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The purpose of the research is to assess the impact of a natural language processing + artificial intelligence (NLP+AI)-based risk communication feedback system to improve quality of risk communication of key tradeoffs during prostate cancer consultations among physicians and to improve patient decision making. In this cluster randomized trial, an evaluable 259 patients with newly diagnosed clinically localized prostate cancer will be cluster randomized within an evaluable 24 physicians to:
In both study arms, there will be an audio-recorded follow-up phone or video call between the physician and patient to allow for further discussion of risk and clarifying any areas of ambiguity, which will be qualitatively analyzed to see if areas of poor communication were rectified. After the follow-up phone call, patients and participating physicians will be asked to complete a very brief survey about their experience.
The study plans to test whether receiving NLP+AI-based feedback improves decisional conflict, shared decision making, and appropriateness of treatment choice over the standard of care in patients undergoing treatment consultations for prostate cancer. Study staff will also test whether providing feedback and grading of risk communication to physicians affects quality of physician risk communication, since providing feedback will promote more accountability for the quality of information provided to patients. The study will also analyze data from the control arm of the randomized controlled trial to understand variation in risk communication of key tradeoffs in relevant subgroups of tumor risk (low-, intermediate-, and high-risk), provider specialty (Urology, Radiation Oncology, Medical Oncology), and patient sociodemographics.
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Inclusion and exclusion criteria
Inclusion Criteria:
Physician Inclusion Criteria
(1) Physicians who typically counsel prostate cancer patients (Urology, Radiation Oncology, Medical Oncology)
Patient Inclusion Criteria
Patient Exclusion Criteria:
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Interventional model
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283 participants in 2 patient groups
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Central trial contact
Timothy Daskivich, MD; Ella Tetrault, AB
Data sourced from clinicaltrials.gov
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