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Unifying Outpatient Practices to Redress Structural Racism in an Urban Health System.
IF 9.5 Q1 HEALTH CARE SCIENCES & SERVICES Pub Date : 2025-02-07 DOI: 10.1001/jamahealthforum.2024.5520
Sofia R Schlozman, Margaret Smirnoff, Ann Scheck McAlearney, Carol R Horowitz, Lynne D Richardson, Radhi Yagnik, Nina A Bickell

Importance: There is a strong and increasing focus on redressing structural racism in health care systems. Structural racism persists by separating clinical care sites that treat patients of racial and ethnic minority groups who are disproportionately covered by Medicaid from sites that treat patients who are White and disproportionately covered by commercial insurance. Practice unification refers to efforts to eliminate this form of segregation.

Objective: To define and investigate the facilitators, barriers, and the effects associated with unification of outpatient practices to reduce structural racism in a large urban health system.

Design, setting, and participants: This qualitative study used semistructured interviews conducted within a large urban health system in New York from February to October 2023. Trained researchers interviewed clinical and administrative leaders of outpatient clinical practices that were pursuing unification, and health system leaders overseeing multiple practices.

Main outcomes and measures: Thematic analysis was used to identify facilitators of and barriers to unification, challenges and benefits after unification, and persistent dimensions of segregation within clinics that had nominally unified. These insights were used to create a framework for the unification process.

Results: The thematic analysis included qualitative information from 5 administrative leaders, 12 clinical leaders, and 6 health system leaders, and found that unification facilitators were financial benefit, relocation to new facility spaces, and advocacy by leaders and trainees, while barriers were financial concerns, space constraints, and physician and staff attitudes. After attaining and experiencing some degree of practice unification, interviewees reported financial gain, more support staff, perceptions of greater equity, better educational experiences, and increased practitioner and trainee satisfaction. Challenges reported after unification were changes in staff roles, financial concerns, patient dissatisfaction, and difficulties interfacing with segregated practices within the health system. Partially unified practices maintained dimensions of segregation, by practitioner, payer, and/or scheduling/time (temporal segregation).

Conclusions and relevance: This qualitative study found that outpatient practice unification was perceived to be a financially and equity-driven process with multiple dimensions. However, not all of the unification procedures had been completely implemented. These findings indicate that successful unification of outpatient practices in a large urban health care system requires attention to multiple dimensions, as well as overcoming challenges regarding finances, facility space, reimbursement policies, and patient and staff satisfaction.

重要性:人们越来越重视纠正医疗保健系统中的结构性种族主义。结构性种族主义持续存在的原因是,治疗少数种族和少数族裔群体病人的临床医疗点与治疗白人病人的临床医疗点被隔离开来,前者享受医疗补助(Medicaid)的比例过高,而后者享受商业保险的比例过高。统一诊疗是指努力消除这种形式的隔离:目的:在一个大型城市医疗系统中,确定并调查与统一门诊实践相关的促进因素、障碍和影响,以减少结构性种族主义:这项定性研究采用半结构式访谈,于 2023 年 2 月至 10 月在纽约的一个大型城市医疗系统内进行。经过培训的研究人员采访了正在寻求统一的门诊临床实践的临床和行政领导,以及监管多个实践的医疗系统领导:通过主题分析,研究人员确定了统一的促进因素和障碍、统一后的挑战和益处,以及名义上已经统一的诊所内部持续存在的隔离问题。这些洞察力被用于创建一个统一进程框架:专题分析包括来自 5 位行政领导、12 位临床领导和 6 位医疗系统领导的定性信息,结果发现,统一的促进因素是经济利益、搬迁到新的设施空间以及领导和学员的倡导,而障碍则是财务问题、空间限制以及医生和员工的态度。在实现并经历了一定程度的业务统一后,受访者报告了经济收益、更多的支持人员、更公平的观念、更好的教育体验以及从业人员和受训人员满意度的提高。据报告,统一后面临的挑战是员工角色的变化、财务问题、病人的不满以及与医疗系统内隔离执业机构的沟通困难。部分统一后的医疗机构仍保持着按从业人员、付款人和/或时间安排/时间(时间上的隔离)等方面的隔离:这项定性研究发现,门诊医疗机构的统一被认为是一个以财务和公平为导向的过程,涉及多个方面。然而,并非所有的统一程序都已完全实施。这些研究结果表明,在一个大型城市医疗系统中,门诊业务的成功统一需要关注多个方面,并克服财务、设施空间、报销政策以及患者和员工满意度等方面的挑战。
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引用次数: 0
Changes in US Primary Care Access and Capabilities During the COVID-19 Pandemic.
IF 9.5 Q1 HEALTH CARE SCIENCES & SERVICES Pub Date : 2025-02-07 DOI: 10.1001/jamahealthforum.2024.5237
Matthew Mackwood, Elliott Fisher, Rachel O Schmidt, Ching-Wen W Yang, A James O'Malley, Hector P Rodriguez, Stephen Shortell, Ellesse-Roselee L Akré, Karen E Schifferdecker

