Development of the Multi-Dimensional Analysis of Patient Outcome Predictions (MD.POP) during medical encounters.

OBJECTIVE: Our first objective was to develop the Multi-Dimensional analysis of Patient Outcome Predictions (MD.POP), an interaction analysis system that assesses how HCPs discuss precisely and exclusively patient outcomes during medical encounters. The second objective was to study its interrater reliability. METHOD: The MD.POP was developed by consensus meetings. Forty simulated medical encounters between physicians and an actress portraying a patient were analysed. Interrater reliability analysis was conducted on 20 of those simulated encounters. RESULTS: The MD.POP includes six dimensions: object, framing, value, domain, probability and form of POP. The coding method includes four steps: 1) transcription of the encounter, 2) POP identification, 3) POP dimension coding and 4) POP scoring. Descriptive analyses show that the MD.POP is able to describe verbal expressions addressing the patient's outcomes. Statistical analyses show excellent interrater reliability (Cohen's Kappa ranging from 0.92 to 0.94). CONCLUSION: The MD.POP is a reliable interaction analysis system that assesses how HCPs discuss patient medical, psychological or social outcomes during medical encounters. PRACTICAL IMPLICATION: The MD.POP provides a measure for researchers to study how HCPs communicate with patients about potential outcomes. Results of such studies will allow to provide recommendations to improve HCP's communication about patients' outcomes.

Predictors of physicians' communication performance in a decision-making encounter with a simulated advanced-stage cancer patient: A longitudinal study.

OBJECTIVES: Physicians' characteristics that influence their communication performance (CP) in decision-making encounters have been rarely studied. In this longitudinal study, predictors of physicians' CP were investigated with a simulated advanced-stage cancer patient. METHODS: Physicians (n=85) performed a decision-making encounter with a simulated patient (SP). Their CP was calculated by analyzing encounter transcripts with validated interaction analysis systems. Potential specific psychological predictors were physicians' empathy towards the SP (Jefferson Scale of Physician Empathy, JSPE) and their decisional conflict about the treatment (Decisional Conflict Scale, DCS). Potential general psychological predictors were physicians' empathy towards cancer patients (JSPE), their decisional conflict about cancer patients' treatments (DCS), and their affective reactions to uncertainty (Physicians' Reactions to Uncertainty, PRU). RESULTS: Physicians' CP was predicted by their decisional conflict about the SP's treatment (DCS) (ß=0.41; p< 0.001) and their affective reactions to uncertainty regarding cancer treatments (PRU) (ß=-0.31; p=0.003). CONCLUSION: During encounters with advanced-stage cancer patients, physicians' awareness of uncertainty about which treatments to consider may facilitate their communication performance, whereas physicians' affective reactions to uncertainty may inhibit their performance. PRACTICE IMPLICATIONS: Physicians' decisional conflict and reactions to uncertainty should be addressed in communication skills training programs.