Cost-effectiveness analysis of cleaning shared medical equipment to reduce healthcare-associated infections

Dr David Brain1, Dr Nicole Whie1, Ms. Nirmali Sivapragasam1, Prof Brett Mitchell2, Dr Kate Browne2, Ms. Georgia Matterson2, A/Prof Andrew Stewardson3, Prof Philip Russo3, Prof Allen Cheng3, Dr Peta Tehan3, Visiting Prof Martin Kiernan4

1Australian Centre For Health Services Innovation (AusHSI), Queensland University of Technology, Brisbane, Australia, 2Avondale University, Cooranbong, Australia, 3Monash University, Clayton, Australia, 4University of West London, Brentford, England

Biography:

Nirmali Sivapragasam (MPP) is a second-year PhD candidate at The Australian Centre for Health Services Innovation (AusHSI), School of Public Health and Social Work, Faculty of Health, Queensland University of Technology. Her research explores the application of cost-effectiveness methods to chronic disease prevention and control programs. Prior to joining AusHSI, she held senior research associate and project management roles at the Program in Health Services and Systems Research, Duke-NUS Medical School, Singapore, and the Institute for Health Policy, Colombo, Sri Lanka, where she co-led several projects in the areas of health services research, health economics, and global health.

Abstract:

Introduction

We undertook a within-trial cost-effectiveness evaluation of a cleaning intervention designed to reduce healthcare-associated infections (HAIs). The world-first randomised control CLEEN trial introduced additional cleaning of shared medical equipment in hospital wards to evaluate the effect on HAIs. We aim to provide healthcare decision-makers with novel evidence, from an economic perspective.

Methods

A decision-analytic model (decision tree) was programmed to compare total costs and infections associated with the intervention and usual care from the hospital perspective. The model’s structure represents possible outcomes for the patient cohort and follows the natural history of having a HAI. Trial data on outcome probabilities and intervention costs were used as model inputs. Costs associated with extra length of stay due to infection were estimated from the literature. Health outcomes were derived from the trial, and included BSI, SSI, pneumonia, and UTI.

Results

There were 2,360 patients in the control group and 2,389 in the intervention. Total costs associated with the intervention group were $2,899,181 compared to $3,482,763 in usual care. There were 48 fewer HAIs in the intervention group (n = 142) compared to the usual care group (n = 190), indicating the effectiveness of the CLEEN intervention. The intervention dominates usual care, as it is both cheaper and more effective. The hospital saved $12,158 per HAI avoided by implementing the intervention.

Conclusion

The CLEEN intervention is a cost-saving initiative and a decision-maker who chooses not to invest in it forgoes an opportunity to maximise health gain from a scarce budget.

 

 

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