(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 are these 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,10th edition [ICD-10 AM]), 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. Eligible patients from the PCOR-Vic underwent a radical prostatectomy between January 2017 and April 2018.Health Information Manager’s in each hospital, provided each patient’s associated administrative ICD-10 AM comorbidity codes. Medical charts were reviewed to extract comorbidity data. 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 the 217 eligible participants who responded to the questionnaire. The presence of comorbidities showed a poor level of agreement between data sources. 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.

Preventing Fragility Fractures: A 3-Month Critical Window of Opportunity

“…Therefore, data quality is subject to coding error, coding bias, or missed information if a patient seeks care outside this tri-state health system. 18 - 21 If patients presented to another institution outside of the system for care of their subsequent fracture, the absolute rate of fragility fracture after fall would be underestimated, indicating an even greater need to intervene than we are able to document. However, we have a large catchment area and our data includes over 23 hospitals in our region.…”

Findings from the 2021 Yearbook Section on Health Information Management

“…While the studies of Mirhashemi et al and Cappetta et al focused specifically on coding of the data in EHRs, two other studies examined the concordance of different data sources. Sheriffdeen et al , in another of the Best Papers, examined the agreement of comorbidity data for prostate cancer patients among medical records, administrative data and patient self-report [ 10 ]. Nshimyiryo et al studied the agreement between individual facility reports and data in a national Health Management and Information System (HMIS) in Rwanda [ 11 ].…”

Detecting non-alcoholic fatty liver disease and risk factors in health databases: accuracy and limitations of the ICD-10-AM

“…In our patient cohort, there was almost perfect concordance between administrative codes and documentation Open access of T2DM in medical records. Recent studies examining hospital data from a trauma centre 19 and cancer outcomes registry 24 in Australia have also reported 'excellent' and 'substantial' agreement, respectively, between administrative data and medical records for T2DM. This high concordance is likely a consequence of the mandatory requirement to code T2DM when it is documented, as well as the need to monitor and treat this condition during the hospital admission.…”