Medical Care最新文献

Background: Poor social health is linked to incident cardiovascular disease, but less is known about how loneliness affects health care utilization after an acute myocardial infarction (AMI).

Objective: Determine the association between loneliness and 30-day emergency department (ED) visit or readmission after AMI hospitalization.

Research design: The REasons for Geographic and Racial Differences in Stroke (REGARDS) study is a national prospective cohort of 30,239 U.S. adults aged 45 years or older.

Measures: We examined the association between loneliness and 30-day post-AMI ED visit or readmission.

Subjects: Seven hundred forty-nine Medicare fee-for-service beneficiaries in REGARDS were discharged alive after an adjudicated AMI.

Results: The mean age was 77 years. Twenty-eight percent self-identified as non-Hispanic Black and 39% as women. Twenty percent reported loneliness. Twenty-nine percent had a 30-day ED visit or readmission. Lonely individuals had 61% increased risk of 30-day ED visit or readmission (RR: 1.61; 95% CI: 1.27-2.04; P <0.001), which remained significant after adjustment for sociodemographic and clinical factors (aRR: 1.48; 95% CI: 1.12-1.95; P =0.006). Stratified analyses demonstrated significant association for those aged 65-74 (aRR 2.48; 95% CI, 1.57-3.91; P <0.001), White adults (aRR: 1.86; 95% CI: 1.35-2.58; P <0.001), and men (aRR: 2.19; 95% CI: 1.59-3.01; P <0.001) but not for those 75+ (aRR: 0.94; 95% CI: 0.63-1.40; P =0.75), Black adults (aRR: 0.89; 95% CI: 0.53-1.49; P =0.660), or women (aRR: 0.81; 95% CI: 0.51-1.30; P =0.380).

Conclusions: Loneliness, even measured years before AMI, was associated with an increased risk of 30-day ED visit or readmission, specifically for those aged 65-74, White participants, and men. These findings may inform discharge strategies to reduce readmissions.

Background: Patients with Alzheimer disease and related dementias (ADRD) face risks from medications labeled "potentially inappropriate in older adults" (risky); concurrent receipt of anti-dementia drugs may amplify risk. We studied adverse events among older adults concurrently receiving anti-dementia and risky medications.

Methods: Using 2016-2019 administrative data from a random 40% sample of fee-for-service Medicare beneficiaries receiving anti-dementia medications (acetylcholinesterase inhibitors (AChEI) and/or memantine), we identified days with concurrent receipt of select, risky medications (benzodiazepines, sedative hypnotics, opioids). We measured diagnosed falls, hip fractures, and deaths among person-days with anti-dementia drug receipt comparing person-days with versus without concurrent risky drug receipt. We stratified regression analyses on long-term care (LTC) residence.

Results: We studied 633,528 beneficiaries; 64.3% were women, 33.7% met LTC residence criteria. Mean (SD) age was 80.9 (7.6) years. Each beneficiary contributed a mean (SD) of 551.7 (449.2) anti-dementia drug receipt days. Overall, 4.5% of person-days involved receipt of AChEI plus benzodiazepines; 3.8% involved AChEI plus an opioid. Falls, the most common outcome, affected 22.5% of our beneficiaries. Concurrent receipt of AChEI and opioids was associated with the greatest fall risk increase. Among community-dwelling beneficiaries, AChEI and opioid receipt (vs. AChEI alone) was associated with a hazard ratio for falls of 2.25 (95% CI: 2.19, 2.32); among LTC residents the corresponding hazard ratio was 1.46 (95% CI: 1.42, 1.51).

Conclusions: Assessment and treatment of symptoms among people with ADRD is complex; concurrent receipt of opioids and dementia medications is uncommon but seems risky. Efforts to eliminate avoidable opioids may decrease adverse events and associated suffering in this population.

Background: Telehealth can improve health care access in underserved areas. Hub-and-spoke-models, wherein providers in regional hubs deliver care through telehealth to patients visiting local "spoke" clinics, can improve access. However, cost impacts of this model are unknown.

Objective: Evaluate the utilization and cost impacts of VA's Clinical Resource Hub program for primary care (CRH-PC), a hub-and-spoke-model.

