Emergency Medical Case Study

Mortality is obviously a significant outcome in emergency medicine (EM), but the comparison of crude mortality rates may be confounded by differences in case mix. Risk adjustment models may be used to assess the emergency healthcare quality 1,2. The observed mortality among emergency admissions can be compared with the predicted risk adjusted mortality to determine whether the number of deaths exceeds the expected rate 3. The shortcomings of existing methods may be due to the failure to adjust routine data adequately and reliably for differences in case mix 4. Existing methods adjust for age, sex, and comorbidities but do not adjust for severity of illness, as indicated by physiological measures or routine blood tests 5,6. This probably reflects …show more content…
However, it remains unclear whether the additional data needed to compute ICU scores improves mortality prediction for critically ill patients compared to the simpler EM scores. Clinicians require firm models for mortality prediction in critically ill patients, and multiple scoring systems have been developed in both the ICU 7-10 and the EM 11-13. In general, EM-based scoring systems employ a handful of variables that are readily available on all patients, while ICU scoring systems employ a larger number of variables that are frequently available only in those patients that are critically ill (e.g., arterial blood gas measurements). It remains unknown which of these scores perform best in patients of ICU. While it seems intuitive that scores using a larger number of data inputs would perform better than more niggardly scoring systems, simpler scores may actually outperform more complex scores when the population has been well-defined. For example, the original Acute Physiology and Chronic Health Evaluation (APACHE) score had 34 variables and when reduced to 12 for APACHE II, it performed better in aggregate than did its predecessor