National probability samples in studies of low-prevalence diseases. Part II: Designing and implementing the HIV cost and services utilization study sample.
OBJECTIVE
The design and implementation of a nationally representative probability sample of persons with a low-prevalence disease, HIV/AIDS.


METHODS
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.


METHODS
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.


METHODS
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.


RESULTS
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.
Frankel
M R
MR
Baruch College, CUNY, USA.
Shapiro
M F
MF
Duan
N
N
Morton
S C
SC
Berry
S H
SH
Brown
J A
JA
Burnam
M A
MA
Cohn
S E
SE
Goldman
D P
DP
McCaffrey
D F
DF
Smith
S M
SM
St Clair
P A
PA
Tebow
J F
JF
Bozzette
S A
SA
D003625:Data Collection; D015658:HIV Infections / Q000191:economics*; D017048:Health Care Costs / Q000706:statistics & numerical data*; D006296:Health Services / Q000191:economics / Q000706:statistics & numerical data*; D006302:Health Services Research / Q000379:methods* / Q000706:statistics & numerical data; D006801:Humans; D015233:Models, Statistical; D018579:Patient Selection; D015995:Prevalence; D011336:Probability; D011897:Random Allocation; D015203:Reproducibility of Results; D012107:Research Design; D018401:Sample Size; D014481:United States