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Computer-Based Decision Tools for Shared Therapeutic Decision-making in Oncology: Systematic Review
Alan Yung1, Judy Kay2, Philip Beale3
1Research in Implementation Science and eHealth, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.
Computer-based decision tools can enhance patient-physician communication in oncology. However, adoption remains low due to integration barriers, despite demonstrating positive outcomes in improving information sharing.
Area of Science:
- Oncology
- Medical Informatics
- Health Services Research
Background:
- Therapeutic decision-making in oncology is complex, involving multiple data sources and communication challenges.
- Physicians face difficulties in clearly communicating complex decisions to patients for informed consent.
- Computer-based decision tools offer potential support for the oncology decision-making process.
Purpose of the Study:
- To systematically review the adoption and impact of computer-based decision tools in oncology consultations.
- To assess the effectiveness of these tools in improving patient-physician joint therapeutic decision-making.
Main Methods:
- A comprehensive systematic literature search was conducted across multiple databases (Cochrane, MEDLINE, Embase, Web of Science, Scopus, PubMed) from inception to February 2021.
- The search utilized PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines.
- A snowball approach and supplementary searches identified additional relevant studies for quality assessment and data extraction.
Main Results:
- Only 10 out of 4431 unique articles met the selection criteria, identifying 8 distinct computer-based decision tools.
- While communication and information sharing between physicians and patients improved, physicians' adoption of these tools was limited.
- The use of these tools added an average of 5 minutes to consultations, and some physicians reported increased patient anxiety.
Conclusions:
- 60% of the reviewed studies showed positive outcomes, 10% negative, and 30% neutral regarding computer-based decision tool use.
- Low adoption rates persist, hindered by factors such as lack of integration with electronic health records.
- Future tools require enhanced integration and consideration of higher-level factors like health policies and administrative influences for successful implementation.
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