primary care data application form · web viewbenchmarking information for named patient lists....

Primary Care DataApplication Form

Customer: Department of HealthTitle: GP metrics

NIC Number: NIC-391038-T4Q7Q

SCCI Reference Number: XXX

BAAS Unique Number: R01246

Data Sharing Framework Contract Reference Number: Not applicable for this data extraction

Copyright ©2016 Health and Social Care Information Centre

Primary Care Data Application Form: Error: Reference source not found v0.1 07/07/2016

Version: 0.1 Date: 07/07/2016

of xxix Copyright © 2016 Health and Social Care Information Centre

Primary Care Data Application Form: NIC-391038-T4Q7Q v0.1 07/07/2016

Contents

1 Contents

2 Summary 4

2.1 Overview 42.2 Sponsor information 52.3 Senior Responsible Owner information 52.4 Business Lead information 52.5 Why the data are needed 52.6 When and how often the data are needed 92.7 How the data will be collected 92.8 Requirements for the future 92.9 Funding and commitment 92.10 Legal basis for the collection 10

3 Elaboration of customer requirements 11

3.1 Information Asset Owner information 113.2 Level of data required 113.3 What data are needed 113.4 Options for delivery of the data 153.5 Recommendation 153.6 Other relationships/dependencies 153.7 Known risks and issues 153.8 Expert HSCIC clinical opinion on the likely quality of the data output 163.9 Certification 163.10 Data transformation process 163.11 How the data will be delivered 17

4 Burden Advice and Assessment Service 19

4.1 BAAS Unique Reference Number 194.2 Burden Assessment findings 19

5 Data management 20

5.1 Data retention 205.2 Data Sharing Agreement 205.3 Data controller, data processor and data recipient 205.4 Location of processing, data storage and territory of use 20

of 29 Copyright © 2016 Health and Social Care Information Centre


5.5 Data minimisation 215.6 Data dissemination 21

6 Data access request (for patient-level data only) 227 Appendix A: Data extraction options 238 Appendix B: Acronyms 289 Appendix C: Data flow process map 29



2 Summary2.1 OverviewThe Government’s mandate to NHS England for 2016-17 includes a deliverable to work with the Health and Social Care Information Centre (HSCIC) to provide general practitioners (GPs) with benchmarking information for named patient lists. The Department of Health (DH) will work with NHS England to achieve this deliverable.

DH has asked the HSCIC to extract and link data for a given set of metrics at individual GP level and report benchmarked data back to general practices.

There will be 12 metrics in total:

4 covering public health 4 covering the management of long term conditions 3 covering mental health and dementia 1 covering emergency admissions and bed days*

* This metric will cover 19 ambulatory care sensitive conditions, all of which are defined in section 3.4 What data are needed.

The HSCIC’s General Practice Extraction Service (GPES) will extract the necessary primary care data.

The 1 metric covering emergency admissions and bed days will involve linking primary care data to Hospital Episode Statistics (HES) data using NHS Number, which means that this will be a patient level data extraction.

All of the metrics will be assured by the HSCIC’s Indicator and Methodology Assurance Service (IMAS); this is expected to be completed by December 2016.

Funding is currently in place for the HSCIC to report two sets of benchmarked data to general practices; the first set of reports are required by January 2017 and the second set of reports are required by April 2017. Data will be extracted to support this deliverable, with the first data extraction scheduled to take place in late 2016.

The reason that funding does not cover more than reporting two sets of benchmarked data to general practices is due to GP metrics effectively being a pilot, in which it will test the methodology of extracting data at the individual GP level and the quality of the data that are extracted.

The data will only be made available for individual GPs and their general practices; it will not be made publically available. Each general practice will only be provided with data from their own general practice; they will not be provided with data from other general practices.

Providing GPs and their general practices with benchmarked data will allow them to review the quality of care and outcomes for their named patients.

Following the first data extraction and reporting of benchmarked data to general practices in


https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/494485/NHSE_mandate_16-17_22_Jan.pdf


January 2017, DH will decide whether or not GP metrics will continue to use the methodology as outlined in this form. If it does then the ambition is for the data extraction and reporting to take place on a quarterly basis.

