Cascade Analysis: An Adaptable Implementation Strategy Across HIV and Non-HIV Delivery Platforms.

BACKGROUND: Cascades have been used to characterize sequential steps within a complex health system and are used in diverse disease areas and across prevention, testing, and treatment. Routine data have great potential to inform prioritization within a system, but are often inaccessible to frontline health care workers (HCWs) who may have the greatest opportunity to innovate health system improvement. METHODS: The cascade analysis tool (CAT) is an Excel-based, simple simulation model with an optimization function. It identifies the step within a cascade that could most improve the system. The original CAT was developed for HIV treatment and the prevention of mother-to-child transmission of HIV. RESULTS: CAT has been adapted 7 times: to a mobile application for prevention of mother-to-child transmission; for hypertension screening and management and for mental health outpatient services in Mozambique; for pediatric and adolescent HIV testing and treatment, HIV testing in family planning, and cervical cancer screening and treatment in Kenya; and for naloxone distribution and opioid overdose reversal in the United States. The main domains of adaptation have been technical-estimating denominators and structuring steps to be binary sequential steps-as well as logistical-identifying acceptable approaches for data abstraction and aggregation, and not overburdening HCW. DISCUSSION: CAT allows for prompt feedback to HCWs, increases HCW autonomy, and allows managers to allocate resources and time in an equitable manner. CAT is an effective, feasible, and acceptable implementation strategy to prioritize areas most requiring improvement within complex health systems, although adaptations are being currently evaluated.

Improving the efficiency of HIV testing with peer recruitment, financial incentives, and the involvement of persons living with HIV infection.

BACKGROUND: The authors piloted an HIV testing and counseling (HTC) approach using respondent-driven sampling (RDS), financial incentives, and persons living with HIV infection (PLHIV). METHODS: Eligible participants were aged 30-60 years, African American or black, and residents of Oakland, CA. Participants were tested for HIV infection and asked to refer up to 3 others. The authors compared the efficiency of RDS to conventional outreach-based HTC with the number needed to screen (NNS). They evaluated the effect of 2 randomly allocated recruitment incentives on the enrollment of high-risk or HIV-positive network associates: a flat incentive ($20) for eligible recruits or a conditional incentive ($10-35) for eligible recruits in priority groups, such as first-time testers. RESULTS: Forty-eight participants (10 PLHIV and 38 HIV negative) initiated recruitment chains resulting in 243 network associates. Nine (3.7%) participants tested HIV positive, of whom 7 (78%) were previously recognized. RDS was more efficient than conventional HTC at identifying any PLHIV (new or previously recognized; RDS: NNS = 27, 95% CI: 14 to 59; conventional: NNS = 154, 95% CI: 95 to 270). There was no difference between the 2 incentive groups in the likelihood of recruiting at least 1 high-risk HIV-negative or HIV-positive network associate (adjusted odds ratio = 0.89, 95% CI: 0.06 to 13.06) or in total number of high-risk HIV-negative or HIV-positive associates (adjusted odds ratio = 0.79, 95% CI: 0.23 to 2.71). CONCLUSIONS: Social network HTC strategies may increase demand for HTC and efficiently identify PLHIV. The flat incentive was as successful as the conditional incentive for recruiting high-risk individuals. Unexpectedly, this method also reidentified PLHIV aware of their status.