Measuring implementation of medication optimization services: Development and validation of an implementation outcomes questionnaire

Melanie Livet, Carrie Blanchard, Chloe Richard, Kelly Sheppard, Mary Yannayon, Todd Sorensen, Mary Roth McClurg

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
Pages (from-to)1623-1630
Number of pages8
JournalResearch in Social and Administrative Pharmacy
Volume17
Issue number9
DOIs
StatePublished - Sep 2021

Bibliographical note

Funding Information:
Acceptability. The one-factor model for Acceptability fit the full sample data adequately (?2 (28) = 21.71, p = 0.79; RMSEA = 0.00; CFI = 1.0; TLI = 1.0; SRMR within-level = 0.08; SRMR between-level = 0.09). The AIC and BIC for the one-factor model were 1120.64 and 1219.10, respectively. Based on the results of the EFA above, a model that included item 6 from the Feasibility measure and items 2, 3, and 5 from the Appropriateness measure was also tested. However, this model had worse fit with an AIC and BIC of 1904.28 and 2056.45, respectively. A similar factor structure emerged in analyses that included only the pharmacist implementing CMM group, supporting the validity of the measure regardless of implementation status. Consequently, the original Acceptability items were examined as a single factor at the within- and between- levels (Table 4). Item 3 and item 4 (reverse-scored) contributed significantly to the single factor at the within-level. At the between-level, only item 3 was significant. The degree of service acceptability seems to be particularly influenced by the pharmacist's belief that it fits with their current way of working regardless of level.Funded by the American College of Clinical Pharmacy (ACCP) and the ACCP Research Institute as part of the Enhancing Performance in Primary Care Medical Practice through Implementation of CMM grant.The authors gratefully acknowledge all of the pharmacists and primary care practices engaged in the parent study for their valuable work and insights. In addition, this work would not have been possible without the contributions and insights provided by the University of North Carolina and the University of Minnesota ?CMM in Primary Care? study research team members. Finally, the authors acknowledge the generous support for this study provided by the American College of Clinical Pharmacy (ACCP) and the ACCP Research Institute. The ?Enhancing Performance in Primary Care Medical Practice through Implementation of CMM? grant was funded by the American College of Clinical Pharmacy (ACCP) and the ACCP Research Institute.

Funding Information:
The authors gratefully acknowledge all of the pharmacists and primary care practices engaged in the parent study for their valuable work and insights. In addition, this work would not have been possible without the contributions and insights provided by the University of North Carolina and the University of Minnesota “CMM in Primary Care” study research team members. Finally, the authors acknowledge the generous support for this study provided by the American College of Clinical Pharmacy (ACCP) and the ACCP Research Institute. The “Enhancing Performance in Primary Care Medical Practice through Implementation of CMM” grant was funded by the American College of Clinical Pharmacy (ACCP) and the ACCP Research Institute .

Publisher Copyright:
© 2021

Keywords

  • Comprehensive medication management
  • Implementation
  • Implementation outcome
  • Medication optimization
  • Pharmacy service
  • Survey

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't
  • Review

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