nach oben

Applied Health Economics and Health Policy

Erschienen in:

01.07.2012 | Original Research Article

Cost Effectiveness of Drug-Eluting Stents in Acute Myocardial Infarction Patients in Germany

Results from Administrative Data Using a Propensity Score-Matching Approach

verfasst von: Michael Bäumler, Tom Stargardt, Jonas Schreyögg, Reinhard Busse

Erschienen in: Applied Health Economics and Health Policy | Ausgabe 4/2012

Einloggen, um Zugang zu erhalten

Abstract

Background: The high number of patients with acute myocardial infarction (AMI) has facilitated greater research, resulting in the development of innovative medical devices. So far, results from economic evaluations that compared drug-eluting stents (DES) and bare-metal stents (BMS) have not shown clear evidence that one intervention is more cost effective than the other.

Objective: The aim of this study was to measure the cost effectiveness of DES compared with BMS in routine care.

Methods: We used administrative data from a large German sickness fund to compare the costs and effectiveness of DES and BMS in patients with AMI. Patients with hospital admission after AMI in 2004 and 2005 were followed up for 1 year after hospital discharge. The cost of treatment and survival after 365 days were compared for patients treated with DES and BMS. We adjusted for covariates defined according to the Ontario Acute Myocardial Infarction Mortality Prediction Rules using propensity score matching. After matching, we calculated incremental cost-effectiveness ratios (ICERs) by (i) using sample means based on bootstrapping procedures and (ii) estimating generalized linear mixed models for costs and survival.

Results: After propensity score matching, the sample included 719 patients treated with DES and 719 patients treated with BMS. A comparison of sample means resulted in average costs of €12 714 and €11714 for DES and BMS, respectively, in 2005 German euros. Difference in 365-day survival was not statistically significant (700 patients with DES and 701 with BMS). The ICER of DES versus BMS was −€718 709 per life saved. Bootstrapping resulted in DES being dominated by BMS in 54.5% of replications and DES being a dominant strategy in 2.7% of replications. Results from regression models and sensitivity analyses confirm these results.

Conclusion: Treatment with DES after admission with AMI is less cost effective than treatment with BMS. Our results are in line with other cost-effectiveness analyses that used administrative data, i.e. under routine care conditions. However, our results do not preclude that DES may be cost effective in specific patient subgroups.

German Federal Statistical Office, Gesundheitsberichterstattung 2009 [online]. Available from URL: http://www.gbe-bund [Accessed 2011 Aug 1]

Cutler DM, McClellan M. Is technological change in medicine worth it? Health Aff 2001; 20(5): 11–29CrossRef

Heidenreich PA, McClellan M. Trends in treatment and outcomes for acute myocardial infarction: 1975–1995. AmJ Med 2001; 15: 165–74CrossRef

Ozaki Y, Violaris AG, Serruys PW. New stent technologies. Prog Cardiovasc Dis 1996; 39(2): 129–40PubMedCrossRef

Hiatt BL, Carter AJ, Yeung AC. The drug-eluting stent: is it the Holy Grail? Rev Cardiovasc Med 2001; 2(4): 190–6PubMed

Stettler C, Wandel S, Allemann S, et al. Outcomes associated with drug-eluting and bare-metal stents: a collaborative network meta-analysis. Lancet 2007; 370: 937–48PubMedCrossRef

de Ridder A, de Graeve D. Can we account for selection bias? A comparison between bare metal and drug-eluting stents. Value Health 2011; 14(1): 3–14PubMedCrossRef

Groeneveld PW, Matta MA, Greenheut AP, et al. The costs of drug-eluting stents among Medicare beneficiaries. Am Heart J 2008; 155(6): 1097–105PubMedCrossRef

Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika 1983; 70(1): 41–55CrossRef

10.

Rubin DB. Matched sampling for causal effects. New York: Cambridge Press, 2006CrossRef

11.

Baser O. Too much ado about propensity score models? Comparing methods of propensity score matching. Value Health 2006; 9(6): 377–85PubMedCrossRef

12.

Austin PC. A critical appraisal of propensity-score matching in the medical literature between 1996 and 2003. Stat Med 2008; 27: 2037–49PubMedCrossRef

13.

Austin PC. Some methods of propensity-score matching had superior performance to others: results of an empirical investigation and Monte Carlo simulations. Biom J 2009; 51(1): 171–84PubMedCrossRef

14.

Groeneveld PW, Matta MA, Greenheut AP, et al. Drug-eluting compared with bare-metal coronary stents among elderly patients. J Am Coll Cardiol 2008; 51: 2017–24PubMedCrossRef

15.

Tu JV, Bowen J, Chiu M, et al. Effectiveness and safety of drug-eluting stents in Ontario. N Eng J Med 2007; 357(14): 1393–402CrossRef

16.

Goeree R, Bowen JM, Blackhouse G, et al. Economic evaluation of drug-eluting stents compared to bare metal stents using a large prospective study in Ontario. Int J Technol Assess Health Care 2009; 25(2): 196–207PubMedCrossRef

17.

Stukel TA, Fisher ES, Wennberg DE, et al. Analysis of observational studies in the presence of treatment selection bias: effects of invasive cardiac management on AMI survival using propensity score and instrumental variable methods. JAMA 2007; 297(3): 278–85PubMedCrossRef

18.

