JAMA Health Forum最新文献

{"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}

{"title":"Sale of Private Equity-Owned Physician Practices and Physician Turnover.","authors":"Victoria Berquist, Lev Klarnet, Leemore Dafny","doi":"10.1001/jamahealthforum.2024.5376","DOIUrl":"10.1001/jamahealthforum.2024.5376","url":null,"abstract":"<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","PeriodicalId":53180,"journal":{"name":"JAMA Health Forum","volume":"6 2","pages":"e245376"},"PeriodicalIF":9.5,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11829224/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143415533","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}

{"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}

{"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}

{"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":"<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","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}

{"title":"Fillings Needed for Gaps in Government Dental Coverage.","authors":"Hawazin W Elani, Benjamin D Sommers","doi":"10.1001/jamahealthforum.2025.0370","DOIUrl":"10.1001/jamahealthforum.2025.0370","url":null,"abstract":"","PeriodicalId":53180,"journal":{"name":"JAMA Health Forum","volume":"6 2","pages":"e250370"},"PeriodicalIF":9.5,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11907204/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143460603","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}

{"title":"Minnesota Law Brings Transparency to the 340B Drug Pricing Program.","authors":"Sayeh Nikpay, Claire McGlave, Stefan Gildemeister","doi":"10.1001/jamahealthforum.2024.5447","DOIUrl":"https://doi.org/10.1001/jamahealthforum.2024.5447","url":null,"abstract":"","PeriodicalId":53180,"journal":{"name":"JAMA Health Forum","volume":"6 2","pages":"e245447"},"PeriodicalIF":9.5,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143415511","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}

{"title":"Understanding Geographic Variation in Health Care Spending.","authors":"Melinda B Buntin, Angela Liu","doi":"10.1001/jamahealthforum.2024.5373","DOIUrl":"10.1001/jamahealthforum.2024.5373","url":null,"abstract":"","PeriodicalId":53180,"journal":{"name":"JAMA Health Forum","volume":"6 2","pages":"e245373"},"PeriodicalIF":9.5,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143415538","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}

{"title":"Using Trademarks to Ensure Completion of Postapproval Trials.","authors":"Catherine S Hwang, S Sean Tu","doi":"10.1001/jamahealthforum.2025.0001","DOIUrl":"https://doi.org/10.1001/jamahealthforum.2025.0001","url":null,"abstract":"","PeriodicalId":53180,"journal":{"name":"JAMA Health Forum","volume":"6 2","pages":"e250001"},"PeriodicalIF":9.5,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143525238","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}

{"title":"Structural Discrimination in Nonprofit Hospital Community Benefit Spending.","authors":"Aaron Hedquist, David Blumenthal, Dannie Dai, Jessica Phelan, E John Orav, Jose F Figueroa","doi":"10.1001/jamahealthforum.2024.5523","DOIUrl":"10.1001/jamahealthforum.2024.5523","url":null,"abstract":"<p><strong>Importance: </strong>Nonprofit hospitals receive substantial tax exemptions to provide a community benefit. However, little is known about the distribution of community benefit spending (CBS) across US communities with varying degrees of social vulnerability beyond the hospital's immediate geographic area.</p><p><strong>Objective: </strong>To assess associations of CBS per capita with community-level characteristics and social determinants of health.</p><p><strong>Design, setting, and participants: </strong>This cross-sectional study used Internal Revenue Service Series 990 Tax Forms from 2018 to 2023, to create a dataset of CBS for nonprofit hospitals in the US. Facility-level CBS allocation to counties was based on inpatient utilization to more accurately reflect a hospital's community. Data were analyzed from January to December 2024.</p><p><strong>Exposures: </strong>County-level race and ethnicity characteristics and socioeconomic factors, including educational attainment, proportion living below 138% of the federal poverty level (FPL), and the Social Vulnerability Index (SVI) score.</p><p><strong>Main outcomes and measures: </strong>The primary outcome was total CBS per capita. Generalized linear regression models with a γ log-link function were used to assess the association of CBS per capita with community-level social determinants of health characteristics.</p><p><strong>Results: </strong>A total of 2465 nonprofit hospitals across 3140 US counties were included. Allocation of CBS varied significantly across communities, with the counties in the highest quintile receiving a mean (SD) of $540 ($250) per capita compared with counties in the lowest quintile with $22 ($16) per capita. Communities in the highest quintile of CBS had a higher proportion of White residents, while communities in the lowest quintile had a higher proportion of residents who were non-Hispanic Black or Hispanic, had lower educational attainment, and were living with incomes below 138% of the FPL. For every 1% proportional increase in non-Hispanic Black or Hispanic residents in a community, there was 1.61% (95% CI, 1.38%-1.84%) and 0.88% (95% CI, 0.63%-1.14%) less CBS per capita, respectively. In addition, there was less allocation of CBS per capita among counties with a greater proportion of people with low educational attainment, greater levels of poverty, or higher SVI scores. These results were consistent before and during the COVID-19 pandemic.</p><p><strong>Conclusions and relevance: </strong>This cross-sectional study found that nonprofit hospitals' CBS was regressively allocated across US communities, with more socially vulnerable or racially and ethnically minoritized communities receiving less benefit than more affluent, non-Hispanic White communities, suggesting that the nonprofit tax system may be structurally discriminatory and contributing to health disparities.</p>","PeriodicalId":53180,"journal":{"name":"JAMA Health Forum","volume":"6 2","pages":"e245523"},"PeriodicalIF":9.5,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11871545/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143525237","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}