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Published on: February 19, 2021
Measuring implementation of medication optimization services: Development and validation of an implementation
Melanie Livet1, Carrie Blanchard1, Chloe Richard1
1Center for Medication Optimization (CMO), Division of Practice Advancement and Clinical Education, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Background:
Implementation outcomes serve as progress and success indicators of the implementation process. They are also key antecedents to achieving the more traditional clinical outcomes typically associated with a service. Despite their importance, there are few implementation outcomes measures with appropriate psychometric properties, none of which have yet been adapted for medication optimization services.
Objectives:
This study aims to develop and validate the Implementation Outcomes Questionnaire (IOQ) to assess implementation of medication optimization services, starting with Comprehensive Medication Management (CMM). The resulting IOQ is a 40-item self-report instrument for six implementation outcomes, including adoption, acceptability, feasibility, appropriateness, penetration, and sustainability.
Methods:
A three-phase approach was used to develop and validate the IOQ. Development of the instrument, Phase I, was informed by a targeted search of existing implementation outcomes measures in other fields, a review of suitableoptions options by an expert panel, and item adaptation. To assess content validity, Phase II, an internal vetting process was conducted using an adapted version of Rubio and colleagues' methodology. Evidence of reliability and construct validity, Phase III, was obtained through a pilot test with 167 pharmacists within 78 different care settings.
Results:
Overall, the results supported the reliability and validity (both content and construct) of the IOQ, with further psychometric testing needed for adoption. The items' relevance, clarity, and alignment with each implementation concept were high, except for Penetration. As a result, the Penetration items were refined for further use. Best-fit models were identified for each outcome based on the MCFA analyses, thereby providing insights into the factor structures and interpretation for each measure. Cronbach' alphas indicated good internal consistency.
Conclusions:
This questionnaire is the first of its kind tailored to medication optimization services, starting with CMM. Access to this survey should facilitate measurement of implementation outcomes, thereby increasing the likelihood of achieving the desired clinical outcomes.
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