Evaluation of a preoperative personalized risk communication tool: a prospective before-and-after study

Abstract

Purpose: Patients want personalized information before surgery; most do not receive personalized risk estimates. Inadequate information contributes to poor experience and medicolegal complaints. We hypothesized that exposure to the Personalized Risk Evaluation and Decision Making in Preoperative Clinical Assessment (PREDICT) app, a personalized risk communication tool, would improve patient knowledge and satisfaction after anesthesiology consultations compared with standard care. Methods: We conducted a prospective clinical study (before-after design) and used patient-reported data to calculate personalized risks of morbidity, mortality, and expected length of stay using a locally calibrated National Surgical Quality Improvement Program risk calculator embedded in the PREDICT app. In the standard care (before) phase, the application’s materials and output were not available to participants; in the PREDICT app (after) phase, personalized risks were communicated. Our primary outcome was knowledge score after the anesthesiology consultation. Secondary outcomes included patient satisfaction, anxiety, feasibility, and acceptability. Results: We included 183 participants (90 before; 93 after). Compared with standard care phase, the PREDICT app phase had higher post-consultation: knowledge of risks (14.3% higher; 95% confidence interval [CI], 6.5 to 22.0; P < 0.001) and satisfaction (0.8 points; 95% CI, 0.1 to 1.4; P = 0.03). Anxiety was unchanged (− 1.9%; 95% CI, − 4.2 to 0.5; P = 0.13). Acceptability was high for patients and anesthesiologists. Conclusion: Exposure to a patient-facing, personalized risk communication app improved knowledge of personalized risk and increased satisfaction for adults before elective inpatient surgery. Trial registration: www.clinicaltrials.gov (NCT03422133); registered 5 February 2018.