Medical Care最新文献

Objective: Characterize the association between Medicare Accountable Care Organizations' (ACOs) behavioral health integration capability and quality and utilization among adults with serious mental illness (SMI).

Background: Controlled research supports the efficacy of integrating physical and mental health care for adults with SMI, yet little is known about the organizations integrating care and associations between integration capability and quality.

Methods: We surveyed Medicare ACOs (2017-2018 National Survey of ACOs, response rate 69%) and linked responses to 2016-2017 fee-for-service Medicare claims for beneficiaries with SMI. We examined the cross-sectional association between ACO-reported integration capability (tertiles of a 14-item index) and 7 patient-level quality and utilization outcomes. We fit generalized linear models for each outcome as a function of ACO integration capability, adjusting for ACO and beneficiary characteristics.

Results: Study sample included 274,928 beneficiary years (199,910 unique beneficiaries) attributed to 265 Medicare ACOs. ACOs with high behavioral health integration capability (top-tertile) served more dual-eligible beneficiaries (67.8%) than bottom-tertile (63.7%) and middle-tertile ACOs (63.3%). Most beneficiaries received follow-up 30 days after mental health hospitalization and chronic disease monitoring-exceeding national quality benchmarks-but beneficiaries receiving care from top-tertile (vs bottom-tertile) ACOs were modestly less likely to receive follow-up [-2.17 percentage points (pp), P < 0.05], diabetes monitoring (-2.19 pp, P < 0.05), and cardiovascular disease monitoring (-6.07 pp, P < 0.05). Integration capability was not correlated with utilization.

Conclusions: ACOs serving adults with substantial physical and mental health needs were more likely to report comprehensive integration capability but were not yet meeting the primary care needs of many adults with SMI.

Objective: Mobile health applications (mHealth apps) can provide health care and health-promoting information while contributing to improving cancer survivors' quality of life and health outcomes. However, little is known about the rural-urban distribution of mHealth app ownership and utilization. In this study, we explore the characteristics of cancer survivors who own and use mHealth apps and examine rural-urban disparities in mHealth app ownership and utilization among cancer survivors.

Methods: We utilized data from the "Health Information National Trends Survey-Surveillance, Epidemiology, and End Results" pilot study, fielded among cancer survivors from 3 U.S. cancer registries (Iowa, New Mexico, and California) in 2021. Our sample included 942 cancer survivors who reported owning a smart device (a smartphone and/or a tablet computer). The analyses included computing weighted proportions and fitting a multivariable regression model.

Results: Overall, 60.3% of cancer survivors reported using mHealth apps, and 16.9% resided in rural areas. Approximately 45.0% of rural cancer survivors reported utilizing mHealth apps (vs 63.5% of urban survivors). Regression analysis revealed that rural cancer survivors had 46.0% lower odds of owning and using mHealth apps compared with their urban counterparts (adjusted odds ratio = 0.54; 95% CI: 0.36, 0.80).

Conclusions: Rural cancer survivors were less likely to own and use mHealth apps compared with urban survivors. Rural cancer survivors usually face structural and health care system-related barriers to health care access and affordability. Leveraging mHealth technology as a tool could potentially contribute to improving health care delivery for rural cancer survivors, and help address existing structural and informational barriers to access.

Background: Restrictive Medicaid policies regarding hepatitis C virus (HCV) treatment may exacerbate rural health care disparities for people who use drugs (PWUD). We assessed associations between Medicaid restrictions and HCV treatment among rural PWUD.

Methods: We compiled state-specific Medicaid treatment policies across 8 US rural sites in 10 states and merged these with participant survey data. We hypothesized that local restrictions regarding prescriber type, sobriety, and fibrosis estimates were associated with HCV treatment outcomes. We conducted a cross-sectional, ecological analysis of treatment restrictions and HCV treatment outcomes using bivariate analyses to characterize differences between PWUD who initiated HCV treatment and unadjusted logistic regressions to assess associations between restrictions and treatment.

Results: Among 944 participants, 111 (12%) reported receiving HCV treatment. Participants receiving treatment were older [median age (interquartile range): 42 (34-53) vs. 35 (29-42), P<0.001], more likely to receive disability support (32% vs. 20%, P=0.002), and less likely to be Medicaid-insured (57% vs. 71%, P < 0.001). More PWUD in states without any restrictions reported receiving treatment (17% vs. 11%, P=0.08) and achieving HCV cure/clearance (42% vs. 30%, P=0.01) than in states with restrictions. Restrictions were associated with lower odds of receiving HCV treatment (odds ratio=0.61, 95% CI: 0.35-1.06, P=0.08). Sensitivity analyses showed a similar association with HCV cure/clearance (odds ratio=0.60, 95% CI: 0.40-0.91, P=0.02).

