DATA QUALITY POLICY. Date effective from: 9 th September Review date: 9 th September Version number: 3.0

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1 DATA QUALITY POLICY Date effective from: 9 th September 2014 Review date: 9 th September 2016 Version number: 3.0 See Document Summary Sheet for full details Date effective from: 9 September 2014 Page 1 of 50

2 CONTENTS Document Summary Sheet 3 Document Amendment sheet 4 PART A Section Description Page 1 Executive summary 6 2 The content of the procedural document Flow chart of procedure Description of procedure/process Purpose of policy Scope Clinical and Administration systems in the Trust Nine key actions for good data quality Prevention Understanding data requirements Detection Monitoring Assurance Compliance Continual Cycle of Improvement Communication Information Governance 16 3 Duties and responsibilities 18 4 Training 21 5 Glossary of Definitions 22 6 Appendices relevant to the procedural document 26 A What is good data quality? 27 B Examples of how data quality can impact on care 29 C Escalation Policy 31 D Implications of the Policy for Users of the York CPD / IMHER System 37 PART B Section Description Page 7 Purpose of Document Policy statement Purpose of document 40 8 Identification of Stakeholders 40 9 References, Evidence Base Associated Documentation Equality Impact Assessment Plan for Dissemination and Implementation Standards/key performance indicators Monitoring Compliance with, & the Effectiveness of the Procedure 49 Date effective from: 9 September 2014 Page 2 of 50

3 DOCUMENT SUMMARY SHEET ALL sections of this form must be completed. Those marked with * will be used as search information on Staffnet. Document title*: Document Reference Number * Member of the Executive Team Responsible* (Title): Document author* (Name and title): Approved by (group): Data Quality Policy IG-0006 Director of Finance Geoffrey Porter Data Quality Improvement Manager Information Governance Group (IGG) Date approved: 20 th August 2014 Ratified by (group/board): Chief Finance Office & SIRO, Chief Information Officer, Caldicott Guardian Date ratified: 4 th September 2014 Review date: 9 th September 2016 Frequency of review: Responsible for the review: Target audience: (List, by title, the people this procedural document is essential for) Responsible for dissemination: At least every two years Geoffrey Porter Data Quality Improvement Manager All staff who collect and record data about service users on Trust systems and their managers. Staff who have responsibility for such systems and their use. Geoffrey Porter Data Quality Improvement Manager Date effective from: 9 September 2014 Page 3 of 50

4 DOCUMENT AMENDMENT SHEET Please record what changes you have made to the procedural document since the last version. This is a summary of changes to the document and is designed to show people exactly what has changed. The version number recorded below should correspond to the ratified version number shown on the Document Summary Sheet. Version Amendment Reason 0.1 Comments Data Quality Improvement Group - discussion 0.2 Revisions/formatting Information Governance Group - comments 0.3 Further Revisions Stakeholders for comment 0.4 Further Revisions Comments from IM&T Governance Committee 1.0 Document ratified 1.1 Updates and new Appendix D 1.2 Summary Sheet amended Implications for data quality of the merger with York, Selby and North Yorkshire (February 2012) To reflect Executive Team approval 2.0 Document ratified 2.1 Updated to current template, improved logical flow, addition of DQ escalation process and assimilation of York services into document. Regular review of document 3.0 Document ratified Date effective from: 9 September 2014 Page 4 of 50

5 PART A Date effective from: 9 September 2014 Page 5 of 50

6 1 EXECUTIVE SUMMARY Good data quality is important because of its impact on care and efficiency of patient administration. It helps to ensure that the Trust achieves its performance targets and secures its income as well as compliance with the law and Information Governance (IG) guidelines for good practice. This policy provides a framework for data quality assurance in the Trust. The aim is to make data quality and good practice implicit in all our systems and procedures so that data is recorded correctly and errors are prevented in the first instance right first time approach. The ethos of good data quality is to ensure that the interests of service users are put first i.e. Better Information, Better Care. This document is primarily written with reference to the use of the PARIS system but also applies to the other clinical systems in use in the Trust including CPD, IAPTUS and SystmOne where the principles and general approach remain valid for all users. The Trust will follow the Nine Actions for good data quality (see Section 2.6 to 2.15) 2 THE POLICY 2.1 Flow chart of policy Not appropriate for this Policy. 2.2 Description of the Policy This policy sets out the Trust s overall approach to Data Quality as stated in the Trust Strategy Improving Health, Improving Lives and in particular Strategic Objective 5 : we govern our Trust effectively and meet our regulatory requirements measure 4 Data Quality Improvement Plan. Good Data Quality underpins the Trust s vision of providing high quality mental health and learning disability services. Better Information, Better Care good data quality contributes to the care of the patient both directly and indirectly. 2.3 Purpose of Policy The key objective of this policy is to provide a framework to enable improvements in data quality in the Trust. This includes promoting a culture of continual improvement, informing staff of their roles and responsibilities concerning the collection and input of good quality data and to establish these standards in training programmes. The policy sets out how the Trust will ensure local and national data quality standards are complied with and that procedures and processes are consistent with them. The policy is an integral part of the Trust s approach to Information Governance and should be read in Date effective from: 9 September 2014 Page 6 of 50

