American Journal of Managed Care最新文献

{"title":"Plan Switching Among Medicare Advantage Enrollees Dually Eligible for Medicaid.","authors":"Grace Mackleby, Angela Liu, Erin Trish","doi":"10.37765/ajmc.2026.90004","DOIUrl":"https://doi.org/10.37765/ajmc.2026.90004","url":null,"abstract":"<p><strong>Objectives: </strong>Despite making up 21% of Medicare enrollment, little is known about how frequently enrollees dually eligible (DE) for full or partial Medicaid benefits switch to other Medicare Advantage (MA) plans. Statutorily, DE beneficiaries can switch often, potentially facilitating better choices but also potentially disrupting care continuity. We compared switching patterns by dual-eligibility status and other characteristics.</p><p><strong>Study design: </strong>We present trends using 2016-2022 administrative enrollment data and test for differences in switching behavior by enrollee characteristics, separated by DE status.</p><p><strong>Methods: </strong>We characterized the share of fully dually eligible beneficiaries (FDEs), partially dually eligible beneficiaries (PDEs), and non-dually eligible beneficiaries (NDEs) who made an MA-to-MA or MA-to-traditional Medicare (TM) switch each year. We tested for differences in MA-to-MA and MA-to-TM switching rates across enrollee risk score and demographic groups.</p><p><strong>Results: </strong>Between 2016 and 2022, the share of MA enrollees who voluntarily switched to a different MA plan increased from 12.49% to 22.49% among FDEs, 17.36% to 30.11% among PDEs, and 9.92% to 13.39% among NDEs. By contrast, only 3.73%, 1.62%, and 0.91% of 2022 FDEs, PDEs, and NDEs switched to TM, respectively. Switching rates varied by age and race/ethnicity.</p><p><strong>Conclusions: </strong>Although MA-to-TM switching is rare, MA-to-MA switching has become increasingly prevalent, especially among DE beneficiaries, meaning an increasing share is likely to change provider networks and other plan aspects. Given the distinct patterns of MA-to-MA switching among DEs, further research is needed to assess the determinants of switching and its implications for health care quality and costs in this population.</p>","PeriodicalId":50808,"journal":{"name":"American Journal of Managed Care","volume":"32 9","pages":"487-490"},"PeriodicalIF":2.1,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149082608","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":"SGLT2 Inhibitor Adherence and Diabetes Hospitalization Risk in Type 2 Diabetes.","authors":"Udim Damachi, Godwin Okoye, Wendy Camelo Castillo, Susan dosReis","doi":"10.37765/ajmc.2026.89950","DOIUrl":"https://doi.org/10.37765/ajmc.2026.89950","url":null,"abstract":"<p><strong>Objectives: </strong>Emerging evidence shows that sodium-glucose cotransporter 2 (SGLT2) inhibitors improve glycemic control and reduce the risk of cardiovascular-related mortality. This is contingent on adherence, yet evidence of SGLT2 inhibitor adherence and associated diabetes-related clinical outcomes in real-world settings is lacking. Therefore, we examined SGLT2 inhibitor longitudinal adherence trajectories and their association with the risk of diabetes-related hospitalizations.</p><p><strong>Study design: </strong>SGLT2 inhibitor new-user retrospective cohort study using a 25% random sample of IQVIA PharMetrics Plus for Academics US health plan claims, 2014 to 2022.</p><p><strong>Methods: </strong>We included new users of SGLT2 inhibitors who had type 2 diabetes with prior cardiovascular disease or risk factors. Group-based trajectory modeling identified SGLT2 inhibitor adherence subgroups using monthly proportions of days covered over the 12 months post SGLT2 inhibitor initiation. Cox proportional hazards models, adjusted for baseline covariates, estimated the HRs for diabetes-related hospitalizations/emergency department (ED) visits in the year following 12-month treatment with SGLT2 inhibitors.</p><p><strong>Results: </strong>We classified 5051 new SGLT2 inhibitor users into 5 SGLT2 inhibitor adherence trajectory groups: nonadherent (14.7%), early decline (13.5%), late decline (10.5%), dynamic adherence (13.0%), and adherent (48.3%). A diabetes-related hospitalization/ED visit occurred in 2.3% of the overall cohort, with a median (IQR) time to event of 151.5 (76-263) days. In the adjusted Cox proportional hazards model, the late decline group (HR, 2.52; 95% CI, 1.38-4.60) and the dynamic adherence group (HR, 2.42; 95% CI, 1.52-3.86) had a statistically significantly greater risk of diabetes-related hospitalizations/ED visits than the adherent group.