Methods Inf Med 2014; 53(04): 269-277
DOI: 10.3414/ME13-01-0132
Original Articles
Schattauer GmbH

Evaluating Methods for Intersectoral Comparison of Quality of Care[*]

A Routine Data Analysis of Elective Percutaneous Coronary Interventions
C. Ohlmeier
1   Leibniz-Institute for Prevention Research and Epidemiology – BIPS, Bremen, Germany
,
R. Linder
2   Scientific Institute of TK for Benefit and Efficiency in Health Care, Köln, Germany
,
D. Enders
1   Leibniz-Institute for Prevention Research and Epidemiology – BIPS, Bremen, Germany
,
R. Mikolajczyk
3   Helmholtz Centre for Infection Research, Braunschweig, Germany
4   Hannover Medical School Hannover, Germany
,
W. Haverkamp
5   Charité University Medicine Berlin, Berlin, Germany
,
D. HorenkampSonntag
2   Scientific Institute of TK for Benefit and Efficiency in Health Care, Köln, Germany
,
E. Garbe
1   Leibniz-Institute for Prevention Research and Epidemiology – BIPS, Bremen, Germany
6   University of Bremen, Bremen, Germany
› Institutsangaben
Weitere Informationen

Publikationsverlauf

received:30. November 2013

accepted:18. Juni 2014

Publikationsdatum:
20. Januar 2018 (online)

Summary

Objectives: To compare the quality of care regarding the use of elective percutaneous coronary interventions (PCIs) in the inpatient and outpatient setting and to evaluate different methods of confounder control in this context.

Methods: Based on data of three statutory health insurances including more than nine million insurance members, a retrospective cohort study between 2005 and 2009 was conducted. The occurrence of myocardial infarction, stroke, further coronary intervention and death was ascertained following the first PCI in the study period, which was preceded by a one-year period without a PCI. A Cox proportional hazard model was used to assess the influence of the setting of the elective PCI on the risk for complications after the PCI for each outcome separately. Age, sex, the number of diseases of the Elixhauser comorbidity measure, past acute coronary syndrome, coronary artery disease, dyslipidemia, past stroke, past coronary artery bypass surgery and the year of the PCI were included as covariables. The analyses were repeated in a propensity score matched cohort as well as in inverse probability of treatment weighted analyses.

Results: The cohort comprised 4,269 patients with an outpatient PCI and 26,044 patients with an inpatient PCI. The majority of the analyses revealed no statistically significant effect of the setting of the PCI on the risk of myocardial infarction, stroke and further coronary interventions, whereas a reduced mortality risk was observed for out-patient PCIs. Similar results were obtained in the propensity score analyses.

Conclusions: The analysis revealed that the adjusted risk for complications following an elective PCI is similar between the inpatient and the outpatient setting. For mortality the risk differed but this might be explained by residual or unmeasured confounding. The different methods applied in this study revealed mostly similar results. Since our study only covered one aspect of quality of care in the field of PCI and did not consider drug treatment in hospital or in the outpatient setting, further studies are needed which include these aspects.

