Evaluation of Eligibility Criteria Relevance for the Purpose of IT-Supported Trial Recruitment: Descriptive Quantitative Analysis

Abstract

Background Clinical trials (CTs) are crucial for medical research; however, they frequently fall short of the requisite number of participants who meet all eligibility criteria (EC). A clinical trial recruitment support system (CTRSS) is developed to help identify potential participants by performing a search on a specific data pool. The accuracy of the search results is directly related to the quality of the data used for comparison. Data accessibility can present challenges, making it crucial to identify the necessary data for a CTRSS to query. Prior research has examined the data elements frequently used in CT EC but has not evaluated which criteria are actually used to search for participants. Although all EC must be met to enroll a person in a CT, not all criteria have the same importance when searching for potential participants in an existing data pool, such as an electronic health record, because some of the criteria are only relevant at the time of enrollment. Objective In this study, we investigated which groups of data elements are relevant in practice for finding suitable participants and whether there are typical elements that are not relevant and can therefore be omitted. Methods We asked trial experts and CTRSS developers to first categorize the EC of their CTs according to data element groups and then to classify them into 1 of 3 categories: necessary, complementary, and irrelevant. In addition, the experts assessed whether a criterion was documented (on paper or digitally) or whether it was information known only to the treating physicians or patients. Results We reviewed 82 CTs with 1132 unique EC. Of these 1132 EC, 350 (30.9%) were considered necessary, 224 (19.8%) complementary, and 341 (30.1%) total irrelevant. To identify the most relevant data elements, we introduced the data element relevance index (DERI). This describes the percentage of studies in which the corresponding data element occurs and is also classified as necessary or supplementary. We found that the query of “diagnosis” was relevant for finding participants in 79 (96.3%) of the CTs. This group was followed by “date of birth/age” with a DERI of 85.4% (n=70) and “procedure” with a DERI of 35.4% (n=29). Conclusions The distribution of data element groups in CTs has been heterogeneously described in previous works. Therefore, we recommend identifying the percentage of CTs in which data element groups can be found as a more reliable way to determine the relevance of EC. Only necessary and complementary criteria should be included in this DERI.

Die Medizininformatik-Initiative im Überblick – Aufbau einer Gesundheitsforschungsdateninfrastruktur in Deutschland

“…2 nichtuniversitäre Krankenhäuser haben sich dem Konsortium 2023 als assoziierte Partner angeschlossen (Chemnitz, ZI Mannheim) und mit dem Aufbau eines DIZ begonnen. Der Mehrwert der in den DIZ etablierten Infrastrukturen wurde belegt anhand klinischer Use Cases (verteiltes maschinelles Lernen für COPD/Asthma [9][10][11][12], IT-Unterstützung für molekulare Tumorboards [13][14][15][16][17][18]) und eines methodischen Use Case (IT-Unterstützung bei der Patientenrekrutierung [19][20][21][22]). Zum Ausbau der medizinischen Informatik an den MIRACUM-Standorten wurden insgesamt 16…”