Importance: Many of the capabilities needed to deliver accessible, high-quality primary care have been defined, but little is known about how their implementation has changed in US practices over the course of the COVID-19 pandemic or about the factors associated with greater capabilities.

Objective: To describe US primary care practices' accessibility and capabilities and examine recent changes.

Design, setting, and participants: This was a retrospective cohort study across 2 surveys, in 2017 to 2018 and 2022 to 2023, among a national sample of primary care practice leaders in the US. Data were analyzed from January 2023 to September 2024.

Exposures: Degree of integrated practice ownership and accountable care organization (ACO) participation.

Main outcomes and measures: Differences by practice ownership and ACO participation, and changes over time in access to care and care delivery capabilities. These were measured by composite scores of responses standardized to a scale of 0 to 100.

Results: This analysis included 710 practices, of which 234 were independently owned, 105 were physician group owned, and 321 were hospital/health system owned in 2017 to 2018, and 68 practices reported no ACO participation, 107 joined between surveys, and 486 otherwise participated in ACOs. Access to care (measured as extended weekday or weekend hours) was reported to decline from the first survey in 2017 to 2018 to the second in 2022 to 2023. Hospital/health system practices and ACO participants had higher rates of extended weekday hours than their comparators in 2022 to 2023. Average capability scores increased from 51 to 54 (increase of 4 points [95% CI, 1-6 points]). There was wide variation in scores within all ownership and ACO participant or nonparticipant groups. Capability scores were higher on average for more integrated practices (for physician groups compared to independent practices, 12 points [95% CI, 5-19 points] in 2017-2018 and 12 points [95% CI, 7-16 points] in 2022-2023) and for ACO participants compared to nonparticipants (13-point difference [6 to 20] in 2017-2018 and 12-point difference [6 to 18] in 2022-2023).

Conclusions and relevance: In this cohort study, over the time period including the COVID-19 pandemic, primary care practices reported a decline in access to care, while average practice capabilities improved. Integrated practice ownership and ACO participation were both associated with better access and capability scores, suggesting that value-based payment and integrated care delivery support the development of higher-quality primary care. Variations across practices point to large opportunities for improvement overall and underscore the importance of incentives and structures as levers to improve primary care delivery.

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引用次数: 0
Health Care Spending After Initiating Sacubitril-Valsartan vs Renin-Angiotensin System Blockers for Heart Failure Treatment.
IF 9.5 Q1 HEALTH CARE SCIENCES & SERVICES Pub Date : 2025-02-07 DOI: 10.1001/jamahealthforum.2024.5385
Catherine S Hwang, Rishi J Desai, Aaron S Kesselheim, Raisa Levin, Sushama Kattinakere Sreedhara, Benjamin N Rome

Importance: For patients with heart failure with reduced ejection fraction (HFrEF), treatment with sacubitril-valsartan, an angiotensin receptor-neprilysin inhibitor, has become increasingly preferred over angiotensin-converting enzyme inhibitors (ACE-Is) and angiotensin II receptor blockers (ARBs). However, sacubitril-valsartan is much more expensive than generic ACE-I/ARBs. It is unknown whether the high cost of sacubitril-valsartan is offset by lower spending on hospitalizations and other treatments.

Objective: To compare total and out-of-pocket health care spending among Medicare beneficiaries initiating sacubitril-valsartan vs ACE-I/ARBs for HFrEF.

Design, setting, and participants: This was a cohort study using data from Medicare fee-for-service claims with propensity score matching of Medicare beneficiaries with HFrEF. Data analysis was performed from November 2022 to December 2023.

