2019, with observed hospitalizations. Observed-to-expected ratios and missed hospitalizations were computed as measures of COVID-19 impact. Mixed linear models were employed to examine associations between hospitalization observed-to-expected ratios and covariates.PRINCIPAL FINDINGSThe COVID-19 pandemic was associated with 16,300,000 (95% uncertainty interval 14,700,000-17,900,000; 18.0% [16.5%-19.4%]) missed hospitalizations in 2020. Diseases of the respiratory (-2,030,000 [-2,300,000 to -1,780,000]), circulatory (-1,680,000 [-1,960,000 to -1,410,000]), and musculoskeletal (-1,480,000 [-1,720,000 to -1,260,000]) systems contributed most to the declines. In 2021, there were an additional 14,700,000 (95% uncertainty interval 13,100,000-16,400,000; 16.3% [14.9%-17.9%]) missed hospitalizations. Total healthcare workers per capita (β = 1.02 [95% CI 1.00, 1.04]) and insurance coverage (β = 1.05 [1.02, 1.09]) were associated with fewer missed hospitalizations. Stringency index (β = 0.98 [0.98, 0.99]) and excess all-cause deaths (β = 0.98 [0.96, 0.99]) were associated with more missed hospitalizations.CONCLUSIONSThere was marked cross-country variability in disruptions to hospitalizations and ambulatory care. Certain health system characteristics appeared to be more protective, such as insurance coverage, and number of inputs including healthcare workforce and beds.WHAT IS KNOWN ON THIS TOPICSubstantial disruptions in health services associated with the coronavirus disease 2019 pandemic have placed a renewed interest in health system resilience. While there is a growing body of evidence documenting disruptions in services, there are limited comparative assessments across diverse countries with different health system designs, preparedness levels, and public health responses. Learning and adapting from health system-specific gaps and challenges highlighted by the pandemic will be critical for improving resilience.WHAT THIS STUDY ADDSAll countries experienced
{"title":"Health system resilience during the COVID-19 pandemic: A comparative analysis of disruptions in care from 32 countries.","authors":"Jorge R Ledesma,Stavroula A Chrysanthopoulou,Mark N Lurie,Jennifer B Nuzzo,Irene Papanicolas","doi":"10.1111/1475-6773.14382","DOIUrl":"https://doi.org/10.1111/1475-6773.14382","url":null,"abstract":"OBJECTIVETo quantify disruptions in hospitalization and ambulatory care throughout the coronavirus disease 2019 (COVID-19) pandemic for 32 countries, and examine associations of health system characteristics and COVID-19 response strategies on disruptions.DATA SOURCESWe utilized aggregated inpatient hospitalization and surgical procedure data from the Organization for Economic Co-operation and Development Health Database from 2010 to 2021. Covariate data were extracted from the Organization for Economic Co-operation and Development Health Database, World Health Organization, and Oxford COVID-19 Government Response Tracker.STUDY DESIGNThis is a descriptive study using time-series analyses to quantify the annual effect of the COVID-19 pandemic on non-COVID-19 hospitalizations for 20 diagnostic categories and 15 surgical procedures. We compared expected hospitalizations had the pandemic never occurred in 2020-2021, estimated using autoregressive integrated moving average modeling with data from 2010 to 2019, with observed hospitalizations. Observed-to-expected ratios and missed hospitalizations were computed as measures of COVID-19 impact. Mixed linear models were employed to examine associations between hospitalization observed-to-expected ratios and covariates.PRINCIPAL FINDINGSThe COVID-19 pandemic was associated with 16,300,000 (95% uncertainty interval 14,700,000-17,900,000; 18.0% [16.5%-19.4%]) missed hospitalizations in 2020. Diseases of the respiratory (-2,030,000 [-2,300,000 to -1,780,000]), circulatory (-1,680,000 [-1,960,000 to -1,410,000]), and musculoskeletal (-1,480,000 [-1,720,000 to -1,260,000]) systems contributed most to the declines. In 2021, there were an additional 14,700,000 (95% uncertainty interval 13,100,000-16,400,000; 16.3% [14.9%-17.9%]) missed hospitalizations. Total healthcare workers per capita (β = 1.02 [95% CI 1.00, 1.04]) and insurance coverage (β = 1.05 [1.02, 1.09]) were associated with fewer missed hospitalizations. Stringency index (β = 0.98 [0.98, 0.99]) and