Evaluation of physician decision making with the use of prior probabilities and a decision-analysis model.

OBJECTIVES

To determine whether treatment decisions could be influenced by supplying probabilities and whether these decisions would be consistent with a decision-analysis model.

DESIGN

Survey with case scenarios and a computerized decision-analysis model.

SETTING

Family practice residency program.

PARTICIPANTS

Forty family practice residents and faculty in the experimental group and six controls.

INTERVENTIONS

Twelve cases scenarios of patients with hypertension and coexisting diseases were developed. Family practice physicians were asked to rank their drugs of choice for each case. In the second phase, six case scenarios included probabilities for efficacy and adverse reactions of step 1 antihypertensives. These drug selections were compared with a computerized decision-analysis model.

MAIN OUTCOME MEASURES

Frequencies of matches between the drug selections of physicians and the computer model.

RESULTS

The frequency of matches before probabilities were provided to physicians was low (45.6%) and there was a significant increase when probabilities were supplied (71.3%). Regardless of experience level, physicians increased their consistency with the computer model after probabilities were supplied.

CONCLUSIONS

This study demonstrated that physician decision making for antihypertensive therapy can be influenced by patient-specific probability estimates. Probability data can help less experienced residents make decisions that are comparable to those of attending physicians. This study was conducted in one residency program and the generalizability to the practicing physician is unknown. These findings would suggest that educational efforts in residency programs, health maintenance organizations, or group practices may benefit from patient-specific probabilities that assist with decisions for drug therapy interventions.