Exposure: Initiation of sacubitril-valsartan or an ACE-I/ARB. Patients were matched by propensity score based on 104 covariates, including demographic characteristics, comorbidities, baseline annual spending, and baseline use of health care services.

Main outcomes and measures: Mean total and out-of-pocket health care expenditures during the 365 days after initiating sacubitril-valsartan or an ACE-I/ARB. Censoring for incomplete follow-up was addressed using Kaplan-Meier probability weighting. Cost differences, cost ratios, and 95% CIs were calculated using a nonparametric bootstrapping method with 500 samples drawn with replacement.

Results: Among 13 755 matched pairs of Medicare patients with HFrEF (mean [SD] age, 77.5 [7.5] years; 5138 [39%] 80 years or older; 9949 females [36%] and 17 561 males [64%]), mean annual total health care spending per person was similar for sacubitril-valsartan initiators and ACE-I/ARB initiators (difference, $701; 95% CI, -$132 to $1593). Sacubitril-valsartan initiators had higher prescription drug costs (difference, $1911; 95% CI, $1704 to $2113), lower inpatient costs (difference, -$790; 95% CI, -$1468 to -$72), lower outpatient costs (difference, -$330; 95% CI, -$664 to -$11), and higher annual out-of-pocket spending (difference, $109; 95% CI, $13 to $208).

Conclusions and relevance: This cohort study found that Medicare beneficiaries initiating sacubitril-valsartan to treat HFrEF had similar total health care spending as those initiating ACE-I/ARBs; higher prescription drug spending was offset by lower inpatient and outpatient spending. However, sacubitril-valsartan use was associated with higher patient out-of-pocket costs, which may exacerbate health disparities and limit access and affordability.

