Medical Care最新文献

{"title":"Anesthesia Provider Type and Veteran Satisfaction: The Authors' Reply.","authors":"Kevin N Griffith, Julia Harris, Jeffrey Darna, Richard P Dutton, Hillary J Mull","doi":"10.1097/MLR.0000000000002314","DOIUrl":"https://doi.org/10.1097/MLR.0000000000002314","url":null,"abstract":"","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147690977","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}

{"title":"RE: Compliance With Recommendations of the Surveillance, Epidemiology, and End Results (SEER) Treatment Data Use Agreement.","authors":"Jason Semprini","doi":"10.1097/MLR.0000000000002329","DOIUrl":"https://doi.org/10.1097/MLR.0000000000002329","url":null,"abstract":"","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2026-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147674967","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}

{"title":"Response to Letter to the Editor: Compliance With Recommendations of the Surveillance, Epidemiology, and End Results (SEER) Treatment Data Use Agreement: A Review of Published Studies.","authors":"Yoon Duk Hong, Angela B Mariotto, Denise R Lewis, Anne-Michelle Noone, Nadia Howlader, Steve Scoppa, Eric J Feuer","doi":"10.1097/MLR.0000000000002327","DOIUrl":"https://doi.org/10.1097/MLR.0000000000002327","url":null,"abstract":"","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2026-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147675052","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}

{"title":"Comparing Approaches to Identify Mobile Crisis Services in Medicaid Administrative Claims.","authors":"Andrew Anderson, Brigham Walker, Alene Kennedy-Hendricks, Jingwei Maggie Li, Mathew Eisenberg, Karen Shen","doi":"10.1097/MLR.0000000000002317","DOIUrl":"https://doi.org/10.1097/MLR.0000000000002317","url":null,"abstract":"<p><strong>Background: </strong>Mobile crisis services offer a community-based alternative to law enforcement and emergency departments for individuals experiencing behavioral health crises. Medicaid claims represent a promising but underused tool for national surveillance of these services. Despite growing federal investment and expansion of crisis response systems, there is no standardized method for identifying mobile crisis encounters in administrative claims, limiting the ability to monitor access, evaluate implementation, or compare delivery across states.</p><p><strong>Objective: </strong>To develop and evaluate claims-based approaches for identifying mobile crisis service delivery in Medicaid administrative data.</p><p><strong>Methods: </strong>We conducted a cross-sectional analysis of 2021 Medicaid claims from the Transformed Medicaid Statistical Information System Analytic Files. We used the 2022 KFF Behavioral Health Services Survey data as the most recent standardized benchmark for Medicaid mobile crisis coverage. We tested 3 claims-based identification approaches that combine national and state-specific procedure codes (eg, H2011) with mobile-relevant place-of-service (POS) codes: strict [POS 15 (mobile unit)], moderate [POS 15 (mobile unit), POS 12 (home), or POS 04 (homeless shelter)], and inclusive [POS 15, POS 12, POS 04, or POS 99 (other)]. We additionally constructed a claims-based score summarizing state-level use of mobile-relevant POS codes and examined its alignment with reported coverage in exploratory analyses.</p><p><strong>Results: </strong>Among 44 states and the District of Columbia with complete survey data, 33 reported Medicaid coverage of mobile crisis services. We identified 97,088 claims under the strict approach, 395,141 under the moderate approach, and 1,152,653 under the inclusive approach. Across all approaches, states reporting coverage had higher median claim counts than noncoverage states, though substantial overlap remained. Under the strict approach, median claim counts were 0 in both coverage and noncoverage states. The moderate approach demonstrated the greatest separation (median, 1324 vs. 364), while the inclusive approach captured larger volumes overall but with greater overlap between groups. Predicted probabilities derived from a claims-based score increased monotonically across score values, indicating stronger directional alignment with reported coverage at higher score levels.</p><p><strong>Conclusion: </strong>A claims-based approach combining mobile unit (POS 15), home (POS 12), and homeless shelter (POS 04) codes with crisis intervention procedure codes provides a practical framework for identifying billed mobile crisis encounters in Medicaid data. This moderate approach showed the strongest directional alignment with state-reported coverage and may support cross-state monitoring of crisis service delivery. Further work is needed to validate these methods using provider-level or encounter-l","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2026-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147623270","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}

