American Journal of Managed Care最新文献

{"title":"The health information technology special issue: evolving tech, fundamental methods.","authors":"Courtney R Lyles","doi":"10.37765/ajmc.2025.89694","DOIUrl":"https://doi.org/10.37765/ajmc.2025.89694","url":null,"abstract":"<p><p>A letter from the guest editor highlights how the findings in this special issue touch on timely themes in health technology research and yield real-world considerations for practice.</p>","PeriodicalId":50808,"journal":{"name":"American Journal of Managed Care","volume":"31 3","pages":"108"},"PeriodicalIF":2.5,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143575960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Demographic disparities in video visit telemetry: understanding telemedicine utilization.","authors":"Daniel Stein, Mark L Moubarek, Jeffrey Fine, Jeffery Wajda, Mark Avdalovic","doi":"10.37765/ajmc.2025.89699","DOIUrl":"https://doi.org/10.37765/ajmc.2025.89699","url":null,"abstract":"<p><strong>Objectives: </strong>To investigate demographic disparities in failed episodes of telemedicine utilization. The primary hypothesis was that certain demographic groups, including older adults and specific racial or ethnic groups, would experience disparate amounts of failed video visits.</p><p><strong>Study design: </strong>A retrospective review was conducted using electronic health record-integrated scheduled telehealth video visit telemetry data gathered for all video visits at a California academic health center from September 1, 2020, to November 30, 2020. For each visit, we collected demographics including age, sex, ethnicity, primary language, and race.</p><p><strong>Methods: </strong>Outcomes were categorized as successful or failed based on review of telemetry data. Successful visits were defined as simultaneous connections and completion of video visit, whereas failed visits were defined as provider-reported failure or lack of simultaneous connections for the telemedicine visit. Binomial generalized logistic regression using a generalized estimating equation approach was used to assess the impact of demographic factors on video visit success. Of 47,065 scheduled telemedicine video visits, telemetry data were available for 30,996; the 16,069 visits excluded from the study were due to no-shows, cancellations, or a nonintegrated solution being utilized.</p><p><strong>Results: </strong>Of 30,996 visits included in the study, 27,273 were successfully completed. Analysis of the 3723 failed visits revealed that older adults and African American/Black patients were more likely to experience failed video visits, with ORs of 2.02 and 1.56, respectively.</p><p><strong>Conclusions: </strong>This study highlights the significant demographic disparities in failed video visit occurrence caused by technical failure as demonstrated by telemetry data. These findings highlight the need for targeted interventions and opportunity for improved outcomes.</p>","PeriodicalId":50808,"journal":{"name":"American Journal of Managed Care","volume":"31 3","pages":"e69-e73"},"PeriodicalIF":2.5,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143576001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The \"new\" new normal: changes in telemedicine utilization since COVID-19.","authors":"Soumik Mandal, Batia M Wiesenfeld, Devin M Mann, Oded Nov","doi":"10.37765/ajmc.2025.89700","DOIUrl":"https://doi.org/10.37765/ajmc.2025.89700","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate trends in telemedicine utilization overall and across clinical specialties, providing insights into its evolving role in health care delivery.</p><p><strong>Study design: </strong>This retrospective cross-sectional study analyzed 1.9 million telemedicine video visits from a large academic health care system in New York City between 2020 and 2023. The data, collected from the health care system's electronic health records, included telemedicine encounters across more than 500 ambulatory locations.</p><p><strong>Methods: </strong>We used descriptive statistics to outline telemedicine usage trends and compared telemedicine utilization rates and evaluation and management characteristics across clinical specialties.</p><p><strong>Results: </strong>Telemedicine utilization peaked during the COVID-19 pandemic, then declined and stabilized. Despite an overall decline, 2 non-primary care specialties (behavioral health and psychiatry) experienced continued growth in telemedicine visits. Primary care and urgent care visits were mainly characterized by low-complexity visits, whereas non-primary care specialties witnessed a rise in moderate- and high-complexity visits, with the number of moderate-level visits surpassing those of low complexity.</p><p><strong>Conclusions: </strong>The findings highlight a dynamic shift in telemedicine utilization, with non-primary care settings witnessing an increase in the complexity of cases. To address future demands from increasingly complex medical cases managed through telemedicine in non-primary care, appropriate resource allocation is essential.