{"title":"Health Care Spending After Initiating Sacubitril-Valsartan vs Renin-Angiotensin System Blockers for Heart Failure Treatment.","authors":"Catherine S Hwang, Rishi J Desai, Aaron S Kesselheim, Raisa Levin, Sushama Kattinakere Sreedhara, Benjamin N Rome","doi":"10.1001/jamahealthforum.2024.5385","DOIUrl":"10.1001/jamahealthforum.2024.5385","url":null,"abstract":"<p><strong>Importance: </strong>For patients with heart failure with reduced ejection fraction (HFrEF), treatment with sacubitril-valsartan, an angiotensin receptor-neprilysin inhibitor, has become increasingly preferred over angiotensin-converting enzyme inhibitors (ACE-Is) and angiotensin II receptor blockers (ARBs). However, sacubitril-valsartan is much more expensive than generic ACE-I/ARBs. It is unknown whether the high cost of sacubitril-valsartan is offset by lower spending on hospitalizations and other treatments.</p><p><strong>Objective: </strong>To compare total and out-of-pocket health care spending among Medicare beneficiaries initiating sacubitril-valsartan vs ACE-I/ARBs for HFrEF.</p><p><strong>Design, setting, and participants: </strong>This was a cohort study using data from Medicare fee-for-service claims with propensity score matching of Medicare beneficiaries with HFrEF. Data analysis was performed from November 2022 to December 2023.</p><p><strong>Exposure: </strong>Initiation of sacubitril-valsartan or an ACE-I/ARB. Patients were matched by propensity score based on 104 covariates, including demographic characteristics, comorbidities, baseline annual spending, and baseline use of health care services.</p><p><strong>Main outcomes and measures: </strong>Mean total and out-of-pocket health care expenditures during the 365 days after initiating sacubitril-valsartan or an ACE-I/ARB. Censoring for incomplete follow-up was addressed using Kaplan-Meier probability weighting. Cost differences, cost ratios, and 95% CIs were calculated using a nonparametric bootstrapping method with 500 samples drawn with replacement.</p><p><strong>Results: </strong>Among 13 755 matched pairs of Medicare patients with HFrEF (mean [SD] age, 77.5 [7.5] years; 5138 [39%] 80 years or older; 9949 females [36%] and 17 561 males [64%]), mean annual total health care spending per person was similar for sacubitril-valsartan initiators and ACE-I/ARB initiators (difference, $701; 95% CI, -$132 to $1593). Sacubitril-valsartan initiators had higher prescription drug costs (difference, $1911; 95% CI, $1704 to $2113), lower inpatient costs (difference, -$790; 95% CI, -$1468 to -$72), lower outpatient costs (difference, -$330; 95% CI, -$664 to -$11), and higher annual out-of-pocket spending (difference, $109; 95% CI, $13 to $208).</p><p><strong>Conclusions and relevance: </strong>This cohort study found that Medicare beneficiaries initiating sacubitril-valsartan to treat HFrEF had similar total health care spending as those initiating ACE-I/ARBs; higher prescription drug spending was offset by lower inpatient and outpatient spending. However, sacubitril-valsartan use was associated with higher patient out-of-pocket costs, which may exacerbate health disparities and limit access and affordability.</p>","PeriodicalId":53180,"journal":{"name":"JAMA Health Forum","volume":"6 2","pages":"e245385"},"PeriodicalIF":9.5,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11829231/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143415509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Errors in Figure.
IF 9.5 Q1 HEALTH CARE SCIENCES & SERVICES Pub Date : 2025-02-07 DOI: 10.1001/jamahealthforum.2024.5633
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引用次数: 0
Physician Voting Rates in the 2020 and 2022 US Elections.
IF 9.5 Q1 HEALTH CARE SCIENCES & SERVICES Pub Date : 2025-02-07 DOI: 10.1001/jamahealthforum.2024.5443
Julianna Pacheco, Nathan K Micatka, Caroline Tolbert
{"title":"Physician Voting Rates in the 2020 and 2022 US Elections.","authors":"Julianna Pacheco, Nathan K Micatka, Caroline Tolbert","doi":"10.1001/jamahealthforum.2024.5443","DOIUrl":"10.1001/jamahealthforum.2024.5443","url":null,"abstract":"","PeriodicalId":53180,"journal":{"name":"JAMA Health Forum","volume":"6 2","pages":"e245443"},"PeriodicalIF":9.5,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11829221/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143415521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Sale of Private Equity-Owned Physician Practices and Physician Turnover.
IF 9.5 Q1 HEALTH CARE SCIENCES & SERVICES Pub Date : 2025-02-07 DOI: 10.1001/jamahealthforum.2024.5376
Victoria Berquist, Lev Klarnet, Leemore Dafny
<p><strong>Importance: </strong>Private equity (PE) acquisition of physician practices is increasing, with owners targeting sales, or exits, in 3 to 7 years. Little is known about the association of exit with physician retention and subsequent employment.</p><p><strong>Objective: </strong>To examine whether PE exit of physician practices is associated with changes in physician retention and subsequent choice of practice size.</p><p><strong>Design, setting, and participants: </strong>Using data from the Centers for Medicare & Medicaid Services Doctors and Clinicians National Downloadable File from December 31, 2014, to December 31, 2020, this case-control study compared employment changes for physicians at PE-exiting practices sold between January 1, 2016, and December 31, 2018 (treatment group), with employment changes for matched control physicians in practices not sold by PE owners but with the same specialty, hospital referral region, practice size, and time period. Physicians billing fee-for-service Medicare during the study period were eligible for inclusion. A difference-in-differences design was used to compare retention between the treatment and control groups in the 2 years before and after exit using a multinomial logit model that adjusted for physician decade of graduation. Data were analyzed from August 1, 2023, to November 9, 2024.