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Introduction: Hospitalizations are common among people with opioid use disorder (OUD). While hospitalizations represent opportunities to engage patients and offer treatment, they are also destabilizing events associated with an increased risk of death in the post-hospitalization period.
Methods: We conducted a retrospective cohort study within the Veterans Health Administration including all Veterans with OUD who experienced at least one medical hospitalization between January 2011 and December 2021 (part of CTN-0087). We examined which patient-level clinical and demographic factors were associated with all-cause and opioid-related mortality within 0-30 and 0-365 days following an index medical hospitalization.
Results: The cohort included 90,920 Veterans with OUD who experienced one or more medical hospitalizations during the study period. Median age was 58 years, and 93% were male. Older age (adjusted Odds Ratio [aOR] range 30d: 1.50-2.66; 1y: 1.58-3.28), higher medical complexity (aOR range 30d: 2.11-6.23; 1y: 1.96-7.34), multiple substance use disorders (SUD; aOR 30d: 1.81 (95% CI 1.44, 2.27) 1y: 1.48 [95% CI 1.36, 1.62]), and length of hospitalization (aOR 30d: 6.78 [95% CI 4.85, 9.47] 1y: 3.45 [95% CI 2.96, 4.01]) were associated with increased all-cause mortality following hospitalization. Homelessness (aOR 30d: 0.75 [95% CI 0.63, 0.90]; 1y: 0.85 [95 % CI 0.80, 0.91]), depression (aOR 1y: 0.89 [95 % CI 0.84, 0.95]), bipolar disorder (aOR 1y: 0.88 [95% CI 0.82, 0.94]), buprenorphine receipt (aOR 1y: 0.79 [95% CI 0.69, 0.91]), and service connection (aOR 30d: 0.76 [95% CI 0.60, 0.97] 1y: 0.64 [95 % CI 0.59, 0.70]) were associated with reduced all-cause mortality. Younger age (aOR range 30d: 3.21-5.24; 1y: 2.71-2.38), homelessness (aOR 1y: 1.40 [95% CI 1.20, 1.63]), and multiple SUD (aOR 1y: 1.78 [95% CI 1.33, 2.38]) were among factors associated with increased opioid-related mortality after hospitalization. Black race (aOR 1y: 0.61 [95% CI 0.50, 0.74]) and higher service connection (aOR 30d: 0.41 [95 % CI 0.21, 0.81]; 1y: 0.53 [95% CI 0.43-0.66]) were associated with reduced opioid-related mortality after hospitalization.
Conclusions: Several patient-level factors were associated with increased all-cause mortality (e.g., length of hospital stay), reduced all-cause mortality (e.g., homelessness), increased opioid-related mortality (e.g., multiple SUD), and reduced opioid-related mortality (e.g., service connection) after hospitalization. This information provides a roadmap for future development and study of tailored supports and risk stratification tools to enhance post-hospitalization transitional care for patients with OUD.
Related protocols: CTN-0087
Engaging people living with HIV who report substance use (PLWH-SU) in care is essential to HIV medical management and prevention of new HIV infections. Factors associated with poor engagement in HIV care include a combination of syndemic psychosocial factors, mental and physical comorbidities, and structural barriers to healthcare utilization. Patient navigation (PN) is designed to reduce barriers to care, but its effectiveness among PLWH-SU remains unclear. In this study, researchers analyzed data from NIDA Clinical Trials Network protocol CTN-0049, a three-arm randomized controlled trial testing the effect of a 6-month PN with and without contingency management (CM), on engagement in HIV care and viral suppression among PLWH-SU (n=801). Latent profile analysis was used to identify subgroups of individuals’ experiences to 23 barriers to care. The effects of PN on engagement in care and viral suppression were compared across latent profiles. Three latent profiles of barriers to care were identified. The results revealed that PN interventions are likely to be most effective for PLWH-SU with fewer, less severe healthcare barriers. Special attention should be given to individuals with a history of abuse, intimate partner violence, and discrimination, as they may be less likely to benefit from PN alone and require additional interventions.
Related protocols: CTN-0049
People living with HIV who report substance use (PLWH-SU) face many barriers to care, resulting in an increased risk for poor health outcomes and the potential for ongoing disease transmission. This study evaluates the mechanisms by which patient navigation (PN) and contingency management (CM) interventions may work to address barriers to cae and improve HIV outcomes in this population.
