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(Dis)concordance of comorbidity data and cancer status across administrative datasets, medical charts, and self-reports.
Sheriffdeen, A; Millar, J L; Martin, C; Evans, M; Tikellis, G; Evans, S M.
Affiliation
  • Sheriffdeen A; Department of Epidemiology & Preventive Medicine, Monash University, Melbourne, Australia.
  • Millar JL; Department of Epidemiology & Preventive Medicine, Monash University, Melbourne, Australia.
  • Martin C; William Buckland Radiotherapy Centre, The Alfred, Melbourne, Australia.
  • Evans M; Department of Epidemiology & Preventive Medicine, Monash University, Melbourne, Australia.
  • Tikellis G; Department of Epidemiology & Preventive Medicine, Monash University, Melbourne, Australia.
  • Evans SM; Department of Epidemiology & Preventive Medicine, Monash University, Melbourne, Australia.
BMC Health Serv Res ; 20(1): 858, 2020 Sep 11.
Article in En | MEDLINE | ID: mdl-32917193
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.
Subject(s)
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Prostatic Neoplasms / Comorbidity / Medical Records / International Classification of Diseases Type of study: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Aged / Humans / Male / Middle aged Country/Region as subject: Oceania Language: En Journal: BMC Health Serv Res Journal subject: PESQUISA EM SERVICOS DE SAUDE Year: 2020 Document type: Article Affiliation country: Australia

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Prostatic Neoplasms / Comorbidity / Medical Records / International Classification of Diseases Type of study: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Aged / Humans / Male / Middle aged Country/Region as subject: Oceania Language: En Journal: BMC Health Serv Res Journal subject: PESQUISA EM SERVICOS DE SAUDE Year: 2020 Document type: Article Affiliation country: Australia