{"title":"Use of Telemental Health Care by Adults in the United States.","authors":"Mark Olfson, Chandler McClellan, Samuel H Zuvekas, Carlos Blanco","doi":"10.1097/MLR.0000000000002290","DOIUrl":"https://doi.org/10.1097/MLR.0000000000002290","url":null,"abstract":"<p><strong>Background: </strong>Although the recent proliferation of telemental health care has transformed delivery of outpatient mental health care for many patients, little is known about population-level access to telehealth, hybrid, and in-person outpatient mental health care in the US.</p><p><strong>Objectives: </strong>The objective of this report is to characterize patterns of all telehealth, hybrid, and all in-person outpatient mental health care by US adults.</p><p><strong>Methods: </strong>An analysis is presented of 2021-2022 Medical Expenditure Panel Survey data (n=39,561) focusing on annual percentages of adults receiving all telehealth, hybrid, and all in-person outpatient mental health care. Results are presented overall and stratified by sociodemographic characteristics. Differences are reported in average marginal estimates from logistic regressions for each sociodemographic characteristic controlling for age group, sex, and psychological distress (Kessler-6).</p><p><strong>Results: </strong>Approximately 12.0% of adults annually received outpatient mental health care, including 3.3% all telemental health care, 2.6% hybrid, and 6.1% all in-person mental health care. After controlling for age, sex, and distress, unemployed adults 65 years of age or younger were less likely than employed adults to receive all mental health care (-1.0 percentage points, 95% CI: -1.6 to -0.4), and uninsured individuals were less likely than those with private insurance (-2.8 percentage points, 95% CI: -3.6 to -1.9). By contrast, college graduates were 3.2 percentage points (95% CI: 2.3-4.0) more likely than those with less than a high school diploma, higher-income individuals were 1.6 percentage points (95% CI: 0.8-2.30) more likely than those below the poverty level, and urban residents were 1.9 percentage points (95% CI: 1.1-2.7) more likely than rural residents to receive all telemental health care.</p><p><strong>Conclusions: </strong>These national patterns highlight differences in US telemental health care access across employment, education, income, insurance, and geographic groups.</p>","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":"64 4","pages":"216-220"},"PeriodicalIF":2.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147434221","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}

{"title":"Designing Cluster Randomized Trials: A Practical Guide for Investigators.","authors":"Kendra Davis-Plourde, Xiaoying Yu, Jeanne A Teresi","doi":"10.1097/MLR.0000000000002283","DOIUrl":"10.1097/MLR.0000000000002283","url":null,"abstract":"<p><strong>Background: </strong>An important consideration in the design stage of randomized controlled trials is whether individuals within each site should or can be randomized to study arms (an individually randomized controlled trial) or whether entire sites should be randomized (a cluster randomized trial) where the clusters are sites. Recently, cluster randomized trials have grown in popularity; however, investigators have expressed a need for guidelines related to selection of the best design-especially when considering more complex designs such as stepped wedge. This commentary attempts to provide such guidance.</p><p><strong>Methods: </strong>In this commentary, we address common misconceptions surrounding the appropriate use of cluster randomization and crossover designs (such as the stepped wedge design). The intracluster correlation coefficients for different levels of clustering are presented, and the impact of different designs on sample size discussed. We provide practical recommendations that are accessible to investigators from all disciplines, regardless of their level of statistical training. On the basis of these recommendations, we present a flowchart to help researchers identify a suitable trial design for their study. In addition, we provide a table of commonly used statistical definitions related to cluster randomized trials and a table of design considerations for more complex designs to support effective consultation with a statistician during the design phase.</p><p><strong>Conclusion: </strong>On the basis of these guidelines, it is recommended that researchers prioritize the use of individual randomization and a parallel trial design when the goal of the study is to assess the efficacy or effectiveness of an intervention.</p>","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":" ","pages":"179-191"},"PeriodicalIF":2.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147284325","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}

