Camouflaged sampling and contacting of people from administrative databases: reaching target patients without knowing who they are.
BACKGROUND
Methods are needed for using confidential data to select and reach patients without compromising their health privacy.


METHODS
(a)


METHODS
we created (1) an anonymous list of encrypted personal health numbers (EPHNs) of target patients (e.g., users of the medications of interest) and (2) an anonymous list of EPHNs of people randomly sampled from the general population of non-users. The two lists were merged and randomly ordered to make a camouflaged list. People on the second list were called camouflagers. Then EPHNs were matched to names and contact information, and the EPHNs were removed from the contact list. (b) Contacting: when we contacted patients by mail or telephone, we told them their names were selected from one of two lists, and their health status was unknown to us. We invited respondents to answer (1) a short survey for the general population or (2) a longer survey concerning the target condition.


RESULTS
In five studies, the percentage of camouflagers--equal to one minus the positive predictive value of the camouflaged list--has varied from 10 to over 50%. This depended on the psychosocial sensitivity of the target medications or health conditions, the natural camouflaging by the population's heterogeneity or inaccuracy of the data on the target characteristic, the degree of stratification of the sample, and the cost of contacting.


CONCLUSIONS
Camouflaging enables administrative data to be used for contacting target patients in selected populations while adhering to current data privacy laws and ethics principles.
Maclure
Malcolm
M
School of Health Information Science, Faculty of Human and Social Development, University of Victoria, Victoria, BC, Canada. mmaclure@uvic.ca
Warren
Leanne
L
Willison
Donald
D
Cassels
Alan
A
Carleton
Bruce
B
D003219:Confidentiality / Q000941:ethics* / Q000592:standards; D016208:Databases, Factual; D006761:Hospitals; D006801:Humans; D016134:Organizational Policy; D018579:Patient Selection; D012494:Sampling Studies