BACKGROUND: Therapeutic decision-making in oncology is a complex process because physicians must consider many forms of medical data as well as treatment guidelines and protocols. Another challenge for physicians is to clearly communicate their decision-making process with patients to ensure informed consent. Computer-based decision tools have the potential to play a valuable role to support this complex process, which calls for identification of treatment options, analysis of their efficacy, and discussion of these options with patients in the context of the supporting evidence.
OBJECTIVE: This systematic literature review aimed to investigate the extent to which computer-based decision tools have been successfully adopted in oncology consultations to improve patient-physician joint therapeutic decision making. The following questions guided this review: (a) What is the extent of adoption of computer-based decision tools in oncology consultations? (b) Is there a difference in level of adoption by country and period? (c) What factors may have influenced the adoption of the technology? (d) What are the lessons learned to improve adoption of the technology?
METHODS: This review was carried out in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 checklist and guidelines. A literature search was conducted on February 4, 2021 across Cochrane Database of Systematic Reviews (2005 to January 28, 2021), Cochrane Central Register of Controlled Trials December 2020, MEDLINE (1946 to February 04, 2021), EMBASE (1947 to 2021 February 04), Web of Science 1900 to 2021, Scopus 1969 to 2021, and PubMed 1991 to 2021 databases. We used a “snowball” approach to identify additional studies by searching the reference lists of the studies included for full-text review. Additional supplementary searches of relevant journals and grey literature websites were also conducted. Reviewers screened articles eligible for review for quality and inclusion before data extraction.
RESULTS: There are relatively few studies looking at the use of computer-based decision tools in oncology consultations. From 4431 unique articles obtained from searches, only ten studies satisfied the selection criteria. Out of the ten selected studies, eight computer-based decision tools were identified. 60% of the studies were conducted in the US. Communication and information sharing were improved between physicians and patients. However, physicians did not change their habits to take advantage of computer assisted decision making tools or the information they provide. On average, usage of these computer-based decision tools added approximately five minutes to the total length of consultations. Also, some physicians felt that the technology increased patients’ anxiety.
CONCLUSIONS: Six studies demonstrated positive outcomes, one showed negative results, and three were neutral. Adoption of computer-based decision tools during oncology consultations continues to be low. This review shows that information sharing and communication between physicians and patients can be improved with the assistance of technology. However, lack of integration with electronic health records is a barrier. This review provides a set of key requirements for implementation to increase the chance of success of future adoption of computer-based decision tools during oncology consultations. However, it did not aim to show the effects of healthcare policies, regulations or business administration on physicians’ propensities to adopt the technology. Nevertheless, it is important that future research address the influence of these higher-level factors as well.