Design: Adjusted difference-in-difference and event study analyses comparing patients at program-sites who used CRH-PC services with patients who never used CRH-PC services, prepost program adoption, fiscal years 2018-2021. We also compared all patients at CRH-PC sites versus at non-CRH-PC sites to assess site-wide impacts.

Participants: CRH-PC sites: 164 sites and 1,546,892 patients; Non-CRH-PC sites: 704 sites and 4,062,797 patients.

Measures: Costs and number of VA-provided and VA-purchased primary, emergency, and acute inpatient care visits.

Results: At CRH-PC sites, 64,973 patients (4%) used CRH-PC services. Rural patients, African-American patients, and patients with greater comorbidities had higher odds of receiving program services. Program exposure was associated with an 18% increase in primary care visits (+0.7) and $612 per program-user per year. Comparing all patients (users and nonusers) at program-sites versus nonprogram sites, we found no impact, except video-based care more often replaced in-person services at program-sites.

Conclusions: Among program-users, VA's CRH-PC increased mean primary care visits and VA costs, but as only 4% of patients at program-clinics were program-users, there were no differences in overall cost or utilization between program and nonprogram clinics. Findings suggest clinics can offer primary care telehealth services to high-need populations without affecting clinic-level costs, but costs should be monitored upon wider adoption.

Objective: We sought to examine changes in mild-to-moderate TBI-related symptoms among service members and veterans (SM/Vs) following participation in a 5-site inpatient rehabilitation program with the US Department of Veterans Affairs between 7/1/2022 and 5/30/2024.

Methods: Neurobehavioral outcomes, posttraumatic stress disorder (PTSD) symptoms, pain interference, and lifestyle behaviors related to brain injury were assessed at baseline, discharge, and a 6-month follow-up. Mixed effects linear regression models, adjusting for key patient characteristics, were estimated to determine changes in TBI-related outcomes across the 3 time points.

Results: Mean participant age, for those with complete data (n = 127), was 41.64 years (SD = 5.57), with a mean of 7.45 deployments (SD = 3.12) and 16.32 concussive events (SD = 7.21). Participants were predominantly White (73.23%) Special Operations personnel (82.68%). TBI-related outcomes, including neurobehavioral symptoms, pain interference, PTSD, and brain injury adaptability, decreased significantly from baseline to discharge (b = -14.36, SE = 1.03; b = -3.79, SE = 0.49; b = -11.14, SE = 1.27; b = -2.41, SE = 0.41), with Cohen's d effect sizes of 1.14, 0.71, 0.69, and 0.56, respectively. Six-month follow-up, TBI-related outcomes remained statistically and practically below baseline levels in all measures except adaptability.

Conclusions and relevance: Findings illustrate an interdisciplinary, inpatient rehabilitation program for mild-to-moderate TBI yields significant improvements in TBI-related symptoms that are common among SM/Vs and are sustained at 6 months postdischarge.

Introduction: The Surveillance, Epidemiology, and End Results (SEER) Program collects data on the first course of cancer treatment, but no and unknown receipt of treatment cannot be distinguished for radiation therapy (RT) and chemotherapy. As part of the Data Use Agreement (DUA), users must acknowledge that they understand the data limitations and agree to include a description of the limitations in any analyses published using the data. The objective of this review was to evaluate users' compliance with the recommendations of the DUA.

Methods: Publications from a PubMed search were matched with the names of SEER treatment data users, and keywords were applied to identify relevant studies. Five reviewers (with 2 per publication) independently assessed if the authors (a) conducted analyses supported by these data, (b) correctly labelled no/unknown treatment as "no/unknown", and (c) described the limitations of their use. Publications were classified as "followed recommendations", "partially followed recommendations", or "did not follow recommendations" of the DUA.

Results: Among a total of 120 studies included in the review, 106 (88.3%) studies did not follow recommendations, 11 (9.2%) partially followed recommendations, and 3 studies (2.5%) followed recommendations. Only 11.7% of publications correctly labelled the "no/unknown" category as "no/unknown", and described the limitations associated with the no/unknown issue.

Conclusions: In this review, we found substantial misuse of the SEER treatment data and limited acknowledgement of the limitations of the SEER treatment data in publications. Such findings highlight the need to think of effective ways of encouraging appropriate use of the treatment data.

