Discrepancies Identified with the Use of Prescription Claims and Diagnostic Billing Data Following a Comprehensive Medication Review
Journal of Managed Care Pharmacy
BACKGROUND: The University of Florida College of Pharmacy's Medication Therapy Management Communication and Care Center (UF MTMCCC) provides medication therapy management (MTM) services to patients enrolled in a State of Florida Medicaid Waiver Program: Medicaid for the Aged and Disabled. To provide these services, UF MTMCCC was given access to patients' prescription claims data and diagnostic billing data in the form of ICD-9 codes. Prior to calling a patient, a precomprehensive medication
... sive medication review (CMR) work-up was performed to identify potential medicationrelated problems (MRPs) and/or health-related problems (HRPs). Based on information provided by the patient in relation to comorbidities, medications, and medical history during the interactive telephone conversation, problems were either confirmed or eliminated. All of the reported information was also assessed to identify any new MRPs or HRPs. Accordingly, telephonic MTM services have the potential to bridge the gap between pharmacy claims data and patient self-reported information, since the MTM services provided rely on the accuracy of both informational resources. What this study adds report of tobacco use. Overall, 4,441 data elements were identified as confirmed, eliminated, or new across the 147 CMRs. Among those data elements, 56% of the data was confirmed; 23% was eliminated; and 21% was discovered as new. CONCLUSIONS: The study met its objective in determining the degree of discrepancies that existed when prescription claims data and ICD-9 billing data were used to identify MRPs and/or HRPs versus using patient-reported data. Data revealed that the presence of discrepancy is relatively large depending on the category, indicating a difficulty in accurately making recommendations with incomplete data or solely based on prescription claims and billing data. MTM services with patient interaction are vital in identifying information that allows for more appropriate decision making.