</p><p><strong>Exposure: </strong>Exit of a PE-owned physician practice.</p><p><strong>Main outcomes and measures: </strong>Physician employment outcomes included staying (continuing to bill through the initial practice), working elsewhere (only billing through other practices), and retirement (no longer billing). Whether a physician left to a join large (>120-physician) practice was also evaluated.</p><p><strong>Results: </strong>Of the 1215 physicians included in the analysis (405 at 70 PE-exiting practices and 810 matched controls; 814 [67.0%] male and 401 (33.0%) were female. Physicians in all PE-exiting practices were typically in practices of more than 20 physicians (471 [65.2%]) and often in the South (373 [51.7%]). Dermatology was the leading specialty (216 [29.9%]), followed by family medicine (94 [13.0%]). Physicians employed in PE-exiting practices were 16.5 (95% CI, 10.6-22.3) percentage points less likely to continue working in that practice 2 years after exit compared with matched controls. There was no significant change in the probability of retirement (0 percentage points; 95% CI, -4.1 to 4.0). Physicians in PE-exiting practices were 10.1 (95% CI, 6.5 to 13.7) percentage points likelier than matched controls to join a large practice of more than 120 physicians.</p><p><strong>Conclusions and relevance: </strong>In this case-control study, PE exit was followed by an increase in physician turnover and subsequent employment at a large (>120-physician) practice relative to matched controls, notwithstanding similar turnover rates between these physicians and matched controls prior to exit. The in
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引用次数: 0
Error in Results. 结果错误。
IF 9.5 Q1 HEALTH CARE SCIENCES & SERVICES Pub Date : 2025-02-07 DOI: 10.1001/jamahealthforum.2025.0120
{"title":"Error in Results.","authors":"","doi":"10.1001/jamahealthforum.2025.0120","DOIUrl":"10.1001/jamahealthforum.2025.0120","url":null,"abstract":"","PeriodicalId":53180,"journal":{"name":"JAMA Health Forum","volume":"6 2","pages":"e250120"},"PeriodicalIF":9.5,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11871534/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143525234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
New FDA Policies Could Limit the Full Value of AI in Medicine.
IF 9.5 Q1 HEALTH CARE SCIENCES & SERVICES Pub Date : 2025-02-07 DOI: 10.1001/jamahealthforum.2025.0289
Scott Gottlieb
{"title":"New FDA Policies Could Limit the Full Value of AI in Medicine.","authors":"Scott Gottlieb","doi":"10.1001/jamahealthforum.2025.0289","DOIUrl":"https://doi.org/10.1001/jamahealthforum.2025.0289","url":null,"abstract":"","PeriodicalId":53180,"journal":{"name":"JAMA Health Forum","volume":"6 2","pages":"e250289"},"PeriodicalIF":9.5,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143257252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Recognizing and Strengthening the 4 Pillars of US Childhood Vaccine Policy.
IF 9.5 Q1 HEALTH CARE SCIENCES & SERVICES Pub Date : 2025-02-07 DOI: 10.1001/jamahealthforum.2025.0363
Joshua M Sharfstein, Sarah Despres
{"title":"Recognizing and Strengthening the 4 Pillars of US Childhood Vaccine Policy.","authors":"Joshua M Sharfstein, Sarah Despres","doi":"10.1001/jamahealthforum.2025.0363","DOIUrl":"https://doi.org/10.1001/jamahealthforum.2025.0363","url":null,"abstract":"","PeriodicalId":53180,"journal":{"name":"JAMA Health Forum","volume":"6 2","pages":"e250363"},"PeriodicalIF":9.5,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143411491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Drivers of Variation in Health Care Spending Across US Counties.
IF 9.5 Q1 HEALTH CARE SCIENCES & SERVICES Pub Date : 2025-02-07 DOI: 10.1001/jamahealthforum.2024.5220
Joseph L Dieleman, Maxwell Weil, Meera Beauchamp, Catherine Bisignano, Sawyer W Crosby, Drew DeJarnatt, Haley Lescinsky, Ali H Mokdad, Samuel Ostroff, Hilary Paul, Ian Pollock, Maitreyi Sahu, John W Scott, Kayla V Taylor, Azalea Thomson, Marcia R Weaver, Lauren B Wilner, Christopher J L Murray
<p><strong>Importance: </strong>Understanding the drivers of health care spending across US counties is important for developing policies and assessing the allocation of health care services.</p><p><strong>Objective: </strong>To estimate the amount of cross-county health care spending variation explained by (1) population age, (2) health condition prevalence, (3) service utilization, and (4) service price and intensity.</p><p><strong>Design, setting, and participants: </strong>In this cross-sectional study, data for 4 key drivers of per capita spending were extracted for 3110 US counties, 148 health conditions, 38 age-sex groups, 4 payers, and 7 types of care for 2019. Service utilization was measured as service volume per prevalent case, while price and intensity was measured as spending per visit, admission, or prescription. Das Gupta and Shapley decomposition methods and linear regression were used to estimate the contribution of each factor. The data analysis was conducted between March 2024 and July 2024.</p><p><strong>Exposures: </strong>Age, disease prevalence, service utilization, or service price and intensity.</p><p><strong>Main outcomes and measures: </strong>Variation in health care spending across US counties.