7 conjunction with other related information governance policies (See Section 10 Associated Documentation ). 2.4 Scope The scope of this policy primarily covers the data quality standards applicable to the collection, processing and exchange of data relating to clinical service delivery. Detailed clinical case-notes, either hard-copy or electronic free-text, are not covered by this policy. The exception is clinical information collected in a codified form such as HoNOS scores. 2.5 Clinical and Administration Systems in the Trust PARIS is the Trust s main Clinical and Administration system which is used on all Leeds sites excepting the Leeds Addiction Unit which uses SystmOne. It is also planned that the system will be implemented in York and North Yorkshire replacing the CPD system in a phased way by 31 st March SystmOne is used for service users in the Leeds Addiction Unit. The system is NHS Spine compliant. Core Patient Database (CPD) is the Clinical and Administration system for the Trust s York and North Yorkshire service which is being phased out with the implementation of PARIS. IAPTUS (Improving Access to Psychological Therapies) system is used for recording the IAPT service in York. The system is NHS Spine compliant. Data Warehouse - all data from these systems except SystmOne is downloaded into the Trust s Data Warehouse for purposes of statutory data submissions and reporting. 2.6 Nine Key Actions for good data quality The following sections 2.7 to 2.15 detail the approach and actions required to ensure that our data is of a high standard. The Policy defines good data quality as data that is Complete, Accurate, Up to Date, Fit for Purpose and Relating to the Right Person. It details nine key actions required to achieve good data quality: 1. Prevention 2. Understanding data requirements 3. Detection* 4. Monitoring* 5. Assurance* 6. Compliance* 7. Continual Cycle of Improvement 8. Communication 9. Governance * There are four important strands in day-to-day data quality management i.e. Detection (2.9), Monitoring (2.10), Assurance (2.11) and Compliance (2.12). Date effective from: 9 September 2014 Page 7 of 50

8 2.7 Prevention The aim is to make data quality implicit by ensuring that Trust systems are properly configured to ensure that the systems are user friendly and to encourage accurate input of data thus preventing errors. Prevention also includes ensuring local working instructions are in place, standard codes are used, appropriate fields are made mandatory and by enabling the means to collect and input data System Requirements PARIS, CPD, IAPTUS and SystmOne are the Trust s clinical and patient administration systems. As such, all service user activity must be input into them and all current records be kept up to date. The functionality of the systems must be configured and used to the fullest extent, following the business processes NHS Spine compliance NHS Spine compliance of systems is a major advantage to ensure that the correct patient is selected; the NHS number is validated and duplicate records avoided. This important functionality is currently not available in PARIS, although this is planned in a future release Electronic Patient Record (EPR) PARIS, IAPTUS and SystmOne will become the Trust s EPR and already much clinical information is being stored on them. Details about service users stored electronically are just as much part of their record as paper records and so are equally important and will become even more so Approved Trust Systems All clinical and administrative records must be input into approved Trust systems. Tactical databases should only be set up in exceptional circumstances such as for research projects and then only for specific, timelimited purposes. These must be approved by the Information Governance Group and other appropriate Trust groups System Configuration and Business Processes The PARIS system will be configured, where possible, to ensure that the business processes are followed. In particular, that the system is configured to meet the Patient Care Pathway. The collection and input trigger points will be identified and referenced by the Business Process Maps User Defined Form (UDF) Developments in PARIS Date effective from: 9 September 2014 Page 8 of 50

9 All new UDFs produced by the PARIS Development Team will be quality controlled to assure standards concerning the accuracy of recording data Procedures and Local Working Instructions (LWI) A procedure for recording clinical activity and data on PARIS including controls to improve and maintain data quality has been agreed and is included in training. This gives best practice and guidance for the collection and input of accurate data. Additionally printed copies are available to staff at all Trust sites, on StaffNet and through the Help function on PARIS. This procedure will be periodically reviewed and updated in line with local and national standards, guidance and policies; and will comply with the requirements of the Information Governance Toolkit. Any Local Working Instructions (LWIs) will incorporate and reference this procedure Standard Codes and Code Change Requests Codes will comply with national and local standards. The Code Change Request procedure ensures that new codes requested are compliant to these standards and that there is compliance with any new Information Standards Notices (ISN). Any mappings required will be made in the Trust s Data Warehouse Mandatory Fields and New Code Sets Fields will be made mandatory where a data item must be collected in all circumstances. The need to make further fields mandatory is kept under review subject to the necessary criteria Crystal Registration Form This report automatically populates current demographic data onto the printed form allowing more efficient collection of data. This is particularly useful for clinicians visiting a service user in their own home. It should be routinely used and be incorporated into local working instructions. The form is an important tool in improving the quality of data collection allowing details to be confirmed with a service user. The report has been developed to work in conjunction with the extension of more mandatory fields and the Quick Data Entry Form (QDE) in PARIS Quick Data Entry Form (QDE) in PARIS The QDE will become the new User Interface to update demographic details in the PARIS Central Index for use by clinicians for subsequent attendances. This form has the advantage of displaying all patient demographic data on one screen. 2.8 Understanding Data Requirements Date effective from: 9 September 2014 Page 9 of 50