</p><p><strong>Conclusions: </strong>These findings suggest that variable adherence to SGLT2 inhibitors can negatively impact diabetes-related outcomes.</p><p><strong>Objectives: </strong>Emerging evidence shows that sodium-glucose cotransporter 2 (SGLT2) inhibitors improve glycemic control and reduce the risk of cardiovascular-related mortality. This is contingent on adherence, yet evidence of SGLT2 inhibitor adherence and associated diabetes-related clinical outcomes in real-world settings is lacking. Therefore, we examined SGLT2 inhibitor longitudinal adherence trajectories and their association with the risk of diabetes-related hospitalizations.</p>","PeriodicalId":50808,"journal":{"name":"American Journal of Managed Care","volume":"32 9","pages":"492-499"},"PeriodicalIF":2.1,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149082693","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":"Letter Regarding \"The Relationship Between Preventive Dental Care and Overall Medical Expenditures\".","authors":"Jiayi Chen","doi":"10.37765/ajmc.2026.89944","DOIUrl":"https://doi.org/10.37765/ajmc.2026.89944","url":null,"abstract":"<p><p>This letter emphasizes the need for rigorous study designs, particularly quasi-experimental methods, to accurately assess the causal impact of preventive health services on health care utilization and costs.</p>","PeriodicalId":50808,"journal":{"name":"American Journal of Managed Care","volume":"32 9","pages":"e300-e301"},"PeriodicalIF":2.1,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149082349","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":"Examining the Distinct Effects of Structural, Financial, and Information-Sharing Integration on Hospital Costs.","authors":"Na-Eun Cho","doi":"10.37765/ajmc.2026.89945","DOIUrl":"https://doi.org/10.37765/ajmc.2026.89945","url":null,"abstract":"<p><strong>Objective: </strong>Hospitals are pursuing integration strategies to contain costs, but evidence remains limited. This study examined the independent associations of 3 forms of integration-structural, financial, and information sharing-with hospital costs.</p><p><strong>Study design: </strong>Hospital fixed-effects panel regression using data from multiple sources-CMS Hospital Compare, Let's Get Healthy California, and the American Hospital Association Annual Surveys and Information Technology Supplements-for years 2014-2016.</p><p><strong>Methods: </strong>Three integration dimensions were measured: (1) structural integration (health maintenance organization [HMO] participation rate, hospital physician employment/foundation models, and system affiliation); (2) financial integration (% of the hospital's net patient revenue paid on a shared-risk basis); and (3) information-sharing integration (use of electronic patient data received from outside sources). Hospital fixed-effects regressions with 2-way clustering by hospital and county were estimated to assess within-hospital changes in spending associated with each dimension, controlling for 3 ownership types and size.</p><p><strong>Results: </strong>Financial integration was associated with lower hospital spending, whereas structural and information-sharing integration showed no independent association. Considered jointly, the 3 integration dimensions were statistically significant as a group. These findings were robust to alternative specifications, including excluding HMO participation from the structural index, orthogonalizing financial integration to the other dimensions, and measuring information-sharing integration by the extent. Additional checks found no evidence that capitation adoption or the capitation share of revenue was related to lower spending.</p><p><strong>Conclusions: </strong>These findings suggest that carefully designed financial incentives should be prioritized when implementing integration measures in policy and practice.