, Volume 37, Issue 1, pp 63–74 | Cite as

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

  • Katharina Kähm
  • Michael Laxy
  • Udo Schneider
  • Rolf Holle
Original Research Article



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.


The primary aim was to explore different strategies that address the economic impact of multiple type 2 diabetes-related complications and their interactions.


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.


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.


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.



This research is carried out on behalf of the Helmholtz Zentrum München, the German Research Center for Environmental Health (HMGU), which is a member of the German Center for Diabetes Research (DZD). The HMGU is an independent organization funded by the German and Bavarian governments.

Author Contributions

KK and RH planned the study design. Cohort selection, data processing, and statistical data analysis were conducted by KK. US was the key contact person at the WINEG/TK and provided continuous technical support during data processing and analysis. The manuscript was drafted and improved by KK, ML, and RH. RH and ML provided methodological input. All authors critically reviewed the manuscript and approved its final version. RH supervised all steps of the work. The overall guarantor for the content of this paper is KK.

Compliance with Ethical Standards

Conflict of interest

KK, ML, US, and RH have no financial, academic or other conflicts of interest to declare.

Supplementary material

40273_2018_699_MOESM1_ESM.doc (411 kb)
Supplementary material 1 (DOC 411 kb)


  1. 1.
    Battegay E, Cheetham M, Holzer BM, Nowak A, Schmidt D, Rampini S. Multimorbidity management and the physician’s daily clinical dilemma. Der Internist. 2017;58(4):344–53.CrossRefGoogle Scholar
  2. 2.
    Workneh MH, Bjune GA, Yimer SA. Prevalence and associated factors of tuberculosis and diabetes mellitus comorbidity: a systematic review. PLoS One. 2017;12(4):e0175925.CrossRefGoogle Scholar
  3. 3.
    Ording AG, Sorensen HT. Concepts of comorbidities, multiple morbidities, complications, and their clinical epidemiologic analogs. Clin Epidemiol. 2013;5:199–203.CrossRefGoogle Scholar
  4. 4.
    Alonso-Moran E, Orueta JF, Esteban JI, Axpe JM, Gonzalez ML, Polanco NT, et al. Multimorbidity in people with type 2 diabetes in the Basque Country (Spain): prevalence, comorbidity clusters and comparison with other chronic patients. Eur J Int Med. 2015;26(3):197–202.CrossRefGoogle Scholar
  5. 5.
    Bommer C, Sagalova V, Heesemann E, Manne-Goehler J, Atun R, Barnighausen T, et al. Global economic burden of diabetes in adults: projections from 2015 to 2030. Diabetes Care. 2018;41(5):963–70.CrossRefGoogle Scholar
  6. 6.
    Clarke PM, Gray AM, Briggs A, Farmer AJ, Fenn P, Stevens RJ, et al. A model to estimate the lifetime health outcomes of patients with type 2 diabetes: the United Kingdom Prospective Diabetes Study (UKPDS) Outcomes Model (UKPDS no. 68). Diabetologia. 2004;47(10):1747–59.CrossRefGoogle Scholar
  7. 7.
    The CDC Diabetes Cost-Effectiveness Group. Cost-effectiveness of intensive glycemic control, intensified hypertension control, and serum cholesterol level reduction for type 2 diabetes. Jama. 2002;287(19):2542–51.CrossRefGoogle Scholar
  8. 8.
    Alva M, Gray A, Mihaylova B, Clarke P. The effect of diabetes complications on health-related quality of life: the importance of longitudinal data to address patient heterogeneity. Health Econ. 2014;23(4):487–500.CrossRefGoogle Scholar
  9. 9.
    Hunger M, Thorand B, Schunk M, Doring A, Menn P, Peters A, et al. Multimorbidity and health-related quality of life in the older population: results from the German KORA-age study. Health Qual Life Outcomes. 2011;18(9):53.CrossRefGoogle Scholar
  10. 10.
    Palmer AJ, Clarke P, Gray A, Leal J, Lloyd A, Grant D, et al. Computer modeling of diabetes and its complications: a report on the Fifth Mount Hood challenge meeting. Value Health J Int Soc Pharm Outcomes Res. 2013;16(4):670–85.Google Scholar
  11. 11.
    Kreis K, Neubauer S, Klora M, Lange A, Zeidler J. Status and perspectives of claims data analyses in Germany—a systematic review. Health Policy (Amst Neth). 2016;120(2):213–26.CrossRefGoogle Scholar
  12. 12.
    Kähm K, Laxy M, Schneider U, Rogowski WH, Lhachimi SK, Holle R. Health care costs associated with incident complications in patients with type 2 diabetes in Germany. Diabetes Care. 2018;41(5):971–8.CrossRefGoogle Scholar
  13. 13.
