Abstract P4-07-22: Clinical decision support systems for multidisciplinary team decision-making in patients with solid cancer: an implementation model based on a scoping review

Abstract

Background Clinical decision-making by multidisciplinary teams (MDTs) is getting more complex as treatment advice for the individual patient must be based on an increasing amount of patient and tumor characteristics, and scientific evidence on treatment efficacy. Clinical decision support systems (CDSSs) can make an important contribution to assist but also optimize MDT decision-making. However, implementation of CDSSs in clinical practice is challenging. Aim & methods The aim of our study is to set up a CDSSs implementation model for multidisciplinary decision-making in solid cancer. It is based on a scoping review of the currently reported CDSSs for MDT decision-making in solid cancers with identification of reported barriers and facilitators for implementation of these CDSSs. For this we systematically searched the Cochrane Library, MEDLINE (accessed through PubMed) and Scopus up to September 1st 2021. Results Of the 710 screened abstracts, 38 papers met the inclusion criteria (table 1). Sixteen different CDSSs were identified. For implementation of CDSSs, 87 barriers and 73 facilitators were reported. The reported barriers could be categorized in the same categories as those of the facilitators (a factor can be reported as a barrier if the factor is not addressed well, and as a facilitator if the factor is properly addressed). The most frequently reported barriers for CDSS implementation for MDT decision making mainly concerned CDSS maintenance (e.g. not incorporating guideline updates), loco-regional feasibility of the CDDS recommendation (e.g. no access to diagnostics or treatment), validity, not incorporating patient preference in decision making, data accuracy, noncoverage of certain patient subpopulations, lack of an information standard, usability, data availability and no interoperability of the CDSS with the electronic health record. The most frequently reported facilitators included, besides the categories as mentioned above, the category shared decision making (reporting of alternative treatment options) and technical skills (involvement of a computer scientist). Table 2 shows the most frequently reported categories of barriers and facilitators, and scores for each included study the number of reported barriers (B) and facilitators (F) in each category. Conclusion Based on the identified barriers and facilitators, we developed a CDSS implementation model to guide more successful CDSS integration in the clinical workflow to support MDTs (the model will be shown at the congress). The usability of this theoretical model should be explored in future studies. Table 1. Characteristics of 38 included articles Table 2. Overview of the most frequently reported categories of barriers and facilitators. For each included study the number of reported barriers (B) and facilitatiors (F) are scored for each category. Citation Format: Mathijs P. Hendriks, Kees C. Ebben, Janine A. Van Til, Agnes Jager, Sabine Siesling. Clinical decision support systems for multidisciplinary team decision-making in patients with solid cancer: an implementation model based on a scoping review [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P4-07-22.