2.2 Sponsor information

Name: Jonathan Marron

Role: Director NHS Group

Email: [email protected]

Telephone:

Organisation: Department of Health

Organisation type: Other Health and Social Care System Public Body

Further details: https://www.gov.uk/government/organisations/department-of-health

2.3 Senior Responsible Owner information

Name: Dave Roberts

Role: Head of Primary Care Information


Telephone: 0113 254 2541

Organisation: HSCIC


Further details: http://www.hscic.gov.uk/about-us

2.4 Business Lead information

Name: Richard Taylforth

Role: Business and Operational Delivery Manager


Telephone: 0113 866 5631

Organisation: HSCIC


Further details: http://www.hscic.gov.uk/about-us

2.5 Why the data are neededHigh level summary:

The data are required to support one of the objectives in the Government’s mandate to NHS England for 2016-17, whereby a 2016-17 deliverable is for the HSCIC to provide GPs with benchmarking information for named patient lists. Metrics at the individual GP level are currently unavailable, which is why this data extraction is required. Providing GPs and their general practices with this benchmarked information will allow GPs and general practices to review, and improve, the quality of care and outcomes for their named patients.




http://www.hscic.gov.uk/about-us

mailto:[email protected]

http://www.hscic.gov.uk/about-us


https://www.gov.uk/government/organisations/department-of-health



Rationale behind GP metrics as a whole:

The Government’s mandate to NHS England for 2016-17 sets out the objectives to 2020 in order to support the delivery of NHS’s Five Year Forward View and a seven-day NHS. Each objective is underpinned by specific deliverables to be achieved in the short term, for the year 2016-17, and to be achieved in the long term, by 2020 or beyond.

Objective 6 of this mandate is “to improve out-of-hospital care.” The part of this objective that covers “new models of care and general practice” includes the following 2020 goals:

100% of population has access to weekend/evening routine GP appointments. Measurable reduction in age standardised emergency admission rates and

emergency inpatient bed-day rates; more significant reductions through the New Care Model programme covering at least 50% of population.

Significant measurable progress in health and social care integration, urgent and emergency care (including ensuring a single point of contact), and electronic health record sharing, in areas covered by the New Care Model programme.

5,000 extra doctors in general practice.

One of the 2016-17 deliverables to support these 2020 goals is to:

Publish practice-level metrics on quality of and access to GP services and, with the Health and Social Care Information Centre, provide GPs with benchmarking information for named patient lists.

This provides the rationale for this data extraction.

The purpose of extracting and reporting these data is to support GPs and their general practices in overseeing, benchmarking, reviewing and continuously improving the quality of care that the general practices provide for their named patients.

Rationale behind proposed methodology:

From 1 April 2015, general practices have been required under the General Medical Services (GMS) contract to allocate a named accountable GP to all registered patients (including children). The role of the named accountable GP is to take responsibility for the co-ordination of all appropriate services and ensure that they are delivered to each of their patients where required (based on the GP's clinical judgement) 1.

In January 2016, the HSCIC conducted a feasibility study into the options and requirements for delivering GP metrics. This study identified three possible options for extracting the primary care data from general practice clinical systems:

1. Add the appropriate General Medical Council (GMC) reference number to the ‘Patient allocated named accountable general practitioner’ CTV3 / Read V2 / SNOMED CT code. Under the GMS contract, this code should be entered in a patient’s clinical

1 NHS Employers (2015). 2015/16 General Medical Services (GMS) contract: Guidance for GMS contract 2015/16. Accessed 4 July 2016 from: http://www.nhsemployers.org/~/media/Employers/Documents/Primary%20care%20contracts/GMS/GMS%20guidance%202010-present/2015-16/201516%20GMS%20Guidance.pdf


http://www.nhsemployers.org/~/media/Employers/Documents/Primary%20care%20contracts/GMS/GMS%20guidance%202010-present/2015-16/201516%20GMS%20Guidance.pdf

http://www.nhsemployers.org/~/media/Employers/Documents/Primary%20care%20contracts/GMS/GMS%20guidance%202010-present/2015-16/201516%20GMS%20Guidance.pdf

https://www.england.nhs.uk/ourwork/futurenhs/



record to signify that the patient has been allocated a named accountable GP. Adding the GMC reference number of the individual GP to this code, in the same way that a blood pressure value could be added to a blood pressure code, would provide the link between a patient and their GP. This option required general practice system suppliers to carry out development work and also general practices to re-code all of their patients as they had not previously been required to enter the GMC reference number alongside the ‘Patient allocated named accountable general practitioner’ code.

2. Extract data from the existing GP_USUAL data field; this is one of the items included in the Patient Table as outlined in the GPES Interoperability Standard, the purpose of which is to define GPES. The GP_USUAL data field is defined as “doctor usually seen by” and the data item returned in this field is detailed as being the NHS specified doctor number, which is expected to be either the GMC reference number or the General Medical Practitioner (GMP) reference number. This option did not require development work for the general practice system suppliers as this data field is included in the GPES Interoperability Standard.

