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Data quality policy

Contents

1 Introduction

Rotherham, Doncaster and South Humber NHS Foundation Trust recognise the importance of reliable information as a fundamental requirement for the delivery of effective treatment for patients. The availability of complete and up-to-date information is essential to ensuring patients receive effective ongoing care. Data quality underpins clinical, research and information governance, management, planning and accountability for service level agreements.

Poor data quality can lead to financial implications and time inefficiencies within the trust. In worse cases, poor data quality can have a detrimental clinical impact.

Data quality is also important for legal reasons. The Data Protection Act (2018) (opens in new window) provides a legal obligation for organisations to ensure that personal information is accurate, complete, and up-to-date and applies to both electronic and paper records.

This policy ensures a positive impact on equality and diversity due to robust data collection principles, as reliable information is vital in supporting the trust to achieve its goals.

2 Purpose

The purpose of this policy is to set out the trust’s data quality principles to ensure processes conform to NHS data standards. These principles will be adopted and supported by data quality procedures.

3 Scope

The focus of this policy is all data entered and reported from the trust electronic patient record. However, there is an expectation that all other trust adopted information systems and business information, for example, financial and personnel records, should follow as a minimum the principles of “CARAT” which states data should be:

  • complete
  • accessible
  • relevant
  • accurate
  • timely

4 Responsibilities, accountabilities and duties

All employees are accountable for the safe management and accuracy of data collected for both patients and staff as outlined in:

4.1 Information governance and management framework

Data quality is an element of the broader information governance remit.

The trust works in accordance with the information governance policy and management framework.

The trust promotes data quality using its governance structure, policies and procedures and associated statutory professional requirements to ensure that wherever possible, information quality will be assured at the point of collection.

Roles and responsibilities for information governance and data management are available within information governance policy and management framework.

4.2 Care groups

The trust has five care groups for the delivery of operational services:

  • Doncaster adult mental health and learning disabilities care group
  • Doncaster physical health and neurodiversity care group
  • Rotherham care group
  • North Lincolnshire and talking therapies care group
  • Children’s care group

Care groups are responsible for:

  • timely, complete, and accurate data entry
  • providing clear specifications and engaging in system and reporting developments including agreeing signoff of the final product

Care groups should also promote and support the use of SystmOne superusers to further embed good data quality across the electronic patient record (EPR). Further information on superusers (staff access only) (opens in new window).

Each care group will provide representation at the trust’s data quality and process improvement group (DQPIG).

4.3 Corporate responsibility

The trust has a responsibility to ensure that systems are configured to collect data according to agreed standards and to undertake maintenance at system level. The trust also has a responsibility to provide a framework of policies and procedures designed to promote data quality. It will monitor and audit data quality and publish this information to relevant staff and managers to action and provide training where appropriate.

The director of health informatics will oversee development and implementation of data quality policies and promote a data quality culture in relation to data entered in the electronic patient record (EPR) and, or managed through the trust’s data warehouse and business intelligence reporting solutions; supported by the wider health informatics portfolio, predominantly by the information management and business intelligence (IMBI) and Information quality (IQ) teams.

Other trust executives have a responsibility to ensure that their services adhere to the CARAT principles when dealing with data.

4.4 Clinical Systems team

The trust’s clinical systems team have the responsibility for system configuration, testing, training, and end user support of the electronic patient record (EPR) systems. This supports data quality in the following areas:

4.4.1 Configuration

Ensure that the system is configured to trust ‘rules and standards’, and promotes accurate record keeping and data quality through system and process best practice principles.

4.4.2 Testing

Ensure that prior to releasing any system configuration changes, these are appropriately tested. This includes peer review, clinical assurance, and user acceptance testing (UAT).

4.4.3 Training

Ensure that training is offered in a timely fashion, and covers all aspects of functionality used in the electronic patient record systems. As well as undertaking an appropriate assessment of competency.

4.4.4 End user support

Ensure that requests for support on the electronic patient record systems are responded to in a timely manner, providing accurate information or resolution that are in line with data quality principles.

If data quality issues are highlighted in any of the above work streams, these are to be escalated to the data quality and process improvement group for review and action.