10 This section concerns the awareness of staff in the Trust of issues that affect the accuracy of data in Trust systems. This also includes the configuration of systems and data standards to ensure that good quality is implicit Training (see also Section 4 below) Staff will be provided with training appropriate to their needs on how to use the appropriate Trust system and record information by using coding structures correctly. This will include attendance on the Trust s Induction Course and completion of the e-learning Information Governance Course which is a mandatory pre-requisite before permission is granted to use information systems. Any changes to information requirements and/or systems may require further update training where necessary and this will be provided. This training will also include data quality aspects as well as how to use the system and also refer to local procedures. Staff will also be encouraged to complete the Data Quality e-learning Course Data Standards and Data-sets The Trust will comply with national Data Standards and Data-set requirements. The NHS Data Manual and Data Dictionary are accessible through Staffnet. The Trust will also comply with the requirements of relevant new Information Standards Notices (ISNs) received from the Health & Social Care Information Centre (HSCIC) ensuring that the Trust produces comparable data for each of the data sets e.g. Mental Health and Learning Disabilities Data Set (MHLDDS). Data-sets are important to Commissioners for contract monitoring and also increasingly to the NHS for obtaining statutory and other important information. The Trust s Data Warehouse processes the Trust s submissions. Code Changes for the Data Warehouse are logged in a database and have to be approved by the weekly Information Change Advisory Board (CAB) The Help Function and Local Data Dictionary (LDD) The Help Function accessible in PARIS will be used to provide links to important documents, training manuals, guides to good practice and web-sites to help improve the quality of input. It will also provide links to useful documents and guidance on the input of accurate data. A Local Data Dictionary will be developed that will be accessible via the Help function on PARIS and also be available through Staffnet. This will define and explain local codes and the reason for their collection. It will also give examples and frequently asked questions (FAQ s). It is envisaged that this will also link to the national Data Dictionary and Trust performance indicators/dq completeness reports Clinical Coding Date effective from: 9 September 2014 Page 10 of 50

11 The Trust will adhere to the standards set out in the NHS Clinical Coding Instruction Manual and uses the International Classification of diseases (ICD10) for diagnoses and the OPCS 4.7 (Office of Population and Censuses) for procedures such as Electro-convulsive Therapy (ECT). Clinical coding on PARIS and CPD will be carried out for all Finished Consultant Episodes (FCEs) by trained clinical coders according to the local working instructions for Clinical Coding from auditable source documents. The Trust will arrange for an annual audit to be carried out by a nationally accredited external clinical coding auditor to comply with the requirements of IG Toolkit requirement # Detection Detection is the first strand in the day-to-day management of data quality. The aim is to improve the detection of data quality errors by automating processes where possible, establishing their importance and notifying key errors. The detection of errors concerns finding errors in individual records in Trust systems. The DQ Team will develop and employ the necessary tools in innovative ways to improve detection so that they can be corrected at source. The Team may also carry out a limited data cleansing role where appropriate Prompt correction of errors The responsibility and ownership of data rests with the system user who must ensure that any errors are corrected promptly at source Dealing with errors that cannot be corrected by system users In cases where the system does not allow a user to correct or amend an error these should be logged with the IT Service desk for PARIS System Management to action. On rare occasions this may require the appropriate software supplier to correct them (i.e. to Civica for PARIS) Data Quality Data Warehouse (DQDW) The Data Quality Data Warehouse is an important tool for improving data quality as it provides the means of identifying errors from the source data and their timely correction at source by Directorates on a regular basis. Stage One of the implementation of the DQDW covered impossible errors many of which concern non-consecutive dates e.g. a hospital inpatient spell start date before the inpatient referral date. Rules have been set which are checked against data at the nightly processing stage; failures are placed into the DQDW rather than into the Data Warehouse. For the PARIS system automatic s and reminders are sent out to the individual user concerned as identified from the PARIS audit trail. The user then corrects the data at source or logs a call with the IT Service Desk for this to be done by System Management. This ensures that future errors are minimised and fits in with the ethos of right first time and continual quality improvement. Summary reports are monitored by the DQ Team and analysed in order to identify Date effective from: 9 September 2014 Page 11 of 50

