Standardized assessment of medication reconciliation in post-acute care

Background Medication reconciliation (MR) facilitates safety during transitions of care, which occur frequently across post-acute care (PAC) settings. Under the intent of the IMPACT Act of 2014, the Centers for Medicare & Medicaid Services contracted with the RAND Corporation to develop and test standardized assessment data elements (SADEs) that assess the MR process. Methods We employed an iterative process that incorporated stakeholder input and three rounds of testing to identify, refine, and evaluate MR SADEs. Testing took place in 186 PAC sites (57 home health agencies, 28 inpatient rehabilitation facilities, 28 long-term care hospitals, and 73 skilled nursing facilities). There were 2951 patients in the final test. Novel MR SADEs, based on the Joint Commission's framework, were refined. The final SADEs assessed whether: patient was taking high-risk medications; an indication was noted for each medication class; discrepancies were identified; patient or family/caregiver was involved in addressing discrepancies; discrepancies were communicated to physician (or designee) within 24 h; recommended physician actions regarding discrepancies were implemented within 24 h after physician response; and the reconciled list was communicated to patient, prescriber, and/or pharmacy. Two assessors per facility collected data for each patient. Analyses described completion time, data missingness, and interrater reliability, as well as feedback on assessor burden. Results Time to complete the MR SADEs was 3.2 min. Missing data were <5%. Interrater reliability was moderate to high (kappa: 0.42 [whether a reconciled list was communicated to prescribers] to 0.89 [identifying patients taking hypoglycemics]). For identifying high-risk medication classes, interrater reliability was high (kappa: 0.72-0.89). There were minimal differences by setting. Conclusions This is the first set of MR SADEs that have been assessed across the PAC settings. Results demonstrate feasibility, based on missing data and completion time, and moderate to strong reliability, based on interrater comparisons, of assessing MR.