excess all-cause deaths (β = 0.98 [0.96, 0.99]) were associated with more missed hospitalizations.CONCLUSIONSThere was marked cross-country variability in disruptions to hospitalizations and ambulatory care. Certain health system characteristics appeared to be more protective, such as insurance coverage, and number of inputs including healthcare workforce and beds.WHAT IS KNOWN ON THIS TOPICSubstantial disruptions in health services associated with the coronavirus disease 2019 pandemic have placed a renewed interest in health system resilience. While there is a growing body of evidence documenting disruptions in services, there are limited comparative assessments across diverse countries with different health system designs, preparedness levels, and public health responses. Learning and adapting from health system-specific gaps and challenges highlighted by the pandemic will be critical for improving resilience.WHAT THIS STUDY ADDSAll countries experienced ","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":"6 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142263849","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}
Sayeh Nikpay, Michelle Leeberg, Katy Kozhimannil, Michael Ward, Julian Wolfson, John Graves, Beth A. Virnig
ObjectiveTo develop a method of consistently identifying interfacility transfers (IFTs) in Medicare Claims using patients with ST‐Elevation Myocardial Infarction (STEMI) as an example.Data Sources/Study Setting100% Medicare inpatient and outpatient Standard Analytic Files and 5% Carrier Files, 2011–2020.Study DesignObservational, cross‐sectional comparison of patient characteristics between proposed and existing methods.Data Collection/Extraction MethodsWe limited to patients aged 65+ with STEMI diagnosis using both proposed and existing methods.Principal FindingsWe identified 62,668 more IFTs using the proposed method (86,128 versus 23,460). A separately billable interfacility ambulance trip was found for more IFTs using the proposed than existing method (86% vs. 79%). Compared with the existing method, transferred patients under the proposed method were more likely to live in rural (p < 0.001) and lower income (p < 0.001) counties and were located farther away from emergency departments, trauma centers, and intensive care units (p < 0.001).ConclusionsIdentifying transferred patients based on two consecutive inpatient claims results in an undercount of IFTs and under‐represents rural and low‐income patients.
{"title":"A proposed method for identifying Interfacility transfers in Medicare claims data","authors":"Sayeh Nikpay, Michelle Leeberg, Katy Kozhimannil, Michael Ward, Julian Wolfson, John Graves, Beth A. Virnig","doi":"10.1111/1475-6773.14367","DOIUrl":"https://doi.org/10.1111/1475-6773.14367","url":null,"abstract":"ObjectiveTo develop a method of consistently identifying interfacility transfers (IFTs) in Medicare Claims using patients with ST‐Elevation Myocardial Infarction (STEMI) as an example.Data Sources/Study Setting100% Medicare inpatient and outpatient Standard Analytic Files and 5% Carrier Files, 2011–2020.Study DesignObservational, cross‐sectional comparison of patient characteristics between proposed and existing methods.Data Collection/Extraction MethodsWe limited to patients aged 65+ with STEMI diagnosis using both proposed and existing methods.Principal FindingsWe identified 62,668 more IFTs using the proposed method (86,128 versus 23,460). A separately billable interfacility ambulance trip was found for more IFTs using the proposed than existing method (86% vs. 79%). Compared with the existing method, transferred patients under the proposed method were more likely to live in rural (<jats:italic>p</jats:italic> < 0.001) and lower income (<jats:italic>p</jats:italic> < 0.001) counties and were located farther away from emergency departments, trauma centers, and intensive care units (<jats:italic>p</jats:italic> < 0.001).ConclusionsIdentifying transferred patients based on two consecutive inpatient claims results in an undercount of IFTs and under‐represents rural and low‐income patients.","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":"432 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142221292","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}
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