Mediation analysis was conducted using data from CTN-0049 (Project HOPE), a randomized, multi-site trial testing PN interventions to improve HIV care outcomes among 801 hospitalized PLHW-SU. Direct and indirect effects of PN and PN+CM were evaluated through five potential mediators (psychosocial conditions, healthcare avoidance, financial hardship, system barriers, and self-efficacy for HIV treatment adherence) on engagement in HIV care and viral suppression.
The PN+CM intervention had an indirect effect on improving engagement in HIV care at 6 months by increasing self-efficacy for HIV treatment adherence. PN+CM also led to increases in viral suppression at 6 months via increases in self-efficacy, although the direct effects were not significant. No mediating effects were observed for PN alone.
Conclusions: PN+CM interventions for PLWH-SU can increase an individual’s self-efficacy for HIV treatment adherence, which in turn improves engagement in care at 6 months and may contribute to viral suppression over 12 months. Building self-efficacy may be a key factor in the success of such interventions and should be considered as a primary goal of PN+CM in practice.
Related protocols: CTN-0049, CTN-0049-A-1
While patient navigation has been shown to be an effective approach for linking persons to HIV care, and contingency management is effective at improving substance use-related outcomes, Project HOPE combined these two interventions in a novel way to engage HIV-positive patients with HIV and substance use treatment.
The aims of this paper are to examine patient navigator views regarding how contingency management interacted with and affected their navigation process. Individual, semi-structured interviews lasting approximately 60 minutes were administered to 22 patient navigators from the original 10 Project HOPE study sites. The interviews address the patient navigator’s professional background, descriptions of the participant population, substance use disorder vs. HIV treatment entry and engagement issues, and the use of contingency management within the navigation service delivery protocol.
Patient navigators believed that financial incentives helped motivate participant attendance at navigation sessions, particularly early in study involvement, which helped them to establish rapport and develop relationships with participants. Patient navigators often noted that financial incentives positively influenced targeted HIV health-related behaviors, such as attending medical appointments, which provided a rapid pay-off with an escalating sum. Contingency management was more complex when used by the patient navigators for substance use-related behaviors, particularly when incentives revolved around negative urine screening. Patient navigators noted that not all participants responded the same way to the contingency management and that the incentives were particularly helpful when participants were financially strained with limited resources or when internal motivation was lacking.
Conclusions: Overall, patient navigators found the inclusion of contingency management to be helpful and effective at influencing participant behaviors, particularly concerning navigation session attendance and HIV healthcare-related participation. However, issues and concerns surrounding the inclusion of contingency management for drug-related behaviors as delivered in Project HOPE were noted.
Related protocols: CTN-0049
This secondary analysis of data from Clinical Trials Network protocol CTN-0049, Project HOPE, compares outcomes for two groups of HIV+ substance users randomized in a 3-arm trial to receive Patient Navigation with (PN+CM) or without (PN) contingent financial incentives (CM). Mean age of participants was 45 years; the majority was male (67%), African American (78%), unemployed (35%), or disabled (50%). Behaviors incentivized for PN+CM were (1) attendance at HIV care visits and (2) verification of an active HIV medication prescription.
Incentives were associated with shorter time to treatment initiation and higher rates of behaviors during the 6-month intervention with exception of month 6 HIV care visits. Median HIV care visits were 3 (IQR 2–4) for PN+CM versus 1.5 (IQR 0–3) for PN (Wilcoxon p < 0.001); median validated medication checks were 4 (IQR 2–6) for PN+CM versus 1 (IQR 0–3) for PN (Wilcoxon p < 0.001). Viral suppression rates at end of treatment were not significantly different for the two groups but were directly related to the number of behaviors completed for both care visits and validated medication.
Conclusions: Contingent financial incentives added to a PN intervention were associated with better engagement in the navigation intervention, including earlier initiation and higher sustained rates of key health-related behaviors deemed necessary to achieve a final goal of viral load suppression. In addition to higher rates of initiation, it was notable that incentives were associated with a shorter average time both to the initial HIV care visit and to first verified pick up of HIV medication among those who ever initiated these behaviors. These robust results suggest value of incentives as a tool to enhance linkage to care, as well as speeding up or “kick starting” early steps in the care process within a navigation intervention. Adjustments to the incentive program may be needed to achieve greater rates of sustained health behavior change that result in improved viral load outcomes.
Related protocols: CTN-0049, CTN-0049-A-1