Developing an Implementation Facilitation Strategy for a Behavioral Health Screening and Referral to an Ehealth Positive Affect Intervention for People Living with HIV: Mixed-Methods Findings from Pre-Implementation Research in the Ryan White Case Managem

Background and Purpose: Depression is alarmingly common in people living with HIV (PLWH) and is a significant barrier to optimal engagement in HIV care. Positive affect, independent of depression, predicts slower disease progression, better adherence to medication, and higher likelihood of achieving suppressed viral load. Thus, interventions to increase positive affect may support more effective engagement in and success with HIV care. In partnership with AIDS Foundation Chicago, and guided by the Consolidated Framework for Implementation Research (CFIR), this study conducted pre-implementation research in order to develop a system-wide implementation strategy for the clinic-based implementation of a behavioral health screener and eHealth positive affect intervention for people living with HIV and depression.

Methods: The study analyzes survey and in-depth interview data from staff at 16 HRSA-funded Ryan White Medical Case Management sites in the Chicagoland area. Medical case managers (MCMs) and supervisors were recruited via email for a survey covering CFIR domains. Survey data was analyzed to understand clinic- and systems-level implementation barriers and facilitators, and to inform a purposive sampling frame and interview protocol with MCMs and supervisors from all 16 medical case management sites. Interview data were analyzed by a team of five researchers using a Rapid Qualitative Analysis method validated for use in implementation science studies guided by the CFIR. Qualitative analysts completed interview summaries for each individual interview and assessed the reliability of the summary analysis in partnership with another coder. Interview summaries were then synthesized in an analysis matrix in alignment with the CFIR constructs (i.e., Intervention Characteristics) and domains (i.e., Complexity).

Results: Survey respondents (n=58; 68% response rate) had somewhat positive views of the inner setting, including team culture, learning climate, and implementation readiness (Ms = 3.8 to 3.88 on 5-point scale). However, rewards/incentives for quality improvement projects were identified in only 44% of clinics. Other potential implementation barriers included complexity (M = 2.54), (human resource) cost (Ms = 2.91 to 3.33), and moderate relative advantage (Ms = 2.44 to 2.81). Structured interviews with n = 15 MCMs and supervisors expanded upon these results, leading to refinements in the implementation plan, including: (1) adding screening and referral prompts within the case management system (to reduce complexity), (2) training on using the intervention to complement, rather than substitute for, other behavioral health services (to heighten relative advantage), and (3) providing regular feedback to each clinic regarding referrals of eligible clients (to heighten rewards/incentives). Data were combined with clinic information (e.g., demographics) to inform the development of an implementation research logic model, implementation strategies, and training materials, as well the grouping of clinics for a stepped wedge trial of the behavioral health screener and eHealth intervention.

Conclusion: Pre-implementation research using the CFIR model can serve as a useful guide to boosting the reach and effectiveness of interventions targeting PLWH. This work also is integral for ensuring that interventions in case management systems can be implemented with integrity and sustainability without overburdening case management staff.