3. Produce a new data field in the patient record in order to record named accountable GP. It was anticipated that this would involve each general practice’s clinical system including a drop down list of all of the named accountable GPs at the general practice, from which staff could select the appropriate GP for each of their registered patients. Selecting the appropriate GP would then populate the new data field with the GMC / GMP reference number, which GPES would be able to extract. As with option 1, this new requirement required significant development work for general practice system suppliers and general practices were also required to code the named accountable GP for all of their registered patients.

The HSCIC has been asked to deliver the reporting benchmarked data to general practices in January 2017; therefore, due to the costs and time needed for the development work required from general practice system suppliers, as well as the time and burden that coding all registered patients would place on general practices themselves, option 2 was chosen as the preferred option.

This means that GPES will extract the existing information from the GP_USUAL data field. This field is defined as “doctor usually seen by”, which may or may not be the same as a patient’s named accountable GP.

This data extraction will effectively be a pilot, in that it aims to test:

1. The methodology of extracting data at the level of the individual GP.2. The quality of the data stored within the GP_USUAL data field.

Rationale behind chosen metrics:

DH convened a reference group to help inform the development of the GP metrics listed in section 3.4 What data are needed. This reference group brought together professional and technical advisers from NHS England, Care Quality Commission (CQC), HSCIC and National Institute for Health and Care Excellence (NICE), together with an independent GP academic.

Based on views from this reference group, DH presented the list of metrics to



representatives from the British Medical Association’s (BMA) General Practitioners Committee (GPC). DH took the GPC’s views into consideration, that metrics where possible should focus on patients for whom the most impact could be achieved in terms of GPs assessing the way in which care is planned and provided. Another view expressed by stakeholders was that the metrics where possible should be based on those that currently exist and that, where possible, they should align with the practice level metrics that will be published on My NHS.

Taking the breadth of these views, DH selected metrics that align with general practice level metrics, focus on patient groups for whom the most impact can be achieved, whilst filtering out metrics used at general practice level that are not technically feasible to link at named accountable GP level (e.g. the GP Practice Survey). The use of existing indicators presents a good starting point whilst enabling the metrics to be delivered by the end of January 2017.

Following further discussion with NHS England, DH recommended that the metrics focus on recognisable measures for the treatment of long term conditions.

The chosen metrics seek to take account of the GPC’s views that they should concern a relevant patient population, for which named accountable GPs can usefully assess the care that the general practice is providing, whilst avoiding numbers that are so low as to be statistically meaningless. The metrics are expected to cover about 30 per cent of the registered general practice population. These patients are most likely to require continuity of care, have more frequent contact with the same GP, and account for high numbers of emergency admissions.

One of the most consistent themes that emerged from the discussions with the GPC and other GPs is a concern that the doctor named as the accountable GP may not be the doctor who actually sees the patient most often, and that the named accountable GP will not find the data meaningful. DH and the HSCIC have explored whether or not it is possible for general practice system suppliers to automatically identify the GP who most often sees each patient, so that this could be entered as a default, but this is not technically possible; this is why option 2 for the proposed methodology has been chosen.

Following discussions with the GPC, DH have also explored the merits of building up evidence over time on the metrics that most benefit GPs and their general practices in terms of assessing the way in which care is provided. DH believe that there is some merit in being able to say to the profession that, whilst we are pressing ahead with this initial dataset, we are commissioning research to help make longer-term decisions about which metrics will be most helpful to the profession as a whole, as well as to individual general practices.

2.6 When and how often the data are neededThe first data extraction is scheduled to take place in late 2016 ahead of the HSCIC reporting the benchmarked data to general practices in late January 2017.

The second data extraction is scheduled to take place in early 2017 ahead of the HSCIC reporting the benchmarked data to general practices in late April 2017.

Following April 2017, the intention is for the data extraction and reporting to take place on a quarterly basis.



Each data extraction will take place after the quarter in question as there is a lag between the end of the quarter and the date that the data are extracted in order to allow general practices to make sure that they have recorded all of the necessary information.

2.7 How the data will be collectedThe primary care data will be extracted via GPES.

The secondary care data for linkage will use the HES Admitted Patient Care extract. Note that it is not in the scope of this Primary Care Data Application Form to cover how the HES data are extracted.