4.5 Clinical and research governance

Clinical governance ensures NHS organisations are accountable for continuously improving the quality of their services and safeguarding high standards of care. It is also a collective term for the quality of various component activities that aim to improve the experience of patients, carers and the public. These include:

  • patient, carer, and public involvement
  • risk management
  • clinical audit
  • research and clinical effectiveness
  • staffing and staff management
  • education and continuous personal and professional development
  • use of information to support clinical governance

Research governance is a framework that aims to ensure research is of high quality, safe, and meets agreed scientific and ethical standards. Both clinical and research governance are dependent on high quality information to be effective and continuously improve the quality-of-service provision. See research governance policy.

4.6 Business and performance management

Accurate patient-based data is essential for both internal and external management of the trust’s activities. It is important for the effective running of the trust’s services to have accurate information about both the volume and quality of services that are provided. In addition to supporting the day to day running of the trust, such information is essential in the development of new services.

The trust requires accurate information to monitor and manage legally binding contracts with commissioners and partner organisations.

4.7 National requirements

The trust adheres and reports against several national standards. The trust applies a standard assurance framework (see appendix A) for all National submissions, using an appropriate level of validation required for each measure dependent on criticality, risk, impact, and relevance. Reporting requirements are reviewed and amended in line with relevant guidance.

4.8 Audit

The trust is regularly audited to ensure that:

  • there is compliance with NHS and trust policies and standards
  • to ensure data is complete, accessible, relevant, and accurate, and entered in a timely way (CARAT)

5 Procedure or implementation

5.1 Data standards

The NHS data model and dictionary (opens in new window) gives common definitions and guidance to support the sharing, exchange, and comparison of information across the NHS. The common definitions, known as data standards, make up the base currency of commissioning data sets.

NHS data standards are presented as a logical data model, ensuring that the standards are consistent and integrated across all NHS business areas. Changes to the content of the NHS data dictionary are published by the standardisation committee for care information (SCCI).

The use of data standards within systems can greatly improve data quality. These can be incorporated into systems either using electronic validation programmes, which are conformant with NHS standards, for example, drop down menus, or manually generated lists for services that do not yet have computer facilities. Either method requires the list to be generated from nationally or locally agreed standards and definitions, for example, for GP practice codes, ethnicity. These must be controlled, maintained, and updated in accordance with any changes that may occur, and in addition electronic validation programmes must not be switched off or overridden by operational staff.

The NHS communicates key changes to data standards, and deadlines affecting changes are made through information standard notifications (ISNs).

IAOs are responsible for gaining assurance that information systems are updated in accordance with new ISNs to ensure systems conform to all requirements.

From a commissioning perspective, all new developments or changes to existing reporting must be agreed by the relevant care groups and performance team.

In certain situations, there will be no applicable NHS national standards. In these instances, the trust will agree local standards and definitions as part of the contracting and service definition process. It is important that any local standards are subject to annual reviews, as there will be no automatic input received from national sources. This process will ensure their validity and continued relevance. The IMBI role is to update reporting in line with new and existing contracts as guided by contracts, performance, and operational services.

The trust use national clinical coding standards, consisting of ICD, OPCS and SNOMED CT:

  • ICD is the international classification of diseases and is used for coding diagnosis in our inpatient services
  • OPCS classification of interventions and procedures is used for coding clinical procedures that take place throughout the trust
  • SNOMED CT, systematised nomenclature of medicine clinical terms is used throughout our electronic patient record system for clinical data entry in a variety of formats (for example, data entry templates, questionnaires, alert indicators). SNOMED CT is a structured clinical vocabulary used in electronic health records and is the national standard for all NHS healthcare providers in England

The trust also maintains and reports on national data sets and submission data aligned to annual commitments, ISN notifications, data quality feedback reports and data quality maturity index.

The trust will promote and improve data quality standards by working with services to assess the quality of their clinical data and identify areas for improvement.

5.2 Data storage

It should be noted that all collection, storage, processing, and reporting of personal information is governed by detailed legal requirements under the Data Protection Act (2018). Staff should refer to data security and protection breaches or information governance incident reporting policy for further guidance.

5.3 Measurement of good data quality

As a trust we apply and promote the following data quality principles:

5.3.1 Timeliness

This is the time taken between the end of the data period and when the information can be produced and reviewed. The acceptable data lag will be different for different performance indicators. Data should be captured as quickly as possible after the event or activity and must be available for the intended use within a reasonable time. Data must be available quickly and frequently enough to support information needs and to influence the appropriate level of service or management decisions.

