Hospital Readmissions by Variation in Engagement in the Health Care Hotspotting Trial: A Secondary Analysis of a Randomized Clinical Trial.

Importance: Variability in intervention participation within care management programs can complicate standard analysis strategies. Objective: To evaluate whether care management was associated with reduced hospital readmissions among individuals with higher participation probabilities. Design, Setting, and Participants: A total of 800 hospitalized patients aged 18 years and older were randomized as part of the Health Care Hotspotting randomized clinical trial, which was conducted in Camden, New Jersey, from June 2014 to September 2017. Data were collected through October 2018. In this new analysis performed between April 6, 2022, and April 23, 2023, the distillation method was applied to account for variable intervention participation. A gradient-boosting machine learning model produced predicted probabilities of engaged participation using baseline covariates only. Predicted probabilities were used to trim both intervention and control populations in an equivalent manner, and intervention effects were reevaluated within study population subsets that were increasingly concentrated with patients having higher participation probabilities. Patients had 2 or more hospitalizations in the 6-month preenrollment period and documented evidence of chronic illness and social complexity. Intervention: Multidisciplinary teams provided services to patients in the intervention arm for a mean 120 days after hospital discharge. Patients in the control group received usual postdischarge care. Main Outcomes and Measures: Hospital readmission rates and counts 30, 90, and 180 days postdischarge. Results: Of 800 eligible patients, 782 had complete discharge information and were included in this analysis (mean [SD] age, 56.6 [12.7] years; 395 [50.5%] female). In the intent-to-treat analysis, the unadjusted 180-day readmission rate for treatment and control groups was 60.1% vs 61.7% (adjusted odds ratio, 0.95; 95% CI, 0.71-1.28; P = .73) and the mean (SD) number of 180-day readmissions was 1.45 (1.89) vs 1.48 (1.94) (adjusted incidence rate ratio, 0.99, 95% CI, 0.88-1.12; P = .86). Among the population with the highest participation probabilities, the mean (SD) 180-day readmission count was 1.22 (1.74) vs 1.57 (1.74) and the incidence rate ratio attained statistical significance (adjusted incidence rate ratio, 0.74; 95% CI, 0.56-0.99; P = .045). Adjusted odds ratios and adjusted incidence rate ratios for 30- and 90-day outcomes reached statistical significance after population distillation. Conclusions and Relevance: This secondary analysis of a randomized clinical trial found that care management was associated with reduced readmissions among patients with higher participation probabilities, suggesting that program operation could be improved by addressing barriers to participation and refining inclusion criteria to identify patients most likely to benefit. Trial Registration: ClinicalTrials.gov Identifier: NCT02090426.

Dosage and outcomes in a complex care intervention.

OBJECTIVES: The purpose of our study was to assess the relationship between intervention dosage and hospital utilization outcomes among patients with complex health and social needs enrolled in a care management program. We highlight the importance of measuring patient engagement and intervention dosage in program evaluation. STUDY DESIGN: We performed a secondary analysis of data collected between 2014 and 2018 as part of a randomized controlled trial of the Camden Coalition's signature care management intervention. Our analytical sample consisted of 393 patients. METHODS: We calculated a time-invariant cumulative dosage rank based on the number of hours spent by care teams working with or on behalf of patients and then divided patients into low- and high-dosage groups. We applied propensity score reweighting to compare hospital utilization outcomes between patients in these 2 groups. RESULTS: Compared with patients in the low-dosage group, those in the high-dosage group had a lower readmission rate at 30 (21.6% vs 36.6%; P < .001) and 90 (41.7% vs 55.2%; P = .003) days post enrollment. The difference between the 2 groups at 180 days post enrollment was not statistically significant (57.5% vs 64.9%; P = .150). CONCLUSIONS: Our study elucidates a gap in how care management programs for patients with complex health and social needs are evaluated. Although the study shows an association between intervention dosage and care management outcomes, patients' medical complexity and social circumstances are among the factors that can attenuate the dose-response relationship over time.

Assessing the relationship between housing and health among medically complex, chronically homeless individuals experiencing frequent hospital use in the United States.

