D R M Smith1, K B Pouwels2, S Hopkins3, N R Naylor4, T Smieszek5, J V Robotham6. 1. Modelling and Economics Unit, National Infection Service, Public Health England, London, UK; Healthcare-Associated Infection and Antimicrobial Resistance Division, National Infection Service, Public Health England, London, UK; Pharmacoépidémiologie et Maladies Infectieuses, Institut Pasteur, U1181, Inserm, UVSQ, Paris, France; UVSQ, Université Paris-Saclay, Versailles, France; Laboratoire MESuRS, Conservatoire National des Arts et Métiers, Paris, France. Electronic address: david.smith@pasteur.fr. 2. Modelling and Economics Unit, National Infection Service, Public Health England, London, UK; Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK; Department of Health Sciences, Global Health, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands. 3. Healthcare-Associated Infection and Antimicrobial Resistance Division, National Infection Service, Public Health England, London, UK; Directorate of Infection, Royal Free London NHS Foundation Trust, London, UK; National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London, UK. 4. National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London, UK. 5. Modelling and Economics Unit, National Infection Service, Public Health England, London, UK; Healthcare-Associated Infection and Antimicrobial Resistance Division, National Infection Service, Public Health England, London, UK. 6. Modelling and Economics Unit, National Infection Service, Public Health England, London, UK; Healthcare-Associated Infection and Antimicrobial Resistance Division, National Infection Service, Public Health England, London, UK; National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London, UK.
Abstract
BACKGROUND: Catheter-associated urinary tract infection (CAUTI) and bloodstream infection (CABSI) are leading causes of healthcare-associated infection in England's National Health Service (NHS), but health-economic evidence to inform investment in prevention is lacking. AIMS: To quantify the health-economic burden and value of prevention of urinary-catheter-associated infection among adult inpatients admitted to NHS trusts in 2016/17. METHODS: A decision-analytic model was developed to estimate the annual prevalence of CAUTI and CABSI, and their associated excess health burdens [quality-adjusted life-years (QALYs)] and economic costs (£ 2017). Patient-level datasets and literature were synthesized to estimate population structure, model parameters and associated uncertainty. Health and economic benefits of catheter prevention were estimated. Scenario and probabilistic sensitivity analyses were conducted. FINDINGS: The model estimated 52,085 [95% uncertainty interval (UI) 42,967-61,360] CAUTIs and 7529 (UI 6857-8622) CABSIs, of which 38,084 (UI 30,236-46,541) and 2524 (UI 2319-2956) were hospital-onset infections, respectively. Catheter-associated infections incurred 45,717 (UI 18,115-74,662) excess bed-days, 1467 (UI 1337-1707) deaths and 10,471 (UI 4783-13,499) lost QALYs. Total direct hospital costs were estimated at £54.4M (UI £37.3-77.8M), with an additional £209.4M (UI £95.7-270.0M) in economic value of QALYs lost assuming a willingness-to-pay threshold of £20,000/QALY. Respectively, CABSI accounted for 47% (UI 32-67%) and 97% (UI 93-98%) of direct costs and QALYs lost. Every catheter prevented could save £30 (UI £20-44) in direct hospital costs and £112 (UI £52-146) in QALY value. CONCLUSIONS: Hospital catheter prevention is poised to reap substantial health-economic gains, but community-oriented interventions are needed to target the large burden imposed by community-onset infection. Crown
BACKGROUND: Catheter-associated urinary tract infection (CAUTI) and bloodstream infection (CABSI) are leading causes of healthcare-associated infection in England's National Health Service (NHS), but health-economic evidence to inform investment in prevention is lacking. AIMS: To quantify the health-economic burden and value of prevention of urinary-catheter-associated infection among adult inpatients admitted to NHS trusts in 2016/17. METHODS: A decision-analytic model was developed to estimate the annual prevalence of CAUTI and CABSI, and their associated excess health burdens [quality-adjusted life-years (QALYs)] and economic costs (£ 2017). Patient-level datasets and literature were synthesized to estimate population structure, model parameters and associated uncertainty. Health and economic benefits of catheter prevention were estimated. Scenario and probabilistic sensitivity analyses were conducted. FINDINGS: The model estimated 52,085 [95% uncertainty interval (UI) 42,967-61,360] CAUTIs and 7529 (UI 6857-8622) CABSIs, of which 38,084 (UI 30,236-46,541) and 2524 (UI 2319-2956) were hospital-onset infections, respectively. Catheter-associated infections incurred 45,717 (UI 18,115-74,662) excess bed-days, 1467 (UI 1337-1707) deaths and 10,471 (UI 4783-13,499) lost QALYs. Total direct hospital costs were estimated at £54.4M (UI £37.3-77.8M), with an additional £209.4M (UI £95.7-270.0M) in economic value of QALYs lost assuming a willingness-to-pay threshold of £20,000/QALY. Respectively, CABSI accounted for 47% (UI 32-67%) and 97% (UI 93-98%) of direct costs and QALYs lost. Every catheter prevented could save £30 (UI £20-44) in direct hospital costs and £112 (UI £52-146) in QALY value. CONCLUSIONS: Hospital catheter prevention is poised to reap substantial health-economic gains, but community-oriented interventions are needed to target the large burden imposed by community-onset infection. Crown
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