2.8 Requirements for the futureFollowing the first data extraction and reporting of benchmarked data to general practices in January 2017, DH will decide whether or not GP metrics will continue to use the methodology as outlined in this form.

Following April 2017, the intention is for the data extraction and reporting to take place on a quarterly basis.

If this extraction does continue into the 2017-18 financial year then the appropriate measures would need to be put in place for SNOMED CT becoming the standard clinical coding terminology within primary care; this relates to the removal of CTV3 / Read V2 codes. The Primary Care Domain and GPES are aware that this change is taking place and are in discussions with the UK Terminology Centre surrounding this.

2.9 Funding and commitmentThe current funding available for this work, as listed in the Work Package that DH issued to the HSCIC, covers costs for the HSCIC to report two sets of benchmarked data to general practices (i.e. in January 2017 and April 2017).

If DH does decide to continue the data extraction and reporting on a quarterly basis following April 2017 then they will have to bid for further funding in order to support this.

The primary care data that are required for the metrics being extracted via GPES, as well as the HSCIC’s Primary Care Domain performing the appropriate analysis and disseminating the data to general practices, are business commitments for the HSCIC. The necessary funding and resources are available to support this commitment.

2.10 Legal basis for the collectionDH will Direct the HSCIC to establish and operate a system for the collection and analysis of the GP metrics data under Section 254 of the Health and Social Care Act (the Act).

The HSCIC will then require all general practices in England to provide the necessary data under Section 259 of the Act. This will provide the legal basis for the extraction of the data.

DH will lead on all of the communications surrounding the purpose and direction of travel of


http://www.legislation.gov.uk/ukpga/2012/7/section/259/enacted

http://www.legislation.gov.uk/ukpga/2012/7/section/254/enacted


the GP metrics. They will also lead on all of the engagement and consultation with general practices surrounding this work.



3 Elaboration of customer requirements3.1 Information Asset Owner information

Name: Dave Roberts

Role: Head of Primary Care Information


Telephone: 0113 254 2541

3.2 Level of data requiredPatient level data will be required due to the 1 metric covering emergency admissions and bed days involving linking primary care data to HES data using NHS Number.

Exactly how the data will be extracted is to be confirmed – see Appendix A: Data extraction options for possible options as to what the data extract will look like.

3.3 What data are neededAll general practices in England (approximately 7,800 in total) will be required to ‘opt-in’ to this data extraction, whereby all general practices will have the opportunity to view their data before it is stored.

The proposed metrics are listed below.

Please note that the finalised wording of these metrics is yet to be agreed.

4 metrics covering public health

1. Flu vaccinations – coverage of over 65s (Annual, Public Health England)2. Flu vaccinations – coverage of other at-risk groups (Annual, Public Health England)3. Percentage of women aged 25-64 with record of a cervical smear4. Percentage of children aged up to the age of 2 with record of childhood immunisations

(composite)

4 metrics covering the management of long term conditions

5. Percentage of patients with hypertension with blood pressure 150/90mmHg or less6. Percentage of patients with atrial fibrillation currently treated with anticoagulation

therapy7. Percentage of diabetes patients whose last glucose reading (HbA1c) is 64 mmol/mol

or less8. Percentage of COPD patients with a confirmed diagnosis by a post bronchodilator

spirometry

3 metrics covering mental health and dementia

9. Percentage of patients with schizophrenia, bipolar affective disorder and other psychoses who have a comprehensive, agreed care plan documented in the preceding 12 months

10.Percentage of patients with dementia with face-to-face review in the last 12 months




11.Percentage of patients with serious mental illness with cardiovascular disease risk assessment in the last 12 months (Annual, NICE)

1 metric covering emergency admissions and bed days

12.Emergency Admissions for 19 Ambulatory Care Sensitive Conditions*

* This metric will cover the following 19 ambulatory care sensitive conditions, as taken from the Emergency hospital admissions for ambulatory care-sensitive conditions: identifying the potential for reductions data briefing paper published by The Kings Fund:

Vaccine-preventable: Influenza and pneumonia Other vaccine-preventable conditions

Chronic: Asthma Congestive heart failure Diabetes complications Chronic obstructive pulmonary disease (COPD) Angina Iron-deficiency anaemia Hypertension Nutritional deficiencies

Acute: Dehydration and gastroenteritis Pyelonephritis Perforated/bleeding ulcer Cellulitis Pelvic inflammatory disease Ear, nose and throat infections Dental conditions Convulsions and epilepsy Gangrene

Primary care data extraction:

Exactly how the primary care data will be extracted is to be confirmed; there are two possible options, both of which are explained in full detail in Appendix A: Data extraction options:

Option 1) Combined aggregate level and patient level data extraction

This will involve extracting:

Aggregate level data in the form of counts of the number of patients for the numerator and denominator for each of the 11 metrics covering public health, management of long term conditions and mental health and dementia, broken down by individual GP.

