The objective of this study was to determine the sensitivity of an AIDS case-finding algorithm.
This study applied the AIDS case-finding algorithm to paid Medicaid claims linked to New Jersey AIDS surveillance data and assesses its sensitivity across subgroups of patients.
Of the 7183 cases with confirmed AIDS, based on the state’s registry information, 95% (n = 6818) were correctly detected using all Medicaid claims, including pharmacy. For patients in a community-based waiver program, covered by Medicare, diagnosed with a severe mental illness, or continuously enrolled in Medicaid, with regular contact with the medical system, the algorithm identified almost all patients. To further evaluate algorithm performance, it was used with 2 groups of interest to researchers. For AIDS patients in the last 6 months of life, 88% were correctly detected without use of pharmacy claims and 95% when pharmacy claims were included. For pregnant women, data from the 6 months before the latest delivery date identify 27% of pregnant women without pharmacy claims and 41% when pharmacy claims were included. Using claims made after the latest delivery date, 81% of pregnant women were detected without pharmacy claims and 93% when pharmacy claims were included
Results demonstrate that a multilevel screen can be used with Medicaid claims to effectively to detect most patients with AIDS. Detection is lower for some subgroups, and the absence of pharmacy claims can compromise detection.
From the Institute for Health, Health Care Policy, and Aging Research, Rutgers University, New Brunswick, New Jersey.
This research was supported by a grant from the NIMH GRANT, AGING GRANT and State/Territorial Minority HIV/AIDS Demonstration Grant, D92MP99003-01.
The findings and opinions reported here are those of the authors and do not necessarily represent the views of any other individuals or organizations.
Reprints: James T. Walkup, PhD, Institute for Health, Health Care Policy, and Aging Research, Rutgers University, 30 College Avenue, New Brunswick, NJ 08901. E-mail: email@example.com.