TY - JOUR

T1 - TEOS: A framework for constructing operational definitions of medication adherence based on Timelines – Events – Objectives – Sources

AU - Dima, Alexandra L.

AU - Allemann, Samuel S.

AU - Dunbar-Jacobs, Jacqueline

AU - Hughes, Dyfrig

AU - Vrijens, Bernard

AU - Wilson, Ira

PY - 2021/6

Y1 - 2021/6

N2 - Aim: Managing adherence to medications is a priority for health systems worldwide. Adherence research is accumulating, yet the quality of the evidence is reduced by various methodological limitations. In particular, the heterogeneity and low accuracy of adherence measures have been highlighted in many literature reviews. Recent consensus-based guidelines advise on best practices in defining adherence (ABC) and reporting of empirical studies (EMERGE). While these guidelines highlight the importance of operational definitions in adherence measurement; such definitions are rarely included in study reports. To support researchers in their measurement decisions, we developed a structured approach to formulate operational definitions of adherence. Methods: A group of adherence and research methodology experts used theoretical, methodological and practical considerations to examine the process of applying adherence definitions to various research settings, questions and data sources. Consensus was reached through iterative reviewing of discussion summaries and framework versions. Results: We introduce TEOS, a four-component framework to guide the operationalization of adherence concepts: 1) describe treatment as four simultaneous interdependent timelines (recommended and actual use, conditional on prescribing and dispensing); 2) locate four key events along these timelines to delimit the three ABC phases (first and last recommended use, first and last actual use); 3) revisit study objectives and design to finetune research questions and assess measurement validity and reliability needs, and 4) select data sources (e.g., electronic monitoring, self-report, electronic healthcare databases) that best address measurement needs.Conclusion: Using the TEOS framework when designing research and reporting explicitly on these components can improve measurement quality.

AB - Aim: Managing adherence to medications is a priority for health systems worldwide. Adherence research is accumulating, yet the quality of the evidence is reduced by various methodological limitations. In particular, the heterogeneity and low accuracy of adherence measures have been highlighted in many literature reviews. Recent consensus-based guidelines advise on best practices in defining adherence (ABC) and reporting of empirical studies (EMERGE). While these guidelines highlight the importance of operational definitions in adherence measurement; such definitions are rarely included in study reports. To support researchers in their measurement decisions, we developed a structured approach to formulate operational definitions of adherence. Methods: A group of adherence and research methodology experts used theoretical, methodological and practical considerations to examine the process of applying adherence definitions to various research settings, questions and data sources. Consensus was reached through iterative reviewing of discussion summaries and framework versions. Results: We introduce TEOS, a four-component framework to guide the operationalization of adherence concepts: 1) describe treatment as four simultaneous interdependent timelines (recommended and actual use, conditional on prescribing and dispensing); 2) locate four key events along these timelines to delimit the three ABC phases (first and last recommended use, first and last actual use); 3) revisit study objectives and design to finetune research questions and assess measurement validity and reliability needs, and 4) select data sources (e.g., electronic monitoring, self-report, electronic healthcare databases) that best address measurement needs.Conclusion: Using the TEOS framework when designing research and reporting explicitly on these components can improve measurement quality.

KW - electronic healthcare data

KW - electronic monitoring

KW - measurement

KW - medication adherence

KW - persistence

KW - Self-report

U2 - https://doi.org/10.1111/bcp.14659

DO - https://doi.org/10.1111/bcp.14659

M3 - Article

VL - 87

SP - 2521

EP - 2533

JO - British Journal of Clinical Pharmacology

JF - British Journal of Clinical Pharmacology

SN - 0306-5251

IS - 6

ER -