Evaluating Migration Errors in COA: Development and Validation of the IQVIA Migration Error Severity Scale (I-MESS)
Author(s)
Lindsay Hughes, PhD1, Margalida A Frau-Méndez, PhD2, Shawn McKown, MA3, Angie Lee, MBA4, Elan Josielewski, BS4.
1Principal, IQVIA, New York, NY, USA, 2IQVIA, Durham, NC, USA, 3IQVIA, Tolland, CT, USA, 4IQVIA, New York, NY, USA.
1Principal, IQVIA, New York, NY, USA, 2IQVIA, Durham, NC, USA, 3IQVIA, Tolland, CT, USA, 4IQVIA, New York, NY, USA.
OBJECTIVES: Clinical Outcome Assessment (COA) migration into electronic platforms is a complex and challenging process requiring both translation and technical expertise. Tight timelines and budget constraints in clinical trials can compromise migration quality making errors in the end product a known industry-wide pain point. Decisions around eCOA are primarily operational rather than scientific. Stakeholders must recognize the importance of inconsistencies even if they may seem minor. We evaluated inconsistencies found across studies, assessments and languages using a scientifically developed severity scale.
METHODS: A comparison of the approved paper version and the electronic version of translated assessments was completed by translation specialists within IQVIA. Inconsistencies found were logged and analyzed by IQVIA’s Patient Centered Solutions (PCS) Scientific team. They were scored using an eCOA migration error severity scale (I-MESS) developed by the PCS team including behavioral scientists and measurement science experts. I-MESS was used to classify inconsistencies by severity , based on potential impact to patient and data, which could help prioritize the urgency of response.
RESULTS: While research is ongoing, anecdotal evidence and preliminary findings show inconsistencies across various assessments, countries and languages, revealing the already known widespread nature of the issue. Most errors appear to be of lower severity, but their frequency remains unacceptably high. Initial findings reveal, for example, mismatches between the button instructions and labels, which may confuse patients and lead to frustration or data entry errors which could ultimately jeopardize data integrity. We plan to present the application of I-MESS across 10 to 20 studies covering multiple indications, from multiple Language Service Providers (LSPs) and eCOA vendors.
CONCLUSIONS: The research in progress already highlights the need for the scale. As new technology such as AI-enabled migration and proofreading tools becomes available, application of the I-MESS could be productively integrated to improve quality outcomes and address errors early through scientific methods.
METHODS: A comparison of the approved paper version and the electronic version of translated assessments was completed by translation specialists within IQVIA. Inconsistencies found were logged and analyzed by IQVIA’s Patient Centered Solutions (PCS) Scientific team. They were scored using an eCOA migration error severity scale (I-MESS) developed by the PCS team including behavioral scientists and measurement science experts. I-MESS was used to classify inconsistencies by severity , based on potential impact to patient and data, which could help prioritize the urgency of response.
RESULTS: While research is ongoing, anecdotal evidence and preliminary findings show inconsistencies across various assessments, countries and languages, revealing the already known widespread nature of the issue. Most errors appear to be of lower severity, but their frequency remains unacceptably high. Initial findings reveal, for example, mismatches between the button instructions and labels, which may confuse patients and lead to frustration or data entry errors which could ultimately jeopardize data integrity. We plan to present the application of I-MESS across 10 to 20 studies covering multiple indications, from multiple Language Service Providers (LSPs) and eCOA vendors.
CONCLUSIONS: The research in progress already highlights the need for the scale. As new technology such as AI-enabled migration and proofreading tools becomes available, application of the I-MESS could be productively integrated to improve quality outcomes and address errors early through scientific methods.
Conference/Value in Health Info
2025-11, ISPOR Europe 2025, Glasgow, Scotland
Value in Health, Volume 28, Issue S2
Code
PCR80
Topic
Clinical Outcomes, Patient-Centered Research, Real World Data & Information Systems
Topic Subcategory
Adherence, Persistence, & Compliance, Instrument Development, Validation, & Translation, Patient-reported Outcomes & Quality of Life Outcomes
Disease
No Additional Disease & Conditions/Specialized Treatment Areas