</p>","PeriodicalId":50808,"journal":{"name":"American Journal of Managed Care","volume":"32 9","pages":"516-520"},"PeriodicalIF":2.1,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149082898","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":"Pilot Testing the Johns Hopkins Early Discharge Planning Calculator.","authors":"Daniel L Young, Rebecca Engels, Elizabeth Colantuoni, Erik H Hoyer","doi":"10.37765/ajmc.2026.90008","DOIUrl":"https://doi.org/10.37765/ajmc.2026.90008","url":null,"abstract":"<p><strong>Objectives: </strong>To validate the Johns Hopkins Early Discharge Planning Calculator (JH-EDPC) machine learning algorithm in routine clinical practice for predicting postacute care (PAC) needs and evaluate whether knowledge of predictions influenced physical therapy (PT) consultation rates.</p><p><strong>Study design: </strong>Pilot controlled clinical validation study conducted from October 2022 to March 2023.</p><p><strong>Methods: </strong>The JH-EDPC mobile app was deployed to 7 hospitalists (intervention group patients, n = 51 adult inpatients hospitalized ≥ 48 hours); hospitalists on the same units served as controls (patients, n = 111). Predictors included age, admission date, living status, surgery, and daily Activity Measure for Post Acute Care (AM-PAC) mobility scores. Accuracy metrics (area under curve [AUC], sensitivity, specificity, negative predictive value [NPV]) were calculated at a PAC probability cutoff of 0.25 using lowest 48-hour AM-PAC scores. Day-7 PT consultation rates were compared using inverse probability of treatment weighting.</p><p><strong>Results: </strong>Overall, 11.7% of patients required PAC. The JH-EDPC correctly predicted discharge location for 85% of patients (AUC = 0.77), demonstrating 68% sensitivity, 87% specificity, and a high NPV of 95.4%. Adjusted day-7 PT consultation rates were 38% for intervention vs 35% for controls. Among patients predicted for home discharge, intervention patients received fewer PT consultations (19% vs 23%).</p><p><strong>Conclusions: </strong>The JH-EDPC successfully integrated into clinical workflows with high specificity and NPV to rule out PAC needs. Findings suggest potential for optimizing hospital resource allocation by directing rehabilitation consultations to patients with the highest need.</p>","PeriodicalId":50808,"journal":{"name":"American Journal of Managed Care","volume":"32 9","pages":"e306-e308"},"PeriodicalIF":2.1,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149082437","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":"Reply to Letter Regarding \"Preventive Dental Care and Overall Medical Expenditures\".","authors":"Heather L Taylor, Ann M Holmes, Nir Menachemi, Justin Blackburn","doi":"10.37765/ajmc.2026.89992","DOIUrl":"https://doi.org/10.37765/ajmc.2026.89992","url":null,"abstract":"<p><p>This letter addresses a letter about the study, \"The Relationship Between Preventive Dental Care and Overall Medical Expenditures,\" with the letter detailing why quasi-experimental studies should be used to address bias from unobserved factors.</p>","PeriodicalId":50808,"journal":{"name":"American Journal of Managed Care","volume":"32 9","pages":"e301-e302"},"PeriodicalIF":2.1,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149082545","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":"Community Care Consultations for Veterans with Diabetic Foot Ulcers.","authors":"Hiroyuki Suzuki, Mary Vaughan-Sarrazin, Michael Ohl, Bradley Mecham, Kimberly McCoy, Meghan B Brennan, Jeffrey M Robbins, Daniel J Livorsi","doi":"10.37765/ajmc.2026.90009","DOIUrl":"https://doi.org/10.37765/ajmc.2026.90009","url":null,"abstract":"<p><strong>Objectives: </strong>To quantify community care consultations for patients with newly diagnosed diabetic foot ulcers (DFUs), identify associated patient- and facility-level characteristics, and measure time to specialty care within and outside the Veterans Health Administration (VHA).</p><p><strong>Study design: </strong>A retrospective cohort study.