In the United States and abroad, health systems have begun to address housing insecurity through programs that adhere to the Housing First model. The model provides permanent supportive housing without disqualification due to current mental health problems or substance use, along with optional case management services. This study used qualitative methods to explore how housing stability affected chronic disease management and social and community relationships among individuals with complex health and social needs and patterns of high hospital utilisation who were housed as part of a scattered-site Housing First program in a mid-size city in the northeastern United States. 26 individual, semi-structured interviews were conducted with Housing First clients in their homes or day program sites between March and July 2017. Interviews were digitally recorded and transcripts were analysed using a qualitative descriptive methodology until thematic saturation was reached. Findings suggest that housing provided the physical location to manage the logistical aspects of care for these clients, and an environment where they were better able to focus on their health and wellness. Study participants reported less frequent use of emergency services and more regular interaction with primary care providers. Additionally, case managers' role in connecting clients to behavioural health services removed barriers to care that clients had previously faced. Housing also facilitated reconnection with family and friends whose relationships with participants had become strained or distant. Changes to physical and social communities sometimes resulted in experiences of stigmatisation and exclusion, especially for clients who moved to areas with less racial and socioeconomic diversity, but participation in the program promoted an increased sense of safety and security for many clients.

Characteristics and behavioral health needs of patients with patterns of high hospital use: implications for primary care providers.

BACKGROUND: A small percentage of patients relies extensively on hospital-based care and account for a disproportionately high share of health care spending in the United States. Evidence shows that behavioral health conditions are common among these individuals, but understanding of their behavioral health needs is limited. This study aimed to understand the behavioral health characteristics and needs of patients with high hospital utilization patterns in Camden, New Jersey. METHODS: The sample consisted of patients in a care management intervention for individuals with patterns of high hospital utilization who were referred for behavioral health assessments (N = 195). A clinical psychologist conducted the assessments, which informed a multiaxial evaluation with diagnostic criteria from the Diagnostic and Statistical Manual of Mental Disorders and a Mental Status Examination, to facilitate accurate diagnosis. Demographic characteristics, housing instability, exposure to trauma, and health care service utilization data were also collected through self-report and chart reviews. RESULTS: Ninety percent of patients were diagnosed with a psychiatric and/or active substance use disorder. Depression was the most common psychiatric disorder and alcohol use was the most common substance use disorder. However, only 10% of patients with an active substance use disorder were in treatment, and only 17% of patients with a mental health diagnosis were receiving mental health treatment. Nearly all (91%) patients reported having a primary care provider at the time of assessment and most had seen their primary care provider within three months of their last hospital discharge. Non-medical barriers to health and wellness, specifically housing instability and exposure to trauma, were also common (35 and 61% of patients, respectively) among patients. CONCLUSION: Findings highlight the importance of identifying and treating patients with behavioral health needs in the primary care setting. Developing connections with community agencies who provide behavioral health and substance use treatment can enhance primary care providers' efforts to address their patients' non-medical barriers to treatment, as can embedding behavioral health providers within primary care offices. The study also underscores the need for trauma-informed care in primary care settings.

Outcomes of a Citywide Campaign to Reduce Medicaid Hospital Readmissions With Connection to Primary Care Within 7 Days of Hospital Discharge.

