Publications by authors named "Arnold Milstein"

Importance: Large language models (LLMs) have shown promise in their performance on both multiple-choice and open-ended medical reasoning examinations, but it remains unknown whether the use of such tools improves physician diagnostic reasoning.

Objective: To assess the effect of an LLM on physicians' diagnostic reasoning compared with conventional resources.

Design, Setting, And Participants: A single-blind randomized clinical trial was conducted from November 29 to December 29, 2023.

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Importance: Large language model (LLM) artificial intelligence (AI) systems have shown promise in diagnostic reasoning, but their utility in management reasoning with no clear right answers is unknown.

Objective: To determine whether LLM assistance improves physician performance on open-ended management reasoning tasks compared to conventional resources.

Design: Prospective, randomized controlled trial conducted from 30 November 2023 to 21 April 2024.

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Importance: The long-term effect of interventions that assist patients with establishing their end-of-life care preferences among patients with cancer remain relatively unknown.

Objective: To evaluate the association of a long-term intervention of a lay health worker-led advance care planning intervention among patients with advanced stages of cancer with overall survival and end-of-life health care use and costs.

Design, Setting, And Participants: This follow-up study of the EPAC randomized clinical trial conducted between August 2013 and February 2015 used data from 9.

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Objectives: Generic medications represent 90% of prescriptions in the US market and provide a tremendous financial benefit for patients. Recently, multiple generic drugs have been recalled due to the presence of carcinogens, predominantly N-nitrosodimethylamine (NDMA), including an extensive recall of extended-release (ER) metformin products in 2020.

Study Design: Primary pharmaceutical quality testing and database analysis.

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Article Synopsis
  • * Conducted across multiple medical institutions, the research involved 50 resident and attending physicians working on clinical vignettes, with some using GPT-4 and others using only conventional resources.
  • * Results showed a slight improvement in diagnostic scores for the GPT-4 group (76.3%) versus those using conventional resources (73.7%), but the difference was not statistically significant.
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Background: The COVID-19 pandemic transformed the home lives of many families in the United States, especially those with young children. Understanding the relationship between child and parent screen time and family stressors exacerbated by the pandemic may help inform interventions that aim to support early child development.

Objective: We aim to assess the changing relationship between family screen time and factors related to pandemic-induced remote work and childcare or school closures.

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Importance: The burden of caring for children with complex medical problems such as major congenital anomalies falls principally on mothers, who in turn suffer a variety of potentially severe economic consequences. As well, health consequences of caregiving often further impact the social and economic prospects of mothers of children with major congenital anomalies (MCMCAs). Evaluating the long-term economic consequences of extensive in-home caregiving among MCMCAs can inform strategies to mitigate these effects.

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Diffusion of innovations, defined as the adoption and implementation of new ideas, processes, products, or services in health care, is both particularly important and especially challenging. One known problem with adoption and implementation of new technologies is that, while organizations often make innovations immediately available, organizational actors are more wary about adopting new technologies because these may impact not only patients and practices but also reimbursement. As a result, innovations may remain underutilized, and organizations may miss opportunities to improve and advance.

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In analyzing direct hospitalization cost and clinical data from an academic medical center, commonly used metrics such as diagnosis-related group (DRG) weight explain approximately 37% of cost variability, but a substantial amount of variation remains unaccounted for by case mix index (CMI) alone. Using CMI as a benchmark, we isolate and target individual DRGs with higher than expected average costs for specific quality improvement efforts. While DRGs summarize hospitalization care after discharge, a predictive model using only information known before admission explained up to 60% of cost variability for two DRGs with a high excess cost burden.

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In a randomized, pre-post intervention study, we evaluated the influence of a large language model (LLM) generative AI system on accuracy of physician decision-making and bias in healthcare. 50 US-licensed physicians reviewed a video clinical vignette, featuring actors representing different demographics (a White male or a Black female) with chest pain. Participants were asked to answer clinical questions around triage, risk, and treatment based on these vignettes, then asked to reconsider after receiving advice generated by ChatGPT+ (GPT4).

