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Table2_An Objective Approach to Identify Priority Rare Diseases for the Development of Solutions Reducing the Diagnostic Delay Based on French Data.xlsx (61.94 kB)

Table2_An Objective Approach to Identify Priority Rare Diseases for the Development of Solutions Reducing the Diagnostic Delay Based on French Data.xlsx

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posted on 2021-10-22, 15:54 authored by Pierre Etienne Chazal, Ségolène Aymé

A timely diagnosis is a critical step to ensure a proper access to expert clinical management for patients. However, diagnosing rare diseases (RD) is a major challenge, as they are not only numerous but also extremely diverse in their expression and cause. This generates a long lag time between first symptoms and diagnosis, unanimously thought to be unacceptably long in many cases, and amenable to improvement. Digital technologies offer new opportunities for improving diagnosis and care in a sector with urgent needs. However, developing and testing digital solutions would only be possible for a limited number of rare diseases (RD). The approach presented here aims at proposing an objective way of defining a subset of “priority” RD to focus on for the development and test of new solutions to reduce the time to diagnosis. An approach which is relevant not only when developing and testing new digital solutions but also organizational solutions in the field of RDs. The priority RDs presented herein have been highlighted using two objective criteria: the existence of a well-defined and established standard of care management, defined as the availability of a medicinal product specifically targeting the disease; and / or the existence of authoritative clinical guidelines. Our approach, based on French data, led to the establishment of a list of 251 RD for which a delayed diagnosis would be especially detrimental for the patient. This work demonstrates the feasibility of identifying objectively a subset of RD at urgent needs for the development of solutions to reduce the delay to diagnosis, if choices have to be made, based on publicly and well-established available data. The proposed list needs to be updated and adapted to the local situation, and validated by experts to establish if the delay to diagnosis can be reduced.

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