Patient level data in the form of NHS Numbers for all of the patients registered at


http://www.kingsfund.org.uk/sites/files/kf/field/field_publication_file/data-briefing-emergency-hospital-admissions-for-ambulatory-care-sensitive-conditions-apr-2012.pdf

http://www.kingsfund.org.uk/sites/files/kf/field/field_publication_file/data-briefing-emergency-hospital-admissions-for-ambulatory-care-sensitive-conditions-apr-2012.pdf


the general practice, broken down by individual GP.

Option 2) Full patient level data extraction

This will involve extracting:

Patient level data in the form of the NHS Numbers of all of the patients registered at the general practice, broken down by individual GP and whether or not the patients fall into the numerator and denominator for each of the 11 metrics covering public health, management of long term conditions and mental health and dementia.

The HSCIC’s preferred option would be to proceed with option 1 but this will depend on the technical feasibility of GPES and the general practice system suppliers. If option 1 is not feasible, then option 2 will be used instead.

The CTV3 / Read V2 codes that will be used to define the 11 metrics covering public health, management of long term conditions and mental health and dementia will be published in the technical specification document (also known as the business rules) for this extraction; this document will underpin how the data extraction should work and will be published on the HSCIC website.

Secondary care data extraction:

The secondary care data for linkage will use the HES Admitted Patient Care extract. These extracts will include the NHS Numbers of all of the patients who:

1. were admitted to hospital as an emergency (as determined by the field name ‘Method of admission’ – i.e. ADMIMETH)

AND2. have a primary diagnoses of one of the 19 ambulatory care sensitive conditions listed

above (as determined by the field name ‘All Diagnosis codes’ – i.e. DIAG_01)

The NHS Numbers of patients who fall outside the above criteria will not be included in the HES extracts.

Two flags will need to be included alongside the NHS Number in the secondary care data extract:

1. To signify which of the 19 ambulatory care sensitive conditions each patient has (i.e. ACSC_Flag). This is because a patient may have a more than one primary diagnosis and will therefore need to be linked to all of the appropriate 19 ambulatory care sensitive conditions. In such an instance, the same NHS Number (i.e. the same patient) would appear multiple times within an extract but each NHS Number would reference a different ambulatory care sensitive condition.

2. To signify the episode start date of each ambulatory care sensitive conditions (i.e. EPISTART). This is because a patient may have multiple episodes of the same primary diagnosis and will therefore need to be linked to all of the episodes of the same ambulatory care sensitive condition. In such an instance, the same NHS Number (i.e. the same patient) would appear multiple times within an extract but each



NHS Number would reference a different episode start date for the same ambulatory care sensitive condition.

The below table illustrates what each HES extract will look like; see the yellow highlighted text for an example of the same patient having a primary diagnosis for multiple ambulatory care sensitive conditions and see the green highlighted text for an example of the same patient having multiple instances of a primary diagnoses for the same ambulatory care sensitive condition. Note that the ACSC_Flag column will be coded but for the purpose of this illustration the full names of the ambulatory care sensitive conditions are shown.

NHS_Number ACSC_Flag EPISTART

7149920358 Influenza and pneumonia 21/10/2008

2240861138 COPD 19/08/2006

6410053480 Hypertension 06/10/1997

7374508181 Angina 02/03/2010

6271083506 Dental conditions 18/10/1998

5479349001 Cellulitis 11/02/2002

5479349001 Pyelonephritis 28/05/2008

5479349001 Gangrene 28/06/2015

8738073530 Asthma 21/03/2006

8738073530 Asthma 20/06/2008

8738073530 Asthma 05/05/2009

Section 3.10 Data transformation process details how the primary care and secondary care data extractions will be transformed.

3.4 Options for delivery of the dataThe primary care data will be delivered via GPES; this involves:

General Practice Extraction Tool – Query (GPET-Q) General Practice Extraction Tool – Extract (GPET-E) General practices

See Appendix C: Data delivery process for GPES for information on how the data will flow from general practices into GPES.

The secondary care HES extracts will be taken from the SUS data warehouse.