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Background: Depression is a common comorbidity for patients with chronic medical conditions. Although the costs of treating chronic medical illness in combination with depression are believed to be significantly higher than the costs of treating each condition independently, few studies have formally modeled the cost consequences of mental health comorbidity.

Purpose: To estimate the relative magnitude of the independent and synergistic contributions to health care costs from depression diagnosis and other chronic physical health conditions.

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Importance: Low back and neck pain are often self-limited, but health care spending remains high.

Objective: To evaluate the effects of 2 interventions that emphasize noninvasive care for spine pain.

Design, Setting, And Participants: Pragmatic, cluster, randomized clinical trial conducted at 33 centers in the US that enrolled 2971 participants with neck or back pain of 3 months' duration or less (enrollment, June 2017 to March 2020; final follow-up, March 2021).

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Although individual psychotherapy is generally effective for a range of mental health conditions, little is known about the moment-to-moment language use of effective therapists. Increased access to computational power, coupled with a rise in computer-mediated communication (telehealth), makes feasible the large-scale analyses of language use during psychotherapy. Transparent methodological approaches are lacking, however.

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Background: Negative healthcare delivery experiences can cause lasting patient distress and medical service misuse and disuse. Yet no multi-site study has examined whether care-team members understand what most upsets patients about their care.

Methods: We interviewed 373 patients and 360 care-team members in the medical oncology and ambulatory surgery clinics of 11 major healthcare organizations across six U.

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Background: Spine pain is one of the most common conditions seen in primary care and is often treated with ineffective, aggressive interventions, such as prescription pain medications, imagery and referrals to surgery. Aggressive treatments are associated with negative side effects and high costs while conservative care has lower risks and costs and equivalent or better outcomes. Despite multiple well-publicised treatment guidelines and educational efforts recommending conservative care, primary care clinicians (PCCs) widely continue to prescribe aggressive, low-value care for spine pain.

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Background: Given the rapidly aging society, shrinking workforce, and reducing dependency ratio, there is an increasing challenge for family members to provide care for older adults. While a broad understanding of caregiver burden and its consequences have been studied across various contexts, there is a need to better understand this challenge among family caregivers in Asian societies.

Methods: This study is a cross-sectional observational study.

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Objective: This population-based, matched cohort study aimed to evaluate utilization of health care services by mothers of children with major congenital anomalies (MCAs), compared to mothers of children without MCAs over a 20-year post-birth time horizon in Denmark.

Methods: Our analytic sample included mothers who gave birth to an infant with a MCA (n = 23,927) and a cohort of mothers matched to them by maternal age, parity and infant's year of birth (n = 239,076). Primary outcomes were period prevalence and mothers' quantity of health care utilization (primary, inpatient, outpatient, surgical, and psychiatric services) stratified by their child's age (i.

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Background: Low back and neck pain (together, spine pain) are among the leading causes of medical visits, lost productivity, and disability. For most people, episodes of spine pain are self-limited; nevertheless, healthcare spending for this condition is extremely high. Focusing care on individuals at high-risk of progressing from acute to chronic pain may improve efficiency.

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Parkinson's disease (PD) is a brain disorder that primarily affects motor function, leading to slow movement, tremor, and stiffness, as well as postural instability and difficulty with walking/balance. The severity of PD motor impairments is clinically assessed by part III of the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS), a universally-accepted rating scale. However, experts often disagree on the exact scoring of individuals.

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Currently, the quality of care for autistic individuals is not good. Many care services for autistic individuals are not well coordinated, nor are they tailored. We wanted to find out a better model for autism care and believed that the autism community knows where these programs are.

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Objective: To estimate health care systems' value in treating major illnesses for each US state and identify system characteristics associated with value.

Data Sources: Annual condition-specific death and incidence estimates for each US state from the Global Burden Disease 2019 Study and annual health care spending per person for each state from the National Health Expenditure Accounts.

Study Design: Using non-linear meta-stochastic frontier analysis, mortality incidence ratios for 136 major treatable illnesses were regressed separately on per capita health care spending and key covariates such as age, obesity, smoking, and educational attainment.

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