5.3.2 Monitoring (granularity)

This is the degree to which the trust can drill down into data to review and understand operational performance. The level to which the trust needs to drill down into the data will vary for different performance indicators. Some information should always be available at patient level for performance monitoring purposes. Whereas some information may be sufficient if it is available at speciality level for all specialties or even trust level for performance monitoring purposes.

5.3.3 Completeness

There are two aspects to completeness. This is the extent to which all the expected attributes of the data are populated but also the extent to which all the records for the relevant population are provided.

5.3.4 Validation

This is the extent to which the data has been validated to ensure it is accurate and in compliance with relevant requirements. For example, correct application of rules and definitions. The level of validation required will vary from indicator-to-indicator and will depend on the level of data quality risk. Final validation is classified as sufficient where validation has been completed and where the indicator has received final approval from responsible individuals.

5.3.5 Audit

This is the extent to which the integrity of data (completeness, accuracy, validity, reliability, relevance, and timeliness) has been audited by someone independent of the KPI owner (for example, internal audit, external audit, clinical audit or peer review) and the extent to which the assurance provided from the audit is positive.

5.3.6 Reliability

This is the extent to which the data is generated by a computerised system, with automated information technology (IT) controls, or a manual process. It also relates to the degree of documentation outlining the data flow, for example, documented process with controls and data flows mapped. Data should reflect stable and consistent data collection processes across collection points and over time, whether using manual or computer-based systems or a combination. Managers and stakeholders should be confident that progress toward performance targets reflects real changes rather than variations in data collection approaches or methods.

5.3.7 Relevance

This is the extent to which the data is captured for the purposes for which it is used. This entails periodic review of the selection of key performance indicators to reflect changing needs, such as new strategic objectives. For example, is this indicator the right indicator by which to measure performance against a strategic objective?

5.3.8 Breach

This is the extent to which the data being recorded and validated is seen to cause a significant breach in guideline implementation.

5.4 Validation and quality assurance

The trust routinely process, manage, and monitor information from its services. This information is used to monitor service performance, contractual and national commitments and contributes to service planning and continuous improvement.

Sufficient and appropriate checks are made by the performance team to ensure that the information received is accurate and complete. Where data falls outside anticipated ranges, a more detailed evaluation and validation is undertaken with assistance from appropriate technical and business parties.

Regular checks and validation are completed using data quality reporting and exception management. It is expected that care groups use the suite of data quality (DQ) reports to manage their service and data on a day-to-day basis, correcting data quality issues as they arise ensuring that their data is as accurate and as up-to-date as it can possibly be.

Validation rules and routines are implemented into processes and systems where possible, supported by regular user training and guidance on the importance of correct, accurate and timely data recording. This includes the use of automated validation, dashboards, and alerts.

On submission of data returns, the trust ensures appropriate governance, validation and assurance is completed with IAO’s.

The trust will endeavour to ensure that timescales for submission of information are adhered to, and that the quality and accuracy of such submissions is of the highest standard. Internal deadlines for the completion of data sets, to ensure national timescales are achieved, will be explicit and monitored.

The trust conducts regular monthly meetings to facilitate the sharing, scrutiny, and challenge of information, providing an opportunity to raise data quality concerns and agree prioritisation for investigation and corrective action. These meetings include but are not limited to:

  • quality assurance (care group level)
  • data quality and Process improvement group (DQPIG)
  • finance performance and informatics committee (FPIC)
  • operations and health informatics programs
  • board of directors

Feedback from external submissions also assists in the identification and communication of data quality assurance.

5.5 Health informatics spot checks

The health informatics team complete monthly spot checks on a selection of high-profile performance indictors to ensure that:

  • reporting tools are fit for purpose and accurately display performance
  • clinicians are adhering to trust policy and SystmOne guidance when recording patient activity
  • reported activity data is aligned to national guidance

A data collection tool is devised for each performance indicator that is to be reviewed as part of the spot check and is explicit in the requirements of each data point that is being checked, for example, referral date, discharge date, date patient was assessed. The check is undertaken via manual interrogation of a patient’s electronic clinical record to ensure the patient’s journey matches to the activity that has been reported.  Where clinical interpretation of guidance is required, advice will be sought from the most relevant clinical area.

Once results have been evaluated, findings will be shared with operational services and the FPIC. All known errors in the clinical record will be corrected in accordance with trust policy. The owner of the data errors will be agreed on a case-by-case basis and be expected to support corrections.

