Implementation and Clinical Adoption of Precision Oncology Workflows Across a Healthcare Network
Author:
Dias-Santagata Dora1ORCID, Heist Rebecca S2ORCID, Bard Adam Z1, da Silva Annacarolina F L3, Dagogo-Jack Ibiayi2, Nardi Valentina1, Ritterhouse Lauren L1, Spring Laura M2, Jessop Nicholas1, Farahani Alexander A1, Mino-Kenudson Mari1, Allen Jill2, Goyal Lipika2, Parikh Aparna2, Misdraji Joseph14, Shankar Ganesh5, Jordan Justin T2, Martinez-Lage Maria1, Frosch Matthew1, Graubert Timothy2, Fathi Amir T2, Hobbs Gabriela S2, Hasserjian Robert P1, Raje Noopur2, Abramson Jeremy2, Schwartz Joel H2, Sullivan Ryan J2, Miller David2ORCID, Hoang Mai P1, Isakoff Steven2, Ly Amy1, Bouberhan Sara2, Watkins Jaclyn1, Oliva Esther1, Wirth Lori2ORCID, Sadow Peter M1ORCID, Faquin William1, Cote Gregory M2ORCID, Hung Yin P1, Gao Xin2, Wu Chin-Lee1, Garg Salil1, Rivera Miguel1, Le Long P1, John Iafrate A1, Juric Dejan2, Hochberg Ephraim P2, Clark Jeffrey2, Bardia Aditya2ORCID, Lennerz Jochen K1ORCID
Affiliation:
1. Department of Pathology, Massachusetts General Hospital, Harvard Medical School , Boston, MA , USA 2. Massachusetts General Hospital Cancer Center, Harvard Medical School , Boston, MA , USA 3. Department of Pathology, Brigham and Women’s Hospital, Harvard Medical School , Boston, MA , USA 4. Department of Pathology, Yale University Present affiliation: , New Haven, CT , USA 5. Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School , Boston, MA , USA
Abstract
Abstract
Background
Precision oncology relies on molecular diagnostics, and the value-proposition of modern healthcare networks promises a higher standard of care across partner sites. We present the results of a clinical pilot to standardize precision oncology workflows.
Methods
Workflows are defined as the development, roll-out, and updating of disease-specific molecular order sets. We tracked the timeline, composition, and effort of consensus meetings to define the combination of molecular tests. To assess clinical impact, we examined order set adoption over a two-year period (before and after roll-out) across all gastrointestinal and hepatopancreatobiliary (GI) malignancies, and by provider location within the network.
Results
Development of 12 disease center-specific order sets took ~9 months, and the average number of tests per indication changed from 2.9 to 2.8 (P = .74). After roll-out, we identified significant increases in requests for GI patients (17%; P < .001), compliance with testing recommendations (9%; P < .001), and the fraction of “abnormal” results (6%; P < .001). Of 1088 GI patients, only 3 received targeted agents based on findings derived from non-recommended orders (1 before and 2 after roll-out); indicating that our practice did not negatively affect patient treatments. Preliminary analysis showed 99% compliance by providers in network sites, confirming the adoption of the order sets across the network.
Conclusion
Our study details the effort of establishing precision oncology workflows, the adoption pattern, and the absence of harm from the reduction of non-recommended orders. Establishing a modifiable communication tool for molecular testing is an essential component to optimize patient care via precision oncology.
Funder
MGH Pathology Departmental and Divisional Funds Ruane Fund for Thyroid Cancer Research National Institutes of Health
Publisher
Oxford University Press (OUP)
Subject
Cancer Research,Oncology
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