Brecht Claerhout1, Dipak Kalra2, Christina Mueller1, Gurparkash Singh3, Nadir Ammour4, Laura Meloni1, Juuso Blomster5, Mark Hopley6, George Kafatos7, Almenia Garvey8, Peter Kuhn9, Martine Lewi10, Bart Vannieuwenhuyse10, Benoît Marchal11, Ketan Patel12, Christoph Schindler13, Mats Sundgren14. 1. Custodix N.V., Gent, Belgium. 2. European Institute for Innovation through Health Data (i-HD), Brussels, Belgium. 3. Janssen Research & Development LLC, Fremont, United States. 4. Sanofi-Aventis R&D, Chilly-Mazarin, France. 5. Turku University Hospital, Turku, Finland. 6. Boehringer-Ingelheim, Ingelheim, Germany. 7. Amgen, Uxbridge, UK. 8. ICON PLC, Paris, France. 9. Comprehensive Cancer Center Ulm, University Hospital Ulm, Ulm, Germany; Institute of Medical Systems Biology, Ulm University, Ulm, Germany. 10. Janssen Pharmaceuticals, Beerse, Belgium. 11. F. Hoffmann-La Roche, Basel, Switzerland. 12. AstraZeneca, Cambridge, UK. 13. Medizinische Hochschule Hannover, Hannover, Germany. 14. AstraZeneca, Gothenburg, Sweden. Electronic address: mats.sundgren@astrazeneca.com.
Abstract
OBJECTIVE: To determine if inclusion/exclusion (I/E) criteria of clinical trial protocols can be represented as structured queries and executed using a secure federated research platform (InSite) on hospital electronic health records (EHR) systems, to estimate the number of potentially eligible patients. METHODS: Twenty-three clinical trial protocols completed during 2011-2017 across diverse disease areas were analyzed to construct queries that were executed with InSite using EHR records from 24 European hospitals containing records of >14 million patients. The number of patients matching I/E criteria of each protocol was estimated. RESULTS: All protocols could be formalized to some extent into a medical coding system (e.g. ICD-10CM, ATC, LOINC, SNOMED) and mapped to local hospital coding systems. The median number of I/E criteria of protocols tested was 29 (range: 14-47). A median of 55% (range 38-89%) of I/E criteria in each protocol could be transformed into a computable format. The median number of eligible patients identified was 26 per hospital site (range: 1-134). CONCLUSION: Clinical trial I/E eligibility criteria can be structured computationally and executed as queries on EHR systems to estimate the patient recruitment pool at each site. The results further suggest that an increase in structured coded information in EHRs would increase the number of I/E criteria that could be evaluated. Additional work is needed on broader deployment of federated platforms such as InSite.
OBJECTIVE: To determine if inclusion/exclusion (I/E) criteria of clinical trial protocols can be represented as structured queries and executed using a secure federated research platform (InSite) on hospital electronic health records (EHR) systems, to estimate the number of potentially eligible patients. METHODS: Twenty-three clinical trial protocols completed during 2011-2017 across diverse disease areas were analyzed to construct queries that were executed with InSite using EHR records from 24 European hospitals containing records of >14 million patients. The number of patients matching I/E criteria of each protocol was estimated. RESULTS: All protocols could be formalized to some extent into a medical coding system (e.g. ICD-10CM, ATC, LOINC, SNOMED) and mapped to local hospital coding systems. The median number of I/E criteria of protocols tested was 29 (range: 14-47). A median of 55% (range 38-89%) of I/E criteria in each protocol could be transformed into a computable format. The median number of eligible patients identified was 26 per hospital site (range: 1-134). CONCLUSION: Clinical trial I/E eligibility criteria can be structured computationally and executed as queries on EHR systems to estimate the patient recruitment pool at each site. The results further suggest that an increase in structured coded information in EHRs would increase the number of I/E criteria that could be evaluated. Additional work is needed on broader deployment of federated platforms such as InSite.
Authors: Muhammad Shariq Usman; Harriette G C Van Spall; Stephen J Greene; Ambarish Pandey; Darren K McGuire; Ziad A Ali; Robert J Mentz; Gregg C Fonarow; John A Spertus; Stefan D Anker; Javed Butler; Stefan K James; Muhammad Shahzeb Khan Journal: Nat Rev Cardiol Date: 2022-05-17 Impact factor: 49.421
Authors: Shawn N Murphy; Shyam Visweswaran; Michael J Becich; Thomas R Campion; Boyd M Knosp; Genevieve B Melton-Meaux; Leslie A Lenert Journal: J Am Med Inform Assoc Date: 2022-03-15 Impact factor: 7.942