3.5 RecommendationThe recommendation for the delivery of the data is via GPES as there is no other option.



3.6 Other relationships/dependenciesThis data extraction will be dependent on:

GPET-Q GPET-E General practice system suppliers GPES as a whole

3.7 Known risks and issuesGP practices may choose not to ‘opt-in’ to this data extraction but, with it involving a Direction, general practices will be legally obliged to comply with the requirement for data from the HSCIC so this is deemed as low risk.

GPES has never before extracted data at the level of the individual GP and therefore this data extraction methodology could be a risk.

The quality of the data stored in the GP_USUAL data field is also relatively unknown. The GP_USUAL data field is defined as “doctor usually seen by” and the data item returned in this field is detailed as being the NHS specified doctor number, which is expected to be either the GMC reference number or the GMP reference number. As GPES has never before extracted data from the GP_USUAL data field, the quality of the data is an uncertainty. The HSCIC aim to get some sample data on the GP_USUAL data field from the general practice system suppliers in order to test data quality prior to the first data extraction.

3.8 Expert HSCIC clinical opinion on the likely quality of the data outputDH has consulted with the GPC in agreeing these metrics (see section 2.5 Why the data are needed).

The corresponding CTV3 / Read V2 codes, which make up the 11 metrics covering public health, management of long term conditions and mental health and dementia will be reviewed and agreed by the HSCIC Clinical Informatics Advisors.

The ICD-10 codes that will be used to determine the 19 ambulatory care sensitive conditions will be agreed by the HSCIC Clinical Classifications Service.

3.9 CertificationAn Extraction Requirement will be sent to the general practice system suppliers (i.e. EMIS, INPS, Microtest and TPP). This sets out the data that will need to flow to GPES.

To reduce the risk of general practice system suppliers misinterpreting the Extraction Requirement and to avoid any data extraction errors, GPES offers a certification service. This is where general practice system suppliers are able to test their technical data extraction specifications against a set of sample data.

GPES offers three levels of certification standards against the Extraction Requirement: Gold, Silver and Bronze, with Gold being the most comprehensive.

This data collection will be certified against the Gold standard.



3.10 Data transformation processThe primary care data that are extracted via GPES and the secondary care data extract that is taken from the HES Admitted Patient Care extract will undergo validation at the at the file level before being loaded into the HSCIC’s Data Management Environment (DME), which involves the following 4 steps:

Step 1) Load

For the primary care data extracted via GPES, one Extensible Markup Language (XML) data file per general practice (approximately 7,800 in total) will be loaded into DME.

The HES data extract clone will be moved into the DME server space for filtering.

Step 2) Validate

The validation of the primary care data in DME will take place at the field level for following data fields:

GP_USUAL NHS_Number GP_Practice_Code

It is anticipated that the HES data will have already been validated prior to being loaded into DME. If this is not the case then the necessary validation on the NHS_Number data field will take place.

Step 3) Transform

This is where the primary care data will be linked to the secondary care data for the 1 metric covering emergency admissions and bed days. The data linkage will involve a many to many join on NHS Number from both data extracts. This will be due to multiple instances of the same NHS Number being included in the primary care and secondary care extracts. Multiple instances of the same NHS Number will be present in the secondary care data extract due to patients being admitted for different ambulatory care sensitive conditions or being admitted for the same ambulatory care sensitive condition on more than one occasion (see section 3.4 What data are needed).

Step 4) Release

The data will be imported into a Microsoft Structured Query Language (SQL) Sever database so that a Microsoft SQL Server Reporting Services (SSRS) report can then be produced. This will include all relevant analyses, such as:

Calculating the percentages for each of the 11 metrics covering public health, management of long term conditions and mental health and dementia, broken down by individual GP.

Determining the number of patients who were admitted to hospital as an emergency for each of the 19 ambulatory care sensitive conditions, broken down



by individual GP. Determining the number of emergency admissions to hospital (not the number of

patients who were admitted to hospital as an emergency) for each of the 19 ambulatory care sensitive conditions, broken down by individual GP.

Any data quality issues, such as the number (and percentage) of invalid NHS Numbers, broken down by individual GP.

See 9 Appendix C: Data flow process map for a high level overview of the steps involved in extracting and disseminating the data.

3.11 How the data will be deliveredThe intention is to produce one SSRS Portable Document Format (PDF) report per general practice, which will include the metrics for all of the individual GPs who are registered as working at that general practice.

