Identifying controlled substance patterns of utilization requiring evaluation using administrative claims data

• Published in: The American journal of managed care Vol. 10; no. 11 Pt 1; p. 783
• Main Authors: Parente, Stephen T, Kim, Susan S, Finch, Michael D, Schloff, Lisa A, Rector, Thomas S, Seifeldin, Raafat, Haddox, J David
• Format: Journal Article
• Language: English
• Published: United States 01.11.2004
• Subjects: Adolescent; Adult; Analgesics, Opioid - therapeutic use; Benzodiazepines - therapeutic use; Butorphanol - therapeutic use; Carisoprodol - therapeutic use; Clinical Pharmacy Information Systems - utilization; Contraindications; Databases as Topic; Drug and Narcotic Control - methods; Drug and Narcotic Control - organization & administration; Drug Prescriptions - statistics & numerical data; Drug Utilization Review - methods; Humans; Insurance Claim Review; Managed Care Programs - standards; Middle Aged; Pain - drug therapy; Pattern Recognition, Automated; Prevalence; Substance-Related Disorders - diagnosis; Substance-Related Disorders - epidemiology; Substance-Related Disorders - prevention & control; United States
• ISSN: 1088-0224

To develop a systems approach to identify, for further evaluation, patients with potential controlled substance misuse or mismanagement using software queries applied to administrative health claims data. Retrospective validation of the system using insurance claims. Data from administrative health claims databases representing nearly 7 million individuals younger than 65 years were used by multidisciplinary expert panels to develop and validate controlled substance patterns of utilization requiring evaluation (CS-PURE) criteria. Thirty-four CS-PURE queries were developed in SAS and applied to administrative claims records to identify patients with potential controlled substance misuse or mismanagement. From these, we identified 10 CS-PURE with the highest expert agreement that intervention was warranted. Expert panel agree, ment that CS-PURE correctly identified cases ranged from 48% to 100%, with at least 50% agreement in 9 of 10 CS-PURE. The prevalence rates for CS-PURE ranged from 0.001% to 0.252%. This translates to identifying between 5 and 1116 patients for individual CS-PURE in a 500 000-member health plan. We developed and empirically validated a group of queries using CS-PURE to identify patients with potential controlled substance misuse or mismanagement that would warrant further evaluation by the treating physician, a quality assurance function, or the medical director. Claims-based CS-PURE identification is generalizable to most health insurers with access to medical and pharmaceutical claims records. Although CS-PURE are not direct measures of misuse, they can direct attention to potential problems to determine if intervention is needed.