12 individuals and teams consistently creating errors. In some cases this may require escalation to Team Managers or may identify training needs (see Appendix C Escalation Procedure ). The Data Quality Data Warehouse (DQDW) will be further developed and will play an increasingly important contribution in improving data quality Completeness and validity of key fields in the PARIS Central Index The Data Quality Team will run daily reports which look for specific data errors including missing or invalid demographic details such as: NHS numbers, main language, no current address, no current civil status. Other checks include: incorrect client statuses, duplicate client records. These are sent out to users for prompt amendment. This also involves feeding back results to Team managers and the individuals concerned Out-of-Area checks (SLA with Finance) There is a particular emphasis on fields used for the purposes of invoicing and billing: i.e. client post-codes, GP Practice & NHS number. (Completeness checking will be done daily; validity to be checked daily through batch-tracing see below) as established in a Service Level Agreement (SLA) with the Finance Department concerning the quality of Out-of-Area patient records (see Section 9 Reference/Evidence) Daily Batch-Tracing Batch-Tracing from the NHS Patient Demographic Service (PDS) is carried out on a daily basis on new referrals in the PARIS and CPD systems. Bulk batch tracing is also carried out periodically from the entire Central index of both systems. Duplicate records are also identified from batch tracing reports and other reports set up for the purpose and are dealt with in accordance with Trust procedure. Current arrangements for batch-tracing from the CPD system will continue to be carried out by the York Hospital Trust. On a weekly basis deceased patients are identified by running death reports from the PDS. The Trust Procedure for Recording Deceased Service Users on the PARIS system (OP-0013) is followed. This initiates the necessary steps to ensure that the Service Directorates are aware of a death and carry out the necessary administrative procedures including the cancellation of appointments; and to inform the Medical Records Department who perform the corporate role of updating the PARIS Death Module. This prevents the selection of a deceased person by mistake Monitoring Monitoring is the second strand in the day-to-day management of data quality. Date effective from: 9 September 2014 Page 12 of 50

13 The Data Quality Team performs a monitoring role in viewing aggregated data in order to detect at a high level where errors are occurring and whether the interventions of the Team have achieved improvements. This is achieved by running a series of reports. Monitoring confirms whether the Trust is achieving its targets on data quality and also identifies areas of concern. Interventions made by the Data Quality Team will also be monitored as part of the cycle of improvement to ensure that improvements are being achieved. Monitoring is also part of the cycle of improvement. Routinely this monitoring consists of: Completeness and Validity Reports (MHLDDS) this is a high-level internal COGNOS report which examines key demographic fields by Team and specialty. This analyses completeness and validity flagging where performance is below the required target figure (in percentage terms). The report will also be sent to team managers for information and action. Timeliness Reports monitor whether input is up to date and will also be run on a monthly basis. Teams that are below expected levels will be notified to ensure that any backlog can be input. COGNOS Reports will be used internally to monitor the quality of data and performance at a high level by Team. Any concerns will then be further investigated which will include involvement with the relevant Team(s). DQ Dashboards (SUS data) The DQ Team will monitor the high level data quality dashboards for the Trust s Commissioning Dataset (CDS) submissions to the Secondary Uses Service (SUS). This includes the completeness of key fields such as NHS number and GP Practice for Admitted Patient Care (APC) and Outpatient submissions. A traffic-light system is used to flag performance compared with the national average. This allows the Trust to verify data quality with known issues. These Dashboards also allow comparison with other similar Trusts in the country and region. MHLDDS DQ Reports which are published on the HSCIC website and will also be regularly monitored. Although there is an over-lap with some fields in the CDS submissions the MHLDDS submissions include community contacts. This may also include verifying local mappings from the Data Warehouse. The DQ Team will also submit a monthly return concerning the management and improvement of poor performance and also the quality of submissions Assurance Assurance of data is the third strand in data quality management. Policies and Procedures - The Trust will have policies and procedures in place in order to assure the quality of data and also to correct errors. Verification of NHS numbers these will be verified through the batch-tracing process, both on a daily basis but also periodically from bulk batch tracing the Date effective from: 9 September 2014 Page 13 of 50

14 entire databases. This is an important requirement for statutory submissions. Duplicate records and deceased patients are also identified by this process. Identifying duplicate records and duplicate merge such records could have serious clinical consequences. The Trust will have procedures in place to ensure that duplicates as detected by either: batch-tracing, by users or by reports run by the Data Quality Team. The duplicate merge procedure will be adhered to in order to ensure that records are merged properly on PARIS and also that hardcopy medical records are also merged according to procedure. Trust Death Procedure (OP-0013) - will be followed by confirming on the NHS Spine to ensure that a deceased patient s record is not selected accidentally which could have serious clinical consequences. Data Quality Reporting will be used to target and encourage Directorates to improve and quality assure their data. These reports include completeness reports for the MHLDDS, use of Data Quality Dashboards from SUS data and other reports as run by the Data Quality Improvement Team and distributed to Directorate Support Managers. Reports for Finance for Billing and Contracting Monitoring The Finance Department receive regular reports listing patient activity whose responsible CCG is Out-of-Area. The quality assurance of this data is carried out by the daily running of a report from batch tracing to find mismatches of a GP recorded on Trust systems compared to that recorded on the NHS Spine. This is important not only to update Trust systems for the billing of out-of-area patients but also to ensure that the correct Leeds or York CCG is identified for contract monitoring. This is achieved by the batch tracing process on referrals recorded on a daily basis. A separate report is run daily to identify out-of-area inpatients with the SCR checked manually. Routine Reporting The Trust s main reporting tool, COGNOS will be used to produce routine reports for all purposes such as for management, performance and monitoring. This has a particularly important role in monitoring data quality. Such reports include completeness of demographic data used in the MHLDDS and are used to target areas for improvement. Involving Clinicians in Validation/verification of data. Clinicians play an important role in the validation and verification of data. This is achieved by, for example, confirming caseload lists and activity levels through reporting which may also be used for Consultant appraisals. Accordingly Directorate Support Managers will continue to build partnerships with clinicians in order to assure that all data is collected and input into the appropriate Trust system. Clinicians must regularly check their caseloads on a Date effective from: 9 September 2014 Page 14 of 50

