Data Quality Strategy

Transcription

1 Data Quality Strategy

2 Foreword We are excited to launch the new Data Quality Strategy. It comes at a crucial time for the Trust, as we embark on the next phase of the Culture and Leadership programme. The best quality data can be one of the fundamental pillars of the continuous quality improvement environment all staff are working on to create. Data quality can by a dry and uninspiring topic, but not here. We need to imagine a future state where narratives from patients, families, carers and staff are transformed into intelligence and knowledge. We need to use technology that is already available to help us achieve this. We need to free up our staff to enable them to provide more great care. We need electronic interfaces to ease access to services, and to provide more opportunities for feedback. We need to help develop a culture where data quality is a valued commodity. If great data quality is seamless and unseen there is much to do, and that should not daunt us. Think about how our non-nhs lives have been transformed by digital technology, from banking, shopping, and booking holidays, to the connecting and sharing provided by social media sites. These work through having both fantastic kit, and cutting edge software, though it is the people that make the biggest difference. How we translate our daily activities into meaningful information is one of the biggest challenges in the NHS, this data quality strategy is not a solution on its own, but will help guide the Trust forward to this new future. The critical issue is how the strategy is implemented through smart objectives and actions, and more fundamentally how we engage with all staff to realise this ambition. Dr John Brewin, Chief Executive Officer 2

3 Introduction This strategy aims to provide an overarching framework to ensure that the Trust operates with high quality data in order to achieve its clinical and quality priorities. Good quality data delivers Improved services and more effective decisions regarding patient care Informed strategic development Improved local and national benchmarking Accurate payment Compliance with legal requirements A stimulus for research and innovation Poor quality data leads to Poor service delivery and potential patient harm Financial loss Poor use of finite resources Ineffective management of performance Lack of stakeholder trust in our services The characteristics of Data Quality are clearly identified by the Audit Commission. Accuracy Data should be sufficiently accurate for the intended use and should be captured only once Validity Data should be recorded and used in compliance with relevant requirement Reliability Data should reflect stable and consistent data collection processes Timeliness Data should be captured as quickly as possible after the event or activity Relevance Data captured should be relevant to the purposes for which it is to be used Completeness Data requirements should be clearly specified based on the information needs of the organisation 3

4 Where Are We Now? Our known Issues There is a lack of automation in many of our reports- and manual intervention leads to errors There is a proliferation of reporting systems rather than one version of the truth Data quality has been viewed as an outcome rather than a process Our main block contract has inhibited improvements to data quality There is no process of kite marking to evidence quality assurance on our data There is a lack of shared understanding of the language used to describe performance Previous efforts to improve data quality have been unsustainable using fixed term resource to trouble shoot as opposed to fixing the root causes of data quality Causes of poor data quality There are a number of consistent drivers of poor quality of data across all sectors and data sets Equipment that is cumbersome and does not easily lend itself to data input Patient not willing to engage or divulge data Processes where there are gaps or too many local variations Staff lack of technical training or not following agreed procedure Culture whereby data quality is not seen as the responsibility of every member of staff Our Strategic Priorities will address these factors in order to achieve our 2022 Data Quality Vision. 4

5 Our 2022 Data Quality Vision Vision: Our Data will be a valuable asset to our services and patients Mission: To provide staff and patients with information that is easy to understand, has integrity, adds value to the user, and supports the delivery of our Strategic and Quality priorities. Strategic Priorities to Achieve Our Vision: Single Source of the Truth A Business Intelligence tool will be the primary source for operational, performance management and income reporting. Automation Automate the current processes of information provision in order to improve accuracy and use resources more effectively. Kite Marking Develop a visual indicator backed up by an assurance process that makes an explicit assessment of our data quality. Data Stewardship All staff will understand that data quality is an organisational priority. Through training and development they will understand how their actions directly affect the validity of data and the potential to use data to promote better patient outcomes. Simple Empower staff with simplified data collection and validation processes, reducing the need for manual reconciliation. Business Rules Develop a shared understanding for all staff of the language used to describe our services and performance reporting. Sustainable All of our data quality improvement efforts will be linked to a central work plan and clear governance structure. 5

