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The impact of hospital-acquired infections on the patient-level reimbursement-cost relationship in a DRG-based hospital payment system

  • Klaus KaierEmail author
  • Martin Wolkewitz
  • Philip Hehn
  • Nico T. Mutters
  • Thomas Heister
Research Article

Abstract

Hospital-acquired infections (HAIs) are a common complication in inpatient care. We investigate the incentives to prevent HAIs under the German DRG-based reimbursement system. We analyze the relationship between resource use and reimbursements for HAI in 188,731 patient records from the University Medical Center Freiburg (2011–2014), comparing cases to appropriate non-HAI controls. Resource use is approximated using national standardized costing system data. Reimbursements are the actual payments to hospitals under the G-DRG system. Timing of HAI exposure, cost-clustering within main diagnoses and risk-adjustment are considered. The reimbursement-cost difference of HAI patients is negative (approximately − €4000). While controls on average also have a negative reimbursement-cost difference (approximately − €2000), HAI significantly increase this difference after controlling for confounding and timing of infection (− 1500, p < 0.01). HAIs caused by vancomycin-resistant Enterococci have the most unfavorable reimbursement-cost difference (− €10,800), significantly higher (− €9100, p < 0.05) than controls. Among infection types, pneumonia is associated with highest losses (− €8400 and − €5700 compared with controls, p < 0.05), while cost-reimbursement relationship for Clostridium difficile-associated diarrhea is comparatively balanced (− €3200 and − €500 compared to controls, p = 0.198). From the hospital administration’s perspective, it is not the additional costs of HAIs, but rather the cost-reimbursement relationship which guides decisions. Costs exceeding reimbursements for HAI may increase infection prevention and control efforts and can be used to show their cost-effectiveness from the hospital perspective.

Keywords

HAI G-DRG Incentives Reimbursement Cost 

JEL Classification

I10 

Notes

Acknowledgements

We would like to thank Barbara Schroeren-Boersch, Markus Dettenkofer, and Hajo Grundmann for providing the dataset, Susanne Hanser and Werner Vach for helpful comments regarding the analysis and Sabine Engler-Hüsch for technical support.

Compliance with ethical standards

Conflict of interest

This work was supported by the German Research Foundation [Grant No. WO 1746/1-2 to Martin Wolkewitz and Grant No. KA 4199/1-1 to Thomas Heister]. Klaus Kaier has received support from the Innovative Medicines Initiative Joint Undertaking under Grant Agreement No. 115737-2 (Combatting bacterial resistance in Europe—molecules against Gram negative infections [COMBACTE-MAGNET]). The funders had no role in data collection and analysis, decision to publish, or preparation of the manuscript. The authors declare no conflicts of interest.

Informed consent

This research involved no intervention, and all patient records were anonymized prior to use, in accordance with German data protection law. For this type of study formal consent is not required.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Institute of Medical Biometry and StatisticsFaculty of Medicine and Medical Center – University of FreiburgFreiburgGermany
  2. 2.Institute for Infection Prevention and Hospital Epidemiology, Faculty of MedicineMedical Center – University of FreiburgFreiburgGermany

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