Secondary data analysis, open access, comorbidity, multimorbidity, multiple chronic conditions, chronic diseases.
Canadian Institutes of Health Research. Scottish School of Primary Care. Health Research Board Centre for Primary Care Research Centre in Ireland.
Despite the high proportion and growing number of people with comorbidity/multimorbidity, clinical trials often exclude this group, leading to a limited evidence base to guide policy and practice for these individuals [1–5]. This evidence gap can potentially be addressed by secondary analysis of studies that were not originally designed to specifically examine comorbidity/ multimorbidity, but have collected information from participants on co-occurring conditions. For example, secondary data analysis from randomized controlled trials may shed light on whether there is a differential impact of interventions on people with comorbidity/ multimorbidity. Furthermore, data regarding comorbidity/ multimorbidity can often be obtained from registration networks or administrative data sets. These types of data sets can address a range of epidemiological research questions, such as:
Medicine and Health Sciences
van den Akker M, Gunn J, Mercer SW, Fortin M, Smith SM. Secondary analysis of data on comorbidity/multimorbidity: a call for papers. Journal of Comorbidity 2015;5(1):120–121.
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