6 These Strategic Priorities map across to the Trusts overarching Strategic and Quality Priorities (See Appendix A), and will closely align to the Trusts Information Management and Technology Strategy. To ensure there is a focus on best practice, The Data Management Association (DAMA) DAMA-DMBOK2 Body of Knowledge Framework (DAMA International 2014) will be used as a reference point within the work programme. Data Quality Management DAMA-DMBOK2 Framework (DAMA International 2014) 6

7 How Will We Get There? Simple Data Quality Model High quality data is produced when all of the elements in the model above are working well together. The level of quality is determined by the capability or maturity of the system that produces it. Utilising DMAIC, a data-driven element of the Six Sigma Continuous Quality Improvement strategy we will expand our data quality capabilities. Define the problem Measure the performance. Analyse the process to determine root causes of variation, poor performance (defects). Improve process performance by addressing and eliminating the root causes. Control the improved process and future process performance. 7

8 Data quality enablers The Trusts data quality strategy focuses on the following 4 areas. Using the DMAIC model each area will be supported by a detailed annual work programme. Culture & Leadership Training Managing Performance Patient Level Costing System Benefits Realised The benefits that will be realised once the data quality vision has been achieved: Staff feel they have released time to care for patients Staff recognise and own Trust Information Staff feel empowered with data to improve service pathways and performance Stakeholder confidence is high in data quality Meaningful Internal and External Benchmarks are used to improve services Income is maximised Patient Level Income & Costing System is in place and used to manage unwarranted variation 8

9 Ownership and Governance Executive Lead and Governance The Director of Finance & Information will have overall responsibility for data quality and ensure that this Data Quality Strategy is promoted. Data Quality Assurance Group The Data Quality Assurance Group will feed directly into the Business Intelligence Group through the Finance and Performance Committee and up to the Board for governance assurance (Appendix B). Data quality monitoring reports and exception reports will be fed through the Data Quality Dashboard and to the Integrated Performance Board report. Data Owners Data Owners are generally senior people within the organisation who have signed up to be accountable for the quality of a defined dataset. This level of seniority means that they are unlikely to have the time to be involved in data quality activities on a day-to-day basis. For this reason they are likely to be supported by one or more Data Stewards. Data Stewards Data Stewards will be identified from departments within the Trust and will attend regular meetings where data quality issues will be addressed and action plans made for resolving issues. Data Stewards are responsible for the quality of a defined dataset on a day-to-day basis, taking a leadership role for data governance programs and data improvement initiatives, reporting progress to the Data Owner. Operational Procedures Data Stewards will ensure that the Data Quality Strategy is supported by operational procedures wherever data is collected, received, analysed or used. 9

10 Local Data Quality Monitoring Monitoring will be supported by data quality dashboards designed to enable local ownership of data quality. Staff Performance and Development Staff responsible for data collection will be required to adhere to standards regarding the accuracy and timeliness of data collection. Training The Trust has a responsibility to ensure that staff are aware of and appropriately trained to capture and understand relevant data. 10

11 Strategic Principles Improving Service Quality Using Resources more effectively Retaining And developing the business Data Quality Priorities Single source of Truth Simple Kite Mark Data Stewardship Automation Business rules Sustainable Appendix A Strategic Priorities P2 More people will have a positive experience of care and support P6 Support our people to be the best they can be P6 Support our people to be the best they can be P6 Support our people to be the best they can be P6 Support our people to be the best they can be P7 Maximise NHS resources P7 Maximise NHS resources Quality Priorities Q3 Improving services for people with mental health needs who present to A&E Q4 Ensure overall experience of patients/service users, carers and staff is positive and consistent across all Trust services Q5 Develop and implement a robust Quality Improvement methodology Q5 Develop and implement a robust Quality Improvement methodology Q3 Improving services for people with mental health needs who present to A&E Q5 Develop and implement a robust Quality Improvement methodology Q5 Develop and implement a robust Quality Improvement methodology Q5 Develop and implement a robust Quality Improvement methodology 11

12 Appendix B- Governance Structure Diagram 12

13 Trust Headquarters St George s Long Leys Road Lincoln LN1 1FS Single Point of Access Tel: facebook.com/lpftnhs Twitter.com/LPFTNHS 13