TY - JOUR
T1 - Evaluating chronic disease management in real-world settings in six European countries
T2 - Lessons from the collaborative DISMEVAL project
AU - Elissen, Arianne
AU - Nolte, Ellen
AU - Hinrichs, Saba
AU - Conklin, Annalijn
AU - Adams, John
AU - Cadier, Benjamin
AU - Chevreul, Karine
AU - Durand-Zaleski, Isabelle
AU - Erler, Antje
AU - Flamm, Maria
AU - Frølich, Anne
AU - Fullerton, Birgit
AU - Jacobsen, Ramune
AU - Knai, Cécile
AU - Saz-Parkinson, Zuleika
AU - Sarria-Santamera, Antonio
AU - Sönnichsen, Andreas
AU - Vrijhoef, Hubertus J.M.
AU - on behalf of the DISMEVAL consortium
PY - 2014/6
Y1 - 2014/6
N2 - Objective: To describe the interventions, research methods and main findings of the international DISMEVAL project, in which the “real-world” impact of exemplary European disease management approaches was investigated in six countries using advanced analytic techniques. Design: Across countries, the project captured a wide range of disease management strategies and settings; approaches to evaluation varied per country, but included, among others, difference-in-differences analysis and regression discontinuity analysis. Setting: Austria, Denmark, France, Germany, The Netherlands, and Spain. Participants: Health care providers and/or statutory insurance funds providing routine data from their disease management interventions, mostly retrospectively. Intervention(s): This study did not carry out an intervention but evaluated the impact of existing disease management interventions implemented in European care settings. Main outcome measure(s): Outcome measures were largely dependent on available routine data, but could concern health care structures, processes, and outcomes. Results: Data covering 10 to 36 months were gathered concerning more than 154,000 patients with three conditions. The analyses demonstrated considerable positive effects of disease management on process quality (Austria, Germany), but no more than moderate improvements in intermediate health outcomes (Austria, France, Netherlands, Spain) or disease progression (Denmark) in intervention patients, where possible compared with a matched control group. Conclusions: Assessing the “real-world” impact of chronic disease management remains a challenge. In settings where randomization is not possible and/or desirable, routine health care performance data can provide a valuable resource for practice-based evaluations using advanced analytic techniques.
AB - Objective: To describe the interventions, research methods and main findings of the international DISMEVAL project, in which the “real-world” impact of exemplary European disease management approaches was investigated in six countries using advanced analytic techniques. Design: Across countries, the project captured a wide range of disease management strategies and settings; approaches to evaluation varied per country, but included, among others, difference-in-differences analysis and regression discontinuity analysis. Setting: Austria, Denmark, France, Germany, The Netherlands, and Spain. Participants: Health care providers and/or statutory insurance funds providing routine data from their disease management interventions, mostly retrospectively. Intervention(s): This study did not carry out an intervention but evaluated the impact of existing disease management interventions implemented in European care settings. Main outcome measure(s): Outcome measures were largely dependent on available routine data, but could concern health care structures, processes, and outcomes. Results: Data covering 10 to 36 months were gathered concerning more than 154,000 patients with three conditions. The analyses demonstrated considerable positive effects of disease management on process quality (Austria, Germany), but no more than moderate improvements in intermediate health outcomes (Austria, France, Netherlands, Spain) or disease progression (Denmark) in intervention patients, where possible compared with a matched control group. Conclusions: Assessing the “real-world” impact of chronic disease management remains a challenge. In settings where randomization is not possible and/or desirable, routine health care performance data can provide a valuable resource for practice-based evaluations using advanced analytic techniques.
KW - Care pathways
KW - Complex intervention
KW - Health services research
KW - Multidisciplinary teamwork
KW - Organized care
KW - Quality
U2 - 10.1177/2053435414541644
DO - 10.1177/2053435414541644
M3 - Journal article
SN - 2053-4345
VL - 17
SP - 25
EP - 37
JO - International Journal of Care Coordination
JF - International Journal of Care Coordination
IS - 1-2
M1 - A003
ER -