This report will then be pushed out to general practices so as to place the minimum burden on reporting the benchmarked data to general practices. The HSCIC are aiming to use the Messaging Exchange for Social Care and Health (MESH) mailbox to send the reports to general practices. This will involve a member of each general practice (most likely a Practice Manager) accessing the data via a new Role Based Access Control (RBAC) codes and a smartcard.



4 Burden Advice and Assessment Service4.1 BAAS Unique Reference NumberR01246

4.2 Burden Assessment findingsTo avoid duplication, the findings of the Burden Assessment for this data extraction have not been included in this document. Instead, these findings should be viewed in conjunction with this Primary Care Data Application Form at the relevant SCCI meeting.



5 Data management5.1 Data retentionIt is anticipated that the primary care and secondary care data that are loaded into DME will be retained for a maximum period of 1 quarter.

5.2 Data Sharing AgreementA Data Sharing Agreement is not applicable for this data extraction as the HSCIC will report the benchmarked to the general practices.

5.3 Data controller, data processor and data recipientThe below diagram illustrates the relationship between the data controller, data processor and data recipient:

5.4 Location of processing, data storage and territory of useProcessingOrganisation: HSCICTeam: GPESAddress: 8th Floor | Bridgewater Place | Water Lane | Leeds | LS11 5BZ

Data storageOrganisation: HSCICTeam: DMEAddress: 1 Trevelyan Square | Boar Lane | Leeds | LS1 6AE



Organisation: HSCICTeam: HESAddress: 1 Trevelyan Square | Boar Lane | Leeds | LS1 6AE

Note that the servers that store the data are based in Harrogate or Plymouth.

Territory of useEngland

5.5 Data minimisationThis data extraction follows the data minimisation principles in that:

The data will only be held for the minimum amount of time required (i.e. 1 quarter). Only the minimum amount of data necessary for the data linkage between the

primary care and secondary care data are being extracted. This linkage is just taking place on NHS Number alone, as opposed to using other personal identifiers, such as date of birth, sex, etc.

5.6 Data disseminationAs the data will not be made publically available, it is anticipated that there will be no small number suppression in the data reports as the data are only being reported back to general practices (i.e. the data controllers), rather than being made available to the general public.

The HSCIC’s Disclosure Control Panel (DCP) and Infrastructure Security Team (IST) will decide the outcome to this decision.

Prior to dissemination, the data will also be assured by the HSCIC’s Solutions Assurance team.



6 Data access request (for patient-level data only)Not applicable to this data extraction due to the HSCIC reporting the benchmarked data to the general practices (i.e. the data controllers); DCP and IST will advise as appropriate.



7 Appendix A: Data extraction optionsOption 1: Combined aggregate level and patient level data extraction

For the each of the 11 metrics covering public health, management of long term conditions and mental health and dementia, GPES will extract a numerator and denominator for each individual GP within the general practice. Each numerator and denominator will be an aggregated count of the number of patients who fall into the necessary criteria for the metrics.

For the 1 metric covering emergency admissions and bed days, GPES will extract the NHS Numbers of all of the patients that are assigned to each individual GP within the general practice. Determining which patients are linked to which individual GP will be done by using the GP_USUAL data field from the GPES Patient Table. The GP_USUAL data field is defined as “doctor usually seen by” and the data item returned in this field is detailed as being the NHS specified doctor number, which is expected to be either the GMC reference number or the GMP reference number.

For each data extraction, GPES will extract one data file per general practice. This will include the aggregated counts of the number of patients for the numerators and denominators for each of the 11 aggregated metrics, broken down by individual GP, as well as a list of the NHS Numbers of the patients that are assigned to each individual GP. Note that GP practice code does not need to be extracted as this will be included separately in the data file that is returned to GPES. The below table illustrates what each data file will look like; the ellipses (i.e. “. . .”) signify that numerous patient NHS Numbers may be assigned to each of the individual GPs.

GP_USUAL Indicator_ID Value

G1048937 1_Numerator 38

G1048937 1_Denominator 48























G1048937 12_NHS_Number 6620120044

G1048937 12_NHS_Number 9063163605

G1048937 12_NHS_Number 2849358807

G1048937 12_NHS_Number . . .























G5128295 12_NHS_Number 2338635026



G5128295 12_NHS_Number 1251616289

G5128295 12_NHS_Number 7837780505

G5128295 12_NHS_Number . . .

Option 2: Full patient level data extraction

GPES will extract the NHS Numbers of all of the patients that fall into the numerator and denominator for each of the 11 metrics covering public health, management of long term conditions and mental health and dementia. These NHS Numbers will be aggregated into counts of the number of patients, in order to provide a numerator and denominator count for each metric, following the data extraction.

