Part of Data quality assurance framework for providers part 1
People
Roles and responsibilities
Objective
To ensure that, where possible, dedicated roles are in place to assure and promote data quality and that responsibility for data quality is explicit within job descriptions and objectives for all staff involved in the capture of clinical and administrative data.
Benefits
Having in place clear roles and responsibilities attributed to data quality at all levels demonstrates the importance that data quality plays in the delivery of high-quality patient care, clinical and operational decision making and providing assurance and confidence in the performance of the organisation. Setting measurable data quality objectives for staff linked to the organisation’s internal metrics (see Part 2 of the framework) supports performance review and continuous improvement.
Best practice
All clinical and administrative staff should have clearly defined data quality related responsibilities in their job descriptions and corresponding personal objectives as part of the organisation’s Performance & Development Review process. All responsibilities and objectives should be aligned to the organisation’s Data Quality Policy as set by the Data Quality Group (see Part 2 of the framework). Experience and knowledge of data quality practices should be listed as essential criteria within all advertised vacancies. Where critical to the role, these should be evidenced at interview as part of the recruitment and selection process for all clinical and administrative staff directly involved in the health data capture and upkeep.
Case study
Great Ormond Street Hospital launched their ‘smart working lab’ in 2018 with a research platform named DriVE, being an integral part of this. This was only made possible by working clinicians and the data teams who helped to optimise the toolset including the writing of data quality rules and their implementation. Success continues as data quality is seen as a core business requirement with staff roles being valued and defined around this. “We need the right people to link everything together especially when it comes to data and quality. But the model must work with other organisations as well where different cultures exist. We can solve the infrastructure easily, but the people thing is what drives success”
Last edited: 6 March 2025 3:06 pm