Journal of General Internal Medicine

, Volume 29, Issue 4, pp 653–660

Multimorbidity and Evidence Generation

Authors

  • Carlos O. Weiss
    • Department of Family Medicine, College of Human MedicineMichigan State University
    • Division of Geriatric Medicine and GerontologyJohns Hopkins University
  • Ravi Varadhan
    • Division of Geriatric Medicine and GerontologyJohns Hopkins University
    • The Johns Hopkins Center on Aging and Health
    • Department of BiostatisticsJohns Hopkins Bloomberg School of Public Health
  • Milo A. Puhan
    • Department of EpidemiologyJohns Hopkins Bloomberg School of Public Health
  • Andrew Vickers
    • Department of Epidemiology & BiostatisticsMemorial Sloan-Kettering Cancer Center
  • Karen Bandeen-Roche
    • The Johns Hopkins Center on Aging and Health
    • Department of BiostatisticsJohns Hopkins Bloomberg School of Public Health
  • Cynthia M. Boyd
    • Division of Geriatric Medicine and GerontologyJohns Hopkins University
    • Predictive Analytics and Comparative Effectiveness (PACE) Center, Institute for Clinical Research and Health Policy StudiesTufts Medical Center
Multimorbidity Symposium

DOI: 10.1007/s11606-013-2660-5

Cite this article as:
Weiss, C.O., Varadhan, R., Puhan, M.A. et al. J GEN INTERN MED (2014) 29: 653. doi:10.1007/s11606-013-2660-5

Abstract

Most people with a chronic disease actually have more than one, a condition known as multimorbidity. Despite this, the evidence base to prevent adverse disease outcomes has taken a disease-specific approach. Drawing on a conference, Improving Guidelines for Multimorbid Patients, the goal of this paper is to identify challenges to the generation of evidence to support the care of people with multimorbidity and to make recommendations for improvement. We identified three broad categories of challenges: 1) challenges to defining and measuring multimorbidity; 2) challenges related to the effects of multimorbidity on study design, implementation and analysis; and 3) challenges inherent in studying heterogeneity of treatment effects in patients with differing comorbid conditions. We propose a set of recommendations for consideration by investigators and others (reviewers, editors, funding agencies, policymaking organizations) involved in the creation of evidence for this common type of person that address each of these challenges. The recommendations reflect a general approach that emphasizes broader inclusion (recruitment and retention) of patients with multimorbidity, coupled with more rigorous efforts to measure comorbidity and comorbidity burden and the influence of multimorbidity on outcomes and the effects of therapy. More rigorous examination of heterogeneity of treatment effects requires careful attention to prioritizing the most important comorbid-related questions, and also requires studies that provide greater statistical power than conventional trials have provided. Relatively modest changes in the orientation of current research along these lines can be helpful in pointing to and partially addressing selected knowledge gaps. However, producing a robust evidence base to support patient-centered decision making in complex individuals with multimorbidity, exposed to many different combinations of potentially interacting factors that can modify the risks and benefits of therapies, is likely to require a clinical research enterprise fundamentally restructured to be more fully integrated with routine clinical practice.

KEY WORDS

evidence-based medicinechronic diseaseguidelinescomorbidityclinical trials

Copyright information

© Society of General Internal Medicine 2013