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Background Globally, geriatric patients are the dominant population requiring global medical care. We established a frailty index for geriatric trauma patients by retrospectively analysing electronic hospital records to identify patients with frailty characteristics and poor prognostic outcomes. Method Data were obtained from 2016 US National Emergency Department Sample and Shanghai Trauma Emergency Medical Association (2015–18). Overall, 141,267 hospitalised geriatric trauma patients (age ≥ 65 years) were included. We used a three-step method to construct geriatric trauma frailty index (GTFI) based on the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnostic codes. Systematic cluster analysis was used. The accuracy of GTFI was verified in national validation cohort, and its applicability to Chinese patients was assessed in local validation cohort. Results In development cohort (n  = 28,179), frail patients had longer lengths of stay and higher Charlson co-morbidity index than non-frail patients (18.2 ± 12.4 days, 5.59 ± 2.0 versus 5.3 ± 5.3 days, 5.33 ± 1.8, respectively). In national validation cohort (n  = 113,089), frail patients had longer lengths of stay (8.5 ± 8.8 days versus 4.5 ± 3.1 days) and higher in-hospital mortality than non-frail patients (2,795, 11.69% versus 589, 0.66%). Areas under the curves for GTFI for length of stay (>14 days) and in-hospital mortality were 0.848 (0.841, 0.854) and 0.885 (0.880, 0.891) in national validation cohort, and were 0.791 (0.779, 0.804) and 0.903 (0.885, 0.922) in local validation cohort (n  = 14,827). Conclusions The GTFI helps hospitals and emergency departments to identify geriatric trauma patients with poor prognostic outcomes, and has been proven to be useful in China. [ABSTRACT FROM AUTHOR]

Objective: The aim was to assess the magnitude of health care disparities in treatment for substance use disorder (SUD) and the role of health plan membership and place of residence in observed disparities in Medicaid Managed Care (MMC) plans in New York City (NYC)., Data Source: Medicaid claims and managed care plan enrollment files for 2015-2017 in NYC., Research Design: We studied Medicaid enrollees with a SUD diagnosis during their first 6 months of enrollment in a managed care plan in 2015-2017. A series of linear regression models quantified service disparities across race/ethnicity for 5 outcome indicators: treatment engagement, receipt of psychosocial treatment, follow-up after withdrawal, rapid readmission, and treatment continuation. We assessed the degree to which plan membership and place of residence contributed to observed disparities., Results: We found disparities in access to treatment but the magnitude of the disparities in most cases was small. Plan membership and geography of residence explained little of the observed disparities. One exception is geography of residence among Asian Americans, which appears to mediate disparities for 2 of our 5 outcome measures., Conclusions: Reallocating enrollees among MMC plans in NYC or evolving trends in group place of residence are unlikely to reduce disparities in treatment for SUD. System-wide reforms are needed to mitigate disparities., Competing Interests: T.L. reports grant funding from the Agency for Healthcare Research and Quality. J.W. reports a relationship to Medicaid Transformation and Financing at Aurrera Health Group. R.L.F. reports institutional support from the New York State Psychiatric Institute and the Office of Mental Health. The remaining authors declare no conflict of interest., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Importance: There is limited evaluation of the performance of Medicaid managed care (MMC) private plans in covering substance use disorder (SUD) treatment., Objective: To compare the performance of MMC plans across 19 indicators of access, quality, and outcomes of SUD treatment., Design Setting and Participants: This cross-sectional study used administrative claims and mandatory assignment to plans of up to 159 016 adult Medicaid recipients residing in 1 of the 5 counties (boroughs) of New York, New York, from January 2009 to December 2017 to identify differences in SUD treatment access, patterns, and outcomes among different types of MMC plans. Data from the latest years were received from the New York State Department of Health in October 2019, and analysis began soon thereafter. Approximately 17% did not make an active choice of plan, and a subset of these (approximately 4%) can be regarded as randomly assigned., Exposures: Plan assignment., Main Outcomes and Measures: Percentage of the enrollees achieving performance measures across 19 indicators of access, process, and outcomes of SUD treatment., Results: Medicaid claims data from 159 016 adults (mean [SD] age, 35.9 [12.7] years; 74 261 women [46.7%]; 8746 [5.5%] Asian, 73 783 [46.4%] Black, and 40 549 [25.5%] White individuals) who were auto assigned to an MMC plan were analyzed. Consistent with national patterns, all plans achieved less than 50% (range, 0%-62.1%) on most performance measures. Across all plans, there were low levels of treatment engagement for alcohol (range, 0%-0.4%) and tobacco treatment (range, 0.8%-7.2%), except for engagement for opioid disorder treatment (range, 41.5%-61.4%). For access measures, 4 of the 9 plans performed significantly higher than the mean on recognition of an SUD diagnosis, any service use for the first time, and tobacco use screening. Of the process measures, total monthly expenditures on SUD treatment was the only measure for which plans differed significantly from the mean. Outcome measures differed little across plans., Conclusions and Relevance: The results of this cross-sectional study suggest the need for progress in engaging patients in SUD treatment and improvement in the low performance of SUD care and limited variation in MMC plans in New York, New York. Improvement in the overall performance of SUD treatment in Medicaid potentially depends on general program improvements, not moving recipients among plans., Competing Interests: Conflict of Interest Disclosures: Drs Alegria, Falgas-Bague, and Rigotti and Ms Fukuda reported grants from National Institute on Drug Abuse (NIDA) during the conduct of the study. Ms O’Malley and Dr Stein reported grants from National Institutes of Health during the conduct of the study. Dr Layton reported personal fees from Greaylock McKinnon and Associates outside the submitted work. Dr Wallace reported grants from NIDA during the conduct of the study; additionally, his spouse is the Director of Medicaid Transformation and Financing at Aurrera Health Group. Dr Neighbors reported personal fees from Harvard University during the conduct of the study. Dr Wakeman reported personal fees from Celero Systems outside the submitted work. Dr Kane reported grants from the Health Resources and Services Administration outside the submitted work. No other disclosures were reported., (Copyright 2022 Alegría M et al. JAMA Health Forum.)

Introduction: With the Safety Ensuring Lives Future Deployment and Research in Vehicle Evolution (SELF DRIVE) Act in the United States, there is a growing interest in autonomous vehicles (AVs). One avenue of innovation would be to use them to mobilize and coordinate response efforts during natural disasters. This study uses an earthquake response in an urban, developed setting as a hypothetical example case study. In this hypothetical scenario, private AVs would be mobilized to help rescue victims from collapsed structures., Methods: A Markov model compared an intervention arm with AVs to a status quo arm using a hypothetical cohort of American earthquake victims. The three possible health states were trapped but alive, rescued and alive, and dead. The cycle length of the Markov model was 6 h., Results: The cost of deploying AVs was $90,139 relative to $87,869 in status quo arm. Using AVs produced an incremental cost of $2269 (95% credible interval (CI) = $-12,985-$8959). Victims have 7.33 quality-adjusted life years (QALYs) in the intervention arm compared to 7.20 QALYs in the status quo arm, resulting in an incremental gain of 0.13 (95% CI = -0.73-2.19) QALYs. The incremental cost-effectiveness ratio (ICER) was $16,960/QALY gained (95% CI = cost-saving-$69,065/QALY)., Discussion: The mobilization of private AVs in the setting of an earthquake has the potential to save money and reduce the loss of life. AVs may advance emergency management competencies.