* Supplementary material published on our website www.methods-online.de


 
  • References

  • 1 World Health Organization (WHO) [Internet]. Cardiovascular Diseases (CVDs). [cited 2014 May 05>. Available from. http://www.who.int/mediacentre/factsheets/fs317/en/index.html
  • 2 EUGLOREH. Non-communicable diseases and related time trends: Prevalence, incidence and mortality; the status of health in the European Union: towards a healthier Europe. 2009
  • 3 Gosswald A, Schienkiewitz A, Nowossadeck E, Busch MA. Prevalence of myocardial infarction and coronary heart disease in adults aged 40-79 years in Germany: results of the German Health Interview and Examination Survey for Adults (DEGS1). Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2013; 56 5-6 650-655.
  • 4 Czwikla J, Ohlmeier C, Enders D, N’Diaye I, Timmer A, Mikolajczyk R. et al. Häufigkeit koronarer Interventionen zwischen 2004 und 2009 in Deutschland. Proceedings of the 8th annual Conference of the German Association of Epidemiology. Leipzig, Germany: Sep 24-27 2013
  • 5 Deutsche Herzstiftung. Deutscher Herzbericht 2011. Frankfurt am Main. 2012
  • 6 Robra B-P. Swart E, Vogt T. Veränderungen des Umfangs der vertragsärztlichen Leistungen durch Leistungsverlagerungen zwischen dem stationären und dem ambulanten Sektor. Magdeburg. 2010
  • 7 Albrecht A, Levenson B, Gohring S, Haerer W, Reifart N, Ringwald G. et al The QuIK-Registry of the German Society of Cardiologists in private practice: countrywide and benchmarking quality assurance in invasive cardiology. Dtsch Med Wochenschr 2009; 134 (Suppl. 06) Suppl S211-S213.
  • 8 AQUA-Institut. Qualitätsreport 2009. Göttingen. 2010
  • 9 Boy O, Hahn S, Kociemba E. BQS-Fachgruppe Kardiologie. Koronarangiographie und Perkutane Koronarintervention (PCI). Düsseldorf. 2008
  • 10 Jeschke E, Baberg HT, Dirschedl P, Heyde K, Levenson B, Malzahn J. et al Complication rates and secondary interventions after coronary procedures in clinical routine: 1-year follow-up based on routine data of a German health insurance company. Dtsch Med Wochenschr 2013; 138 (12) 570-575.
  • 11 Austin PC. An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies. Multivariate Behav Res 2011; 46 (03) 399-424.
  • 12 Mikolajczyk RT, Kraut AA, Garbe E. Evaluation of pregnancy outcome records in the German Pharmacoepidemiological Research Database (GePaRD). Pharmacoepidemiol Drug Saf 2013; 22 (08) 873-880.
  • 13 Pigeot I, Ahrens W. Establishment of a pharmacoepidemiological database in Germany: methodological potential, scientific value and practical limitations. Pharmacoepidemiol Drug Saf 2008; 17 (03) 215-223.
  • 14 DIMDI Deutsches Institut für Medizinische Dokumentation und Information [Internet]. Internationale Statistische Klassifikation der Krankheiten und verwandter Gesundheitsprobleme: 10. Revision: Version 2008. [cited 2014 May 05>. Available from. http://www.dimdi.de/static/de/klassi/icd-10-gm/kodesuche/onlinefassungen/htmlgm2008/index.htm
  • 15 DIMDI Deutsches Institut für Medizinische Dokumentation und Information [Internet]. Operationen- und Prozedurenschlüssel (OPS) Version 2008. [cited 2014 May 05>. Available from. www.dimdi.de/static/de/klassi/ops/kodesuche/onlinefassungen/opshtml2008/
  • 16 Kassenärztliche Bundesvereinigung [Internet]. Einheitlicher Bewertungsmaßstab (EBM). [cited 2014 May 05>. Available from. http://www.kbv.de/html/ebm.php
  • 17 Quan H, Sundararajan V, Halfon P, Fong A, Burnand B, Luthi JC. et al Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care 2005; 43 (11) 1130-1139.
  • 18 Daly LE. Confidence limits made easy: interval estimation using a substitution method. Am J Epidemiol 1998; 147 (08) 783-790.
  • 19 Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care 1998; 36 (01) 8-27.
  • 20 Parsons L. Reducing bias in a propensity score matched-pair sample using greedy matching techniques. SUGI 26. 2010
  • 21 Normand ST, Landrum MB, Guadagnoli E, Ayanian JZ, Ryan TJ, Cleary PD. et al Validating recommendations for coronary angiography following acute myocardial infarction in the elderly: a matched analysis using propensity scores. J Clin Epidemiol 2001; 54 (04) 387-398.
  • 22 Robins JM, Hernan MA, Brumback B. Marginal structural models and causal inference in epidemiology. Epidemiology 2000; 11 (05) 550-560.
  • 23 Cole SR, Hernan MA. Constructing inverse probability weights for marginal structural models. Am J Epidemiol 2008; 168 (06) 656-664.
  • 24 Simard T, Hibbert B, Ramirez FD, Froeschl M, Chen YX, O’Brien ER. The evolution of coronary stents: a brief review. Can J Cardiol 2014; 30 (01) 35-45.
  • 25 Mack MJ, Head SJ, Holmes Jr. DR, Stahle E, Feldman TE, Colombo A. et al Analysis of stroke occurring in the SYNTAX trial comparing coronary artery bypass surgery and percutaneous coronary intervention in the treatment of complex coronary artery disease. JACC Cardiovasc Interv 2013; 6 (04) 344-354.
  • 26 Weintraub WS. The pathophysiology and burden of restenosis. Am J Cardiol 2007; 100 5A 3K-9K.
  • 27 Sturmer T, Joshi M, Glynn RJ, Avorn J, Rothman KJ, Schneeweiss S. A review of the application of propensity score methods yielded increasing use, advantages in specific settings, but not substantially different estimates compared with conventional multivariable methods. J Clin Epidemiol 2006; 59 (05) 437-447.
  • 28 Schneeweiss S, Rassen JA, Glynn RJ, Avorn J, Mogun H, Brookhart MA. High-dimensional propensity score adjustment in studies of treatment effects using health care claims data. Epidemiology 2009; 20 (04) 512-522.
  • 29 Glynn RJ, Schneeweiss S, Sturmer T. Indications for propensity scores and review of their use in pharmacoepidemiology. Basic Clin Pharmacol Toxicol 2006; 98 (03) 253-259.
  • 30 Kurth T, Walker AM, Glynn RJ, Chan KA, Gaziano JM, Berger K. et al Results of multivariable logistic regression, propensity matching, propensity adjustment, and propensity-based weighting under conditions of nonuniform effect. Am J Epidemiol 2006; 163 (03) 262-270.
  • 31 Petersen ML, Porter KE, Gruber S, Wang Y, van der Laan MJ. Diagnosing and responding to violations in the positivity assumption. Stat Methods Med Res 2012; 21 (01) 31-54.