</p><p><strong>Methods: </strong>This study included patients 65 years and older with newly diagnosed DFUs who received specialty care between 2019 and 2023. Data were sourced from the VHA Corporate Data Warehouse and linked Medicare data. Community care consultation was defined as receiving specialized consultations (ie, podiatry, vascular surgery, infectious disease, endocrinology) at a community health care system within 1 year of DFU diagnosis. Patient demographics, comorbidities, and facility characteristics were analyzed with multivariable mixed-effects logistic regression models to assess factors associated with community care consultation while controlling for facility-level clustering.</p><p><strong>Results: </strong>A total of 60,121 patients with a new diagnosis of DFU were included. Of these, 29.2% had a community care consultation. Those receiving community care were more often older, White, living in a rural area, and cared for in lower-complexity facilities. Patients were more frequently referred to community care for vascular surgery, infectious disease, and endocrinology consultations than for podiatry. For all specialties, the time to a new consultation was longer for community care than for a consultation within the VHA.</p><p><strong>Conclusions: </strong>Community care consultations for patients with DFUs in the VHA system were substantial but varied significantly across facilities. Rural and lower-complexity facilities relied more on community care, particularly for vascular surgery, infectious disease, and endocrinology. Future research should explore the impact of community care on DFU outcomes and strategies to enhance multidisciplinary care coordination.</p>","PeriodicalId":50808,"journal":{"name":"American Journal of Managed Care","volume":"32 9","pages":"e309-e315"},"PeriodicalIF":2.1,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149082875","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":"Federal PBM Compensation Shifts: Early CAA 2026 Considerations.","authors":"Kayla Holland","doi":"10.37765/ajmc.2026.90007","DOIUrl":"https://doi.org/10.37765/ajmc.2026.90007","url":null,"abstract":"<p><p>The Consolidated Appropriations Act, 2026 (CAA 2026) introduces the most significant federal restructuring of pharmacy benefit manager (PBM) compensation to date. Effective January 2028, the act restructures Medicare Part D by effectively eliminating spread pricing, mandating the full pass-through of manufacturer remuneration, restricting PBM revenue to bona fide service fees delinked from drug prices and codifying \"any willing pharmacy\" network inclusivity. Similar mandates apply under the Employee Retirement Income Security Act of 1974 (ERISA) for employer-sponsored plans, though they are primarily subject to mandatory pass‑through and fiduciary reasonableness standards rather than explicit statutory delinking of service fees. Reforms to the Internal Revenue Code of 1986, the Public Health Service Act, Medicare, and ERISA aim to improve transparency and auditing for patients, payers, and the federal government while reducing incentives tied to high list prices. This transparency redefines PBM-payer engagement, reconfiguring the PBM's role within the drug supply chain. Furthermore, the CAA 2026 redistributes PBM profits to Medicare and ERISA plans, shifting the emphasis from rebate maximization to net cost savings and transferring greater financial risk to plan sponsors. This commentary examines the structural implications of these reforms for managed care pharmacy, including emerging challenges related to incentive alignment, administrative burden, and formulary design. Importantly, these implications represent early interpretations of potential downstream effects rather than finalized regulatory outcomes. Early evidence suggests that while the CAA 2026 enhances accountability, it may also introduce new distortions in pricing strategies. Managed care organizations will likely need to adapt to a data-intensive, plan-centric model of oversight as these reforms continue to evolve.</p>","PeriodicalId":50808,"journal":{"name":"American Journal of Managed Care","volume":"32 9","pages":"e303-e305"},"PeriodicalIF":2.1,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149082928","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":"Oncology Patients in Clinical Trials: A Health Care Cost Analysis.","authors":"Christine Ferro, Kate Fitch, Prachi D Bhatt, Phil Ellenberg, Bela Bapat, Adrienne M Gilligan, Chad Moretz, Robert H Dumanois","doi":"10.37765/ajmc.2026.90012","DOIUrl":"https://doi.org/10.37765/ajmc.2026.90012","url":null,"abstract":"<p><strong>Objectives: </strong>To assess health care resource utilization and costs among commercially insured patients with colorectal cancer (CRC) or ovarian cancer (OC) participating in clinical trials (PCTs).