For each indicator that has been reviewed under this process, an assessment is undertaken to identify the level of compliance against each of the seven principles of data quality and a kite-mark applied (see appendix B).

5.6 Data quality incidents

Careful monitoring and error correction supports good data quality; however, it is more effective and efficient for data to be entered correctly in the first instance, therefore the trust delivers a robust EPR training package to all staff with access.

When data quality errors occur or are identified, they should be reported immediately using the trust’s incident reporting system and corrective action commenced. No level of inaccuracy should be viewed as acceptable after it is identified.

Data quality reports are available to help staff identify data quality issues within the EPR and national data sets.

To facilitate an understanding of data requirements and usage, clinical system (staff access only) (opens in new window) and BI reporting guides are available.

5.7 Audit

The trust has 3 main audit work streams. Clinical, internal and external.

The trusts clinical audit team undertake a suite of annual audits. Further information regarding clinical audit work programme (staff access only) (opens in new window).

360 assurance audits provide ad-hoc data quality reviews as instructed by the trust.

External audits provide assurance to the trust annual quality accounts.

The scope of audit should be pre-determined based upon identified need prior to the audit commencing.

Audit findings are used to:

  • inform management
  • improve patient processes
  • ensure reporting is in line with national guidance
  • ensure targeted training and support
  • enhance documentation
  • enable more complete and accurate data capture

5.8 Monitoring

A suite of data quality reports are available on the trust’s BI reporting solution called RePortal. These reports refresh daily and can be filtered to show data quality for individual teams.

Some trust physical health services utilise ‘front end’ reporting direct from SystmOne.

It is the responsibility of operational staff to access these reports frequently and utilise the information to improve data quality.

Trust performance reporting provides regular overall monitoring as part of contractual and performance commitments, raising and managing reporting exceptions to assure data correctness and reliability. All reporting anomalies must be raised and managed through internal processes and escalated according to risk and criticality. This is done via the care group assurance meetings.

Critical and mandatory data areas will be continuously monitored to ensure compliance and improvement towards trust, CCG and national targets.

All critical data quality issues are reported through the trust incident system, and escalated through:

  • care group quality assurance meeting
  • data quality and process improvement group
  • operational management meeting
  • Executive Management team

Where data quality concerns are raised, they must be logged with the appropriate owning service. Issues will be resolved swiftly and managed at a low level via appropriate meeting actions logs, however other more significant issues will require a more coordinated approach. Where there is a risk to the trust these must be logged on the trust risk register accompanied by a supporting action plan. Identified owners from clinical and corporate teams will work through the action plan recording progress and providing updates to the governing group.

5.9 Training

The trust operates a single EPR, SystmOne. EPR training (staff access only) (opens in new window) is mandatory for all new starters and an extensive suite of system guidance (staff access only) (opens in new window) exists to assist  staff in capturing all the relevant data required to meet national, regional, and local reporting requirements and are developed and updated as required.

Individual departments who operate other data capture and reporting systems are responsible for providing training for those systems. For example, services that utilise dictation software must follow its support guides and liaise with the IT department to ensure accurate record keeping is maintained.

5.10 Financial requirements

A service provided by the trust will be under a service level agreement (a written contract with commissioners) based upon the persons registered GP or their normal place of residence (for persons not registered with a GP).  Outside these contractual arrangements, referrals that have been accepted and treated will be under non-contract activity processes.

To provide accurate information to commissioners, other trusts, and partner organisations and facilitate appropriate financial flows, it is essential to record the following demographic information to assist in identifying the responsible commissioner for a patient:

  • home address (including postcode)
  • registered GP

Upon receipt of this information from the patient, it should be possible to ascertain if they are an overseas visitor or from out of area.

If a patient is from overseas, the trust is obliged to record this along with any charging exemptions which may apply to the patient within the electronic patient record (this will be shown under the chargeable status tab on their summary).

If the patient is from out of area, and presents for non-emergency treatment, the commissioning organisation in most cases will need to give authority prior to treatment being delivered.

If the patient requires emergency care, treatment should be given as normal, however it is best practice to provide notification to the commissioning organisation responsible for paying for the patient’s treatment.

Failure to adhere to this practice could result in financial loss to the trust.

Further information on determining responsibility for payments to providers can be found within the published NHS England ‘Who Pays?’ guidance.

