National probability samples in studies of low-prevalence diseases. Part II: Designing and implementing the HIV cost and services utilization study sample

Health Serv Res. 1999 Dec;34(5 Pt 1):969-92.

Abstract

Objective: The design and implementation of a nationally representative probability sample of persons with a low-prevalence disease, HIV/AIDS.

Data sources/study setting: One of the most significant roadblocks to the generalizability of primary data collected about persons with a low-prevalence disease is the lack of a complete methodology for efficiently generating and enrolling probability samples. The methodology developed by the HCSUS consortium uses a flexible, provider-based approach to multistage sampling that minimizes the quantity of data necessary for implementation.

Study design: To produce a valid national probability sample, we combined a provider-based multistage design with the M.D.-colleague recruitment model often used in non-probability site-specific studies.

Data collection: Across the contiguous United States, reported AIDS cases for metropolitan areas and rural counties. In selected areas, caseloads for known providers for HIV patients and a random sample of other providers. For selected providers, anonymous patient visit records.

Principal findings: It was possible to obtain all data necessary to implement a multistage design for sampling individual HIV-infected persons under medical care with known probabilities. Taking account of both patient and provider nonresponse, we succeeded in obtaining in-person or proxy interviews from subjects representing over 70 percent of the eligible target population.

Conclusions: It is possible to design and implement a national probability sample of persons with a low-prevalence disease, even if it is stigmatized.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Data Collection
  • HIV Infections / economics*
  • Health Care Costs / statistics & numerical data*
  • Health Services / economics
  • Health Services / statistics & numerical data*
  • Health Services Research / methods*
  • Health Services Research / statistics & numerical data
  • Humans
  • Models, Statistical
  • Patient Selection
  • Prevalence
  • Probability
  • Random Allocation
  • Reproducibility of Results
  • Research Design*
  • Sample Size
  • United States