PT - JOURNAL ARTICLE AU - Hua-Gen Li, Michael AU - Hutchinson, Anastasia AU - Tacey, Mark AU - Duke, Graeme TI - Reliability of comorbidity scores derived from administrative data in the tertiary hospital intensive care setting: a cross-sectional study AID - 10.1136/bmjhci-2019-000016 DP - 2019 Apr 01 TA - BMJ Health & Care Informatics PG - e000016 VI - 26 IP - 1 4099 - http://informatics.bmj.com/content/26/1/e000016.short 4100 - http://informatics.bmj.com/content/26/1/e000016.full SO - BMJ Health Care Inform2019 Apr 01; 26 AB - Background Hospital reporting systems commonly use administrative data to calculate comorbidity scores in order to provide risk-adjustment to outcome indicators.Objective We aimed to elucidate the level of agreement between administrative coding data and medical chart review for extraction of comorbidities included in the Charlson Comorbidity Index (CCI) and Elixhauser Index (EI) for patients admitted to the intensive care unit of a university-affiliated hospital.Method We conducted an examination of a random cross-section of 100 patient episodes over 12 months (July 2012 to June 2013) for the 19 CCI and 30 EI comorbidities reported in administrative data and the manual medical record system. CCI and EI comorbidities were collected in order to ascertain the difference in mean indices, detect any systematic bias, and ascertain inter-rater agreement.Results We found reasonable inter-rater agreement (kappa (κ) coefficient ≥0.4) for cardiorespiratory and oncological comorbidities, but little agreement (κ<0.4) for other comorbidities. Comorbidity indices derived from administrative data were significantly lower than from chart review: −0.81 (95% CI − 1.29 to − 0.33; p=0.001) for CCI, and −2.57 (95% CI −4.46 to −0.68; p=0.008) for EI.Conclusion While cardiorespiratory and oncological comorbidities were reliably coded in administrative data, most other comorbidities were under-reported and an unreliable source for estimation of CCI or EI in intensive care patients. Further examination of a large multicentre population is required to confirm our findings.