Handling problems of ecological fallacy in program planning and evaluation

HIV-Related Implementation Research for Key Populations: Designing for Individuals, Evaluating Across Populations, and Integrating Context

INTRODUCTION

Key populations, including men who have sex with men, transgender people, sex workers, people who inject drugs, and incarcerated populations, experience high burdens of HIV and urgently need effective interventions. Yet the evidence base for implementation research (IR) with key populations remains weak and poses specific challenges to epidemiologic inference. We apply the Consolidated Framework for IR to consider specific challenges and recommendations for IR with key populations.

DISCUSSION

Individuals within key populations exist within inner and outer settings-including organizational structures, legal (eg, criminalization), and funding environments-which influence the design, adoption and fidelity of interventions, and the potential sustainability of intervention scale-up. Underlying vulnerabilities and external stressors experienced at the individual level (eg, homelessness, violence) further impact participation and retention in IR. Thus, researchers should account for representation in the research process, beginning with community engagement in IR design and consideration of enumeration/sampling methods for key populations who lack probabilistic sampling frames. Interventions for key populations require substantial adaptation and complexity (eg, individually tailored, multicomponent) to ensure appropriateness; however, there is tension between the need for complexity and challenges to internal validity (fidelity) and external validity (generalizable scale-up). Finally, integrating contextual, sampling, and implementation elements into analytic approaches is critical for effectiveness evaluation.

CONCLUSIONS

Translation of efficacious findings at the individual level to effectiveness at the population level requires recognition of risk heterogeneity. Recognizing the nuances of working with key populations is essential to ensure that individuals are represented by design and therefore gains in population health can be achieved.

The use of zip coded population data in social area studies of service utilization

Social area analysis (SAA) is a well-established methodology for geographically based analysis of service delivery and other health related outcome measures. However, SAA has been limited in application by the complexities of computerized geocoding and difficulties in obtaining appropriate measures of community characteristics. In this paper we demonstrate that these problems can be overcome by employing zip code as well as the unit of analysis for SAA and obtaining commercially available measures of community characteristics. Regression analyses, using New York City zip code populations as the unit of observation were used to illustrate the role of epidemiologic risk factors in predicting rates of inpatient discharge and ambulatory care visits.