The electronic Cumulative Illness Rating Scale: a reliable and valid tool to assess multi-morbidity in primary care

Martin Fortin*, Karin Steenbakkers, Catherine Hudon, Marie-Eve Poitras, Jose Almirall, Marian van den Akker

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


Rationale, aims and objectives The presence of multiple concomitant diseases is an increasing health problem, and prompted by the limitations of the disease count, several indices measuring multi-morbidity or co-morbidity have been described to account for the overall burden of morbidity. The Cumulative Illness Rating Scale (CIRS) is one of those indices. We developed an electronic version of the CIRS (eCIRS) to take advantage of computerized data processing. The aim of this study was to evaluate the reliability and validity of the eCIRS scored in a primary care setting. Methods Two nurses interviewed 48 adult patients recruited during consecutive consultation periods in a primary care setting and scored the eCIRS in a random order during two sessions of data collection 01 and T2) 1 month apart. We measured intra- and inter-rater reliability [intra-class correlation coefficient (ICC)]. We also assessed concomitant validity [(Pearson's correlation (0] using standard CIRS scored by the attending family doctors. Results Intra-rater (ICC: 0.90 and 0.95) and inter-rater reliability (ICC: 0.86 and 0.91) were both excellent. No significant differences between the nurses' scores at T1 and T2 (P=0.40 for nurse 1, P=0.73 for nurse 2) were found. The eCIRSs scored by the nurses were highly correlated with the CIRSs scored by the doctors (r = 0.80 and 0.88). Conclusion Reliable and valid, the eCIRS completed during patient interviews with trained nurses can be used to quantify multi-morbidity in primary care, either for research or clinical use.
Original languageEnglish
Pages (from-to)1089-1093
JournalJournal of Evaluation in Clinical Practice
Issue number6
Publication statusPublished - Dec 2011


  • computerized data processing
  • multi-morbidity
  • primary care
  • reliability of results
  • severity of illness index
  • validity of results

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