Texas Oncology, Dallas, TX
Lalan S. Wilfong, Mark Ferencik, Marcus A. Neubauer
Background: Fourteen practices within the US Oncology Network are participating in the Center for Medicare and Medicaid Innovation’s (CMMI) Oncology Care Model. To meet the requirement of documenting a care plan that contains the 13 components in the Institute of Medicine Care Management Plan, an electronic treatment plan was developed which incorporates core elements from our EMR, IKnowMed, supplemented by additional physician documentation. Physicians must document in their own words the prognosis section of the care plan. Methods: To better understand the word choices physicians use for prognosis, we evaluated the word choices used in over 50,000 treatment plans. Using an excel based word count macro, all contents of the free text entry “prognosis” field were sorted based on frequency of the same answer and were then ranked from most common use to least common. A word count method was applied to determine and rank the most commonly used words across all answers. The “current status of disease” field in the treatment plan was used to divide the prognosis answers into those that mentioned “Metastatic” and “Not Metastatic” so that prognosis wording trends could be compared using pivot tables and data filters. Results: 70% of prognosis word choices were single words: “excellent, good, fair, poor, or guarded” were the most common. 20% of phrases were multi-word that appeared repeatedly such as “will depend on the response to therapy.” Only 10% of answers were uniquely worded per treatment plan and felt to be personal to the patient’s situation. Additionally, the number of words did not differ between metastatic and non-metastatic disease. Conclusions: To our knowledge, this is the largest cohort of treatment plans where the word choices used by physicians are described to document prognosis to patients. The results indicate that single words or short phrases are commonly used to describe prognosis when the treatment plan is shared with patients. The data set has high potential for further study to better understand the role and impact of written treatment plans (including downstream events) to help physicians refine this documentation for better patient understanding of this important topic.
Disclaimer
This material on this page is ©2024 American Society of Clinical Oncology, all rights reserved. Licensing available upon request. For more information, please contact licensing@asco.org
Abstract Disclosures
2024 ASCO Quality Care Symposium
First Author: Puneeth Indurlal
2023 ASCO Annual Meeting
First Author: Edward Christopher Dee
2019 ASCO Quality Care Symposium
First Author: Ellen Miller-Sonet
2022 ASCO Quality Care Symposium
First Author: Tanvi Dandawate