Validation of an algorithm to prioritize patients for comprehensive medication management in primary care settings

Background: Comprehensive medication management (CMM) programs optimize the effectiveness and safety of patients' medication regimens, but CMM may be underutilized. Whether healthcare claims data can identify patients appropriate for CMM is not well-studied.

Aim: Determine the face validity of a claims-based algorithm to prioritize patients who likely need CMM.

Method: We used claims data to construct patient-level markers of "regimen complexity" and "high-risk for adverse effects," which were combined to define four categories of claims-based CMM-need (very likely, likely, unlikely, very unlikely) among 180 patient records. Three clinicians independently reviewed each record to assess CMM need. We assessed concordance between the claims-based and clinician-review CMM need by calculating percent agreement as well as kappa statistic.

Results: Most records identified as 'very likely' (90%) by claims-based markers were identified by clinician-reviewers as needing CMM. Few records within the 'very unlikely' group (5%) were identified by clinician-reviewers as needing CMM. Interrater agreement between CMM-based algorithm and clinician review was moderate in strength (kappa = 0.6, p < 0.001).

Conclusion: Claims-based pharmacy measures may offer a valid approach to prioritize patients into CMM-need groups. Further testing of this algorithm is needed prior to implementation in clinic settings.