Use of an application that extracts and consolidates adverse events and concomitant medication data from clinical systems to increase clinical trial data entry efficiency, trust, and satisfaction.
Authors: Yuravlivker Leemor , Young Kim Bo , Buckley Michael T. , Bouvier Nancy , Panchal Renata , Lengfellner Joseph M. , Delgado Chanda , Terzulli Stephanie Lucia , Sabbatini Paul 
Published: May 2024

e13651

Background: Manual abstraction of data from a site’s clinical systems to a biopharmaceutical firm’s electronic data capture (EDC) system is inefficient and error prone. In partnership with data managers (DMs), we used a human-centered design thinking methodology to create a web application, CTDataHub, to reduce the effort associated with this process. CTDataHub extracts and consolidates adverse events (AE) and concomitant medications (ConMed) data from clinical systems and displays it in a user-friendly view for easy entry into EDCs. Methods: CTDataHub was launched to DMs in July 2023 at a large, high-volume academic cancer center. To evaluate the App’s impact on DMs, we assessed: 1) App usage, 2) data entry efficiency, 3) trust in data (data is correct to enter in sponsor EDC) assessed via a 5-point Likert attitudinal trust scale, and 4) satisfaction using Net Promoter Score (NPS) by comparing two surveys. Survey 1 (S1) was sent to 313 DMs prior to receiving access to CTDataHub to establish a baseline. Survey 2 (S2) was sent to meaningful users of CTDataHub; those who used the App and viewed data pages at least 10 times between 09/01/23-10/31/23. Behavioral usage on CTDataHub was tracked using Heap Analytics. Results: App Use: S1 had a 72% response rate (n=225), and S2 had a 51% response rate (n=30); with all respondents of S2 completing S1. Meaningful use DMs sent S2 (59) used CTDataHub to view data 3,094 times, with 76% copying data values directly from the App (1,033 times) for abstraction. Data Entry Efficiency: On average, S1 respondents spend 10.2 hours/week abstracting AEs and ConMeds. In S2, the App increased DM efficiency by reducing average data abstraction time 18% (2h). Most respondents (70%, n=21) reported CTDataHub increased efficiency, 20% (n=6) noted no impact, and 10% (n=3) reported decreased efficiency by 18%. Notably, time savings were greater for DMs who used the App who were new to their role (<1 year) versus seasoned DMs (>1 year); 24% vs. 13%. Trust in Data:DMs responded that CTDataHub was more likely to correctly retrieve ConMed and AE data when compared to their manual methods (4.07 mean (n=30) vs. 3.4 mean (n=225) on a 5-point Likert trust scale. App User Satisfaction:NPS for CTDataHub versus DM standard workflows using various clinical systems (on average 2.5 systems) used for data entry was 23 compared to 4, likely due to its ease-of-use. Conclusions: CTDataHub decreased data abstraction times for AEs and ConMeds for 70% of meaningful users by an average of 2h/week relative to other clinical systems. In addition to DM satisfaction, the App increased trust in data being abstracted. The App will be enhanced with additional data sets (site local labs, vitals, tumor response) and automated EHR2EDC capabilities in 2024.