MP34-15: Prostate cancer quality of care disparities and their impact on patient outcomes

Prostate cancer quality of care disparities and their impact on patient outcomes

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INTRODUCTION

The ability to rigorously measure disparities in care that drive poor patient outcomes is essential for developing effective strategies for quality improvement. As real-world case-mix adjusted quality variations have yet to be reported in prostate cancer, our objective was to apply a data-driven analytical framework to determine the validity of expert-defined quality indicators (QIs) in order to reveal true disparities in prostate cancer care and their impact on patient outcomes.

METHODS

Hospital-level quality of care was assessed according to 10 published, expert-defined QIs utilizing data derived from the United States National Cancer Database (NCDB). Case-mix adjusted hospital benchmarking was performed using indirect standardization methodology and multivariable regression models as previously described by our group [1]. In a training set of hospitals, a composite measure of hospital quality, the Prostate Cancer Quality Score (PC-QS), was derived from those individual QIs that discriminated hospital performance in a manner associated with poor patient outcomes; including the need for salvage therapy, initiation of androgen deprivation therapy, 30- and 90-day mortality, and overall mortality. Subsequently, associations between the PC-QS and hospital volume, academic affiliation, and patient outcomes (as above) were determined in a separate validation set of hospitals.

RESULTS

Collectively, data from over 1100 hospitals were analyzed, with widespread variation observed across all QIs. In the training set, between 3-36% of hospitals were identified as poor outliers compared to the national average level of care for a given QI. Based on associations between outlier status and the aforementioned patient outcomes, 5 individual QIs were incorporated into the PC-QS. In the validation set, lower PC-QS hospitals displayed smaller referral volumes and were less likely to be academic hospitals than those with higher PC-QS (p < 0.001). Higher PC-QS was associated with lower rates of salvage therapy, ADT initiation and 30-day mortality (adjusted hazard ratio [confidence interval]: 0.85 [0.79-0.91], 0.94 [0.91-0.98], adjusted odds ratio 0.92 [0.87-0.97] per PC-QS unit increase, respectively).

CONCLUSION

Data-driven benchmarking of hospital-level quality performance reveals the widespread disparities that exist in prostate cancer care. This data supports the use of our novel PC-QS composite metric as a benchmarking tool for quality improvement. 1. Lawson KA et. al. Eur Urol 2017; 72: 379-386.

Funding: Princess Margaret Cancer Centre Foundation