BACKGROUND: Using patient-reported data to supplement claims-based indicators may be helpful in identifying Medicare beneficiaries likely to benefit from medication therapy management (MTM) services. OBJECTIVE: Our objective was to develop and initially assess a patient medication user self-evaluation (MUSE) tool to identify Medicare Part D beneficiaries who would benefit from a comprehensive medication review. METHODS: A random sample of 225 patient medication profiles was created from a survey of Medicare beneficiaries; the survey also included demographic characteristics, responses to adherence questions, and reported symptoms. Three clinical pharmacists used the patient profiles to make judgments regarding the likelihood (low, moderate, or high) that each patient would benefit from an MTM visit in the next 3 months. A total of 150 cases were used for model calibration, and 75 were used for validation. Ordinal logistic regression models were fit to predict the likelihood of benefit from an MTM visit by using different combinations of potential MUSE items. Final model selection was based on the Akaike information criterion and the percent agreement between model prediction and expert judgments in the validation data. Measures considered for inclusion in the MUSE tool were related to medication use, medical conditions, and health care utilization. RESULTS: The final MUSE items incorporated number of medications, number of physicians, number of pharmacies, number of hospitalizations in the past 6 months, having forgotten to take medications, cost-related problems, and number of medical conditions. CONCLUSION: The 7-item MUSE tool could be used in targeting MTM services, such as comprehensive medication reviews, among Medicare beneficiaries.
BACKGROUND: Using patient-reported data to supplement claims-based indicators may be helpful in identifying Medicare beneficiaries likely to benefit from medication therapy management (MTM) services. OBJECTIVE: Our objective was to develop and initially assess a patient medication user self-evaluation (MUSE) tool to identify Medicare Part D beneficiaries who would benefit from a comprehensive medication review. METHODS: A random sample of 225 patient medication profiles was created from a survey of Medicare beneficiaries; the survey also included demographic characteristics, responses to adherence questions, and reported symptoms. Three clinical pharmacists used the patient profiles to make judgments regarding the likelihood (low, moderate, or high) that each patient would benefit from an MTM visit in the next 3 months. A total of 150 cases were used for model calibration, and 75 were used for validation. Ordinal logistic regression models were fit to predict the likelihood of benefit from an MTM visit by using different combinations of potential MUSE items. Final model selection was based on the Akaike information criterion and the percent agreement between model prediction and expert judgments in the validation data. Measures considered for inclusion in the MUSE tool were related to medication use, medical conditions, and health care utilization. RESULTS: The final MUSE items incorporated number of medications, number of physicians, number of pharmacies, number of hospitalizations in the past 6 months, having forgotten to take medications, cost-related problems, and number of medical conditions. CONCLUSION: The 7-item MUSE tool could be used in targeting MTM services, such as comprehensive medication reviews, among Medicare beneficiaries.
Authors: Emiley Chang; Victor Lin; Regine Goh; Canossa Chan; Michael K Ong; Edward Hui; Catherine Sarkisian Journal: J Gen Intern Med Date: 2020-09-21 Impact factor: 5.128