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Many countries across Europe and elsewhere have been experimenting with various structured approaches to manage patients with chronic illness as a way to improve quality of care, reduce costs and lead to better population health outcomes in the long run. Despite a body of studies of disease management interventions, uncertainty about the effects of these remains not least because current guidance on evaluation methods and metrics require further development to enhance scientific rigour while also being practical in routine operations. This report reviews the academic and grey literature to help advance the task of improving the science of assessing disease management initiatives in Europe. It provides a comprehensive inventory of current evaluation methods and performance measures, and highlights potential challenges to evaluating complex interventions such as disease management. Challenges identified are methodological, analytical and conceptual in nature, with a key issue being the establishment of the counterfactual. An array of sophisticated statistical techniques and analytical frameworks can assist in the construction of a sound comparison strategy when a randomised controlled trial is not possible. Issues to consider include: a clear framework of the mechanisms of action and expected effects of disease management; an understanding of the characteristics of disease management (scope, content, dose, context), and of the intervention and target populations (disease type, severity, case-mix); a period of observation over multiple years; and a logical link between performance measures and the intervention's aims and underlying theory of behaviour change.

Table of Contents

  • Chapter One

    Introduction

  • Chapter Two

    Evaluating Disease Management: Objectives and Principles

  • Chapter Three

    Implementing Evaluation of Disease Management Interventions

  • Chapter Four

    Conclusion

  • Appendix A

    Summary of Literature Search Strategy

  • Appendix B

    Methods of Randomisation and Types of Control Groups

  • Appendix C

    Determining Statistical Significance A Priori

  • Appendix D

    Five Principles of Generalised Causal Inference

Research conducted by

The research described in this report was prepared for the European Commission's Seventh Framework Programme and was conducted by RAND Europe.

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