Applying systems engineering to implement an evidence-based intervention at a community health center

Making Smarter Decisions Faster: Systems Engineering to Improve the Global Public Health Response to HIV

PURPOSE OF REVIEW

This review offers an operational definition of systems engineering (SE) as applied to public health, reviews applications of SE in the field of HIV, and identifies opportunities and challenges of broader application of SE in global health.

RECENT FINDINGS

SE involves the deliberate sequencing of three steps: diagnosing a problem, evaluating options using modeling or optimization, and providing actionable recommendations. SE includes diverse tools (from process improvement to mathematical modeling) applied to decisions at various levels (from local staffing decisions to planning national-level roll-out of new interventions). Contextual factors are crucial to effective decision-making, but there are gaps in understanding global decision-making processes. Integrating SE into pre-service training and translating SE tools to be more accessible could increase utilization of SE approaches in global health. SE is a promising, but under-recognized approach to improve public health response to HIV globally.

Characterizing implementation strategies using a systems engineering survey and interview tool: a comparison across 10 prevention programs for drug abuse and HIV sexual risk behavior

Background

Although many behavioral interventions have proven to be efficacious, new methodologies are required beyond efficacy trials to understand how to adopt, implement with fidelity, and sustain behavioral interventions in community settings. In this paper, we present a new approach, based on systems engineering concepts and methods, for characterizing implementation strategies that are used to deliver evidence-based behavioral interventions in health and social service settings. We demonstrate the use of this approach with implementation strategies, used or being used for broader dissemination of 10 evidence-based prevention program projects focused on the prevention of drug or HIV sex risk behaviors.

Results

The results indicate that there are wide variations in intervention approaches and that there are challenges in program implementation including maintaining program fidelity, serving community needs, and adequate resources. The results also indicate that implementation requires a committed partnership between the program developers, implementation researchers, and community partners. In addition, there is a need for adaptability within programs to meet community needs, resources, and priorities while maintaining program fidelity.

Conclusions

Our methodological approach enabled us to highlight challenges associated with the community implementation of health risk prevention interventions. We also demonstrate how comprehensive descriptions of interventions facilitate understanding of the requirements of program implementation and decisions about the feasibility of implementing a program in community settings.

Adaptation of an evidence-based intervention to promote colorectal cancer screening: a quasi-experimental study

Background

To accelerate the translation of research findings into practice for underserved populations, we investigated the adaptation of an evidence-based intervention (EBI), designed to increase colorectal cancer (CRC) screening in one limited English-proficient (LEP) population (Chinese), for another LEP group (Vietnamese) with overlapping cultural and health beliefs.

Methods

Guided by Diffusion of Innovations Theory, we adapted the EBI to achieve greater reach. Core elements of the adapted intervention included: small media (a DVD and pamphlet) translated into Vietnamese from Chinese; medical assistants distributing the small media instead of a health educator; and presentations on CRC screening to the medical assistants. A quasi-experimental study examined CRC screening adherence among eligible Vietnamese patients at the intervention and control clinics, before and after the 24-month intervention. The proportion of the adherence was assessed using generalized linear mixed models that account for clustering under primary care providers and also within-patient correlation between baseline and follow up.

Results

Our study included two cross-sectional samples: 1,016 at baseline (604 in the intervention clinic and 412 in the control clinic) and 1,260 post-intervention (746 in the intervention and 514 in the control clinic), including appreciable overlaps between the two time points. Pre-post change in CRC screening over time, expressed as an odds ratio (OR) of CRC screening adherence by time, showed a marginally-significant greater increase in CRC screening adherence at the intervention clinic compared to the control clinic (the ratio of the two ORs = 1.42; 95% CI 0.95, 2.15). In the sample of patients who were non-adherent to CRC screening at baseline, compared to the control clinic, the intervention clinic had marginally-significant greater increase in FOBT (adjusted OR = 1.77; 95% CI 0.98, 3.18) and a statistically-significantly greater increase in CRC screening adherence (adjusted OR = 1.70; 95% CI 1.05, 2.75).

Conclusions

Theoretically guided adaptations of EBIs may accelerate the translation of research into practice. Adaptation has the potential to mitigate health disparities for hard-to-reach populations in a timely manner.