Results of the IROCA international clinical audit in prostate cancer radiotherapy at six comprehensive cancer centres.

To assess adherence to standard clinical practice for the diagnosis and treatment of patients undergoing prostate cancer (PCa) radiotherapy in four European countries using clinical audits as part of the international IROCA project. Multi-institutional, retrospective cohort study of 240 randomly-selected patients treated for PCa (n = 40/centre) in the year 2015 at six European hospitals. Clinical indicators applicable to general and PCa-specific radiotherapy processes were evaluated. All data were obtained directly from medical records. The audits were performed in the year 2017. Adherence to clinical protocols and practices was satisfactory, but with substantial inter-centre variability in numerous variables, as follows: staging MRI (range 27.5-87.5% of cases); presentation to multidisciplinary tumour board (2.5-100%); time elapsed between initial visit to the radiation oncology department and treatment initiation (42-102.5 days); number of treatment interruptions ≥ 1 day (7.5-97.5%). The most common deviation from standard clinical practice was inconsistent data registration, mainly failure to report data related to diagnosis, treatment, and/or adverse events. This clinical audit detected substantial inter-centre variability in adherence to standard clinical practice, most notably inconsistent record keeping. These findings confirm the value of performing clinical audits to detect deviations from standard clinical practices and procedures.

Finding the match between healthcare worker and expert for optimal audit and feedback on antimicrobial resistance prevention measures.

BACKGROUND: The potentials of audit and feedback (AF) to improve healthcare are currently not exploited. To unlock the potentials of AF, this study focused on the process of making sense of audit data and translating data into actionable feedback by studying a specific AF-case: limiting antimicrobial resistance (AMR). This was done via audit and feedback of AMR prevention measures (APM) that are executed by healthcare workers (HCW) in their day-to-day contact with patients. This study's aim was to counterbalance the current predominantly top-down, expert-driven audit and feedback approach for APM, with needs and expectations of HCW. METHODS: Qualitative semi-structured interviews were held with sixteen HCW (i.e. physicians, residents and nurses) from high-risk AMR departments at a regional hospital in The Netherlands. Deductive coding was succeeded by open and axial coding to establish main codes, subcodes and variations within codes. RESULTS: HCW demand insights from audits into all facets of APM in their working routines (i.e. diagnostics, treatment and infection control), preferably in the form of simple and actionable feedback that invites interdisciplinary discussions, so that substantiated actions for improvement can be implemented. AF should not be seen as an isolated ad-hoc intervention, but as a recurrent, long-term, and organic improvement strategy that balances the primary aims of HCW (i.e. improving quality and safety of care for individual patients and HCW) and AMR-experts (i.e. reducing the burden of AMR). CONCLUSIONS: To unlock the learning and improvement potentials of audit and feedback, HCW' and AMR-experts' perspectives should be balanced throughout the whole AF-loop (incl. data collection, analysis, visualization, feedback and planning, implementing and monitoring actions). APM-AF should be flexible, so that both audit (incl. collecting and combining the right data in an efficient and transparent manner) and feedback (incl. persuasive and actionable feedback) can be tailored to the needs of various target groups. To balance HCW' and AMR-experts' perspectives a participatory holistic AF development approach is advocated.

Quantifying data quality for clinical trials using electronic data capture.

BACKGROUND: Historically, only partial assessments of data quality have been performed in clinical trials, for which the most common method of measuring database error rates has been to compare the case report form (CRF) to database entries and count discrepancies. Importantly, errors arising from medical record abstraction and transcription are rarely evaluated as part of such quality assessments. Electronic Data Capture (EDC) technology has had a further impact, as paper CRFs typically leveraged for quality measurement are not used in EDC processes. METHODS AND PRINCIPAL FINDINGS: The National Institute on Drug Abuse Treatment Clinical Trials Network has developed, implemented, and evaluated methodology for holistically assessing data quality on EDC trials. We characterize the average source-to-database error rate (14.3 errors per 10,000 fields) for the first year of use of the new evaluation method. This error rate was significantly lower than the average of published error rates for source-to-database audits, and was similar to CRF-to-database error rates reported in the published literature. We attribute this largely to an absence of medical record abstraction on the trials we examined, and to an outpatient setting characterized by less acute patient conditions. CONCLUSIONS: Historically, medical record abstraction is the most significant source of error by an order of magnitude, and should be measured and managed during the course of clinical trials. Source-to-database error rates are highly dependent on the amount of structured data collection in the clinical setting and on the complexity of the medical record, dependencies that should be considered when developing data quality benchmarks.