15 weekly basis reporting any discrepancies with immediate effect to their Directorate Support Manager for investigation. Similarly Care Co-ordinators must ensure that their caseloads are valid. Discrepancies must also be reported to their Directorate Support Manager and/or the Data Quality Improvement Team. Downloads from SUS data will be carried out on a monthly basis to quality assure our CDS submissions. Systematic checks will be carried out checking the validity and completeness of code use. Any discrepancies will be crossreferenced with monitoring reports and investigated. This will work in conjunction with IG Toolkit requirement #507 (see below). IGT507 Completeness and Validity check An important requirement of the Information Governance Toolkit is the completeness and validity check (IGT507) where the Trust must meet the required standard on one month selected from the current financial year Compliance Compliance is the fourth strand in data quality management. Capability failure of staff members to comply with the Trust s Data Quality Policy and Procedures may result in the individual being put through the Trust s Disciplinary Process. This may become evident from monitoring of error reports. Training needs will also be established through this process if the same person or Team is making persistent errors. The Escalation Procedure (see Appendix C) will be followed to identify in such cases. Performance issues monitoring also reveals how compliant a team has been concerning data quality e.g. the monthly completeness reports for MHLDDS run by the DQ Team. This will be used to improve performance. Staff responsibility for data quality is included in job all descriptions in accordance with the requirements of the Information Governance Toolkit (IGT). Annual audits of compliance with established procedures will be carried out on a targeted basis by the Data Quality Team, in accordance with IG Toolkit requirement #506. Service managers will support the implementation of action plans based on the recommendations for change arising from the findings of monitoring and audit activities. Letters produced by the PARIS system must contain the patient s NHS number as the main identifier (IGT requirement #401) Continual Cycle of Improvement The Trust will adopt a total quality management approach to data quality of Right First Time. No level of inaccuracy will be viewed as acceptable. Date effective from: 9 September 2014 Page 15 of 50

16 Data should be input into Trust systems as near to the provision of the service as possible and in the timeliest possible way to the occurrence. This may be either by clinicians themselves or administrative support staff working closely with them. On-going the provisions of the Information Governance Toolkit will be used as a framework to monitor and improve data quality. The monitoring of data quality is important in this process with feedback being given by users and service directorates as per the Trust s Data Quality Communication Plan (see 2.14 below). This feedback loop enables the continual improvement of processes, procedures and system configuration Communication The framework for communication on data quality and other information matters (see Reference Documents) has created a network for continuous improvement within the Trust. The specific methods are: o Active participation in Data Quality Improvement Group by Directorate Support leads and other corporate members including PARIS Trainers (see reference documents for DQI Group Terms of Reference ). o Communication in directorates through each directorate s organisational structure both top-down and bottom up approach. Team members are encouraged to discuss with Support Managers any problems or suggestions they have encountered in their everyday work. o Communication between directorates is encouraged by impromptu networking with staff at all levels and through the Data Quality Improvement Group. o Staff should consult the Data Quality and Data Quality Improvement Project sites on Staffnet concerning data collection and the use of Trust systems such as: Frequently Asked Questions (FAQs); and Questions and Answers (Q&As). This site will be kept up to date with tips and news on good practice. o Dissemination of Communication Data Quality bulletins via Trust and regular data quality newsletters. o Log ideas/concerns/comments on IT Service-Desk by under the category Data Quality Team/PARIS Design Authority as they arise. o PARIS Trainers to offer help and means of communication channels; and to be consulted on data quality matters as appropriate. o Feedback from the wide range of data quality reports will be provided particularly from clinicians to achieve a continuous cycle of improvement. o Clinicians should be actively involved in reporting data quality issues including those found within the PARIS system such as errors in caseloads Information Governance Date effective from: 9 September 2014 Page 16 of 50

