Preop Eval vs EBM Stats Calc

Preop Eval organizes and presents much of the guidance that one needs in order to evaluate and prepare adult patients for non-cardiac surgery. It is based upon the guidelines on this topic from the American College of Cardiology, the European Society of Anaesthesiology, the American Society of Anesthesiologists, the Institute for Clinical Systems Improvement, the American College of Chest Physicians, and more (full references in the app). The app contains 1 algorithm and 3 resources: the cardiac evaluation algorithm, guidance on starting and stopping key medications in the perioperative period, guidance on timing of surgery after cardiac events, and guidance on preoperative testing. It also contains a review of preoperative evaluation mainly for students and residents. The app addresses such common questions as: - who needs bloodwork before surgery? - who needs an EKG or a CXR? - how do I handle patients on warfarin, clopidogrel, and DOAC's? - which patients need adjustment of perioperative insulin and diabetic meds, and how? - which active cardiac conditions preclude surgery? - how long after MI or stent should a patient wait before surgery? - are there adjustments to make on psych meds, rheumatologic meds, ACE's and ARB's? This app is written and intended for practicing physicians like internists, family physicians, and hospitalists; for resident physician trainees; and for medical students. In addition to being a reference, the algorithm is written to be a teaching tool by not just delivering an answer, but instead walking a physician through the evaluation process so that one learns that process along the way. As an educator and clinician, I am interested in feedback and I would be grateful for guidance on improving the tool.

Occasionally in medicine, we really need to "do the math". This app will help. EBM Stats Calc let's a clinician do calculations that are hard or impossible to do in one's head. A clinician can get NNT's (number needed to treat) from rates, percentages, or raw event and patient numbers. And a clinician can use sensitivity and specificity or likelihood ratios (LR+, LR-) to go from a pretest probability to posttest probability and positive predictive value and negative predictive value. Although these calculators themselves are somewhat novel for apps, the unique tool in this app is for educators. Students and residents have a hard time understanding how the utility of a test can vary with pretest probability. Instead of saying it in words and hoping they get it, now you can demonstrate it. A test might perform well, giving good PPV and NPV, when pretest probability is in a certain range. But slide that pretest probability up or down and see the diagnostic utility change with the numbers flying right before your eyes. The tool also shows a student that in many cases, an imprecise estimate of pretest probability doesn't much matter. Different doctors might judge a clinical case to suggest likelihood of disease (pretest probability) of 40%, 50%, or 60%. The slider tool shows that the differences may not matter, and the test in mind will render good clarity regardless of differing opinions on pretest probability. The app is written for clinicians, students, residents, and especially educators, in any discipline of medicine. As a clinician and educator myself, I would be grateful for feedback to make the tool better.