Background: Prior work has shown that Medicaid coverage offset reductions in employer-sponsored insurance after COVID-19-related job loss in Medicaid expansion states. However, the effect of Medicaid expansion on health care access is not fully understood.

Objective: To estimate the association of unemployment during COVID-19 with health insurance coverage and health care access in Medicaid expansion versus nonexpansion states.

Study design: We used restricted, longitudinal National Health Interview Survey (NHIS) data from 2019 to 2020, focusing on working-age adults (N=5156). Using triple-difference models, we estimated changes in outcomes for respondents becoming unemployed between 2019 and 2020 (after COVID-19) relative to continuously employed respondents, in Medicaid expansion versus nonexpansion states.

Principal findings: Compared with continuously employed respondents, there was a statistically significant increase in Medicaid coverage among the newly unemployed in expansion states (6.1 percentage points (pp), 95% CI: 1.0 to 11.3, P=0.019) but not in nonexpansion states (3.9 pp, 95% CI: -3.9 to 11.8, P=0.324); however, the triple difference was nonsignificant. Uninsurance increased among the newly unemployed in expansion states by only 4.9 pp (95% CI: 0.9 to 8.9, P=0.016) versus 12.4 pp in nonexpansion states (95% CI: 0.2 to 24.6, P=0.047), but the triple difference was statistically nonsignificant. There was a significant increase in delaying or skipping medical care among newly unemployed respondents in nonexpansion states, but not in expansion states and the triple difference was statistically significant (-15.5 pp, 95% CI: -26.9 to -4.0, P=0.008).

Conclusion: Our results suggest that Medicaid expansion prevented disruptions in health care access for the newly unemployed during COVID-19.

Background: Global shortages for 3 angiotensin receptor-II blockers (ARBs)-valsartan, losartan, and irbesartan-occurred in 2018-2019 after recalls due to ingredient impurities. Provider-level responses to the ARB shortages in the United States and spillovers to other antihypertensive classes are unknown.

Objective: To estimate changes in provider-level prescribing for ARBs and non-ARB antihypertensives up to 18 months after the 2018-2019 recalls and shortages.

Research design: National cohort study of prescribers using all-payer pharmacy claims. Mixed interrupted time series models quantified changes in prescribing postshortages and heterogeneous changes by specialty, region, medical school graduation cohort, sex, and level of prerecall prescribing.

Patients and methods: Active providers exposed to the 2018-2019 valsartan, irbesartan, and losartan shortages (defined as top-25th percentile for these drugs in 2017).

Measures: Within-class changes in prescribing for ARBs (recalled and nonrecalled). Between-class substitutions to non-ARB antihypertensives (ACE-Is, alpha- and beta-adrenergic blockers, calcium channel blockers, diuretics, and other agents).

Results: Among 138,032 prescribers who met the inclusion criteria, per-prescriber fills for valsartan decreased by 57%-59% after it was recalled in July 2018. We observed concurrent increases for losartan and irbesartan fills and no change in overall ARB prescribing. There were no significant changes in fills for ACE-Is or for other antihypertensives. Absolute decreases in valsartan fills were greatest among providers with higher levels of prescribing at baseline. However, relative changes did not differ by prescriber characteristics.

Conclusions: In this prescriber level, national study, substitutions to other ARBs mitigated decreases in valsartan fills after it was recalled. There were no spillovers to non-ARB anti-hypertensives. The availability of close substitutes during drug shortages may mitigate gaps in access for prescribers and their patients.

Background: Identification of transgender and gender diverse (TGD) people has been limited to diagnoses and text rather than self-identified gender identity (SIGI), representing a subset of TGD people. In 2017, the Veterans Health Administration (VHA) implemented SIGI, allowing for precise identification of TGD veterans, including subgroups (transgender man, transgender woman, and nonbinary).

Objectives: Health conditions, adverse social determinants of health (SDOH), and health care utilization were compared among veterans (1) identified by SIGI only, both SIGI and diagnosis/text, diagnosis/text only (ie, without SIGI), and (2) SIGI subgroups.

Research design: Cross-sectional.

Subjects: Twenty thousand seventy-nine TGD VHA patients from 2019 to 2023; SIGI only (n=5523), both SIGI and diagnosis/text (n=4066), and without SIGI (n=10,490).

Measures: Health conditions, adverse SODH and health care utilization.