17 Data Protection Principles Information Governance (IG) is a legal and ethical framework which governs the collection, use, storage, retention and disposal of information. Data Protection Principles must be followed and the following are relevant in this context: o Information should be adequate, relevant and not excessive for purpose. o Information should be accurate and where appropriate, kept up-to-date. These principles underline good data quality as a legal requirement Performance Requirements The Trust will comply with the requirements of the IGT; the requirements of Quality Accounts and Performance Indicators for Monitor. These requirements, along with any other performance measure, will be built into the Trust s data quality activities. Action plans and documentary evidence will be used to support the performance requirements. The principle that data in reports should reflect data on Trust systems without manipulation should be followed. It is a national requirementthat healthcare Trusts comply with the requirements of the Information Governance Toolkit (IGT). The IGT is comprised of numerous requirements which form the basis of Trust IG improvement plans. Data quality features strongly throughout the IGT and Trust data quality must support our annual toolkit submissions by both achieving the minimum required standard for all requirements in any given year and show year-on-year advancement through improved toolkit scores against requirements where maximum performance has not been reached, wherever practicable and possible. The IGT requirements form part of our annual Quality Accounts declaration to the Care Quality Commission (CQC), and these requirements along with any other performance measurement indicators will be built into the Trusts data quality activities so that the Trusts position is established. The Trust will also comply with requirements for calculation of Performance Indicators as required by Monitor. Particular attention will be given to monitoring the accuracy of data used in their construction to ensure accurate reporting. Action plans and documentary evidence will be required to support these performance requirements, with responsibility for these activities delegated to the appropriate members of the Information team and reported to the Data Quality, Information Governance Group and other appropriate groups as necessary. Date effective from: 9 September 2014 Page 17 of 50

18 3 DUTIES AND RESPONSIBILITIES Given the importance of good data quality as detailed above it is important that duties and responsibilities are clearly defined for all staff. 3.1 All staff All staff are responsible and accountable for adhering to relevant data standards and for ensuring that data is accurate and of a good quality. This includes all staff that collect, manage, store or use data about service users and those with line management responsibilities. They must also comply with legislation, Trust policies, procedures and local working instructions. Their personal responsibilities are also incorporated into job descriptions. Duties of specific staff groups are highlighted below: 3.2 Administrative/Reception staff This may include staff that input data on behalf of clinicians from manual or pre-printed forms. Such staff must collect data from the agreed documentation such as for example: referral forms or by the use of the Trust s registration form. This must then be input into the appropriate system in a timely, accurate and complete manner. When in the front-line of services, staff must also check and update demographic details with service users or their representatives. The Summary care Record (SCR) of the NHS Spine should be checked in order to confirm patient details and for the NHS numbers. Administrative staff are also responsible for ensuring that data is corrected or amended when informed about errors or omissions within 2 working days. They should also report to their line manager or support manager any issue affecting data quality that arises from their work and make suggestions for the improvement of systems or training. Errors they are unable to amend on the system must be logged with the IT Service Desk for correction to take place. 3.3 Clinical Coding staff Their role is to ensure that clinical coding is accurate, complete and timely as possible by using the standards set out in the NHS Clinical Coding Instruction manual using ICD10 for diagnoses and OPCS-4.7 for procedures such as ECT and by following Trust policies and procedures. All coding should be carried out from auditable source documents such as case-notes and discharge summary letters. Coders will also liaise with clinical staff on coding issues and report to their line manager any issue affecting data quality. As we move to paper light systems coding will be done using our electronic clinical information systems. 3.4 Clinical Staff Must ensure that data recorded in all areas of the patient record in Trust systems is accurate and complete and that it is input in a timely manner. This includes patient demographic and activity data. Specifically clinicians are responsible for ensuring that standards are met and to comply with legislation. Additionally clinicians must also assist in validating their data by giving regular feedback from activity reports. Date effective from: 9 September 2014 Page 18 of 50

19 3.5 Line Managers including Team Managers Have a responsibility to ensure that all their staff receive the appropriate level of training in data collection procedures as well as use of the appropriate Trust system and are aware of the importance of good quality data. They must also ensure that local working instructions are in place which are consistent with this policy and associated procedures and that these are followed correctly in their areas. 3.6 Directorate Support Managers They are the main lead for data quality in their Directorate and are responsible for ensuring that procedures are followed. As part of their role they will also monitor data quality and take appropriate action within their services to rectify data quality issues that may arise. Such issues will also be communicated to the Data Quality Team and through networking with colleagues. They will also identify any training issues and liaise with Trainers. These responsibilities are incorporated into job descriptions. Nominated persons will participate in the Data Quality Improvement Group. 3.7 Departments & Teams The following teams have specific responsibilities relating to data quality assurance, PARIS system development and Information Governance Informatics Department This Department has the responsibility to provide a framework of policies and procedures designed to promote data quality and to ensure that all systems are robust. The Informatics Manager has overall responsibility for the Department and Data Quality policies and strategies Data Quality Improvement Team This Team actively promotes good practice in the Trust ensuring Trust systems are compliant with national data standards and that data quality performance standards are achieved. Their role includes the monitoring of data, identifying errors and cleansing data where appropriate. Staff also assure the quality of data in the Trust by carrying out audits; disseminating to relevant staff and managers for action as well as liaising with Performance staff. This also involves the interpretation of the Trust s quality reports as published, for example, on the national Secondary Uses Service (SUS) DQ Dashboards. The Team disseminates changes to requirements as notified in Information Standards Notices (ISNs) and maintains the local data dictionary for the Trust Systems Development Team This team are responsible for ensuring that the processing of the Trust s data is robust. On a daily basis they process data into the Trust s Data Warehouse and Data Quality Data Warehouse. This enables reports to be run from the Trust s COGNOS Business Intelligence Reporting System and for data errors to be automatically ed out to source. They are also responsible for the Date effective from: 9 September 2014 Page 19 of 50