Conclusions: We identified significant unadjusted associations between Medicaid restrictions and receipt of HCV treatment and cure, which has substantial implications for health outcomes among rural PWUD. Lifting remaining Medicaid restrictions will be critical to achieving HCV elimination.

Background: There is a lack of consensus on the effectiveness of audio-based care to manage chronic conditions. This knowledge gap has implications for health policy decisions and for health equity, as underserved populations are more likely to access care by telephone.

Objectives: We compared the effectiveness of audio-based care to usual care for managing chronic conditions (except diabetes).

Design: We used systematic review methods to synthesize available evidence.

Studies: We searched for English-language articles reporting on randomized controlled trials (RCTs) of adults diagnosed with a chronic condition published since 2012.

Outcomes: We abstracted data on clinical outcomes, patient-reported health and quality of life, health care access and utilization, care quality and experience, and patient safety.

Results: We included 40 RCTs evaluating audio-based care for a variety of chronic conditions, including cancer, heart failure, neurological disease, respiratory disease, musculoskeletal conditions, kidney disease, and others. There was significant heterogeneity across conditions and interventions. We generally found low to very low certainty of evidence of comparable effectiveness in the use of audio-based care to replace other care. Audio care as a supplement exhibited greater effectiveness in some outcomes, with generally low to very low certainty of evidence for most outcomes but moderate certainty for 2 groups of study outcomes.

Conclusions: More research is needed to identify the conditions, populations, and intervention design combinations that improve outcomes and to determine when audio-based care can effectively replace other synchronous care.

Background: Community-acquired acute kidney injury (CA-AKI) occurs outside of the hospital and is the most common form of AKI. CA-AKI is not well understood, which hinders efforts to prevent, identify, and manage CA-AKI.

Objective: Examine 30-day outcomes following CA-AKI using national administrative and lab data from the Veterans Health Administration (VA).

Research design: Retrospective cohort study.

Subjects: VA primary care patients with recorded outpatient serum creatinine (SCr) with observed CA-AKI (cases) and a standardized mortality ratio propensity-weighted 5% comparator sample without observed CA-AKI in 2013-2017.

Measures: CA-AKI was defined as a ≥1.5-fold relative increase in outpatient SCr or inpatient SCr (≤24 h from admission) from a reference outpatient SCr ≤12 months prior. Outcomes were 30-day mortality and hospitalization and were assessed in separate weighted Cox regression models.

Results: Among 220,777 CA-AKI events and 492,539 comparators without observed CA-AKI, CA-AKI was associated with a higher risk of 30-day all-cause mortality [hazard ratio (HR)=4.17, 95% CI: 3.74, 4.63] and hospitalization (HR=1.82, 95% CI: 1.74, 1.90) versus comparator. Risks increased with severity (mortality HR=3.02, 7.67, and 12.22 for AKI stages 1-3, respectively). Outpatient CA-AKI was associated with a high risk of mortality (HR=2.04, 95% CI: 1.83, 2.28) and even higher for inpatient CA-AKI, present [≤24 h from admission (HR=11.32, 95% CI: 10.16, 12.61)].

Conclusions: In a national cohort of Veterans, CA-AKI was associated with a 2-fold increased risk of hospitalization and a 3-11-fold risk of mortality. Improving identification and management is critical to mitigate adverse outcomes of CA-AKI.

Background: Telehealth services can increase access to care by reducing barriers. Telephone-administered care, in particular, requires few resources and may be preferred by communities in areas that are systemically underserved. Understanding the effectiveness of audio-based care is important to combat the current mental health crisis and inform discussions related to reimbursement privileges.

Objectives: We compared the effectiveness of audio-based care to usual care for managing mental health and substance use disorders (MHSUD).

Design: We used systematic review methods to synthesize available evidence.

Studies: We searched for English-language articles reporting randomized controlled trials (RCTs) of adults diagnosed with MHSUD published since 2012.

Outcomes: We abstracted data on clinical outcomes, patient-reported health and quality of life, health care access and utilization, care quality and experience, and patient safety.

Results: We included 31 RCTs of participants diagnosed with depression, post-traumatic stress disorder (PTSD), other serious mental illness (SMI), anxiety, insomnia, or substance use disorder (SUD). Most of the evidence was for interventions targeting depression, PTSD, and SUD. The evidence demonstrates promise for: (1) replacing in-person care with audio care for depression, other SMI, and SUD (very low to moderate certainty of comparable effectiveness); and (2) adding audio care to monitor or treat depression, PTSD, anxiety, insomnia, and SUD (low to moderate certainty of evidence favoring audio care for clinical outcomes).

Conclusions: MHSUD can be managed with audio care in certain situations. However, more evidence is needed across conditions, and specifically for anxiety and other conditions for which no research was identified.

Objective: To examine the characteristics and risk factors associated with 30-day readmissions, including the impact of home health care (HHC), among older sepsis survivors transitioning from hospital to home.

