How well does routine hospitalisation data capture information on comorbidity in New Zealand?

Diana Sarfati*, Sarah Hill, Gordon Purdie, Elizabeth Dennett, Tony Blakely

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Aims: This study aims to assess the quality of routinely collected comorbidity data in New Zealand which are increasingly used in health service planning and research. Methods: Detailed medical notes-based comorbidity data from a cohort study of New Zealanders diagnosed with colon cancer in 1996-2003, were compared with routine hospital discharge data collected from the same patients using 1-year and 8-year lookback periods. We compared agreement between data sources for individual conditions, Charlson comorbidity index scores and total comorbidity counts using McNemar's p-test and the kappa statistic. We also assessed the association of comorbidity with all-cause survival using Cox proportional hazard models using data ascertained from the two sources. Results: Among these 569 patients, we found generally higher comorbidity was measured from notes than administrative data, with better comparability with an 8-year lookback period. Regardless of source of data, all measures of comorbidity significantly improved the ability of multivariable models to explain all-cause survival, but using both data sources combined resulted in better risk adjustment than either source separately. Conclusion: While differences in medical notes and administrative comorbidity data exist, the latter provides a reasonably useful source of accessible information on comorbidity for risk adjustment particularly in multivariable models.

Original languageEnglish
Pages (from-to)50-61
Number of pages12
JournalNew Zealand Medical Journal
Volume123
Issue number1310
Publication statusPublished - 5 Mar 2010

Fingerprint Dive into the research topics of 'How well does routine hospitalisation data capture information on comorbidity in New Zealand?'. Together they form a unique fingerprint.

Cite this