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Objective: To model the effect of excluding payment for eight hospital-acquired conditions (HACs) on hospital payments in Victoria, Australia.Design, Setting and Participants: Retrospective ecological study using the Victorian Admitted Episodes Dataset. The analysis involved all acute inpatient admissions to Victorian public and private hospitals between 1 July 2007 and 30 June 2008.Interventions: Each admission record includes up to 40 diagnosis and procedure codes from which payments are calculated. The model deleted diagnosis codes for eight HACs from all records, then recalculated payments to estimate the impact of a policy of non-payment for HACs.Main Outcome Measure: The effect on hospital payments of excluding diagnosis codes for eight HACs.Results: 2,047,133 cases with total estimated payments of $4902 million were identified; 994 cases (0.05%) had one or more diagnoses meeting the code definition for a definable HAC, representing total payments of $24.1 million. In-hospital falls and pressure ulcers were the most commonly coded HACs. Applying a model that excluded HAC diagnosis codes changed the diagnosis-related group for 134 cases (13.5%), thereby generating a $448,630 reduction in payments.Conclusions: Introducing a non-payment for HACs policy similar to that introduced by Medicare in the United States would have little direct financial impact in the Australian context, although additional savings would accrue if HAC rates were reduced. Such a policy could add further incentive to current initiatives aimed at reducing HACs. [ABSTRACT FROM AUTHOR]

Objective: To develop a tool to allow Australian hospitals to monitor the range of hospital-acquired diagnoses coded in routine data in support of quality improvement efforts., Design and Setting: Secondary analysis of abstracted inpatient records for all episodes in acute care hospitals in Victoria for the financial year 2005-06 (n=2.032 million) to develop a classification system for hospital-acquired diagnoses; each record contains up to 40 diagnosis fields coded with the ICD-10-AM (International Classification of Diseases, 10th revision, Australian modification)., Main Outcome Measure: The Classification of Hospital Acquired Diagnoses (CHADx) was developed by: analysing codes with a "complications" flag to identify high-volume code groups; assessing their salience through an iterative review by health information managers, patient safety researchers and clinicians; and developing principles to reduce double counting arising from coding standards., Results: The dataset included 126,940 inpatient episodes with any hospital-acquired diagnosis (complication rate, 6.25%). Records had a mean of three flagged diagnoses; including unflagged obstetric and neonatal codes, 514,371 diagnoses were available for analysis. Of these, 2.9% (14,898) were removed as comorbidities rather than complications, and another 118,640 were removed as redundant codes, leaving 380,833 diagnoses for grouping into CHADx classes. We used 4345 unique codes to characterise hospital-acquired conditions; in the final CHADx these were grouped into 144 detailed subclasses and 17 "roll-up" groups., Conclusions: Monitoring quality improvement requires timely hospital-onset data, regardless of causation or "preventability" of each complication. The CHADx uses routinely abstracted hospital diagnosis and condition-onset information about in-hospital complications. Use of this classification will allow hospitals to track monthly performance for any of the CHADx indicators, or to evaluate specific quality improvement projects.

Private health insurance subsidy is now estimated to cost $2.19 billion; government support for private health care includes a further $1.2 billion of Medicare benefits expenditure in hospitals. The subsidy cannot be justified on efficiency grounds, as, on the basis of available evidence and taking casemix into account, public hospitals are more efficient than private hospitals. The original stated objective of the subsidy was to "take pressure off public hospitals". If the insurance subsidy and the Medicare Benefit Schedule rebate expenditure were applied to purchasing public hospital treatment at full average cost, 58% of current private sector demand could be accommodated. If 10% of the demand were met at marginal cost, this would increase to 65%. The objective of "taking pressure off public hospitals" could be more efficiently achieved by direct funding of public hospitals rather than through subsidies for private health insurance.