Health affairs scholarPub Date : 2024-09-27eCollection Date: 2024-10-01DOI: 10.1093/haschl/qxae118
Erin A Taylor, Dmitry Khodyakov, Zachary Predmore, Christine Buttorff, Alice Kim
{"title":"Assessing the feasibility and likelihood of policy options to lower specialty drug costs.","authors":"Erin A Taylor, Dmitry Khodyakov, Zachary Predmore, Christine Buttorff, Alice Kim","doi":"10.1093/haschl/qxae118","DOIUrl":"https://doi.org/10.1093/haschl/qxae118","url":null,"abstract":"<p><p>Specialty drugs are high-cost medications often used to treat complex chronic conditions. Even with insurance coverage, patients may face very high out-of-pocket costs, which in turn may restrict access. While the Inflation Reduction Act of 2022 included policies designed to reduce specialty drug costs, relatively few policies have been enacted during the past decade. In 2022-2023, we conducted a scoping literature review to identify a range of policy options and selected a set of 9 that have been regularly discussed or recently considered to present to an expert stakeholder panel to seek consensus on (1) the feasibility of implementing each policy and (2) its likely impact on drug costs. Experts rated only 1 policy highly on both feasibility and impact: grouping originator biologics and biosimilars under the same Medicare Part B reimbursement code. They rated 3 policies focused on setting payment limits as likely to have positive (downward) impact on costs but of uncertain feasibility. They considered 4 policies as uncertain on both criteria. Experts rated capping monthly out-of-pocket costs as feasible but unlikely to reduce specialty drug costs. Based on these results, we offer 4 recommendations to policymakers considering ways to reduce specialty drug costs.</p>","PeriodicalId":94025,"journal":{"name":"Health affairs scholar","volume":"2 10","pages":"qxae118"},"PeriodicalIF":0.0,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11482634/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142484121","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}
Health affairs scholarPub Date : 2024-09-26eCollection Date: 2024-09-01DOI: 10.1093/haschl/qxae117
Caroline Cerilli, Varshini Varadaraj, Jennifer Choi, Fiona Sweeney, Franz Castro, Scott D Landes, Bonnielin K Swenor
{"title":"Disability inclusion in national surveys.","authors":"Caroline Cerilli, Varshini Varadaraj, Jennifer Choi, Fiona Sweeney, Franz Castro, Scott D Landes, Bonnielin K Swenor","doi":"10.1093/haschl/qxae117","DOIUrl":"10.1093/haschl/qxae117","url":null,"abstract":"<p><p>National surveys are important for understanding the disparities that disabled people experience across social determinants of health; however, limited research has examined the methods used to include disabled people in these surveys. This study reviewed nationally representative surveys administered by the Centers for Disease Control and Prevention (CDC) and the US Census Bureau that collected data in the past 5 years and sampled adults ≥18 years. Data from both publicly available online survey documents and a questionnaire emailed to survey administrators were used to determine whether surveys (1) oversampled disabled people, (2) had a data-accessibility protocol to support data collection, and (3) provided multiple data-collection modalities (eg, phone, paper). Of the 201 surveys identified, 30 met the inclusion criteria for the study. Of these 30 surveys, 1 oversampled disabled people, none had a data-collection accessibility protocol, and 21 provided multiple data-collection modalities. This study highlights barriers and opportunities to including disabled people in national surveys, which is essential for ensuring survey data are generalizable to the US population.</p>","PeriodicalId":94025,"journal":{"name":"Health affairs scholar","volume":"2 9","pages":"qxae117"},"PeriodicalIF":0.0,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11426164/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142335142","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}
Health affairs scholarPub Date : 2024-09-26eCollection Date: 2024-10-01DOI: 10.1093/haschl/qxae123
Redwan Bin Abdul Baten
{"title":"How are US hospitals adopting artificial intelligence? Early evidence from 2022.","authors":"Redwan Bin Abdul Baten","doi":"10.1093/haschl/qxae123","DOIUrl":"https://doi.org/10.1093/haschl/qxae123","url":null,"abstract":"<p><p>US hospitals are rapidly adopting artificial intelligence (AI), but there is a lack of knowledge about AI-adopting hospitals' characteristics, trends, and spread. This study aims to fill this gap by analyzing the 2022 American Hospital Association (AHA) data. The novel Hospital AI Adoption Model (HAIAM) is developed to categorize hospitals based on their AI adoption characteristics in the fields of (1) predicting patient demand, (2) optimizing workflow, (3) automating routine tasks, (4) staff scheduling, and (5) predicting staffing needs. Nearly one-fifth of US hospitals (1107 or 18.70%) have adopted some form of AI by 2022. The HAIAM shows that only 3.82% of hospitals are high adopters, followed by 6.22% moderate and 8.67% low adopters. Artificial intelligence adoption rates are highest in optimizing workflow (12.91%), while staff scheduling (9.53%) has the lowest growth rate. Hospitals with large bed sizes and outpatient surgical departments, private not-for-profit ownership, teaching status, and part of health systems are more likely to adopt different forms of AI. New Jersey (48.94%) is the leading hospital AI-adopting state, whereas New Mexico (0%) is the most lagging. These data can help policymakers better understand variations in AI adoption by hospitals and inform potential policy responses.