5.11 Currency

Adult and older people mental health services covered by the care cluster currency (a basis for payment) must record and submit cluster data as part of the mental health (MHSDS) and IAPT datasets, whether they have used the care clusters as the basis of payment or not. This should be completed in line with the mental health clustering tool and mental health clustering booklet, to assign a care cluster classification to patients.

6 Training implications

A detailed training analysis is not required for this policy.

Training on the clinical information system is mandated prior to staff being given access via a smart card and allocated with a login and password for the system.

IT skills assessment and training if required must be undertaken prior to training being delivered for the clinical information system. Staff must also be compliant with information governance training.

In addition to system training provided by the clinical systems team, staff will have access to additional support from the clinical systems team when requested through the IT service desk.

When new functionality is developed and published in the clinical information system, awareness workshops will be provided in all geographical areas to raise awareness of the changes, if required. If additional support and training is required, a training package will be developed.

Where error problems appear recurrent, training programmes and supporting guidance will be reviewed to provide assurance that these potential problem areas are given focus at initial training and in ongoing support meetings.

As a trust policy, all staff need to be aware of the key points that the policy covers. Staff can be made aware through a variety of means such as:

  • ‘all user’ emails for urgent messages
  • continuous professional development sessions
  • daily email (sent Monday to Friday)
  • group supervision
  • intranet
  • local induction
  • one to one meetings or supervision
  • posters
  • practice development days
  • special meetings
  • team meetings

The training needs analysis (TNA) for this policy can be found in the training needs analysis document which is part of the trust’s mandatory risk management training policy located under policy section of the trust website.

7 Monitoring arrangements

7.1 Data quality and report validation

  • How: Information quality work programme aligned to the trust’s operational service performance indicators.
  • Who: Head of information quality.
  • Reported to: Finance, performance and informatics committee.
  • Frequency: Bimonthly.

8 Equality impact assessment screening

To access the equality impact assessment for this policy, please email rdash.equalityanddiversity@nhs.net to request the document.

8.1 Privacy, dignity and respect

The NHS Constitution states that all patients should feel that their privacy and dignity are respected while they are in hospital. High Quality Care for All (2008), Lord Darzi’s review of the NHS, identifies the need to organise care around the individual, “not just clinically but in terms of dignity and respect”.

As a consequence the trust is required to articulate its intent to deliver care with privacy and dignity that treats all service users with respect. Therefore, all procedural documents will be considered, if relevant, to reflect the requirement to treat everyone with privacy, dignity and respect, (when appropriate this should also include how same sex accommodation is provided).

8.1.1 How will this be met

No issues have been identified in relation to this policy.

8.2 Mental Capacity Act (2005)

Central to any aspect of care delivered to adults and young people aged 16 years or over will be the consideration of the individuals’ capacity to participate in the decision-making process. Consequently, no intervention should be carried out without either the individual’s informed consent, or the powers included in a legal framework, or by order of the Court. Therefore, the trust is required to make sure that all staff working with individuals who use our service are familiar with the provisions within the Mental Capacity Act (2005). For this reason all procedural documents will be considered, if relevant to reflect the provisions of the Mental Capacity Act (2005) to ensure that the rights of individual are protected and they are supported to make their own decisions where possible and that any decisions made on their behalf when they lack capacity are made in their best interests and least restrictive of their rights and freedoms.

8.2.1 How will this be met

All individuals involved in the implementation of this policy should do so in accordance with the principles of the Mental Capacity Act (2005).

The completed equality impact assessment for this policy has been published on this policy’s webpage on the trust policy website.

10 References

NHS England Commissioning for Quality and Innovation (CQUIN) (opens in new window)

Information Commissioner’s Office. Freedom of Information or Data protection (opens in new window)

Data Security and Protection Toolkit NHS Digital (opens in new window)

NHS Data Model and Dictionary (opens in new window)

NHS Digital Mental Health Services Data Set (opens in new window)

11 Appendices

11.1 Appendix A Submission assurance framework

11.2 Appendix B Kite-marking


Document control

  • Version: 8.1.
  • Unique reference number: 286.
  • Ratified by: Corporate policy approval group.
  • Date ratified: 25 January 2024.
  • Name of originator or author: Data quality policy.
  • Name of responsible committee or individual: Director of health informatics.
  • Date issued: 25 January 2024.
  • Review date: May 2025.
  • Target audience: Operational management, clinical, medical and administrative support staff and all trust staff who are responsible for the collection and storage of data and information.

Page last reviewed: January 17, 2025
Next review due: January 17, 2026

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