• Julie E Byles, Catherine D'Este, Lynne Parkinson, Rachel O'Connell, and Carla Treloar.
• Centre for Research and Education in Ageing, The University of Newcastle, Level 2, David Maddison Clinical Sciences Building, Watt Street, Newcastle, NSW 2308, Australia. julie.byles@newcastle.edu.au
• J Clin Epidemiol. 2005 Oct 1; 58 (10): 997-1005.

Background And ObjectivesMeasurement of multimorbidity and comorbidity is important in epidemiologic and health services research. The aim of this research was to derive a generic multimorbidity index based on patient self-report, incorporating severity, for predicting a range of outcomes.MethodsThe dataset was obtained from a trial including 1,541 Veterans and war widows aged 70 years and over. The survey included sociodemographics, hospital admissions, SF-36, and information on deaths was obtained. The methods of Charlson were used to derive Multimorbidity Indices.ResultsAll indices predicted quality of life, with decreasing quality of life for each increase in multimorbidity category. Multimorbidity scores incorporating severity significantly contributed to the prediction of mortality, hospital admission, and follow-up quality of life, regardless of adjustment for baseline quality of life.ConclusionsOur results indicate that a single index cannot predict a variety of relevant outcomes. Consequently, research undertaken to assess the impact of intervention or illness on health outcomes should use an index that is valid for predicting the specific outcome of interest.

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