A Case Study in Healthcare Quality Management: A Practical Methodology for Auditing Total Patient X-Ray Dose During a Diagnostic Procedure

The healthcare industry is adopting many of the best practices familiar to the manufacturing sector. For example the need for ISO 9000 registration is now seen as an important business driver, indeed, BSI offers specific advice for Healthcare organisations seeking to gain ISO 9001:2000 approval. Accompanying the integration of quality systems into the healthcare business is the need to find practical measures of quality that may be used as part of an overall process to deliver improved performance. The manufacturing industry has a rich array of techniques such as JIT (Just In Time), 6 Sigma, SPC (Statistical Process Control), TQM (Total Quality Management) which may all now be found cited in conjunction with the healthcare industry. This paper focuses on the legislatively driven need to locally audit and minimise the diagnostic X-ray dose received by patients during a Barium Enema procedure. This procedure was selected as it has been shown by other authors to have a reasonably narrow spread of total patient dose levels and therefore might be relatively easy to draw statistically significant inferences for management purposes. The Ionising Radiation (Medical Exposure) Regulations 2000 (IRMER) and Health Service Circular on Clinical Governance (HSC1999/065) state that Clinical Audit should be performed to identify and monitor the issues leading to quality improvement and best practice. This is a statement of requirement, which delegates the responsibility of implementation to the local level. The IRMER Regulation also require the setting of local Diagnostic Reference Levels (DRLs). These are levels of radiation dose for individual examinations which under normal circumstances should not be exceeded. Producing a meaningful audit and DRLs in small departments raises many issues: data availability and capture may be time consuming especially if records are kept on paper-based systems; analysis of the data may present a steep learning curve in statistical techniques; a high degree of statistical confidence in the results is required along with sensitivity in their presentation and dissemination to ensure that they become part of a process of continuous improvement (rather than part of a blame culture). This paper presents a practical approach to delivering a meaningful audit of locally collected data using readily available software tools (Excel Spreadsheet), in conjunction with a relatively simple numerical statistical analysis technique called ‘bootstrapping’. Bootstrapping enabled us to set the local DRL for this procedure with an estimate of statistical confidence. An analysis was performed on the data to determine factors contributing to total patient dose.