Implementation and Clinical Adoption of Precision Oncology Workflows Across a Healthcare Network. Academic Article uri icon

Overview

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.

authors

  • Dias-Santagata, Dora
  • Heist, Rebecca S
  • Bard, Adam Z
  • Da Silva, Annacarolina
  • Dagogo-Jack, Ibiayi
  • Nardi, Valentina
  • Ritterhouse, Lauren L
  • Spring, Laura M
  • Jessop, Nicholas
  • Farahani, Alexander A
  • Mino-Kenudson, Mari
  • Allen, Jill
  • Goyal, Lipika
  • Parikh, Aparna
  • Misdraji, Joseph
  • Shankar, Ganesh
  • Jordan, Justin T
  • Martinez-Lage, Maria
  • Frosch, Matthew
  • Graubert, Timothy
  • Fathi, Amir T
  • Hobbs, Gabriela S
  • Hasserjian, Robert P
  • Raje, Noopur
  • Abramson, Jeremy
  • Schwartz, Joel H
  • Sullivan, Ryan J
  • Miller, David
  • Hoang, Mai P
  • Isakoff, Steven
  • Ly, Amy
  • Bouberhan, Sara
  • Watkins, Jaclyn
  • Oliva, Esther
  • Wirth, Lori
  • Sadow, Peter M
  • Faquin, William
  • Cote, Gregory M
  • Hung, Yin P
  • Gao, Xin
  • Wu, Chin-Lee
  • Garg, Salil
  • Rivera, Miguel
  • Le, Long P
  • John Iafrate, A
  • Juric, Dejan
  • Hochberg, Ephraim P
  • Clark, Jeffrey
  • Bardia, Aditya
  • Lennerz, Jochen K

publication date

  • November 3, 2022

Research

keywords

  • Neoplasms

Identity

PubMed Central ID

  • PMC9632318

Scopus Document Identifier

  • 85141890391

Digital Object Identifier (DOI)

  • 10.1200/OP.20.00174

PubMed ID

  • 35852437

Additional Document Info

volume

  • 27

issue

  • 11