Kelley A. Foster

The role of quantitative feedback in coronary angiography radiation reduction

OBJECTIVE To evaluate the benefits of radiation education with and without feedback reporting in altering clinician radiation use behaviour in performing coronary angiography (CA). DESIGN A retrospective review of radiation use (fluoroscopy time) in coronary angiograms performed between July 1996 and December 2005 by 10 cardiologists to assess the impact of various interventions aimed at minimizing radiation risk. The impact of interventions such as education and audit/feedback was correlated against radiation use using cumulative sum and cumulative expected minus observed charts. SETTING Private Hospital in Brisbane, Australia. PARTICIPANTS Ten cardiologists. INTERVENTION Education and audit/feedback. RESULTS Baseline radiation use subject to standard guidelines was stable. Group performance charts show a modest transient improvement in radiation use associated with an education intervention alone. However, regular detailed personalized feedback comparing an individuals radiation use to group and external benchmarks was successful in achieving sustained reduction in overall radiation use. For individual participants, significant improvement was noted in 7 of 10 cardiologists. CONCLUSION Although an improved theoretical understanding of effective radiation hygiene strategies might contribute to reduced radiation use, this study suggests that regular detailed quantitative feedback supporting education is an effective tool in altering radiation use in CA. Understanding triggers that stimulate change in clinician behaviour is critical to the design of systems to optimize clinical performance. Confidentially reported benchmarking systems may be a useful tool to alter clinician behaviour.

Performance Monitoring in Cardiac Surgery: Application of Statistical Process Control to a Single-site Database

BACKGROUND Graphical Statistical Process Control (SPC) tools have been shown to promptly identify significant variations in clinical outcomes in a range of health care settings. We explored the application of these techniques to quantitatively inform the routine cardiac surgical (CAS) morbidity and mortality (M&M) review processes at a single site. METHODS Baseline clinical and procedural data relating to 5265 consecutive cardiac surgical procedures, performed at St Andrews War Memorial Hospital (SAWMH) between the 1st January 2003 and the 30th April 2012, were retrospectively evaluated. A range of appropriate clinical outcome indicators (COIs) were developed and evaluated using a combination of Cumulative Sum charts, Exponentially Weighted Moving Average charts and Funnel Plots. Charts were updated regularly and discussed at the cardiac surgery units bi-monthly M&M meetings. Risk adjustment (RA) for the COIs was developed and validated for incorporation into the charts to improve monitoring performance. RESULTS Discrete and aggregated measures, including blood product/reoperation, major acute post-procedural complications, cardiopulmonary bypass duration and Length of Stay/Readmission < 28 days have proved to be valuable measures for monitoring outcomes. Instances of variation in performance identified using the charts were examined thoroughly and could be related to changes in clinical practice (e.g. antifibrinolytic use) as well as differences in individual operator performance (in some instances, driven by case mix). CONCLUSIONS SPC tools can promptly detect meaningful changes in clinical outcome thereby allowing early intervention to address altered performance. Careful interpretation of charts for group and individual operators has proven helpful in detecting and differentiating systemic versus individual variation.

Data Quality Improvement in Clinical Databases Using Statistical Quality Control Review and Case Study

Ensuring the quality of data being collected in clinical and medical contexts is a concern for data managers and users. Quality assurance frameworks, systematic audits, and correction procedures have been proposed to enhance the accuracy and completeness of databases. Following an overview of the undertaken approaches, particularly statistical methods, the authors promote acceptance sampling plans (ASPs) and statistical process control (SPC) tools, including control charts and root cause analysis, as the technical core of the data quality improvement mechanism. They review ASP and SPC techniques and discuss their implementation in data quality evaluation and improvement. Two case studies are presented in which the authors apply some of the techniques to databases maintained by a local hospital. Finally, guidelines are proposed for which techniques are appropriate with regard to dataflow and database specifications.

Risk Modelling in Quality Clinical Registries: Monitoring Lesion Treatment Failure Rate in Percutaneous Coronary Interventions

AIMS This paper describes the development of a risk adjustment (RA) model predictive of individual lesion treatment failure in percutaneous coronary interventions (PCI) for use in a quality monitoring and improvement program. METHODS AND RESULTS Prospectively collected data for 3972 consecutive revascularisation procedures (5601 lesions) performed between January 2003 and September 2011 were studied. Data on procedures to September 2009 (n=3100) were used to identify factors predictive of lesion treatment failure. Factors identified included lesion risk class (p<0.001), occlusion type (p<0.001), patient age (p=0.001), vessel system (p<0.04), vessel diameter (p<0.001), unstable angina (p=0.003) and presence of major cardiac risk factors (p=0.01). A Bayesian RA model was built using these factors with predictive performance of the model tested on the remaining procedures (area under the receiver operating curve: 0.765, Hosmer-Lemeshow p value: 0.11). Cumulative sum, exponentially weighted moving average and funnel plots were constructed using the RA model and subjectively evaluated. CONCLUSION A RA model was developed and applied to SPC monitoring for lesion failure in a PCI database. If linked to appropriate quality improvement governance response protocols, SPC using this RA tool might improve quality control and risk management by identifying variation in performance based on a comparison of observed and expected outcomes.