Importance: Previous research suggests the important role of timely primary care follow-up in reducing hospital readmissions, although effectiveness varies by program design and patients' readmission risk level. Objective: To evaluate the outcomes of the 7-Day Pledge program to reduce readmissions by increasing access to timely primary care appointments after hospitalization. Design, Setting, and Participants: Retrospective cohort study of hospital readmissions among Medicaid patients 18 years or older hospitalized from January 1, 2014, to April 30, 2016, in Camden, New Jersey. To assess each patient's hospital use before and after hospital discharge, all-payer claims data from 4 health care systems were linked to insurers' lists of patients assigned to Camden-based primary care practices. A total of 1531 records were categorized by timing of a primary care appointment after discharge. Discharges followed by a primary care appointment within 7 days (treatment group) were matched by propensity scores to those with less timely or no primary care follow-up (nontreatment pool). Interventions: Targeted patient enrollment during hospital admission, primary care practice engagement, patient incentives to overcome barriers to keeping an appointment, and reimbursements to practices for prioritizing patients recently discharged from the hospital. Main Outcomes and Measures: The primary outcome was the number of hospital discharges followed by a readmission within 30 days. The secondary outcome was the number of hospital discharges followed by a readmission within 90 days. Results: There were 2580 hospitalizations of patients 18 years and older included on the patient lists from January 1, 2014, to April 30, 2016. Of these, 1531 records categorized by timing of a primary care appointment after discharge were studied. The treatment group consisted of 450 discharged patients (mean [SD] age, 48.7 [14.7] years; 289 [64.2%] female; 203 [45.1%] black, non-Hispanic). The nontreatment pool consisted of 1081 discharged patients (mean [SD] age, 48.1 [14.9] years; 599 [55.4%] female; 526 [48.7%] black, non-Hispanic). Among this cohort, the number of discharges followed by any readmission was lower for patients with a primary care visit within 7 days of hospital discharge than for their matched referents at 30 days (57 of 450 [12.7%] vs 78.8 of 450 [17.5%]; P = .03) and 90 days (126 of 450 [28.0%] vs 174 of 450 [38.7%]; P = .002) after discharge. Conclusions and Relevance: Facilitated receipt of primary care follow-up within 7 days of hospital discharge was associated with fewer Medicaid readmissions. The findings illuminate the importance of reducing barriers that patients and providers face during care transitions.

Cluster Analysis of Acute Care Use Yields Insights for Tailored Pediatric Asthma Interventions.

STUDY OBJECTIVE: We undertake this study to understand patterns of pediatric asthma-related acute care use to inform interventions aimed at reducing potentially avoidable hospitalizations. METHODS: Hospital claims data from 3 Camden city facilities for 2010 to 2014 were used to perform cluster analysis classifying patients aged 0 to 17 years according to their asthma-related hospital use. Clusters were based on 2 variables: asthma-related ED visits and hospitalizations. Demographics and a number of sociobehavioral and use characteristics were compared across clusters. RESULTS: Children who met the criteria (3,170) were included in the analysis. An examination of a scree plot showing the decline in within-cluster heterogeneity as the number of clusters increased confirmed that clusters of pediatric asthma patients according to hospital use exist in the data. Five clusters of patients with distinct asthma-related acute care use patterns were observed. Cluster 1 (62% of patients) showed the lowest rates of acute care use. These patients were least likely to have a mental health-related diagnosis, were less likely to have visited multiple facilities, and had no hospitalizations for asthma. Cluster 2 (19% of patients) had a low number of asthma ED visits and onetime hospitalization. Cluster 3 (11% of patients) had a high number of ED visits and low hospitalization rates, and the highest rates of multiple facility use. Cluster 4 (7% of patients) had moderate ED use for both asthma and other illnesses, and high rates of asthma hospitalizations; nearly one quarter received care at all facilities, and 1 in 10 had a mental health diagnosis. Cluster 5 (1% of patients) had extreme rates of acute care use. CONCLUSION: Differences observed between groups across multiple sociobehavioral factors suggest these clusters may represent children who differ along multiple dimensions, in addition to patterns of service use, with implications for tailored interventions.

Improving Depression Care Through an Online Learning Collaborative.

Depression is a leading cause of disability worldwide, and many internists diagnose and treat depression. This study aimed to examine the impact of a practice improvement intervention on screening and managing patients with depression in primary care. This pre-post study design included a physician practice survey designed to capture what the physicians believed they were doing in practice, a chart audit tool to capture what physicians were actually doing in practice, and an intervention that included an evidence-based educational program, online toolkit, and practice improvement coaching conference calls that promoted group learning. Following completion of the intervention, participants increasingly used the Patient Health Questionnaire-9 to detect, diagnose, and gauge treatment success for depression and reported increased use of guidelines and team-based care. Although barriers to improving depression care exist, this study suggests that evidence-based quality improvement programs can positively affect practice.