Research design: Retrospective cohort study of the Medical Information Mart for Intensive Care (MIMIC)-IV data (2008-2019), using generalized estimating equations (GEE) models adjusting for patient sociodemographic and clinical characteristics.

Subjects: Sepsis admission episodes with in-hospital stays, aged over 65, and discharged home with or without HHC were included.

Measures: The outcome was all-cause hospital readmission within 30 days following sepsis hospitalization. Covariates, including the primary predictor (HHC vs. Home discharges), were collected during hospital stays.

Results: Among 9115 sepsis admissions involving 6822 patients discharged home (66.8% HHC, 33.2% Home), HHC patients, compared with those discharged without services, were older, had more comorbidities, longer hospital stays, more prior hospitalizations, more intensive care unit admissions, and higher rates of septic shock diagnoses. Despite higher illness severity in the HHC discharges, both groups had high 30-day readmission rates (30.2% HHC, 25.2% Home). GEE analyses revealed 14% higher odds of 30-day readmission for HHC discharges after adjusting for risk factors (aOR: 1.14; 95% CI: 1.02-1.27; P=0.02).

Conclusions: HHC discharges experienced higher 30-day readmission rates than those without, indicating the need for specialized care in HHC settings for sepsis survivors due to their complex health care needs. Attention to sepsis survivors, regardless of HHC receipt, is crucial given the high readmission rates in both groups. Further research is needed to optimize postacute care/interventions for older sepsis survivors.

Background: Medicare Bayesian Improved Surname and Geocoding (MBISG), which augments an imperfect race-and-ethnicity administrative variable to estimate probabilities that people would self-identify as being in each of 6 mutually exclusive racial-and-ethnic groups, performs very well for Asian American and Native Hawaiian/Pacific Islander (AA&NHPI), Black, Hispanic, and White race-and-ethnicity, somewhat less well for American Indian/Alaska Native (AI/AN), and much less well for Multiracial race-and-ethnicity.

Objectives: To assess whether temporal inconsistency of self-reported race-and-ethnicity might limit improvements in approaches like MBISG.

Methods: Using the Medicare Health Outcomes Survey (HOS) baseline (2013-2018) and 2-year follow-up data (2015-2020), we evaluate the consistency of self-reported race-and-ethnicity coded 2 ways: the 6 mutually exclusive MBISG categories and individual endorsements of each racial-and-ethnic group. We compare the consistency of self-reported race-and-ethnicity (HOS) to the accuracy of MBISG (using 2021 Medicare Consumer Assessment of Healthcare Providers and Systems data).

Results: Concordance (C-statistic) of HOS baseline and follow-up self-reported race-and-ethnicity was 0.95-0.97 for AA&NHPI, Black, Hispanic, and White, 0.83 for AI/AN, and 0.72 for Multiracial using mutually exclusive categories (weighted concordance=0.956). Concordance of MBISG with self-report followed a similar pattern and had similar values, with somewhat lower AI/AN and Multiracial values. The concordance of individual endorsements over time was somewhat higher than for classification (weighted concordance=0.975).

Conclusions: The concordance of MBISG with self-reported race-and-ethnicity appears to be limited by the consistency of self-report for some racial-and-ethnic groups when employing the 6-mutually-exclusive category approach. The use of individual endorsements can improve the consistency of self-reported data. Reconfiguring algorithms such as MBISG in this form could improve its overall performance.

Objectives: We compared the effectiveness of audio-based care, as a replacement or a supplement to usual care, for managing diabetes.

Background: Diabetes is a chronic condition afflicting many in the United States. The impact of audio-based care on the health of individuals with diabetes is unclear, particularly for those at risk for disparities-many of whom may only be able to access telehealth services through telephone.

Methods: We used systematic review methods to synthesize available evidence. We systematically searched for English-language articles from 2012 reporting randomized controlled trials of adults diagnosed with diabetes. We abstracted data on clinical outcomes (including A1c), patient-reported health and quality-of-life, health care access and utilization, care quality and experience, and patient safety.

Results: Evidence for replacing in-person care with audio care was limited (n = 2), with low certainty of evidence for greater and comparable effectiveness for A1c and harms, respectively. Supplemental audio care (n = 23) had a positive effect on A1c (pooled mean difference A1c -0.20%; n = 8763; 95% CI: -0.36% to -0.04%), with moderate certainty of evidence. Stratified results indicated that audio interventions supplementing usual care performed more favorably in individuals with A1c ≤ 9%; populations not at risk of disparities; interventions with at least monthly contact; and interventions using remote monitoring tools.

Conclusions: This evidence base reveals some promise for managing diabetes with audio-based care as a supplement to in-person care. Future studies could further investigate the effectiveness of audio-based care as a replacement and modify interventions to better serve individuals with poor glucose control and those at risk for disparities.