Schreyögg J, Stargardt T, Tiemann A multilevel approach to explain variation in costs and quality of hospitals in different settings. Health Econ 2011; 20(1): 85–100PubMedCrossRef

19.

Cutler DM. The lifetime costs and benefits of medical technology. J Health Econ 2007; 26(6): 1081–100PubMedCrossRef

20.

Vermeulen MJ, Tu JV, Schull MJ. ICD-10 adaptions of the Ontario acute myocardial infarction mortality prediction rules performed as well as the original versions. J Clin Epidemiol 2007; 60(9): 971–4PubMedCrossRef

21.

Schreyögg J, Stargardt T, Tiemann et al. Methods to determine reimbursement rates for diagnosis related groups (DRG): a comparison of nine European countries. Health Care Manag Sci 2006; 9(3): 215–23PubMedCrossRef

22.

German Federal Statistical Office. Online Database Genesis [online]. Available from URL: https://www.genesis.destatis.de/genesis/online/logon [Accessed 2011 Feb 28]

23.

Tu JV, Austin PC, Walld R, et al. Development and validation of the Ontario acute myocardial infarction mortality prediction rules. J Am Coll Cardiol 2001; 37: 992–7PubMedCrossRef

24.

Evans E, Imanaka Y, Sekimoto M, et al. Risk adjusted resource utilization for AMI patients treated in Japanese hospitals. Health Econ 2007; 16: 347–59PubMedCrossRef

25.

Maier B, Thimme W, Schoeller R, et al. Berlin Myocardial Infarction Registry. Improved therapy and outcome for patients with acute myocardial infarction: data of the Berlin Myocardial Infarction Registry from 1999 to 2004. Int J Cardiol 2008; 130(2): 211–9PubMedCrossRef

26.

Boos DD, Stefanski LA, Wu Y. Fast FSR variable selection with applications to clinical trials. Biometrics 2009; 65(3): 692–700PubMedCrossRef

27.

Neyt M, de Laet C, de Ridder A, et al. Cost effectiveness of drug-eluting-stents in Belgian practice: healthcare payer perspective. Pharmacoeconomics 2009; 27(4): 313–27PubMedCrossRef

28.

Bischof M, Briel M, Bucher HC, et al. Cost-effectiveness of drug-eluting stents in a US Medicare setting: a cost-utility analysis with 3-year clinical follow-up data. Value Health 2009; 12(5): 649–56PubMedCrossRef

29.

Neyt M, Van Brabandt H, Devriese S, et al. Cost-effectiveness analyses of drug eluting stents versus bare metal stents: a systematic review of the literature. Health Pol 2009; 91(2): 107–20CrossRef

30.

McKee M, Brotton A, Black N, et al. Methods in health services research: Interpreting the evidence: choosing between randomised and non-randomised studies. Br Med J 1999; 319: 312–5CrossRef

31.

Reinhold T, Andersohn F, Hessel F, et al. The use of routine data of statutory health insurance (SHI) in health economic research — analysis of applicability. Gesundh Ökon Qual Manag 2011; 16: 153–9CrossRef

32.

Schulz S, Mehilli J, Byrne RA, et al. Stent thrombosis after drug-eluting stent implantation: incidence, timing, and relation to discontinuation of clopidogrel therapy over a 4 year period. Eur Heart J 2009; 30(22): 2714–21PubMedCrossRef

33.

Glaeske G, Jahnsen K. Arzneimittelreport 2006. St. Augustin: Asgard, 2006

34.

Henschke Bäumler M, Gaskins M, et al. Coronary stents and the uptake of new medical devices in the German system of reimbursement. J Intervent Cardiol 2011; 23(6): 546–53CrossRef

35.

German Institute for Hospital Remuneration (InEK). German DRG catalogues 2009–2011 [online]. Available from URL: http://www.g-drg.die [Accessed 2011 Aug 1]

Titel: Cost Effectiveness of Drug-Eluting Stents in Acute Myocardial Infarction Patients in Germany
Results from Administrative Data Using a Propensity Score-Matching Approach
verfasst von: Michael Bäumler
Tom Stargardt
Jonas Schreyögg
Reinhard Busse
Publikationsdatum: 01.07.2012
Verlag: Springer International Publishing
Erschienen in: Applied Health Economics and Health Policy / Ausgabe 4/2012
Print ISSN: 1175-5652
Elektronische ISSN: 1179-1896
DOI: https://doi.org/10.2165/11597340-000000000-00000

Springer Medizin

Abstract

Bitte loggen Sie sich ein, um Zugang zu diesem Inhalt zu erhalten

Weitere Artikel der Ausgabe 4/2012

Resource Utilization and Outcomes in Patients with Atrial Fibrillation

Cost-Effectiveness Analysis of Treatments for Vertebral Compression Fractures

Economic Consequences of the Demography of MRSA Patients and the Impact of Broad-Spectrum Antimicrobials

Economic Evaluation of Clopidogrel in Acute Coronary Syndrome Patients without ST-Segment Elevation in Greece

A New Reimbursement System for Innovative Pharmaceuticals Combining Value-Based and Free Market Pricing