</p>","PeriodicalId":50808,"journal":{"name":"American Journal of Managed Care","volume":"31 3","pages":"e74-e78"},"PeriodicalIF":2.5,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143575957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Managed care reflections: a Q&A with Julia Adler-Milstein, PhD.","authors":"Julia Adler-Milstein, Christina Mattina","doi":"10.37765/ajmc.2025.89693","DOIUrl":"https://doi.org/10.37765/ajmc.2025.89693","url":null,"abstract":"<p><p>To mark the 30th anniversary of The American Journal of Managed Care, each issue in 2025 includes reflections from a thought leader on what has changed over the past 3 decades and what's next for managed care. The March issue, which is our annual health information technology (IT) theme issue, features a conversation with Julia Adler-Milstein, PhD, professor of medicine at the University of California, San Francisco, and guest editor of the 2014 health IT issue.</p>","PeriodicalId":50808,"journal":{"name":"American Journal of Managed Care","volume":"31 3","pages":"106-107"},"PeriodicalIF":2.5,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143576004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reducing readmissions in the safety net through AI and automation.","authors":"Daniel J Bennett, Jean Feng, Seth Goldman, Avni Kothari, Laura M Gottlieb, Matthew S Durstenfeld, James Marks, Susan Ehrlich, Jonathan Davis, Lucas S Zier","doi":"10.37765/ajmc.2025.89697","DOIUrl":"https://doi.org/10.37765/ajmc.2025.89697","url":null,"abstract":"<p><strong>Objectives: </strong>To implement a technology-based, systemwide readmission reduction initiative in a safety-net health system and evaluate clinical, care equity, and financial outcomes.</p><p><strong>Study design: </strong>Retrospective interrupted time series analysis between October 2015 and January 2023.</p><p><strong>Methods: </strong>The readmission reduction initiative standardized inpatient care for patients through a novel, electronic health record-integrated, digitally automated point-of-care decision-support tool. A predictive artificial intelligence algorithm was utilized to identify patients at the highest risk of readmission in both the inpatient and outpatient settings, allowing a population health team to perform proactive outpatient management in medical and social domains to avoid readmission.</p><p><strong>Results: </strong>Readmission rates declined from 27.9% in the preimplementation period to 23.9% in the postimplementation period ( P  < .004) by the end of 2023. A significant gap in readmission rates between Black/African American patients and the general population was eliminated over the course of the evaluation period. Survival analysis demonstrated a reduction in all-cause mortality in the postimplementation period (HR, 0.82; 95% CI, 0.68-0.99; P  = .037). Improvement in readmission rates allowed the health system to retain $7.2 million of at-risk pay-for-performance funding.</p><p><strong>Conclusions: </strong>This technology-based readmission reduction initiative demonstrated efficacy in reducing readmission rates, closing equity gaps, improving survival, and leading to a positive financial impact in a safety-net health system. This approach could be an effective model of technology-based, value-based care for other resource-limited health systems to meet pay-for-performance metrics and retain at-risk funding while improving clinical and equity outcomes.</p>","PeriodicalId":50808,"journal":{"name":"American Journal of Managed Care","volume":"31 3","pages":"142-148"},"PeriodicalIF":2.5,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143575956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Health equity in the era of large language models.","authors":"Aaron A Tierney, Mary E Reed, Richard W Grant, Florence X Doo, Denise D Payán, Vincent X Liu","doi":"10.37765/ajmc.2025.89695","DOIUrl":"https://doi.org/10.37765/ajmc.2025.89695","url":null,"abstract":"<p><p>This commentary presents a summary of 8 major regulations and guidelines that have direct implications for the equitable design, implementation, and maintenance of health care-focused large language models (LLMs) deployed in the US. We grouped key equity issues for LLMs into 3 domains: (1) linguistic and cultural bias, (2) accessibility and trust, and (3) oversight and quality control. Solutions shared by these regulations and guidelines are to (1) ensure diverse representation in training data and in teams that develop artificial intelligence (AI) tools, (2) develop techniques to evaluate AI-enabled health care tool performance against real-world data, (3) ensure that AI used in health care is free of discrimination and integrates equity principles, (4) take meaningful steps to ensure access for patients with limited English proficiency, (5) apply AI tools to make workplaces more efficient and reduce administrative burdens, (6) require human oversight of AI tools used in health care delivery, and (7) ensure AI tools are safe, accessible, and beneficial while respecting privacy. There is an opportunity to prevent further embedding of existing disparities and issues in the health care system by enhancing health equity through thoughtfully designed and deployed LLMs.