Medical Care最新文献

Objective: To assess the association between state policies and sociodemographic characteristics and state mean fair share spending at non-profit hospitals. Fair share spending is a hospital's charity care and community investment less the estimated value of their tax-exempt status.

Background: Hospitals with non-profit status in the United States are exempt from paying taxes. In return, they are expected to provide community benefits by subsidizing medical care for those who cannot pay and investing in the health and social needs of their community.

Methods: We used a multivariable linear regression model to determine the association of state-level sociodemographics and policies with state-level mean fair share spending in 2019. Fair share spending data was obtained from the Lown Institute.

Results: We found no association between the percentage of people living in poverty, in rural areas, or U.S. region and fair share spending. Similarly, there was no association found for state minimum community benefit and reporting requirements. The state percentage of racial/ethnic minorities was associated with higher mean fair share spending [+$1.48 million for every 10% increase (95% CI: 0.01 to 2.96 million)]. Medicaid expansion status was associated with a 6.9-million-dollar decrease (95% CI: -10.4 to -3.3 million).

Conclusions: State-level community benefit policies have been ineffective at raising community benefit spending to levels comparable to the value of non-profit hospital tax-exempt status.

Background/objective: Slowing the progression of diabetic kidney disease (DKD) is critical. We conducted a randomized controlled trial to target risk factors for DKD progression.

Methods: We evaluated the effect of a pharmacist-led intervention focused on supporting healthy behaviors, medication management, and self-monitoring on decline in estimated glomerular filtration rate (eGFR) for 36 months compared with an educational control.

Results: We randomized 138 individuals to the intervention group and 143 to control. At baseline, mean (SD) eGFR was 80.7 (21.7) mL/min/1.73m 2 , 56% of participants had chronic kidney disease and a history of uncontrolled hypertension with a baseline SBP of 134.3 mm Hg. The mean (SD) decline in eGFR by cystatin C from baseline to 36 months was 5.0 (19.6) and 5.9 (18.6) mL/min/1.73m 2 for the control and intervention groups, respectively, with no significant between-group difference ( P =0.75).

Conclusions: We did not observe a significant difference in clinical outcomes by study arm. However, we showed that individuals with DKD will engage in a pharmacist-led intervention. The potential explanations for a lack of change in DKD risk factors can be attributed to 5 broad issues, challenges: (1) associated with enrolling patients with low eGFR and poor BP control; (2) implementing the intervention; (3) limited duration during which to observe any clinical benefit from the intervention; (4) potential co-intervention or contamination; and (5) low statistical power.

Background: We aimed to identify combinations of long-term services and supports (LTSS) Veterans use, describe transitions between groups, and identify factors influencing transition.

Methods: We explored LTSS across a continuum from home to institutional care. Analyses included 104,837 Veterans Health Administration (VHA) patients 66 years and older at high-risk of long-term institutional care (LTIC). We conduct latent class and latent transition analyses using VHA and Medicare data from fiscal years 2014 to 2017. We used logistic regression to identify variables associated with transition.

Results: We identified 5 latent classes: (1) No Services (11% of sample in 2015); (2) Medicare Services (31%), characterized by using LTSS only in Medicare; (3) VHA-Medicare Care Continuum (19%), including LTSS use in various settings across VHA and Medicare; (4) Personal Care Services (21%), characterized by high probabilities of using VHA homemaker/home health aide or self-directed care; and (5) Home-Centered Interdisciplinary Care (18%), characterized by a high probability of using home-based primary care. Veterans frequently stayed in the same class over the three years (30% to 46% in each class). Having a hip fracture, self-care impairment, or severe ambulatory limitation increased the odds of leaving No Services, and incontinence and dementia increased the odds of entering VHA-Medicare Care Continuum. Results were similar when restricted to Veterans who survived during all 3 years of the study period.

Conclusions: Veterans at high risk of LTIC use a combination of services from across the care continuum and a mix of VHA and Medicare services. Service patterns are relatively stable for 3 years.

Background: Social risk screening during inpatient care is required in new CMS regulations, yet its impact on inpatient care and patient outcomes is unknown.

Objectives: To evaluate whether implementing a social risk screening protocol improves discharge processes, patient-reported outcomes, and 30-day service use.

Research design: Pragmatic mixed-methods clinical trial.

Subjects: Overall, 4130 patient discharges (2383 preimplementation and 1747 postimplementation) from general medicine and surgical services at a 528-bed academic medical center in the Intermountain United States and 15 attending physicians.

Measures: Documented family interaction, late discharge, patient-reported readiness for hospital discharge and postdischarge coping difficulties, readmission and emergency department visits within 30 days postdischarge, and coded interviews with inpatient physicians.

Results: A multivariable segmented regression model indicated a 19% decrease per month in odds of family interaction following intervention implementation (OR=0.81, 95% CI=0.76-0.86, P<0.001), and an additional model found a 32% decrease in odds of being discharged after 2 pm (OR=0.68, 95% CI=0.53-0.87, P=0.003). There were no postimplementation changes in patient-reported discharge readiness, postdischarge coping difficulties, or 30-day hospital readmissions, or ED visits. Physicians expressed concerns about the appropriateness, acceptability, and feasibility of the structured social risk assessment.

