BACKGROUND AND OBJECTIVES: Traditional methods of resident evaluation have several limitations, including recall bias and memory decay. We developed a real-time, computerized, data-based evaluation system and determined 1) the feasibility of using such a system in an ambulatory care teaching center and 2) the types of evaluation data such a computer-based evaluation system provides to residency directors, faculty, and residents. METHODS: We developed Precept-Assist, a computerized, data-based evaluation system. Reports from the system provide quantitative data, summative reports, and qualitative comments regarding specific competencies of residents. Following each precepting encounter between a faculty member and a resident, the faculty member entered into the system an array of coded information on the resident's level of performance, competencies achieved, and procedural skills. RESULTS: We have entered more than 15,000 pieces of evaluative data on 4,504 precepting encounters. The average time to enter data was about 40 seconds per encounter. Reports were generated to monitor each resident's progress through the program. The information was used to generate learning plans tailored to each resident's needs. CONCLUSIONS: Precept-Assist was useful for evaluating the performance of residents in this study.
BACKGROUND AND OBJECTIVES: Traditional methods of resident evaluation have several limitations, including recall bias and memory decay. We developed a real-time, computerized, data-based evaluation system and determined 1) the feasibility of using such a system in an ambulatory care teaching center and 2) the types of evaluation data such a computer-based evaluation system provides to residency directors, faculty, and residents. METHODS: We developed Precept-Assist, a computerized, data-based evaluation system. Reports from the system provide quantitative data, summative reports, and qualitative comments regarding specific competencies of residents. Following each precepting encounter between a faculty member and a resident, the faculty member entered into the system an array of coded information on the resident's level of performance, competencies achieved, and procedural skills. RESULTS: We have entered more than 15,000 pieces of evaluative data on 4,504 precepting encounters. The average time to enter data was about 40 seconds per encounter. Reports were generated to monitor each resident's progress through the program. The information was used to generate learning plans tailored to each resident's needs. CONCLUSIONS: Precept-Assist was useful for evaluating the performance of residents in this study.