(Dis)concordance of comorbidity data and cancer status across administrative datasets, medical charts, and self-reports

Abstract Background Benchmarking outcomes across settings commonly requires risk-adjustment for co-morbidities that must be derived from extant sources that were designed for other purposes. A question arises as to the extent to which differing available sources for health data will be concordant when inferring the type and severity of co-morbidities, how close these are to the “truth”. We studied the level of concordance for same-patient comorbidity data extracted from administrative data (coded from International Classification of Diseases, Australian modification,10 th edition [ICD-10AM]), from the medical chart audit, and data self-reported by men with prostate cancer who had undergone a radical prostatectomy. Methods We included six hospitals (5 public and 1 private) contributing to the Prostate Cancer Outcomes Registry-Victoria (PCOR-Vic) in the study. We listed eligible patients from the PCOR-Vic who underwent a radical prostatectomy between January 2017 and April 2018 for the Health Information Manager in each hospital, who provided each patient’s associated ICD-10AM comorbidity codes. Medical charts were reviewed to extract comorbidities used to generate the Charlson Comorbidity Index. The self-reported comorbidity questionnaire (SCQ) was distributed through PCOR-Vic to eligible men. Results The percentage agreement between the administrative data, medical charts and self-reports ranged from 92% to 99% in the 122 patients (from 217 eligible participants, 56%), who responded to the questionnaire. The presence of comorbidities showed a poor level of agreement between data sources. Due to a variety of factors, certain conditions were recorded more than others. Conclusion Relying on a single data source to generate comorbidity indices for risk-modelling purposes may fail to capture the reality of a patient’s disease profile. There does not appear to be a ‘gold-standard’ data source for the collection of data on comorbidities.