Results: In adjusted models, SIGI only veterans were less likely to have documentation of depression (32.4% vs. 60.7% vs. 54.8%), post-traumatic stress disorder (PTSD; 23.5% vs. 41.4% vs. 37.5%), housing instability (8.8% vs. 21.5% vs. 16.1%), unemployment/financial problems (10.5% vs. 23.8% vs. 19.0%), and mental health visits (72.5% vs. 97.7% vs. 95.2%) compared with those with both SIGI and diagnosis/text and without SIGI. Health conditions were more similar across the diagnosis groups (i.e. both SIGI and diagnosis/text and without SIGI). Among veterans with SIGI data, we identified 49% transgender women, 38% transgender men, and 14% nonbinary veterans without many differences across subgroups. In adjusted models, more nonbinary veterans than transgender women and transgender men had documentation of alcohol use disorder (10.1% vs. 6.1% vs. 7.5%), depression (62.3% vs. 42.6% vs. 47.0%), PTSD (45.9% vs. 27.4% vs. 33.5%), mental health visits (96.7% vs. 89.1% vs. 91.9%), and experienced unemployment/financial problems (21.3% vs. 16.9% vs. 14.7%).

Conclusions: Without diagnosis, SIGI enables the identification of healthier TGD veterans. Regardless of SIGI, diagnosis signals much higher rates of health concerns. SIGI data facilitates understanding veteran subgroups, informing TGD policy and practice.

Background: Older adults with Alzheimer's disease and related dementias can benefit from palliative care (PC). Whether specialty and nonspecialty PC have the same effect on outcomes is unclear. We examined the effects of these 2 interventions on comfort, symptom management, satisfaction with care, and potentially burdensome transitions, including hospital admission, emergency department visit, intensive care unit admission in the end-of-life, and in-hospital death.

Methods: This PRISMA-adherent systematic review involved a search of PubMed, Medline, EMBASE, Cochrane Library, ProQuest, and CINAHL for studies published from January 1, 2013, to November 4, 2024. Primary studies that reported at least one of the 7 patient-level outcomes were included: Comfort Assessment in Dying with Dementia (CAD-EOLD), Symptom Management at the End-of-Life (SM-EOLD), Satisfaction with Care at the End-of-Life in Dementia (SWC-EOLD), hospital admissions, emergency department visits, intensive care unit admissions, and in-hospital death.

Results: Nineteen articles involving 142,772 participants were included. The evidence, comprising studies of adequate to strong quality, revealed that both specialty and nonspecialty PC did not differ in terms of comfort, symptom management, or satisfaction with care. However, both approaches significantly reduced the likelihood of intensive care unit admissions and in-hospital deaths. Specialty PC was associated with decreased emergency department visits (OR 0.53, 95% CI 0.28-1.00; I2=86%).

Conclusions: Future research is needed to understand factors influencing PC interventions that can improve comfort, symptom management, and care satisfaction for these individuals and their families.

Background: Timely access to regular dental visits allows the detection of preventable conditions at an earlier stage. Nonetheless, 37% of adults aged 18 and above had no dental visits in 2020. Various factors affect utilization, but little is known about the influence of job characteristics. This study examined the association between paid sick leave (PSL) and different types of dental services utilization among working adults aged 18-64 in the United States.

Methods: The study sample population included employed adults aged 18-64 in the 2019 Medical Expenditure Panel Survey (N=7645). The four outcome variables were a binary variable of having any dental care, including preventive, diagnostic, and treatment dental care in the past 12 months. The primary independent variable was having PSL as a job benefit. A multivariable logistic model was used, adjusting for demographics, socioeconomic status, and general health status. All analyses were adjusted for complex survey design.

Results: Seventy-three percent of working adults had paid sick leave benefits. Availability of PSL was significantly associated with higher utilization of any dental visits [Adjusted odds ratio (aOR): 1.38, 95% CI: 1.17-1.63], preventive dental care (aOR: 1.33, 95% CI: 1.12-1.57), and diagnostic dental care (aOR: 1.31, 95% CI: 1.11-1.55).

Conclusions: PSL is associated with a significant increase in dental services, preventive dental, and diagnostic dental visits. The study offers insights for medical practitioners and policymakers aiming to prevent adverse oral health outcomes, reduce disparities, and manage health care costs.