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Using Registry Data to Construct a Comparison Group for Programmatic Effectiveness Evaluation: The New York City HIV

McKaylee M Robertson1, Levi Waldron1, Rebekkah S Robbins2

  • 1Institute for Implementation Science in Population Health, Graduate School of Public Health and Health Policy, City University of New York, New York, New York.

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A new registry-based comparison method improves intervention effectiveness studies by controlling for external trends. This approach offers a more accurate evaluation than traditional pre-post designs for public health programs.

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Area of Science:

  • Epidemiology
  • Public Health
  • Biostatistics

Background:

  • Nonrandomized interventions often use pre-post designs, which are susceptible to external events influencing outcomes.
  • Evaluating intervention effectiveness requires methods that can isolate the intervention's true impact.

Purpose of the Study:

  • To describe and evaluate a novel method for constructing a surveillance registry-based comparison group.
  • To control for secular trends when estimating intervention effectiveness in observational studies.

Main Methods:

  • Utilized the New York City human immunodeficiency virus (HIV) Surveillance Registry to create a contemporaneous comparison group.
  • Matched the comparison group to the HIV Care Coordination Program (CCP) enrollees on propensity scores, enrollment dates, and baseline viral load.
  • Employed pseudoenrollment dates in the comparison group to align with enrollment trends of the intervention group.

Main Results:

  • Registry-based comparison group estimates of program effectiveness were attenuated compared to pre-post estimates.
  • The developed method allows for controlling secular trends in outcomes of interest.
  • Demonstrated the utility of surveillance registries for creating robust comparison groups.

Conclusions:

  • The surveillance registry-based comparison group method provides a valuable tool for observational intervention effectiveness studies.
  • This methodology enhances programmatic evaluations, particularly for conditions with existing surveillance data.
  • Offers a more rigorous approach than simple pre-post designs for assessing intervention impact.