</p><p><strong>Results: </strong>In 2019, 76.6% of personal health care spending was included in this study. Overall, 64.8% of cross-county health care spending variation among 3110 US counties was explained by service utilization, while population age, disease prevalence, and price and intensity of services explained 4.1%, 7.0%, and 24.1%, respectively. The rate at which these factors contributed to variation in spending differed by payer, type of care, and health condition. Service utilization was associated with insurance coverage, median income, and education. An increase in each of these from the median to the 75th percentile was associated with a 7.8%, 4.4%, and 3.8% increase in ambulatory care utilization, respectively. The fraction of Medicare beneficiaries with Medicare Advantage was associated with less utilization. An increase in Medicare Advantage coverage from the median to the 75th percentile was associated with a 1.9% decrease in ambulatory care utilization. Differences in cross-state spending levels were also attributed to different factors. For Utah, the state with the least health care spending per capita, spending rates were lower for all types of care due principally to the young age profile. For New York, the state with the highest spending, spending rates were relatively high for hospital inpatient and prescribed pharmaceutical spending. For both types of care, high service price and intensity contributed to the above-average spending.</p><p><strong>Conclusions and relevance: </strong>In this cross-sectional study, variation in health care spending among US counties was largely related to variation in service utilization. Understanding the drivers of spending variation in the US may help policymakers assess
{"title":"Drivers of Variation in Health Care Spending Across US Counties.","authors":"Joseph L Dieleman, Maxwell Weil, Meera Beauchamp, Catherine Bisignano, Sawyer W Crosby, Drew DeJarnatt, Haley Lescinsky, Ali H Mokdad, Samuel Ostroff, Hilary Paul, Ian Pollock, Maitreyi Sahu, John W Scott, Kayla V Taylor, Azalea Thomson, Marcia R Weaver, Lauren B Wilner, Christopher J L Murray","doi":"10.1001/jamahealthforum.2024.5220","DOIUrl":"10.1001/jamahealthforum.2024.5220","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Importance: &lt;/strong&gt;Understanding the drivers of health care spending across US counties is important for developing policies and assessing the allocation of health care services.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;To estimate the amount of cross-county health care spending variation explained by (1) population age, (2) health condition prevalence, (3) service utilization, and (4) service price and intensity.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Design, setting, and participants: &lt;/strong&gt;In this cross-sectional study, data for 4 key drivers of per capita spending were extracted for 3110 US counties, 148 health conditions, 38 age-sex groups, 4 payers, and 7 types of care for 2019. Service utilization was measured as service volume per prevalent case, while price and intensity was measured as spending per visit, admission, or prescription. Das Gupta and Shapley decomposition methods and linear regression were used to estimate the contribution of each factor. The data analysis was conducted between March 2024 and July 2024.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Exposures: &lt;/strong&gt;Age, disease prevalence, service utilization, or service price and intensity.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Main outcomes and measures: &lt;/strong&gt;Variation in health care spending across US counties.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;In 2019, 76.6% of personal health care spending was included in this study. Overall, 64.8% of cross-county health care spending variation among 3110 US counties was explained by service utilization, while population age, disease prevalence, and price and intensity of services explained 4.1%, 7.0%, and 24.1%, respectively. The rate at which these factors contributed to variation in spending differed by payer, type of care, and health condition. Service utilization was associated with insurance coverage, median income, and education. An increase in each of these from the median to the 75th percentile was associated with a 7.8%, 4.4%, and 3.8% increase in ambulatory care utilization, respectively. The fraction of Medicare beneficiaries with Medicare Advantage was associated with less utilization. An increase in Medicare Advantage coverage from the median to the 75th percentile was associated with a 1.9% decrease in ambulatory care utilization. Differences in cross-state spending levels were also attributed to different factors. For Utah, the state with the least health care spending per capita, spending rates were lower for all types of care due principally to the young age profile. For New York, the state with the highest spending, spending rates were relatively high for hospital inpatient and prescribed pharmaceutical spending. For both types of care, high service price and intensity contributed to the above-average spending.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions and relevance: &lt;/strong&gt;In this cross-sectional study, variation in health care spending among US counties was largely related to variation in service utilization. Understanding the drivers of spending variation in the US may help policymakers assess","PeriodicalId":53180,"journal":{"name":"JAMA Health Forum","volume":"6 2","pages":"e245220"},"PeriodicalIF":9.5,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11829242/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143416124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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JAMA Health Forum
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