</p>","PeriodicalId":94025,"journal":{"name":"Health affairs scholar","volume":"2 10","pages":"qxae123"},"PeriodicalIF":0.0,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11472248/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142484125","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}
Health affairs scholarPub Date : 2024-09-17eCollection Date: 2024-10-01DOI: 10.1093/haschl/qxae116
Sezen O Onal, Skky Martin, Nicole M Weiss, Jonathon P Leider
{"title":"Exploring the geospatial variations in the public health workforce: implications for diversifying the supply of potential workers in governmental settings.","authors":"Sezen O Onal, Skky Martin, Nicole M Weiss, Jonathon P Leider","doi":"10.1093/haschl/qxae116","DOIUrl":"10.1093/haschl/qxae116","url":null,"abstract":"<p><p>The US public health workforce has markedly declined, falling from 500 000 individuals in 1980 to 239 000 by 2022, a trend exacerbated by economic instability and an aging demographic. There was a temporary surge in staffing through emergency hires during the COVID-19 pandemic, but the permanence of these positions remains uncertain. Concurrently, public health degree conferrals have sharply increased, creating a mismatch between the growing number of graduates and the actual needs of health departments. This study analyzes the distribution of the potential public health labor supply within a 50- and 150-mile radius of health departments, revealing a significant regional imbalance. Most regions experience substantial differences in the concentration of public health graduates when accounting for population size, reflecting geographic disparities in workforce distribution. These findings underscore the necessity for structured partnerships between health departments and educational institutions and advocacy for adaptive policy changes to align educational outputs with labor market demands, essential for a resilient public health workforce.</p>","PeriodicalId":94025,"journal":{"name":"Health affairs scholar","volume":"2 10","pages":"qxae116"},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11450470/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142383063","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}
Health affairs scholarPub Date : 2024-09-11eCollection Date: 2024-09-01DOI: 10.1093/haschl/qxae114
Sayeh Nikpay, Zhanji Zhang, Pinar Karaca-Mandic
{"title":"Return on investments in social determinants of health interventions: what is the evidence?","authors":"Sayeh Nikpay, Zhanji Zhang, Pinar Karaca-Mandic","doi":"10.1093/haschl/qxae114","DOIUrl":"https://doi.org/10.1093/haschl/qxae114","url":null,"abstract":"<p><p>There has been an increasing recognition of the importance and the value of addressing social determinants of health (SDOH) to improve population health outcomes, manage health care costs, and reduce health inequities. Despite the strong interest in investing in SDOH initiatives by various stakeholders, the literature on the return from such investments is scarce. The differences in study populations and methodologies, and the lack of data on SDOH intervention outcomes and/or costs, make it challenging to quantify and generalize outcomes for decision-making. We reviewed the literature on SDOH interventions focused on food and housing insecurity, and developed a methodology for estimating a key outcome: the return on investment (ROI), defined as the net returns from an intervention divided by its costs. The ROI estimates we report can be used by stakeholders to prioritize among alternative SDOH interventions for fundraising, investing, and implementing purposes. The average ROI for food-insecurity programs was 85% (ranging from 1% to 287%; except for 1 study's ROI, -31%) and for housing-insecurity programs was 50% (ranging from 5% to 224%; except for 1 ROI, -38%). In addition, these estimates can serve as key inputs for designing and employing innovative financing and policy solutions to increase the use of these interventions.</p>","PeriodicalId":94025,"journal":{"name":"Health affairs scholar","volume":"2 9","pages":"qxae114"},"PeriodicalIF":0.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11425055/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142335144","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}
Health affairs scholarPub Date : 2024-09-09eCollection Date: 2024-09-01DOI: 10.1093/haschl/qxae111
Ching-Hsuan Lin, Tara A Lavelle, Marie C Phillips, Abigail G Riley, Daniel Ollendorf