For the 1 metric covering emergency admissions and bed days, GPES will extract the NHS Numbers of all of the patients that are assigned to each individual GP within the general practice and that have not already been captured in the 11 metrics covering public health, management of long term conditions and mental health and dementia.

As in option 1, determining which patients are linked to which individual GP will be done by using the GP_USUAL data field from the GPES Patient Table. The GP_USUAL data field is defined as “doctor usually seen by” and the data item returned in this field is detailed as being the NHS specified doctor number, which is expected to be either the GMC reference number or the GMP reference number.

For each data extraction, GPES will extract one data file per general practice. This will be a full patient level extraction that will include the NHS Numbers of all of the patients that fall into the numerator and denominator of each of the 11 metrics covering public health, management of long term conditions and mental health and dementia, as well as NHS Numbers of all of the patients that are not captured by these 11 metrics; these NHS Numbers will be broken down by individual GP. Note that GP practice code does not need to be extracted as this will be included separately in the data file that is returned to GPES. The below table illustrates what each data file will look like; the ellipses (i.e. “. . .”) signify that numerous patient NHS Numbers may be assigned to each of the individual GPs.

GP_USUAL Indicator_ID NHS_Number

G1048937 1_Numerator 4022783529

G1048937 1_Numerator 5700034109

G1048937 1_Numerator 9250614267

G1048937 . . . . . .

G1048937 1_Denominator 5535466518

G1048937 1_Denominator 1072320917

G1048937 1_Denominator 3108268500

G1048937 . . . . . .

G1048937 2_Numerator 6724033918



G1048937 2_Numerator 7191089862

G1048937 2_Numerator 3700016024

G1048937 . . . . . .

G1048937 2_Denominator 9393917660

G1048937 2_Denominator 4371567201

G1048937 2_Denominator 1481849715

G1048937 . . . . . .

G1048937 . . . . . .

G1048937 . . . . . .

G1048937 12_NHS_Number 6973748961

G1048937 12_NHS_Number 3074459899

G1048937 12_NHS_Number 8254172775

G1048937 . . . . . .

G4735495 1_Numerator 7639840629

G4735495 1_Numerator 9783985571

G4735495 1_Numerator 3921214372

G4735495 . . . . . .

G4735495 1_Denominator 8950795839

G4735495 1_Denominator 1864615613

G4735495 1_Denominator 6364554514

G4735495 . . . . . .

G4735495 2_Numerator 5163870934

G4735495 2_Numerator 4131068941

G4735495 2_Numerator 6210229540

G4735495 . . . . . .

G4735495 2_Denominator 1895371525

G4735495 2_Denominator 4627158148

G4735495 2_Denominator 5161091798

G4735495 . . . . . .

G4735495 . . . . . .

G4735495 . . . . . .

G4735495 12_NHS_Number 3012404839

G4735495 12_NHS_Number 9694067537

G4735495 12_NHS_Number 1643902162



G4735495 . . . . . .



8 Appendix B: AcronymsAcronym Description

BAAS Burden Advice and Assessment Service

BMA British Medical Association

CQC Care Quality Commission

CTV3 Clinical Terms Version 3

DH Department of Health

DME Data Management Environment

EMIS Egton Medical Information Systems

GMC General Medical Council

GMP General Medical Practitioner

GMS General Medical Services

GP General Practitioner

GPC General Practitioners Committee

GPES General Practice Extraction Service

GPET-E General Practice Extraction Tool – Extract

GPET-Q General Practice Extraction Tool – Query

HES Hospital Episode Statistics

HSCIC Health and Social Care Information Centre

IMAS Indicator and Methodology Assurance Service

INPS In Practice Systems

MESH Messaging Exchange for Social Care and Health

NHS National Health Service

NICE National Institute for Health and Care Excellence

PDF Portable Document Format

RBAC Role Based Access Control

SCCI Standardisation Committee for Care Information

SNOMED CT Systematized Nomenclature of Medicine -- Clinical Terms

SQL Structured Query Language

SSRS SQL Server Reporting Services

TPP The Phoenix Partnership

XML Extensible Markup Language



9 Appendix C: Data flow process mapThe purpose of this process map if to provide a high level overview of the steps involved in extracting and disseminating the data.

Steps that take place prior to the data being extracted are coloured in Prussian Blue.Steps showing the data flowing into the HSCIC are coloured in Violet.Steps showing the data flowing out of the HSCIC are coloured in Deep Rubine.
