Integrating technology to support data management abstraction of adverse events (AE) and concomitant medications (ConMed) from the electronic health record (EHR) to sponsor electronic data capture (EDC) systems using design thinking (DT) methodology.

Authors

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Leemor Yuravlivker

Memorial Sloan Kettering Cancer Center, New York, NY

Leemor Yuravlivker , Michael T. Buckley , Nancy Bouvier , Sundar Jeevarathnam , Steve Lazan , Renata Panchal , Mairi McKellop , Joseph M. Lengfellner , Stephanie Lucia Terzulli , Paul Sabbatini

Organizations

Memorial Sloan Kettering Cancer Center, New York, NY

Research Funding

Institutional Funding
Memorial Sloan Kettering Cancer Center

Background: Manual abstraction of data from a site’s EHR to pharmaceutical sponsor’s EDC system is labor intensive and inefficient. To reduce the time and effort of this process for data managers (DM), a web-based application, Clinical Trials Data Hub (CTDH), was developed using Design Thinking methods. It extracts and consolidates AE and ConMed data from the EHR and displays it in a user friendly, automated, and consolidated view for easy entry into EDC forms. Methods: Following DT methodology to develop CTDH, we interviewed 12 DMs to identify data entry bottlenecks, and ideated solutions for what is now CTDH. To evaluate CTDH’s value, we built a functioning prototype using Splunk and conducted pilot A/B testing with 6 DMs for 2 use cases (Case I: basic easy to find ConMed linked to the AE, and Case 2: complex, where the ConMed linked to the AE was buried in a 33-page document) using their current workflow (A) versus CTDH (B) where a 5-minute training of CTDH occurred prior to testing. We hypothesized that CTDH would outperform current workflows across 3 primary outcomes: 1) correct data identification, 2) time to identify data, and 3) using a modified Single Ease Question (SEQ) rating scale to assess how difficult users found the task. This study was conducted in Jan-Aug 2022 at a large single-center cancer hospital. Results: DMs spend ~20 hours/week on data entry; the majority of which is spent searching the EHR for which ConMeds are associated with an AE. A/B testing results are noted in Table I (see below). Use case 2 showed that DMs using CTDH reduced the time to find one ConMed linked to an AE by 148%, saving ~5 minutes in one task. 5 of 6 participants preferred CTDH to existing clinical systems. Conclusions: Our findings suggest that CTDH allows DMs to 1) identify AE and ConMed data required for EDCs more quickly than in current workflow, 2) identify data more accurately to be entered in sponsor EDCs, and 3) perceive the task of identifying this data to be easier. CTDH reduces the time DMs spend searching clinical systems and documents and has the potential to save meaningful time per patient per study. CTHD will launch into production in May 2023. Digital tool product development using DT methodology has the potential to improve operational efficiency and the clinical staff user experience. This is particularly important in an industry that has struggled with burnout, cost containment, and high turnover.

Case 1Case 2
ToolCurrent systemCTDHCurrent systemCTDH
Correct data identification rate83%80%50%75%
Time to identify data (minutes)10.257.258.373.38
SEQ (1 = difficult, 5 = easy)2.9424.25

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Abstract Details

Meeting

2023 ASCO Annual Meeting

Session Type

Publication Only

Session Title

Publication Only: Care Delivery and Regulatory Policy

Track

Care Delivery and Quality Care

Sub Track

Digital Technology

Citation

J Clin Oncol 41, 2023 (suppl 16; abstr e13624)

DOI

10.1200/JCO.2023.41.16_suppl.e13624

Abstract #

e13624

Abstract Disclosures