PP100 Characteristics To Consider In A Knowledge Translation Theory, Model Or Framework For Health Technology Reassessment. (December 2021)

• Record Type: Journal Article
• Authors: Esmail, Rosmin; Hanson, Heather M.; Holroyd-Leduc, Jayna; Niven, Daniel J.; Clement, Fiona M.
• Is Part Of: International journal of technology assessment in health care. Volume 37(2021)Supplement 1
• Page Start: 18
• Page End: 19
• Publication Date: 2021-12
• Subjects: Medical technology -- Periodicals; Technology assessment -- Periodicals; 610.28
• DOI: 10.1017/S0266462321001112
• Languages: English
• ISSNs: 0266-4623

Abstract

Abstract : Introduction: Health technology reassessment (HTR) is a structured evidence-based assessment of an existing technology in comparison to its alternatives. The process results in the following four outputs: (i) increased use; (ii) decreased use; (iii) no change; or (iv) de-adoption. However, implementing these outputs remains a challenge. Knowledge translation (KT) can be applied to implement findings from the HTR process. This study sought to identify which characteristics of KT theories, models, and frameworks (TMFs) could be useful, specifically for decreasing the use of or de-adopting a technology. Methods: A qualitative descriptive approach was used to ascertain the perspectives of international KT and HTR experts on the characteristics of KT TMFs for decreasing the use of or de-adopting a technology. One-to-one semi-structured interviews were conducted. Interviews were audio recorded and transcribed verbatim. Themes and sub-themes were deduced from the data through framework analysis using the following five distinctive steps: familiarization; identifying an analytic framework; indexing; charting; and mapping and interpretation. Themes and sub-themes were also mapped to existing KT TMFs. Results: Thirteen experts participated. The following three themes emerged as ideal characteristics of a KT TMF: (i) principles foundational for HTR: evidence-based, high usability, patient-centered, and ability to apply to micro, meso, and macro levels; (ii) levers of change: characterized as positive, neutral, or negative influences for changing behavior; and (iii) steps for knowledge to action: build the case for HTR, adapt research knowledge, assess context, select, tailor, and implement interventions, and assess impact. The Consolidated Framework for Implementation Research had the greatest number of ideal characteristics. Conclusions: Application of KT TMFs to the HTR process has not been clearly established. This is the first study to provide an understanding of characteristics within KT TMFs that could be considered by users undertaking projects to decrease or de-adopt technologies. Characteristics to be considered within a KT TMF for implementing HTR outputs were identified. Consideration of these characteristics may guide users in choosing which KT TMF(s) to use when undertaking HTR projects.