Article type
Abstract
Background: Medical societies, organizations, and researchers frequently use different definitions and terminology for the description of the same disease. Inconsistency in disease definitions can make it difficult to synthesize the evidence to inform development of recommendations. This issue is commonly encountered while developing clinical guidelines, nevertheless, limited evidence exists regarding the approach to unifying inconsistent disease definitions.
Objectives: This study aims to build on the collective experiences with inconsistent disease definitions to formulate a structured process for standardizing disease definitions before conducting a clinical guideline.
Methods: We performed a scoping review of the literature and summarized existing approaches for unifying disease definitions. We subsequently sough input from methodologists and experts in guideline development. The outcome of these iterative efforts culminated in the development of the presented framework. Then, to pilot the framework, we applied it to unify inconsistent disease definitions for multiple guideline efforts (e.g., von Willebrand disease and Acute Hepatic Porphyria).
Results: The process of unifying disease definitions involves several key steps (Figure 1). The initial phase entails reviewing the literature for all the available definitions, ideally through a systematic search to ensure encompassing all the existing definitions in the literature. A core team then rigorously evaluates all the existing definitions, considering all the relevant elements under each definition (example provided in Figure 2). Subsequently, the core team proposes initial draft definitions, seeking broad feedback from experts and stakeholders. Achieving consensus on the proposed definitions is a crucial step, involving a systematic and collaborative process using established techniques like the Delphi method. Identifying diverse stakeholders, including clinical experts, patients, and public representatives, is essential for a well-rounded approach. In addition to diversity, it is important to evaluate potential conflicts of interest among stakeholders. Finally, a face validity check ensures that the proposed definitions align with their intended purpose, are clinically sound, and not leading to overdiagnosis.
Conclusions: Assessment of disease definitions prior to guideline development may be necessary. This framework would serve to assist not just guideline developers but also researchers in different fields for diseases with inconsistent definitions, thereby reducing potential concerns about health care recommendations.
Objectives: This study aims to build on the collective experiences with inconsistent disease definitions to formulate a structured process for standardizing disease definitions before conducting a clinical guideline.
Methods: We performed a scoping review of the literature and summarized existing approaches for unifying disease definitions. We subsequently sough input from methodologists and experts in guideline development. The outcome of these iterative efforts culminated in the development of the presented framework. Then, to pilot the framework, we applied it to unify inconsistent disease definitions for multiple guideline efforts (e.g., von Willebrand disease and Acute Hepatic Porphyria).
Results: The process of unifying disease definitions involves several key steps (Figure 1). The initial phase entails reviewing the literature for all the available definitions, ideally through a systematic search to ensure encompassing all the existing definitions in the literature. A core team then rigorously evaluates all the existing definitions, considering all the relevant elements under each definition (example provided in Figure 2). Subsequently, the core team proposes initial draft definitions, seeking broad feedback from experts and stakeholders. Achieving consensus on the proposed definitions is a crucial step, involving a systematic and collaborative process using established techniques like the Delphi method. Identifying diverse stakeholders, including clinical experts, patients, and public representatives, is essential for a well-rounded approach. In addition to diversity, it is important to evaluate potential conflicts of interest among stakeholders. Finally, a face validity check ensures that the proposed definitions align with their intended purpose, are clinically sound, and not leading to overdiagnosis.
Conclusions: Assessment of disease definitions prior to guideline development may be necessary. This framework would serve to assist not just guideline developers but also researchers in different fields for diseases with inconsistent definitions, thereby reducing potential concerns about health care recommendations.