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An open-source system for efficient clinical trial support: The COMET study experience.

ABSTRACT: Exercise clinical trials are complex, logistically burdensome, and require a well-coordinated multi-disciplinary approach. Challenges include managing, curating, and reporting on many disparate information sources, while remaining responsive to a variety of stakeholders. The Combined Exercise Trial (COMET, NCT04848038) is a one-year comparison of three exercise modalities delivered in the community. Target enrollment is 280 individuals over 4 years. To support rigorous execution of COMET, the study team has developed a suite of scripts and dashboards to assist study stakeholders in each of their various functions. The result is a highly automated study system that preserves rigor, increases communication, and reduces staff burden. This manuscript describes system considerations and the COMET approach to data management and use, with a goal of encouraging further development and adaptation by other study teams in various fields.

SUBMITTER: Clutton J

PROVIDER: S-EPMC10681164 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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An open-source system for efficient clinical trial support: The COMET study experience.

Clutton Jonathan J Montgomery Robert Neal RN Mudaranthakam Dinesh Pal DP Blocker Erin M EM Shaw Ashley R AR Szabo Reed Amanda N AN Vidoni Eric D ED

PloS one 20231127 11

Exercise clinical trials are complex, logistically burdensome, and require a well-coordinated multi-disciplinary approach. Challenges include managing, curating, and reporting on many disparate information sources, while remaining responsive to a variety of stakeholders. The Combined Exercise Trial (COMET, NCT04848038) is a one-year comparison of three exercise modalities delivered in the community. Target enrollment is 280 individuals over 4 years. To support rigorous execution of COMET, the st ...[more]

PMID: 38011138

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Project description:BackgroundMoving to electronic health records (EHRs) confers substantial benefits but risks unintended consequences. Modern EHRs consist of complex software code with extensive local configurability options, which can introduce defects. Defects in clinical decision support (CDS) tools are surprisingly common. Feasible approaches to prevent and detect defects in EHR configuration, including CDS tools, are needed. In complex software systems, use of test-driven development and automated regression testing promotes reliability. Test-driven development encourages modular, testable design and expanding regression test coverage. Automated regression test suites improve software quality, providing a "safety net" for future software modifications. Each automated acceptance test serves multiple purposes, as requirements (prior to build), acceptance testing (on completion of build), regression testing (once live), and "living" design documentation. Rapid-cycle development or "agile" methods are being successfully applied to CDS development. The agile practice of automated test-driven development is not widely adopted, perhaps because most EHR software code is vendor-developed. However, key CDS advisory configuration design decisions and rules stored in the EHR may prove amenable to automated testing as "executable requirements."ObjectiveWe aimed to establish feasibility of acceptance test-driven development of clinical decision support advisories in a commonly used EHR, using an open source automated acceptance testing framework (FitNesse).MethodsAcceptance tests were initially constructed as spreadsheet tables to facilitate clinical review. Each table specified one aspect of the CDS advisory's expected behavior. Table contents were then imported into a test suite in FitNesse, which queried the EHR database to automate testing. Tests and corresponding CDS configuration were migrated together from the development environment to production, with tests becoming part of the production regression test suite.ResultsWe used test-driven development to construct a new CDS tool advising Emergency Department nurses to perform a swallowing assessment prior to administering oral medication to a patient with suspected stroke. Test tables specified desired behavior for (1) applicable clinical settings, (2) triggering action, (3) rule logic, (4) user interface, and (5) system actions in response to user input. Automated test suite results for the "executable requirements" are shown prior to building the CDS alert, during build, and after successful build.ConclusionsAutomated acceptance test-driven development and continuous regression testing of CDS configuration in a commercial EHR proves feasible with open source software. Automated test-driven development offers one potential contribution to achieving high-reliability EHR configuration. Vetting acceptance tests with clinicians elicits their input on crucial configuration details early during initial CDS design and iteratively during rapid-cycle optimization.

Dataset Information

An open-source system for efficient clinical trial support: The COMET study experience.

Publications

An open-source system for efficient clinical trial support: The COMET study experience.

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