Standardizing and improving medication reconciliation implementation strategies by enhancing the consistency in the classification of medication discrepancies

Abstract

Medication discrepancies frequently occur at transitions of care and can result in adverse drug events (ADEs) that may adversely impact patient safety, quality of care, and resources utilization. Medication reconciliation is an essential component of medication safety. The ultimate goal of medication reconciliation is to prevent ADEs related to medication discrepancies at all transitions of care, for all patients, by ensuring accurate and complete medication information transfer across various care settings. However, this process is hampered by the complexity, heterogeneity, and lack of standardised method for quantifying the outcomes of the medication reconciliation process. The rationale of this thesis includes conceptual and practical frameworks. These are standardisation and consistent measures (the taxonomy), and improvement strategies. Accordingly, we suggest that in order to monitor and measure changes that are associated with the implementation of medication reconciliation strategies, standardisation of medication discrepancy nomenclature will improve optimizing measurements and outcomes of medication reconciliation; and therefore, the overall aim of this thesis was to develop and validate a new taxonomy for medication discrepancies to enhance the consistency in the identification and classification of discrepancies, as a critical step in the medication reconciliation process. Findings from a systematic literature review showed significant inconsistencies in reporting, measuring and classifying medication discrepancies and the lack of a well-designed tool to evaluate medication reconciliation outcomes. Therefore, a new taxonomy of medication discrepancies was developed and tested for its content validity, reliability and usability. Additionally, four operational definitions (medication reconciliation, unintentional medication discrepancy, transition of care, and best possible medication list) and instructions were formulated and tested. The second part of this thesis demonstrated that the overall average content validity index (Ave-CVI) of the entire taxonomy was 0.93 and inter-rater reliability was 0.67 (multirater κfree), indicating substantial agreement. In addition, an excellent internal consistency of the taxonomy was established (Kuder–Richardson Formula 20 (KR-20) =0.92). The medication discrepancy taxonomy (MedTax) consists of 12 main types and 28 sub-types of discrepancies that have been arranged in an open hierarchy structure. The usability and test-retest study indicated that the new taxonomy (MedTax) performs as intended, and it is well utilised by the nurses and pharmacists groups. Overall, the (MedTax) provides a valid and reliable approach for various healthcare professionals to be used in different care settings to classify medication discrepancies and to fill an essential void in global endeavors to reinforce standardisation of medication reconciliation practices and to improve medication safety across transitions of care. Further research should be undertaken to investigate the usability and applicability of the tool in clinical practice.