</p>","PeriodicalId":50808,"journal":{"name":"American Journal of Managed Care","volume":"31 3","pages":"112-117"},"PeriodicalIF":2.5,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143576003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-world digitally based diabetes management program implementation by a large employer.","authors":"Jean M Abraham, Teresa Ambroz, Megan Chacon, Renée S M Kidney, Helen M Parsons","doi":"10.37765/ajmc.2025.89698","DOIUrl":"https://doi.org/10.37765/ajmc.2025.89698","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate the implementation of a digitally based diabetes management program by a large, self-insured employer in Minnesota from May 2021 to April 2022.</p><p><strong>Study design: </strong>Descriptive analysis.</p><p><strong>Methods: </strong>We described the development, implementation, and effectiveness of a communications strategy to promote program enrollment in the initial year. Using administrative claims data, we analyzed the demographic and clinical attributes associated with an eligible member's enrollment. Finally, we empirically assessed whether expanding the choice of modalities through which enrollees accessed diabetes self-management education and support (DSMES) increased overall utilization and addressed geographic disparities.</p><p><strong>Results: </strong>Although digital health program applications responded to the timing of the communications campaigns, overall program enrollment in absolute terms was low compared with the size of the eligible population. Among those eligible, female and employee subscribers were more likely to enroll. Overall, DSMES use increased slightly during the initial year, but we did not observe significantly higher rates of use among members in rural areas following the digital health program launch.</p><p><strong>Conclusions: </strong>This study offers new insights to employers and health plans related to supporting digitally based disease management program implementation and enrollee engagement.</p>","PeriodicalId":50808,"journal":{"name":"American Journal of Managed Care","volume":"31 3","pages":"e62-e68"},"PeriodicalIF":2.5,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143575955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Facilitators of and barriers to Medicaid investment in electronic consultation services.","authors":"Julie E Kim, Libby Sagara, Alison M DeDent, Delphine S Tuot","doi":"10.37765/ajmc.2025.89696","DOIUrl":"https://doi.org/10.37765/ajmc.2025.89696","url":null,"abstract":"<p><strong>Objective: </strong>Electronic consultation, or e-consult, programs have enhanced access to specialty care for primary care providers and their patients, reducing unnecessary in-person visits and maintaining cost-effectiveness. In California, there is great variability in access to e-consult programs for low-income patients who rely on Medicaid managed care plans (MCPs) for covered benefits. This study aimed to understand MCP facilitators of and barriers to e-consult investment in California.</p><p><strong>Study design: </strong>Interviews conducted with California Medicaid MCPs' leaders to learn about the facilitators of and barriers to investment in e-consult programs.</p><p><strong>Methods: </strong>Interviews were analyzed using content analysis with multistage coding. The Exploration, Preparation, Implementation, and Sustainment framework was used to organize facilitator and barrier themes into 4 contexts: outer context (landscape of health care delivery in California), inner context (components within the medical neighborhood), innovation factors (characteristics of e-consult programs), and bridging factors (MCP actions).</p><p><strong>Results: </strong>Twelve themes emerged from 16 interviews. Outer context themes were regulatory policies and financial policies (barriers), limited specialty care (facilitator), and patient perceptions (both). Inner context themes were workforce characteristics (both), clinical leadership (facilitator), and clinical workflows (both). Innovation factor themes were adjunct e-consult vendor services (both) and software integration (facilitator). Bridging factor themes included collaboration with other plans (facilitator), financial risk delegation (barrier), and quality improvement considerations (facilitator).</p><p><strong>Conclusions: </strong>Medicaid regulatory and reimbursement policies posed the most significant barriers to e-consult investment by Medicaid MCPs in California. Recognition of e-consult as a mode of specialty care delivery and reimbursement for clinicians could help future e-consult programs succeed in enhancing access to specialty expertise for low-income patients.