Literature DB >> 15258477

Sensitivity of an AIDS case-finding algorithm: who are we missing?

James T Walkup1, Wenhui Wei, Usha Sambamoorthi, Stephen Crystal.   

Abstract

OBJECTIVE: The objective of this study was to determine the sensitivity of an AIDS case-finding algorithm.
METHOD: 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.
FINDINGS: 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
CONCLUSION: 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.

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Year:  2004        PMID: 15258477     DOI: 10.1097/01.mlr.0000132749.20897.46

Source DB:  PubMed          Journal:  Med Care        ISSN: 0025-7079            Impact factor:   2.983


  20 in total

1.  Use of Medicaid data to explore community characteristics associated with HIV prevalence among beneficiaries with schizophrenia.

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2.  Validity of Primary Immunodeficiency Disease Diagnoses in United States Medicaid Data.

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3.  The burden of illness in the first year home: do male and female VA users differ in health conditions and healthcare utilization.

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4.  Pregnancy and mental health among women veterans returning from Iraq and Afghanistan.

Authors:  Kristin M Mattocks; Melissa Skanderson; Joseph L Goulet; Cynthia Brandt; Julie Womack; Erin Krebs; Rani Desai; Amy Justice; Elizabeth Yano; Sally Haskell
Journal:  J Womens Health (Larchmt)       Date:  2010-11-01       Impact factor: 2.681

5.  Psychological Research With Administrative Data Sets: An Underutilized Strategy for Mental Health Services Research.

Authors:  James T Walkup; Philip T Yanos
Journal:  Prof Psychol Res Pr       Date:  2005-10

6.  Studying prescription drug use and outcomes with medicaid claims data: strengths, limitations, and strategies.

Authors:  Stephen Crystal; Ayse Akincigil; Scott Bilder; James T Walkup
Journal:  Med Care       Date:  2007-10       Impact factor: 2.983

7.  Risk for Incident Hypertension Associated With Posttraumatic Stress Disorder in Military Veterans and the Effect of Posttraumatic Stress Disorder Treatment.

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8.  Antidepressant treatment and adherence to antiretroviral medications among privately insured persons with HIV/AIDS.

Authors:  Ayse Akincigil; Ira B Wilson; James T Walkup; Michele J Siegel; Cecilia Huang; Stephen Crystal
Journal:  AIDS Behav       Date:  2011-11

9.  The architecture of co-morbidity networks of physical and mental health conditions in military veterans.

Authors:  Aaron F Alexander-Bloch; Armin Raznahan; Russell T Shinohara; Samuel R Mathias; Harini Bathulapalli; Ish P Bhalla; Joseph L Goulet; Theodore D Satterthwaite; Danielle S Bassett; David C Glahn; Cynthia A Brandt
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10.  Racial, gender and geographic disparities of antiretroviral treatment among US Medicaid enrolees in 1998.

Authors:  W D King; P Minor; C Ramirez Kitchen; L E Oré; S Shoptaw; G D Victorianne; G Rust
Journal:  J Epidemiol Community Health       Date:  2008-09       Impact factor: 3.710

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