Study Assesses Validity of Mental Health Diagnosis Using VA Administrative Data
The literature that examines quality of care and outcomes for patients with mental health disorders often relies on secondary analyses of administrative data to answer important questions about this patient population. Because these data were developed for clinical and not research purposes, investigators must take methodologic considerations into account when trying to identify patients with mental illness. This study estimated the validity of eight ICD9-based algorithms for the identification of mental health disorders in administrative data among 124,716 Veterans with diabetes who used the VA healthcare system in 1998, and also participated in the 1999 Large Health Survey of Veteran Enrollees, which included questions about history of mental health diagnoses.
Findings show that many Veterans with a diagnosed mental health disorder can be identified through VA administrative data; however, the choice of algorithm influenced conclusions. Moreover, the positive predictive value (PPV) and negative predictive value (NPV) varied among the eight ICD9-based algorithms. For example, PPV was optimized by requiring two or more instances of mental health disorder ICD9 codes - or by only accepting codes from mental health visits, while NPV was optimized by supplementing VA data with Medicare data. Since the limitations of administrative data cannot be fully eliminated with any algorithm, the authors suggest that investigators and quality improvement programs also consider conducting sensitivity analyses in which they vary the algorithm, in order to indicate how different assumptions affect conclusions.
Frayne S, Miller D, Sharkansky E, Jackson V, et al. Using Administrative Data to Identify Mental Illness: What Approach is Best? American Journal of Medical Quality Jan-Feb 2010;25(1):42-50.
This study was funded by HSR&D and VA Medical Research-Epidemiology. Drs. Frayne and Jackson are part of HSR&D's Center for Health Care Evaluation in Palo Alto, CA. Dr. Miller is part of HSR&D's Center for Health Quality, Outcomes, and Economic Research in Bedford, MA.
