Graphical Association Analysis for Identifying Variation in Provider Claims for Joint Replacement Surgery.

Identifying potentially fraudulent or wasteful medical insurance claims can be difficult due to the large amounts of data and human effort involved. We applied unsupervised machine learning to construct interpretable models which rank variations in medical provider claiming behaviour in the domain of unilateral joint replacement surgery, using data from the Australian Medicare Benefits Schedule. For each of three surgical procedures reference models of claims for each procedure were constructed and compared analytically to models of individual provider claims. Providers were ranked using a score based on fees for typical claims made in addition to those in the reference model. Evaluation of the results indicated that the top-ranked providers were likely to be unusual in their claiming patterns, with typical claims from outlying providers adding up to 192% to the cost of a procedure. The method is efficient, generalizable to other procedures and, being interpretable, integrates well into existing workflows.

Mortality and readmission differences associated with after-hours hospital admission: A population-based cohort study in Queensland Australia.

Background and Aims: Policy makers and health system managers are seeking evidence on the risks involved for patients associated with after-hours care. This study of approximately 1 million patients who were admitted to the 25 largest public hospitals in Queensland Australia sought to quantify mortality and readmission differences associated with after-hours hospital admission. Methods: Logistic regression was used to assess whether there were any differences in mortality and readmissions based on the time inpatients were admitted to hospital (after-hours versus within hours). Patient and staffing data, including the variation in physician and nursing staff numbers and seniority were included as explicit predictors within patient outcome models. Results: After adjusting for case-mix confounding, statistically significant higher mortality was observed for patients admitted on weekends via the hospital's emergency department compared to within hours. This finding of elevated mortality risk after-hours held true in sensitivity analyses which explored broader definitions of after-hours care: an "Extended" definition comprising a weekend extending into Friday night and early Monday morning; and a "Twilight" definition comprising weekends and weeknights.There were no significant differences in 30-day readmissions for emergency or elective patients admitted after-hours. Increased mortality risks for elective patients was found to be an evening/weekend effect rather than a day-of-week effect. Workforce metrics that played a role in observed outcome differences within hours/after-hours were more a time of day rather than day of week effect, i.e. staffing impacts differ more between day and night than the weekday versus weekend. Conclusion: Patients admitted after-hours have significantly higher mortality than patients admitted within hours. This study confirms an association between mortality differences and the time patients were admitted to hospital, and identifies characteristics of patients and staffing that affect those outcomes.

After-hours emergency department care: Does time or day of arrival affect survival?

OBJECTIVE: To determine whether after-hours presentation to EDs is associated with differences in 7-day and 30-day mortality. The influence of patient case-mix and workforce staffing differences are also explored. METHODS: We conducted a retrospective observational study of 3.7 million ED episodes across 30 public hospitals in Queensland, Australia during May 2013-September 2015 using routinely collected hospital data linked to hospital staffing data and the death registry. Episodes were categorised as within/after-hours using time of presentation. Staffing was derived from payroll records and explored by defining 11 staffing ratios. RESULTS: Weekend presentation was slightly more associated (7-day mortality odds ratio 1.05, 95% confidence interval [CI] 1.01-1.10) or no more associated (30-day mortality odds ratio 1.01, 95% CI 0.98-1.03) with death than weekday presentation. When weeknights are included in the 'after-hours' period, odds ratios are smaller, so that after-hours presentation is no more associated (7-day mortality odds ratio 1.03, 95% CI 0.99-1.08) or less associated (30-day mortality odds ratio 0.95, 95% CI 0.93-0.97) with death. No significant after-hours patient case-mix differences were observed between weekday and weekend presentations for 7-day mortality. In other combinations of outcome and after-hours definition, some differences (especially measures relating to severity of presenting condition) were found. Staffing ratios were not strongly associated with any within/after-hours differences in ED mortality. CONCLUSIONS: After-hours presentation on the weekend to an ED is associated with higher 7-day mortality even after controlling for case-mix.

The National Emergency Access Target (NEAT) and the 4-hour rule: time to review the target.

OBJECTIVE: We explored the relationship between the National Emergency Access Target (NEAT) compliance rate, defined as the proportion of patients admitted or discharged from emergency departments (EDs) within 4 hours of presentation, and the risk-adjusted in-hospital mortality of patients admitted to hospital acutely from EDs. DESIGN, SETTING AND PARTICIPANTS: Retrospective observational study of all de-identified episodes of care involving patients who presented acutely to the EDs of 59 Australian hospitals between 1 July 2010 and 30 June 2014. MAIN OUTCOME MEASURE: The relationship between the risk-adjusted mortality of inpatients admitted acutely from EDs (the emergency hospital standardised mortality ratio [eHSMR]: the ratio of the numbers of observed to expected deaths) and NEAT compliance rates for all presenting patients (total NEAT) and admitted patients (admitted NEAT). RESULTS: ED and inpatient data were aggregated for 12.5 million ED episodes of care and 11.6 million inpatient episodes of care. A highly significant (P < 0.001) linear, inverse relationship between eHSMR and each of total and admitted NEAT compliance rates was found; eHSMR declined to a nadir of 73 as total and admitted NEAT compliance rates rose to about 83% and 65% respectively. Sensitivity analyses found no confounding by the inclusion of palliative care and/or short-stay patients. CONCLUSION: As NEAT compliance rates increased, in-hospital mortality of emergency admissions declined, although this direct inverse relationship is lost once total and admitted NEAT compliance rates exceed certain levels. This inverse association between NEAT compliance rates and in-hospital mortality should be considered when formulating targets for access to emergency care.

Early discharge and its effect on ED length of stay and access block.

Effecting early discharge is a widely recommended strategy for improving patient flow in acute hospitals. This paper analyses the impact of inpatient discharge timing on Emergency Department (ED) flow parameters such as access block and length of stay, while comparing this to the effect on hospital occupancy, to arrive at an understanding of a 'whole of hospital' response to discharge timing. The impact of hospital size is also investigated. The analysis reveals that, on days when the discharge peak lags the peak in inpatient admissions, hospitals of all sizes exhibit increased levels of occupancy, inpatient and ED length of stay, and access block. The findings corroborate the efficacy of early discharge initiatives and 'whole of hospital' flow improvement initiatives for addressing overcrowding and efficiency issues in hospitals.