title: Geographic variation of failure-to-rescue in public acute hospitals in New South Wales, Australia.
abstract: Despite the wide acceptance of Failure-to-Rescue (FTR) as a patient safety indicator (defined as the deaths among surgical patients with treatable complications), no study has explored the geographic variation of FTR in a large health jurisdiction. Our study aimed to explore the spatiotemporal variations of FTR rates across New South Wales (NSW), Australia. We conducted a population-based study using all admitted surgical patients in public acute hospitals during 2002-2009 in NSW, Australia. We developed a spatiotemporal Poisson model using Integrated Nested Laplace Approximation (INLA) methods in a Bayesian framework to obtain area-specific adjusted relative risk. Local Government Area (LGA) was chosen as the areal unit. LGA-aggregated covariates included age, gender, socio-economic and remoteness index scores, distance between patient residential postcode and the treating hospital, and a quadratic time trend. We studied 4,285,494 elective surgical admissions in 82 acute public hospitals over eight years in NSW. Around 14% of patients who developed at least one of the six FTR-related complications (58,590) died during hospitalization. Of 153 LGAs, patients who lived in 31 LGAs, accommodating 48% of NSW patients at risk, were exposed to an excessive adjusted FTR risk (10% to 50%) compared to the state-average. They were mostly located in state's centre and western Sydney. Thirty LGAs with a lower adjusted FTR risk (10% to 30%), accommodating 8% of patients at risk, were mostly found in the southern parts of NSW and Sydney east and south. There were significant spatiotemporal variations of FTR rates across NSW over an eight-year span. Areas identified with significantly high and low FTR risks provide potential opportunities for policy-makers, clinicians and researchers to learn from the success or failure of adopting the best care for surgical patients and build a self-learning organisation and health system.
authors.affiliation: Simpson Centre for Health Services Research, Australian Institute of Health Innovation & South Western Sydney Clinical School, University of New South Wales, Sydney, New South Wales, Australia; Epidemiology, Western Sydney Local Health District, Sydney, New South Wales, Australia.
authors.forename: Hassan
authors.initials: H
authors.lastname: Assareh
authors.affiliation: Simpson Centre for Health Services Research, Australian Institute of Health Innovation & South Western Sydney Clinical School, University of New South Wales, Sydney, New South Wales, Australia.
authors.forename: Lixin
authors.initials: L
authors.lastname: Ou
authors.affiliation: Simpson Centre for Health Services Research, Australian Institute of Health Innovation & South Western Sydney Clinical School, University of New South Wales, Sydney, New South Wales, Australia.
authors.forename: Jack
authors.initials: J
authors.lastname: Chen
authors.affiliation: Simpson Centre for Health Services Research, Australian Institute of Health Innovation & South Western Sydney Clinical School, University of New South Wales, Sydney, New South Wales, Australia.
authors.forename: Kenneth
authors.initials: K
authors.lastname: Hillman
authors.affiliation: Intensive Care Unit, Royal Adelaide Hospital, Adelaide, South Australia, Australia.
authors.forename: Arthas
authors.initials: A
authors.lastname: Flabouris
authors.affiliation: Simpson Centre for Health Services Research, Australian Institute of Health Innovation & South Western Sydney Clinical School, University of New South Wales, Sydney, New South Wales, Australia.
authors.forename: Stephanie J
authors.initials: SJ
authors.lastname: Hollis
mesh_terms: D005843:Geography; D006779:Hospitals, Public / Q000706:statistics & numerical data*; D006801:Humans; D009111:Local Government; D009026:Mortality; D009517:New South Wales; D011183:Postoperative Complications / Q000209:etiology; D012306:Risk; D013997:Time Factors