As part of the approval granted by the Royal Brisbane & Women’s Hospital Human Research Ethics Committee for this study, data is non-disclosable, except for aggregated summary statistics that would not lead to breaches in terms of patient confidentiality. Data contain patient-level information that is therefore potentially identifiable. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: Data have limitations on disclosure as a results of relevant privacy legislation. Received: SeptemAccepted: SeptemPublished: October 10, 2018Ĭopyright: © 2018 Swierkowski, Barnett.
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Given the financial footprint involved, once the findings are extrapolated nationwide, this estimation has far-reaching significance for health funding policy.Ĭitation: Swierkowski P, Barnett A (2018) Identification of hospital cost drivers using sparse group lasso. The proportion of cost variability potentially not clinically warranted was estimated at 33.7%. Our statistical model included 32 potential cost predictors with a sample size of over 50,000 hospital admissions. This ensures reliability of the findings and represents a novel and powerful approach to analysing hospital costs. Crucially, the study then adjusts for possible co-linearity of different cost drivers by the use of the sparse group lasso technique. An essential step is dimension reduction using Principal Component Analysis to pre-process the data by separating out the low value ‘noise’ from otherwise valuable information. This study identifies prime cost drivers in a typical, mid-sized Australian hospital and classifies them as sources of cost variability that are either warranted or not warranted-and therefore contributing to waste.
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Accurate identification of the main hospital cost drivers and relating them quantitatively to the observed cost variability is a necessary step towards identifying and reducing waste. The large cost variability observed between hospitals and also between patients in the same hospital has fueled the belief that consumption of a significant portion of this funding may result in no clinical benefit to patients, thus representing waste. Public hospital spending consumes a large share of government expenditure in many countries.