01 · ABSTRACT
Abstract
Implementation barriers are key instruments to seeing the holistic picture to ensure patients receive new medicines. In the setting of the pharmaceutical industry, "implementation barriers" can be defined as obstacles that prevent a medicine from achieving its intended impact before and after approval. Common categories include clinical, operational, regulatory and health technology assessment (HTA), access, and behavioral and system barriers. Addressing these implementation barriers in an efficient and timely way would greatly assist to inform healthcare decision making and thereby accelerate adoption by clinicians and patients of new medical innovations.
RWD has been used extensively over the years to describe many pieces of the pharma puzzle and has become an essential observational tool. Descriptive studies using RWD abound on the burden of illness, (comparative) effectiveness, (comparative) safety, patient journey, treatment use and switching, just to name a few. RWD hasn't been used in a structured way to address implementation barriers but has tremendous potential for doing so. RWD is most powerful and strategically useful not when it merely measures, but when it explains why, for example, the uptake of a product is low. It is the search for "why" that renders RWD so important for the identification of implementation barriers. Unfortunately, most RWD studies stop at the measurement level.
A structured approach to what RWD is required and what steps should be taken to discover implementation barriers using RWD. The approach is outlined for rare diseases and a detailed example for ATTR-CM is shown and explained. Qualitative methods and AI play an important role in enhancing the power of RWD to investigate implementation barriers and the role they play in ensuring that a new innovation actually reaches the patient, increasing the value proposition for patients, healthcare systems, and industry.
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Keywords
real-world datareal-world evidenceimplementation barriersimplementation scienceintegrated evidencerare diseasepatient journeyclinical adoptionhealth technology assessmentelectronic health recordsnatural language processingartificial intelligencetransthyretin amyloid cardiomyopathyATTR-CM
03 · PUBLICATION RECORD
Article details
JournalMedical Research Archives
IssueVol 14 No 4 (2026): Vol.14 Issue 4 April 2026
SectionEditorial
Published01 May 2026
DOI10.18103/mra.v14i4.7459
ISSN2375-1924
04 · RIGHTS & REUSE
Rights & reuse
This article is published under a Creative Commons Attribution License (CC BY 3.0) and may be shared or distributed by anyone as long as attribution is given to the journal.