{"title":"Public deliberation on health gain measures.","authors":"Ching-Hsuan Lin, Tara A Lavelle, Marie C Phillips, Abigail G Riley, Daniel Ollendorf","doi":"10.1093/haschl/qxae111","DOIUrl":"https://doi.org/10.1093/haschl/qxae111","url":null,"abstract":"<p><p>Researchers and decision-makers use health gain measures to assess the value of health interventions. However, our current understanding of how these measures are understandable and accessible to the community is limited. This study examined a diverse group of stakeholders' attitudes and preferences for 9 commonly used health gain measures. We recruited 20 stakeholders, including patients, caregivers, pharmacists, allied health professionals, and citizens. We conducted 2 in-person deliberative meetings in which participants learned, discussed, deliberated on, and ranked 9 health gain measures. The final ranking conducted after unified deliberation showed the quality-adjusted life year (QALY) as the top-ranked measure, followed by the clinical benefit rating method used by the U.S. Preventive Services Task Force, and multicriteria decision analysis (MCDA). We identified 3 themes during deliberations: the importance of using patient values in population-based health gain measures, examining complementary measures together, and choosing measures that are intuitive and easy to understand. Future policymaking should consider incorporating the QALY, clinical benefit rating, and MCDA into prioritization decisions.</p>","PeriodicalId":94025,"journal":{"name":"Health affairs scholar","volume":"2 9","pages":"qxae111"},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11412319/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142304621","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}
Health affairs scholarPub Date : 2024-09-09eCollection Date: 2024-09-01DOI: 10.1093/haschl/qxae110
Jane M Zhu, Aine Huntington, Simon Haeder, Courtney Wolk, K John McConnell
{"title":"Insurance acceptance and cash pay rates for psychotherapy in the US.","authors":"Jane M Zhu, Aine Huntington, Simon Haeder, Courtney Wolk, K John McConnell","doi":"10.1093/haschl/qxae110","DOIUrl":"10.1093/haschl/qxae110","url":null,"abstract":"<p><p>Cost and insurance coverage remain important barriers to mental health care, including psychotherapy and mental health counseling services (\"psychotherapy\"). While data are scant, psychotherapy services are often delivered in private practice settings, where providers frequently do not take insurance and instead rely on direct pay. In this cross-sectional analysis, we use a large national online directory of 175 083 psychotherapy providers to describe characteristics of private practice psychotherapy providers who accept and do not accept insurance, and assess self-reported private pay rates. Overall, about one-third of private practice psychotherapists did not accept insurance, with insurance acceptance varying substantially across states. We also found significant session rate differentials, with Medicaid rates being on average 40% lower than reported cash pay rates, which averaged $143.26 a session. Taken together, low insurance acceptance across a broad swath of mental health provider types means that access to care is disproportionately reliant on patients' ability to afford out-of-pocket payments-even when covered by insurance. While our findings are descriptive and may not be representative of all US psychotherapists, they add to scant existing knowledge about the cash pay market for an important mental health service that has experienced increased use and demand over time.</p>","PeriodicalId":94025,"journal":{"name":"Health affairs scholar","volume":"2 9","pages":"qxae110"},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11412241/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142304694","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}
Health affairs scholarPub Date : 2024-09-09eCollection Date: 2024-09-01DOI: 10.1093/haschl/qxae112
Aimee Afable, Margaret Salisu, Tenya Blackwell, Anthony Divittis, Mark Hoglund, Gwendolyn Lewis, Carla Boutin-Foster, Montgomery Douglas
{"title":"Community design of the Brooklyn Health Equity Index.","authors":"Aimee Afable, Margaret Salisu, Tenya Blackwell, Anthony Divittis, Mark Hoglund, Gwendolyn Lewis, Carla Boutin-Foster, Montgomery Douglas","doi":"10.1093/haschl/qxae112","DOIUrl":"https://doi.org/10.1093/haschl/qxae112","url":null,"abstract":"<p><p>Health equity drives quality care. Few reliable metrics that capture patients' perceptions of health equity exist. We report on the development of a patient-centered metric for health systems change in central Brooklyn, which stands out as an outlier in New York City with a disproportionate burden of poverty, disease, and death. A community-engaged, sequential, mixed-methods research design was used. Qualitative interviews were conducted with 80 community and health care stakeholders across central Brooklyn. Candidate items were derived from qualitative themes and examined for face, interpretive validity, and language. Interitem reliability and confirmatory factor analysis was assessed using data collected via text and automated discharge calls among 368 patients from a local hospital. Qualitative data analysis informed the content of 11 draft questions covering 3 broad domains: trust-building, provider appreciation of social determinants of health, and experiences of discrimination. Psychometric testing resulted in a Cronbach's alpha of 0.774 and led to deletion of 1 item, resulting in a 10-item Brooklyn Health Equity Index (BKHI). The 10-item BKHI is a novel, brief, and reliable measure that captures patients' perceptions of inequities and offers a real-time measure for health systems and payors to monitor progress toward advancing health equity.