</p>","PeriodicalId":50808,"journal":{"name":"American Journal of Managed Care","volume":"31 3","pages":"128-135"},"PeriodicalIF":2.5,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143576002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Racial and ethnic disparities in telemental health use among publicly insured children.","authors":"Xin Hu, Ilana Graetz, Jordan Gilleland Marchak, Ann C Mertens, Xu Ji, Janet R Cummings","doi":"10.37765/ajmc.2025.89674","DOIUrl":"https://doi.org/10.37765/ajmc.2025.89674","url":null,"abstract":"<p><strong>Objectives: </strong>The COVID-19 pandemic propelled telemental health utilization among children seeking mental health (MH) services. We examined racial and ethnic disparities in telemental health use among publicly insured children before and following COVID-19.</p><p><strong>Methods: </strong>We identified 36,877,141 child-year observations among publicly insured children aged 3 to 17 years with MH-related encounters in a given year from 2016 to 2020. Multivariable linear regressions controlling for individual- and county-level confounders estimated changes in telemental health use before (2016-2019) and following the pandemic (2020) and how these changes differed by individual- and county-level race and ethnicity.</p><p><strong>Results: </strong>The percentage of publicly insured children using telemental health increased from 2.74% pre-COVID-19 to 35.90% in 2020. Among non-Hispanic White children, 3.41% used telemental health care pre-COVID-19, which increased by 36.49 percentage points (PP) in 2020. Non-Hispanic Black children had a lower percentage of telemental health use (2.50%) pre-COVID-19, which increased by 31.20 PP in 2020, resulting in a 5.39 PP smaller increase than non-Hispanic White children (P < .001). Similarly, Hispanic, non-Hispanic Asian, and non-Hispanic Pacific Islander children had 6.19 PP, 15.45 PP, and 12.10 PP smaller increases in telemental health use in 2020 compared with non-Hispanic White children (all P < .001). Moreover, children in counties with the highest (vs lowest) quartiles of non-Hispanic Black and Hispanic populations had lower pre-COVID-19 telemental health use and smaller increases in 2020 (all P < .001).</p><p><strong>Conclusions: </strong>Racial and ethnic disparities in telemental health use widened following COVID-19. Future research should evaluate how telemental health use impacted MH care quality and outcomes among publicly insured children.</p>","PeriodicalId":50808,"journal":{"name":"American Journal of Managed Care","volume":"31 3","pages":"119-126"},"PeriodicalIF":2.5,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143575954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bundled payment impacts uptake of prescribed home health care.","authors":"Jun Li, Lacey Loomer","doi":"10.37765/ajmc.2025.89677","DOIUrl":"https://doi.org/10.37765/ajmc.2025.89677","url":null,"abstract":"<p><strong>Objective: </strong>To determine whether the CMS Comprehensive Care for Joint Replacement (CJR) Model, which incentivizes coordinated and efficient care, increased home health care (HHC) uptake among patients referred to HHC after major joint replacement surgery.</p><p><strong>Study design: </strong>Cohort study using a difference-in-differences design comparing hospitals in 75 metropolitan statistical areas randomized into CJR by CMS with non-CJR hospitals in 119 areas as controls.</p><p><strong>Methods: </strong>The primary outcome was the case mix-adjusted, hospital-level HHC uptake rate, which is the rate of patients referred to HHC at hospital discharge receiving an HHC visit within 14 days. Secondary outcomes included HHC uptake rate by race/ethnicity and the quality of HHC agencies used among referrals, which was measured by agency-level improvement in ambulation, unplanned hospitalizations, emergency department visits, time to the first home health visit, and distinct number of agencies.</p><p><strong>Results: </strong>After the launch of CJR, HHC uptake decreased nationally but there was a 3.73-percentage point (4.5%) lower decrease in CJR hospitals; this was driven by White patients (3.54-percentage point differential; P = .026). A marginally statistically significant (P = .054) 5.05-percentage point differential increase for Black patients was observed due to a slight increase in the treatment group and a large decrease in the control group. There was no statistically significant change for Hispanic or Asian American/Pacific Islander populations. No statistically significant increases were observed in the quality of HHC used.</p><p><strong>Conclusions: </strong>CJR mitigated a trend of decreased HHC uptake, but more work is needed to improve uptake for larger portions of the patient population. Our results suggest that addressing care coordination incentives via CJR may mitigate some racial disparities.</p>","PeriodicalId":50808,"journal":{"name":"American Journal of Managed Care","volume":"31 2","pages":"66-73"},"PeriodicalIF":2.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143469971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}