20 production and dispatch of the Trust s data-set submissions to the Health and Social Care Information Centre (HSCIC) Reporting Team This team are responsible for the production of monitoring and clinical reports to support data quality. They also produce reports for the Finance Department for billing purposes Systems Management Teams (PARIS) This team has the responsibility to ensure that the system is configured to collect data according to agreed standards and to undertake maintenance of the system. They also correct errors on the system that users are unable to do for technical or other reasons. Where it is not possible to correct an error on the system they log a call and liaise with our software supplier Civica Other Systems CPD under our SLA with the York Hospital Trust, ICT Services are responsible for the configuration of this system. IAPTUS by local managers and software suppliers. SystmOne - by local managers and software suppliers Corporate Performance Department This team are responsible for reporting of the Trust s performance indicators to the Trust Board of Directors as supplied by the Information Department. This includes preparing Quality Accounts and other reports for CQC and Monitor. The Team works in conjunction with the Data Quality Team and clinical service directorates to improve data quality Clinical Audit Team This team are responsible for providing the Trust Board of Directors with assurance that all clinical audit projects are conducted in accordance with the Trust s procedural document (OP-0009), i.e. that they are undertaken using ethically defensible and robust methods that comply with information governance and support the implementation of changes aimed at improving clinical care Care Services Performance and Capacity Team This team s focus is on care services performance monitoring and compliance including targets set by Monitor, CQC and local commissioners in Leeds and York as well as the CQuin payment framework. They provide expert interpretation of the care services performance requirement to the information department who develop the reports and information needed to meet the monitoring requirements. The team also work closely with operational services in care services to understand and interpret broad performance targets. Performance is monitored as required to assure key stakeholders of compliance and appropriate actions are initiated when necessary to maintain compliance. Work is also undertaken to validate data collected for performance indicators and commissioners and the team coordinate directorate responses and explanations of performance reports. As the team Date effective from: 9 September 2014 Page 20 of 50

21 works with operational services they will identify data quality issues and correct these within the team. 3.8 Groups Data Quality Improvement Group (DQIG) This group is a forum to discuss and agree resolutions to data quality and related patient administrative issues in the Trust as raised by its members. It consists of corporate data quality staff, clinicians, Directorate Support Administrative leads and other staff with the important role of improving data quality. Their main role is to monitor and enact measures to improve data quality in the Trust as well as to initiate and to develop policy and procedures Information Governance Group (IGG) This group is the parent group of the DQIG. It formally receives the minutes of the latter group s meetings and discusses proposal papers for data quality improvement. It reports to the Finance and Business Committee PARIS Design Authority This group considers and approves developments and other changes to the PARIS system including configuration changes and requirements for User Defined Forms. 3.9 Corporate Governance The Chief Executive has overall responsibility for the Trust s data quality. This is delegated to the Trust Board of Directors which reviews performance in relation to data quality and the Executive Team ratifies policies. The organisation s owner of Data Quality is designated as the Chief Information Officer (CIO) who has access to Trust Board as appropriate. The Chief Financial Officer is nominated lead director for data quality to whom the CIO reports. 4 TRAINING The Data Quality Improvement Team has responsibility for promoting good practice for the collection and input of service user data into Trust systems. In partnership with Directorate Support Managers, Team managers, clinicians and Trainers will raise the awareness of good quality data to system users throughout the Trust. o o o All staff new to the Trust will attend the Trust Induction Course which includes the Marketplace event. Members of the DQ Team will attend in order to publicise the importance of good quality data for patient care. The Data Quality e-learning Course will be publicised at all DQ events and on Staffnet and regularly reviewed for relevance and the numbers of staff taking part. Marketplace session, DQ Newsletters and PARIS trainers to publicise. The Data Quality Improvement Team will regularly liaise with Trainers on matters concerning data quality that may be included in Date effective from: 9 September 2014 Page 21 of 50

