Tag you’re it! Development of a clinical decision support tool to identify NCCN regimens without a costly pathways program
| Autor: | Edward Gu, Aarti Sonia Bhardwaj, Haley Hines Theroux, Michael McLean, Damaris Peralta Hernandez, Cardinale B. Smith |
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| Rok vydání: | 2020 |
| Předmět: | |
| Zdroj: | Journal of Clinical Oncology. 38:308-308 |
| ISSN: | 1527-7755 0732-183X |
| DOI: | 10.1200/jco.2020.38.29_suppl.308 |
| Popis: | 308 Background: Reducing variation in care can improve outcomes and decrease costs. Evidence based medicine drives cancer guidelines and adherence promotes quality cancer care. Value based programs are based on adherence to pathways. Most institutions adopt costly cloud based clinical pathways products but none are mature products that fully integrate with the EHR and they require additional data entry. We present our simple Clinical Decision Support (CDS) tool for identifying best practice treatment protocols driven by the cancer diagnosis in the EMR for our large, multi-site, mixed academic and community cancer system. Methods: Our chemotherapy council must approve all protocols that are published in the system’s Epic Beacon library using a rigorous scoring system based on level of evidence and FDA or NCCN approval. Then each protocol is “tagged” appropriately: “Tier 1A”: Preferred Regimens/NCCN Approved; “Tier 1B”: Preferred Regimens/Chemo Council Approved (but not NCCN Approved); Tier 2: Specific Disease Management Team approved regimens; and finally “Other” or research protocols. When the oncologist enters the treatment plan in EPIC, a list of protocols are suggested, ordered by level of evidence, based on the cancer diagnosis and with the easily visible level of evidence or “tag” to allow data driven decision making. Results: We implemented our CDS tool December 12, 2019. As of mid-June, 2020 a total of 1637 treatment plans have been implemented. Of those, 1323 (81%) are Tier 1A, 310 (2%) are Tier 1B and 4 (.2%) are Tier 2. Thus demonstrating 81% adherence to NCCN approved regimens across the system, regardless of the line of treatment. GI and breast cancers were responsible for the most plans with the highest adherence to Tier 1A plans, specifically 92% among the breast cancer group. Multiple Myeloma and Sarcoma were tied for the lowest adherence rate of 58%. This data can be further stratified by medical oncologist. Interestingly, Multiple Myeloma had the highest utilization of Tier 1B protocols perhaps reflecting the rapidly changing literature that is ahead of the guidelines. Conclusions: We demonstrated adherence to NCCN protocols 81% of the time over a 6 month period and over multiple cancer types. Protocol tagging and reporting utilizing the EMR alone could be used as a powerful model for value based care. We identified disease areas that will require further education regarding evidence based treatment and can consider interventions including real time feedback to clinicians and/or best practice advisories or quality based incentives. |
| Databáze: | OpenAIRE |
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