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Exploring Different Strategies of Assessing the Economic Impact of Multiple Diabetes-Associated Complications and Their Interactions: A Large Claims-Based Study in Germany

Author

Listed:
  • Katharina Kähm

    (Institute of Health Economics and Health Care Management, Helmholtz Zentrum München (GmbH)-German Research Center for Environmental Health (GmbH)
    German Center for Diabetes Research (DZD))

  • Michael Laxy

    (Institute of Health Economics and Health Care Management, Helmholtz Zentrum München (GmbH)-German Research Center for Environmental Health (GmbH)
    German Center for Diabetes Research (DZD))

  • Udo Schneider

    (Scientific Institute of TK for Benefit and Efficiency in Health Care, Techniker Krankenkasse (TK))

  • Rolf Holle

    (Institute of Health Economics and Health Care Management, Helmholtz Zentrum München (GmbH)-German Research Center for Environmental Health (GmbH)
    German Center for Diabetes Research (DZD))

Abstract

Background In the context of an aging population with increasing diabetes prevalence, people are living longer with diabetes, which leads to increased multimorbidity and economic burden. Objective The primary aim was to explore different strategies that address the economic impact of multiple type 2 diabetes-related complications and their interactions. Methods We used a generalized estimating equations approach based on nationwide statutory health insurance data from 316,220 patients with type 2 diabetes (baseline year 2012, 3 years of follow-up). We estimated annual total costs (in 2015 euros) for type 2 diabetes-related complications and, in addition, explored different strategies to assess diabetes-related multimorbidity: number of prevalent complications, co-occurrence of micro- and macrovascular complications, disease–disease interactions of prevalent complications, and interactions between prevalent/incident complications. Results The increased number of complications was significantly associated with higher total costs. Further assessment of interactions showed that macrovascular complications (e.g., chronic heart failure) and high-cost complications (e.g., end-stage renal disease, amputation) led to significant positive effects of interactions on costs, whereas early microvascular complications (e.g., retinopathy) caused negative interactions. The chronology of the onset of these complications turned out to have an additional impact on the interactions and their effect on total costs. Conclusions Health economic diabetes models and evaluations of interventions in patients with diabetes-related complications should pay more attention to the economic effect of specific disease interactions. Politically, our findings support the development of more integrated diabetes care programs that take better account of multimorbidity. Further observational studies are needed to elucidate the shared pathogenic mechanisms of diabetes complications.

Suggested Citation

  • Katharina Kähm & Michael Laxy & Udo Schneider & Rolf Holle, 2019. "Exploring Different Strategies of Assessing the Economic Impact of Multiple Diabetes-Associated Complications and Their Interactions: A Large Claims-Based Study in Germany," PharmacoEconomics, Springer, vol. 37(1), pages 63-74, January.
    • Handle: RePEc:spr:pharme:v:37:y:2019:i:1:d:10.1007_s40273-018-0699-1
    DOI: 10.1007/s40273-018-0699-1
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    References listed on IDEAS

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    1. Kreis, Kristine & Neubauer, Sarah & Klora, Mike & Lange, Ansgar & Zeidler, Jan, 2016. "Status and perspectives of claims data analyses in Germany—A systematic review," Health Policy, Elsevier, vol. 120(2), pages 213-226.
    2. Alan Brennan & Stephen E. Chick & Ruth Davies, 2006. "A taxonomy of model structures for economic evaluation of health technologies," Health Economics, John Wiley & Sons, Ltd., vol. 15(12), pages 1295-1310, December.
    3. Maria Alva & Alastair Gray & Borislava Mihaylova & Philip Clarke, 2014. "The Effect Of Diabetes Complications On Health‐Related Quality Of Life: The Importance Of Longitudinal Data To Address Patient Heterogeneity," Health Economics, John Wiley & Sons, Ltd., vol. 23(4), pages 487-500, April.
    4. Borislava Mihaylova & Andrew Briggs & Anthony O'Hagan & Simon G. Thompson, 2011. "Review of statistical methods for analysing healthcare resources and costs," Health Economics, John Wiley & Sons, Ltd., vol. 20(8), pages 897-916, August.
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