Conclusions: Conducted in the immediate post-COVID timeframe, reduction in family interaction, earlier discharge, and provider concerns with structured social risk assessments likely contributed to the lack of intervention impact on patient outcomes. To be effective, social risk screening will require patient/family and care team codesign its structure and processes, and allocation of resources to assist in addressing identified social risk needs.

Background: Given the many challenges of conducting research that addresses the palliative and end-of-life care needs of patients with serious illnesses, stakeholder engagement starting from the moment of study conceptualization and design is critical to ensure successful participant recruitment, data collection, intervention delivery, data analysis, and dissemination.

Methods: Guided by a conceptual model published by the Patient-Centered Outcomes Research Institute (PCORI) entitled, "Measuring What Matters for Advancing the Science and Practice of Engagement"14 and with the support of a PCORI Engagement Officer, representatives from 9 PCORI-funded study teams formed a working group to survey team members and review, outline, and describe key lessons learned and best practices for promoting stakeholder engagement in palliative care research.

Results: Almost all study teams engaged with patients/caregivers, clinicians, researchers, and health care system experts as stakeholder partners. About half the teams also included payers and training institutions as part of their stakeholder advisors as well as a range of content experts. Study teams relied on a variety of support structures and resources, and they employed 10 distinct methods for maintaining engagement. All engagement methods were generally considered to be effective by teams who used the method, though there was some variability in team-rated engagement quality of each method. Nine barriers to stakeholder engagement were identified across the 9 studies as well as 9 strategies (or facilitators) to overcome these barriers. We share examples of how stakeholder engagement impacted studies in all phases, including the preparatory phase, study initiation phase, execution phase, and data analysis/dissemination phase.

Conclusions: Teams utilized a variety of resources and support structures as well as capitalized on multiple engagement methods for fostering stakeholder engagement, resulting in a high level of collaboration and integration.

Background: Youth comprise one-third of the US homeless population. However, little is known about how homelessness affects health care utilization.

Objective: Examine associations of homelessness with hospitalization, primary care, and ED visits, varying by race/ethnicity, among Medicaid-enrolled youth.

Research design: A cross-sectional analysis was conducted using California Medicaid claims data on youth beneficiaries with complex needs. We examined the number of hospitalizations, preventable and nonpreventable ED, and primary care visits using a multivariate regression. We further explored the differential associations by race/ethnicity.

Results: Approximately 17% of our sampled youth experienced homelessness in 2018 (N=90,202). Compared with their housed counterparts, youth experiencing homelessness had a 1.9 percentage point (pp) higher likelihood of frequent ED visits (95% CI: 1.7-2.2) but a 2.9 pp lower probability of any primary care visits (95% CI: -3.9 to -1.9). Homelessness was associated with 221 more ED visits (95% CI: 182-260), 100 more preventable ED visits (95% CI: 84-116), 19.9 more hospitalizations (95% CI: 12-27), but 56 fewer primary care visits (95% CI: -104 to -7), per 1000 youth. The associations of homelessness with total ED visits, preventable ED visits, and needed and nonpreventable ED visits were all higher among Whites and, particularly, Blacks than for Hispanics and Asians.

Conclusions: Medicaid-enrolled youth who experienced homelessness had more overall ED, preventable ED, and hospital visits, but fewer primary care visits than their housed peers. Our results suggest promoting primary care use should be considered among strategies to improve health and reduce costs.

The Patient-Centered Outcomes Research Institute (PCORI) funded multiple large-scale comparative effectiveness clinical trials evaluating palliative care (PC) and advance care planning (ACP) healthcare delivery models. This article provides an overview of the most common barriers our investigative teams encountered while implementing these trials and the strategies we utilized to overcome these challenges, with particular attention to identifying research partners for multisite trials; addressing contracting and regulatory issues; creating a team governance structure; training and engaging study staff across sites; recruiting, consenting, and enrolling study participants; collecting PC and ACP data and study outcomes; and managing multisite collaborations. The goal of this article is to provide guidance on how to best plan for and conduct rigorous trials evaluating PC and ACP healthcare delivery interventions moving forward.

Over the past decade, the Patient-Centered Outcomes Research Institute (PCORI) funded multiple large-scale, comparative effectiveness clinical trials evaluating palliative care and advance care planning interventions. These are complex multicomponent interventions that need robust but flexible fidelity monitoring. Fidelity is necessary to maintain both internal and external validity within palliative care intervention research and to ultimately evaluate the real-world impact of high-quality interventions. Different trials not only took varying approaches to fidelity monitoring but also uncovered both unique and common challenges and facilitators. This article summarizes 8 of these trials and highlights approaches, adaptations, barriers, and facilitators for intervention fidelity monitoring. Identifying and delivering core elements while simultaneously allowing adaptations of noncore elements is a vital part of fidelity monitoring. Dissemination of such experiences can inform both future palliative care research as well as ongoing implementation of palliative care and advance care planning interventions across diverse clinical practices. Adoption of rigorous intervention fidelity methods is critical to advancing the science and reproducibility of palliative care interventions.