Service Performance Monitoring in Thoracic Surgery: Application of Statistical Process Control to a State-Wide...

Statistical Process Control methods have proven effective in enhancing outcomes monitoring and improvement within various clinical domains. This study investigates their application in supporting thoracic surgical quality assurance processes across public hospitals in Queensland, Australia.

Retrospective evaluation of clinical data from thoracic surgeries performed at five public hospitals between January 1, 2019, and June 30, 2023, was conducted. Performance benchmarks were developed and assessed. Exponentially Weighted Moving Average charts and Funnel Plots were utilised for analysis and reporting. To account for common cause variation, Risk Adjustment models were developed and incorporated into the monitoring process.

Outcome indicators of service quality throughout patient care were examined. Clinical outcome indicators identified as being suitable quality markers included: Death within 90 days, Major Acute Morbidity, Return to Theatre, Length of Stay, Readmission within 30 days and Tumour/Node/Metastasis (TNM) Up/Down Staging. SPC tools revealed patterns of variation over time and between sites, prompting investigation into contributing factors and opportunities for quality improvement projects. While the primary goal is to efficiently and effectively identify instances of underperformance, a structured approach to signal investigation can be used to initiate quality improvement projects when sustained performance is identified that is better than expected.

SPC tools effectively facilitate clinical performance monitoring, aiding in timely detection and intervention in instances of altered performance. Careful interpretation of performance charts assists in identifying both declines and positive experiences, fostering continuous learning and improvement.