22 o o o o o o Training Courses and materials. This may include the exchange of tips on the collection and input of certain fields in systems. Regular informative Newsletters giving tips on good practice will be circulated. As part of a training programme, the Data Quality Improvement Team will also hold promotional events including roadshows and presentations to improve the awareness of users. Setting up of a Data Quality Network of interested system users, super users and managers etc. who can be contacted to cascade information as well as feedback experiences of using systems Proactive use of Staffnet web-site to promote good practice, give news and tips and to send out communications. The DQ Team and IG Group will raise trust wide awareness of data quality issues, common themes, training opportunities and progress via appropriate communications methods. The DQ Team will develop communications materials to inform and advise service users and staff on data quality issues such as newsletters, information and training leaflets, use of StaffNet. 5 GLOSSARY OF DEFINITIONS The following definitions are of relevance to this document: Automated distribution of errors by is the process by which data error reports, accessed from the Data Quality Data Warehouse, are automatically sent out by to the user concerned and also to their designated Team leader and/or support manager. Batch Tracing the process by which multiple records can be submitted electronically to verify patient demographic records in the Central Index of the PARIS and the CPD systems against information held on the NHS Patient Demographics Service (PDS). Clinician this term is used in the document to include all health care professionals. COGNOS Business Intelligence Reporting System which is the Trust s main reporting package. Produces high quality reports using views created in the Data Warehouse from downloaded and processed data. The Trust is making licences available for all authorised staff to be able to use this product. Commissioning Data-sets (CDS) data-sets that include details concerning Responsible CCG. There are separate data-sets for Admitted Care and Outpatients. Core Patient Database (CPD) York, Selby and North Yorkshire s clinical and patient administration system. This includes the Integrated Mental Health Electronic Record (IMHER) module. The system is hosted by the York Date effective from: 9 September 2014 Page 22 of 50

23 Hospitals NHS Foundation Trust and is due to be phased out by 31 st March Crystal Reporting this produces live reports which are accessed through the PARIS System. Such reports are usually required so that another PARIS function can be carried out. Data - the term data is often used to mean the raw information which is collected e.g. the GP and ethnicity of an individual service user. The distinction is made with information which is of a statistical nature useful for a particular purpose e.g. the proportion of service users from an ethnic minority background. Data Quality Assurance is the process by which data is verified as complete, accurate, up to date, fit for purpose, relates to the correct person and is free from duplication and fragmentation. Date Quality Data Warehouse (DQDW) a repository of data that fails the validation rules for the main data warehouse (e.g. due to being incomplete or erroneous). This is run on a daily basis (see also Data Warehouse). Such data is then automatically distributed by for correction at source so that the main record can be updated or amended. Data Warehouse the main repository of the Trust s data including historic data. Data from the PARIS system is downloaded and processed on a daily basis. Our dataset submissions to the Health and Social Care Information Centre are made from the Data Warehouse. Electronic Patient Record (EPR) is a patient record in an electronic format. For the purposes of this document it is service user information recorded on PARIS and CPD. HoNOS Health of the Nation Outcome Scores HoNOS is the most widely used routine clinical outcome measure used by mental health services. IAPTUS (Improving Access to Psychological Therapies) system from Mayden Software provides a complete patient management and reporting solution for psychological therapists providing cognitive behavioural therapy used in North Yorkshire. Integrated Mental Health Electronic Record (IMHER) module part of the Core Patient Database (CPD) see above. Information Governance is a term used to describe good practice in the management of information by ensuring necessary safeguards and appropriate use of personal and patient information. It includes data quality, but also data protection, records management, confidentiality and IT systems security. Date effective from: 9 September 2014 Page 23 of 50

24 Information Governance Toolkit (IGT) has been made available by the Health and Social Care Information Centre to assist organisations to achieve the aims of Information Governance. It is an assessment tool that is also used to improve the Trust s overall compliance with policy. Information Quality Assurance - Although used somewhat interchangeably with the term data quality it is intended to be wider in scope. The term data quality has been used throughout this policy as being more widely understood. Information Standards Notice (ISN) - formal notification of an information standard. It provides a summary of the information standard, with implementation dates, and links through to the following components of an information standard. Issued by the Health and Social CareInformation Centre they replaced DSCNs (Data Standards Change Notices from April 2010). Mental Health and Learning Disabilities Data Set (MHLDDS) is the national dataset as defined by the NHS Data Dictionary concerns adult patients (including elderly and from 1 st September 2014 Learning Disabilities) who receive care in NHS specialist mental health services. This care is delivered within a Mental Health Care Spell. For some patients care will comprise a small number of out-patient attendances over a few weeks. The MHLDDS is assembled and produced monthly comprising of a data set record for each Mental Health Care Spell which occurs wholly or partially within the Reporting Period. NHS Patient Demographic Service (PDS) or NHS Spine is the national NHS database for all patients registered with the NHS in England and Wales which is regarded as the definitive source of information concerning a patient record contained in the Summary Care Record (SCR). The PDS is regularly updated from GP patient notifications and contains demographics, current GP details and also indicates deceased patients. It is also used to verify PARIS and CPD records by batch tracing. PARIS System (Civica software) is the Trust s main clinical and patient administration system as implemented in Leeds in Service user (and carer) - this document uses the term service user as a synonym for patient and client. A service user is someone who receives care from Trust services; they can also be a carer. They will have a record in the PARIS Central Index. Services include: Inpatients, Outpatients and Community. Staffnet The Leeds and York Partnership NHS Foundation Trust s intranet. SUS (Secondary Uses Service) - SUS is the single, comprehensive repository for healthcare data which enables a range of reporting and analyses to support the NHS in the delivery of healthcare services. SUS is Date effective from: 9 September 2014 Page 24 of 50