</p>","PeriodicalId":94025,"journal":{"name":"Health affairs scholar","volume":"2 9","pages":"qxae112"},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11412247/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142304691","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}
Health affairs scholarPub Date : 2024-08-30eCollection Date: 2024-09-01DOI: 10.1093/haschl/qxae108
Ayse Akincigil, Divya Bhagianadh, Clara J Scher, Ceara Somerville, Caitlin Coyle, Natalie E Pope, Emily A Greenfield
{"title":"Dementia-focused programs in older adult centers and health care use among individuals with dementia.","authors":"Ayse Akincigil, Divya Bhagianadh, Clara J Scher, Ceara Somerville, Caitlin Coyle, Natalie E Pope, Emily A Greenfield","doi":"10.1093/haschl/qxae108","DOIUrl":"10.1093/haschl/qxae108","url":null,"abstract":"<p><p>There is growing attention to community-based services for preventing adverse health care outcomes among people aging with dementia. We explored whether the availability of dementia-centered programming within older adult centers (ie, senior centers)-specifically, adult day services (ADS), social adult day centers (SADCs), memory cafes, and caregiver support-is associated with reduced hospitalization, emergency room use, and total Medicare costs for community-dwelling individuals ages 75 and older with Alzheimer's disease and related dementias (ADRD), and whether associations differ by the relative size of the local jurisdiction. We used a novel dataset that links Medicare claims data with data from an organizational census of municipally based Massachusetts older adult centers. Living in a community with an older adult center that facilitates access to ADS and/or SADCs was associated with reduced hospital utilization and costs among residents in smaller jurisdictions. We found no evidence for associations concerning memory cafes or support groups. These findings underscore the potential of older adult centers in curbing health care costs and acute care usage among individuals with ADRD, particularly in smaller communities with centers that provide access to ADS.</p>","PeriodicalId":94025,"journal":{"name":"Health affairs scholar","volume":"2 9","pages":"qxae108"},"PeriodicalIF":0.0,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11416040/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142304693","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}
Health affairs scholarPub Date : 2024-08-28eCollection Date: 2024-09-01DOI: 10.1093/haschl/qxae109
David R Steffen, David D Kim
{"title":"The effects of SNAP emergency allotments on state-level SNAP benefits and enrollment during the COVID-19 pandemic.","authors":"David R Steffen, David D Kim","doi":"10.1093/haschl/qxae109","DOIUrl":"https://doi.org/10.1093/haschl/qxae109","url":null,"abstract":"<p><p>During the COVID-19 pandemic, all US states provided emergency allotments (EA) to enrollees of the Supplemental Nutrition Assistance Program (SNAP) to alleviate rising food insecurity. However, 18 states opted out of the SNAP-EA program before its official expiration in February 2023. Using a staggered difference-in-differences model to account for state-level variation in the timing of the SNAP-EA opt-out decisions, we analyzed SNAP and SNAP-EA data from the US Department of Agriculture Food and Nutrition Service to quantify the impact of state opt-out decisions on SNAP benefit size and enrollment. We found that the average SNAP monthly benefit among 18 SNAP opt-out states was reduced by $183 (95% confidence interval [CI]: -$214, -$152) per beneficiary. The percentage of the state population enrolled in the SNAP program among the opt-out states modestly decreased by 0.35 (95% CI: -0.61, -0.10) percentage points. Additionally, we employed logistic regression models to associate state opt-out decisions with state-level characteristics. We found that the state governor's political party being Republican was the only significant predictor for the state's opt-out decisions. Our findings help explain why opting out of SNAP-EA has been associated with higher food insufficiency and shed light on the impact of political decisions to opt out of SNAP-EA on the lives of millions of Americans.</p>","PeriodicalId":94025,"journal":{"name":"Health affairs scholar","volume":"2 9","pages":"qxae109"},"PeriodicalIF":0.0,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11426163/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142335166","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}