{Reference Type}: Journal Article
{Title}: External validation of the computer aided risk scoring system in predicting in-hospital mortality following emergency medical admissions.
{Author}: Kingsley V;Fox L;Simm D;Martin GP;Thompson W;Faisal M;
{Journal}: Int J Med Inform
{Volume}: 188
{Issue}: 0
{Year}: 2024 Aug 18
{Factor}: 4.73
{DOI}: 10.1016/j.ijmedinf.2024.105497
{Abstract}: <B>BACKGROUND: </B>Clinical prediction models have the potential to improve the quality of care and enhance patient safety outcomes. A Computer-aided Risk Scoring system (CARSS) was previously developed to predict in-hospital mortality following emergency admissions based on routinely collected blood tests and vitals. We aimed to externally validate the CARSS model.<BR><B>METHODS: </B>In this retrospective external validation study, we considered all adult (≥18 years) emergency medical admissions discharged between 11/11/2020 and 11/11/2022 from The Rotherham Foundation Trust (TRFT), UK. We assessed the predictive performance of the CARSS model based on its discriminative (c-statistic) and calibration characteristics (calibration slope and calibration plots).<BR><B>RESULTS: </B>Out of 32,774 admissions, 20,422 (62.3 %) admissions were included. The TRFT sample had similar demographic characteristics to the development sample but had higher mortality (6.1 % versus 5.7 %). The CARSS model demonstrated good discrimination (c-statistic 0.87 [95 % CI 0.86-0.88]) and good calibration to the TRFT dataset (slope = 1.03 [95 % CI 0.98-1.08] intercept = 0 [95 % CI -0.06-0.07]) after re-calibrating for differences in baseline mortality (intercept = 0.96 [95 % CI 0.90-1.03] before re-calibration).<BR><B>CONCLUSIONS: </B>In summary, the CARSS model is externally validated after correcting the baseline risk of death between development and validation datasets. External validation of the CARSS model showed that it under-predicted in-hospital mortality. Re-calibration of this model showed adequate performance in the TRFT dataset.