{"title":"Personal Health Goals in Homeless-Experienced Veterans: Rates, Patterns, and Associations With Health-Related Needs.","authors":"Mariana Ward, Kathryn S Macia, Paige Shaffer, Justeen Hyde, David Smelson, Daniel M Blonigen","doi":"10.1097/MLR.0000000000002291","DOIUrl":"10.1097/MLR.0000000000002291","url":null,"abstract":"<p><strong>Objective: </strong>To advance patient-centered care for high-need homeless-experienced patients, we identified the rates of various personal health goals, the broader domains that underlie these goals, and associations between these domains and the health-related needs of this population.</p><p><strong>Method: </strong>The sample consisted of 176 veterans from 3 VA Medical Centers who were enrolled in primary care, on VA's Homeless Registry, and high utilizers of acute care. An interview was conducted with each participant to collect information on their personal health goals and health-related needs. Exploratory factor analysis was used to identify broad domains underlying endorsement of personal health goals. Associations between these broad goal domains and health-related needs (substance use, mental and physical health, treatment engagement, and psychosocial) were examined using an exploratory structural equation modeling-within-confirmatory factor analysis approach.</p><p><strong>Results: </strong>Three broad domains were found to underlie the personal health goals of the sample: social functioning, health promotion, and substance use. Social functioning and health promotion were highly correlated, whereas substance use was weakly correlated with both social functioning and health promotion. All substance use-related needs were positively associated with substance use goals. Mental and physical health needs were primarily associated with health promotion goals. Treatment engagement and psychosocial needs demonstrated associations across all 3 goal domains.</p><p><strong>Conclusions: </strong>Findings highlight the high value that many high-need homeless-experienced patients place on their social well-being and the potential benefits to measuring both deficiency and growth needs in this population. Clinical implications and future directions for research are discussed.</p>","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":" ","pages":"230-238"},"PeriodicalIF":2.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12970551/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146113456","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}

{"title":"Persistent Frequent Emergency Department Use Before and During the COVID-19 Pandemic: A Longitudinal Study of One Million Users.","authors":"Theodoros V Giannouchos, Wafaa Bkheit, Hye-Chung Kum, Robert L Ohsfeldt","doi":"10.1097/MLR.0000000000002286","DOIUrl":"10.1097/MLR.0000000000002286","url":null,"abstract":"<p><strong>Objective: </strong>To examine changes in persistent emergency department (ED) use by adult frequent ED (FED) users over time comparing prepandemic versus peripandemic periods, and to identify distinct characteristics of individuals who remained FED users over time during the pandemic versus the prepandemic era.</p><p><strong>Methods: </strong>We conducted a retrospective, secondary, longitudinal analysis in Texas, following 2 cohorts of ED users over 36 months (cohort 1: March 2017-February 2020; cohort 2: March 2019-February 2022). The main outcomes were whether a baseline FED (≥9 ED visits/12 mo) user remained a FED user persistently over the next 24 months and whether they were persistent FED users prepandemic or peripandemic. Multivariable regressions estimated changes in persistent FED use across cohorts and assessed differences between individuals who remained persistent FED users during the pandemic compared with the prepandemic period.</p><p><strong>Setting: </strong>All-payer Texas Hospital ED Research Data File from 2016 to 2022.</p><p><strong>Results: </strong>About 1 million individuals had at least one ED visit in the baseline years, totaling 4.6 million visits. Overall, FED users accounted for 8% of all ED users but over 40% of visits. Although more than half of FED users at baseline exhibited persistent FED use over the next 24 months, there was a 7% decline in the proportion of return FED users after the onset of COVID-19 which was statistically significant (AOR=0.82; 95% CI=0.80-0.84), and this effect was more pronounced when patients with any COVID-19-related ED visit during the study period were excluded (AOR=0.10; 95% CI=0.09-0.11). Individuals aged 45 years or older, those with congestive heart failure and diabetes with complications, and those with public insurance (when COVID-19-related visits were excluded) had higher odds of remaining persistent FED users during the pandemic.</p><p><strong>Conclusions: </strong>Many FED users will seek ED care for multiple years, given their medical complexity. Future research should identify heterogeneous subgroups among persistent FED users to tailor interventions towards their needs.</p>","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":" ","pages":"198-206"},"PeriodicalIF":2.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146010608","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}

