ASA Physical Status Determination by General Internists and Impact on Cardiac Risk Assessment.

OBJECTIVES: Estimating cardiac risk is important for preoperative evaluation, and several risk calculators incorporate the American Society of Anesthesiologists (ASA) physical status score. The purpose of this study was to determine the concordance of ASA scores assigned by general internists and anesthesiologists and assess whether discrepancies affected cardiac risk estimation. METHODS: This observational study included military veterans evaluated in a preoperative evaluation clinic at a single center during a 12-month period. ASA scores were recorded by General Internal Medicine residents under the supervision of a General Internal Medicine attending, performing a preoperative medical consultation, and were compared with ASA scores assigned by an anesthesiologist on the day of surgery. ASA scores and Gupta Cardiac Risk Scores incorporating each ASA score were compared. RESULTS: Data were collected on 206 patients, 163 of whom had surgery within 90 days and were included. ASA scores were concordant in 60 patients (37.3%), whereas the ASA scores were rated lower by the general internist in 101 (62.0%) and higher in 2 (1.2%). Interrater reliability was low (κ = 0.08), and general internist scores were significantly lower than anesthesiologist scores (P < 0.01). Gupta Cardiac Risk Scores were calculated for 160 patients, and they exceeded 1% in 14 patients using the anesthesiologist ASA score, compared with 5 patients using the general internist score. CONCLUSIONS: ASA scores assigned by general internists in this study were significantly lower than those assigned by anesthesiologists, and these discrepancies in the ASA score can lead to substantially different conclusions about cardiac risk.

Evaluation of an advanced physical diagnosis course using consumer preferences methods: the nominal group technique.

BACKGROUND: Current evaluation tools of medical school courses are limited by the scope of questions asked and may not fully engage the student to think on areas to improve. The authors sought to explore whether a technique to study consumer preferences would elicit specific and prioritized information for course evaluation from medical students. METHODS: Using the nominal group technique (4 sessions), 12 senior medical students prioritized and weighed expectations and topics learned in a 100-hour advanced physical diagnosis course (4-week course; February 2012). Students weighted their top 3 responses (top = 3, middle = 2 and bottom = 1). RESULTS: Before the course, 12 students identified 23 topics they expected to learn; the top 3 were review sensitivity/specificity and high-yield techniques (percentage of total weight, 18.5%), improving diagnosis (13.8%) and reinforce usual and less well-known techniques (13.8%). After the course, students generated 22 topics learned; the top 3 were practice and reinforce advanced maneuvers (25.4%), gaining confidence (22.5%) and learn the evidence (16.9%). The authors observed no differences in the priority of responses before and after the course (P = 0.07). CONCLUSIONS: In a physical diagnosis course, medical students elicited specific and prioritized information using the nominal group technique. The course met student expectations regarding education of the evidence-based physical examination, building skills and confidence on the proper techniques and maneuvers and experiential learning. The novel use for curriculum evaluation may be used to evaluate other courses-especially comprehensive and multicomponent courses.