</p><p><strong>Study design: </strong>A retrospective claims analysis from 2017 to 2022 was conducted using the Milliman Consolidated Health Cost Guidelines Sources Database, a proprietary database that aggregates deidentified claims data from multiple large commercial insurers representing more than 75 million covered lives.</p><p><strong>Methods: </strong>Participants in CTs were identified with diagnosis, modifier, or procedure codes for a CT and a diagnosis code for either CRC or OC. The first observed CT claim was assigned as the index date (index). For patients with CRC or OC not participating in a CT, proxy episodes were created for each qualified 18-month period following the first observed cancer claim. We compared average allowed costs (per-patient-per-month) incurred in the 9 months following index after adjusting for confounding using inverse probability of treatment weighting.</p><p><strong>Results: </strong>We identified 69 CT participants with CRC, 40,716 nonparticipants with CRC, 49 CT participants with OC, and 17,041 nonparticipants with OC for the study. Adjusted mean costs for both medical and drugs, in the 9 months following index, were lower for CT participants than nonparticipants. Among CRC patients, mean medical costs were $2806 for the CT cohort vs $3996 for the non-CT cohort, a difference of $1190 ( P  = .015), and drug costs were $447 and $1635, respectively, a difference of $1189 ( P  = .0002). Among OC patients, mean medical costs were $2211 and $2508, respectively, a difference of $296 ( P  = .524), and mean drug costs were $371 and $2294, a difference of $1924 ( P  < .0001).</p><p><strong>Conclusions: </strong>Commercially insured patients with OC and CRC enrolled in CTs incurred lower costs following CT initiation than those not enrolled, driven by payers not incurring costs for oncology therapies.</p>","PeriodicalId":50808,"journal":{"name":"American Journal of Managed Care","volume":"32 9","pages":"e334-e342"},"PeriodicalIF":2.1,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149082452","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":"Teach-Back Is Essential Care Infrastructure: A Low-Cost Strategy for Safer, More Equitable Care.","authors":"Aayush Sisodia","doi":"10.37765/ajmc.2026.90016","DOIUrl":"https://doi.org/10.37765/ajmc.2026.90016","url":null,"abstract":"<p><strong>Objectives: </strong>This Insights article argues that health systems should treat teach-back as equity infrastructure because patient understanding is a prerequisite for safe follow-through, medication use, and effective self-management.</p><p><strong>Study design: </strong>Narrative policy and practice commentary grounded in published evidence on health literacy, disparities, and teach-back implementation.</p><p><strong>Discussion: </strong>Many equity strategies focus on access, navigation, and utilization, yet they often leave a hidden gap untouched: whether patients actually understood what they were told. Low health literacy is associated with poorer outcomes and can partially explain disparities. Teach-back offers a practical way to verify comprehension, correct misunderstandings, and make communication safer for all patients, especially during high-risk transitions such as discharge, medication changes, referrals, and informed consent. I propose the \"last-mile equity gap\" as the distance between a completed encounter and a patient's true understanding of what happens next.</p><p><strong>Conclusions: </strong>Teach-back should be measured, operationalized, and funded as a core equity and population health practice rather than treated as optional bedside etiquette.</p>","PeriodicalId":50808,"journal":{"name":"American Journal of Managed Care","volume":"32 Spec. No. 9","pages":"eSP548-eSP550"},"PeriodicalIF":2.1,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149129099","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}