{"title":"Psychiatric Medication Prescribing by Nurse Practitioners and Physician Associates for Medicare Beneficiaries.","authors":"Roderick S Hooker, G Martin Reinhart, Joycelyn M Yamzon, Robert E McKenna","doi":"10.1097/MLR.0000000000002293","DOIUrl":"10.1097/MLR.0000000000002293","url":null,"abstract":"<p><strong>Background: </strong>There is a significant shortage of psychiatrists compared with the demand for their services. We studied Medicare Part D claims of psychiatrists and similar clinician prescribers to identify possible shifts in medication prescribing to address this gap.</p><p><strong>Objective: </strong>This pharmacoepidemiology study aimed to identify prescribing patterns among psychiatrists, family physicians, internists, physician associates/assistants (PAs), and nurse practitioners (NPs), as well as trends.</p><p><strong>Design: </strong>An observational, retrospective cohort study of Medicare Part D claims from 2013 to 2022 was conducted. Psychiatrists' prescription patterns were compared with those of non-psychiatrists, using the National Provider Identifier (NPI). Diagnosis information was not available in the dataset.</p><p><strong>Participants: </strong>In 2022, more than 32,400 psychiatrists' prescriptions were submitted for more than 36.6 million Medicare Part D claims for various medications.</p><p><strong>Main measures: </strong>Prescribers and medication claim counts were analyzed to determine the most commonly prescribed drugs by psychiatrists. Total psychiatrist prescription counts and trends were compared with those of primary care physicians, PAs, and NPs.</p><p><strong>Key results: </strong>Family practice physicians wrote more than 55 million prescriptions in 2022, nearly twice the number written by psychiatrists. From 2013 to 2022, prescriptions written by PAs and NPs showed a strong upward trend. In 2020, prescription claims by NPs surpassed psychiatrists, and by 2022, they had exceeded those of internal medicine physicians.</p><p><strong>Conclusions: </strong>Claims by NPs increased from 8.6% to 24.8%, whereas psychiatrists' claims decreased from 24.4% to 18.0%. As of 2023, NPs and PAs comprise a significant portion of the workforce that addresses gaps in mental health medication care for Medicare patients.</p>","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":" ","pages":"249-256"},"PeriodicalIF":2.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146086185","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}

{"title":"Risk for Acute Care Utilization in Housing-Insecure Adults: A National Study of a Hot Spotter Program in the US Veterans Health Administration.","authors":"Daniel M Blonigen, Kathryn S Macia, Ivan Raikov, Jean Yoon, Jillian Weber","doi":"10.1097/MLR.0000000000002287","DOIUrl":"10.1097/MLR.0000000000002287","url":null,"abstract":"<p><strong>Background: </strong>To identify patients at the highest risk for acute care utilization, health care systems have developed \"hot spotter\" programs. Homelessness is a robust social determinant of acute care utilization.</p><p><strong>Objectives: </strong>To describe the prevalence, patterns, and correlates of meeting criteria for a hot spotter program among housing-insecure adults in the US Veterans Health Administration (VHA).</p><p><strong>Research design: </strong>Among veterans on the VHA Homeless Registry in Fiscal Years 2018-2022 (N=1,469,893), we identified those who met criteria for a Hot Spotter Report [ie, ≥1 hospital admissions and/or ≥2 emergency department (ED) visits in at least one quarter], described their patterns of acute care use, and examined differences in patient characteristics and outpatient service use between those who met report criteria in multiple quarters (vs. one).</p><p><strong>Results: </strong>Thirty percent (N=446,974) met report criteria in at least one quarter; most (56%) met report criteria in ≥2 quarters. Diagnoses of depression (58%) and/or a substance use disorder (51%) were common; however, the rate of hospitalization in an acute medical setting during the cohort period was twice that of being hospitalized in an acute mental health setting (50% vs. 25%). Being on the Hot Spotter Report in multiple quarters (vs. one) was associated with more chronic conditions (M=5.08 vs. 3.29), higher rates of suicidality (23.7% vs. 11.7%), and higher likelihood of all types of outpatient care ( P <0.0001).</p><p><strong>Conclusions: </strong>Given rates of chronic medical conditions and medical hospitalizations, it may behoove hot spotter programs to increase care coordination with medical respite programs to support patients in the postacute phase.</p>","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":" ","pages":"207-215"},"PeriodicalIF":2.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12970552/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145970798","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}