    Krentz AJ, Clough G, Byrne CD. Interactions between microvascular and macrovascular disease in diabetes: pathophysiology and therapeutic implications. Diabetes Obes Metab. 2007;9(6):781–91.CrossRefGoogle Scholar
  14. 14.
    Mihaylova B, Briggs A, O’Hagan A, Thompson SG. Review of statistical methods for analysing healthcare resources and costs. Health Econ. 2011;20(8):897–916.CrossRefGoogle Scholar
  15. 15.
    Walter S, Tiemeier H. Variable selection: current practice in epidemiological studies. Eur J Epidemiol. 2009;24(12):733–6.CrossRefGoogle Scholar
  16. 16.
    Nuno-Solinis R, Alonso-Moran E, Arteagoitia Axpe JM, Ezkurra Loiola P, Orueta JF, Gaztambide S. Healthcare costs of people with type 2 diabetes mellitus in the Basque Country (Spain). Endocrinologia y nutricion : organo de la Sociedad Espanola de Endocrinologia y Nutricion. 2016;63(10):543–50.CrossRefGoogle Scholar
  17. 17.
    Chen HL, Hsu WW, Hsiao FY. Changes in prevalence of diabetic complications and associated healthcare costs during a 10-year follow-up period among a nationwide diabetic cohort. J Diabetes Complicat. 2015;29(4):523–8.CrossRefGoogle Scholar
  18. 18.
    Dimitrova M, Doneva M, Valov V, Yordanova S, Manova M, Savova A, et al. Cost of hospitalizations due to microvascular and macrovascular complications in type 1 and type 2 diabetic patients in Bulgaria. Biotechnol Biotechnol Equip. 2015;29(4):805–13.CrossRefGoogle Scholar
  19. 19.
    Hwang DJ, Lee KM, Park MS, Choi SH, Park JI, Cho JH, et al. Association between diabetic foot ulcer and diabetic retinopathy. PloS One. 2017;12(4):e0175270.CrossRefGoogle Scholar
  20. 20.
    Lavery LA, Hunt NA, Ndip A, Lavery DC, Van Houtum W, Boulton AJ. Impact of chronic kidney disease on survival after amputation in individuals with diabetes. Diabetes Care. 2010;33(11):2365–9.CrossRefGoogle Scholar
  21. 21.
    Ndip A, Lavery LA, Boulton AJ. Diabetic foot disease in people with advanced nephropathy and those on renal dialysis. Curr Diabetes Rep. 2010;10(4):283–90.CrossRefGoogle Scholar
  22. 22.
    Jeng CJ, Hsieh YT, Yang CM, Yang CH, Lin CL, Wang IJ. Diabetic retinopathy in patients with diabetic nephropathy: development and progression. PloS One. 2016;11(8):e0161897.CrossRefGoogle Scholar
  23. 23.
    Grunwald JE, Alexander J, Ying GS, Maguire M, Daniel E, Whittock-Martin R, et al. Retinopathy and chronic kidney disease in the Chronic Renal Insufficiency Cohort (CRIC) study. Arch Ophthalmol. (Chicago, Ill : 1960). 2012;130(9):1136–44.CrossRefGoogle Scholar
  24. 24.
    Damman K, Valente MA, Voors AA, O’Connor CM, van Veldhuisen DJ, Hillege HL. Renal impairment, worsening renal function, and outcome in patients with heart failure: an updated meta-analysis. Eur Heart J. 2014;35(7):455–69.CrossRefGoogle Scholar
  25. 25.
    Silverberg D, Wexler D, Blum M, Schwartz D, Iaina A. The association between congestive heart failure and chronic renal disease. Curr Opin Nephrol Hypertens. 2004;13(2):163–70.CrossRefGoogle Scholar
  26. 26.
    Palsson R, Patel UD. Cardiovascular complications of diabetic kidney disease. Adv Chron Kidney Dis. 2014;21(3):273–80.CrossRefGoogle Scholar
  27. 27.
    Tuttolomondo A, Maida C, Pinto A. Diabetic foot syndrome as a possible cardiovascular marker in diabetic patients. J Diabetes Res. 2015;2015:268390.CrossRefGoogle Scholar
  28. 28.
    Banerjee A, Fowkes FG, Rothwell PM. Associations between peripheral artery disease and ischemic stroke: implications for primary and secondary prevention. Stroke J Cereb Circ. 2010;41(9):2102–7.CrossRefGoogle Scholar
  29. 29.
    Lappenschaar M, Hommersom A, Lucas PJ. Probabilistic causal models of multimorbidity concepts. In: AMIA annual symposium proceedings/AMIA symposium AMIA symposium. 2012;2012:475–84.Google Scholar
  30. 30.
    Brennan A, Chick SE, Davies R. A taxonomy of model structures for economic evaluation of health technologies. Health Econ. 2006;15(12):1295–310.CrossRefGoogle Scholar
  31. 31.
    Khokhar B, Jette N, Metcalfe A, Cunningham CT, Quan H, Kaplan GG, et al. Systematic review of validated case definitions for diabetes in ICD-9-coded and ICD-10-coded data in adult populations. BMJ Open. 2016;6(8):e009952.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Institute of Health Economics and Health Care Management, Helmholtz Zentrum München (GmbH)-German Research Center for Environmental Health (GmbH)NeuherbergGermany
  2. 2.German Center for Diabetes Research (DZD)Munich, NeuherbergGermany
  3. 3.Scientific Institute of TK for Benefit and Efficiency in Health Care, Techniker Krankenkasse (TK)HamburgGermany

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