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Publication, Part of

Mental Health Services Monthly Statistics Performance April, Provisional May 2020

Official statistics, Experimental statistics
Publication Date:
Geographic Coverage:
England
Geographical Granularity:
Clinical Commissioning Groups, Councils with Adult Social Services Responsibilities (CASSRs), Independent Sector Health Care Providers, Mental Health Trusts, Provider, Regions, Sustainability and Transformation Partnerships
Date Range:
01 Feb 2020 to 31 May 2020

Methodology

Data collection

These statistics are produced from the Mental Health Services Data Set (MHSDS) and are published monthly.

The MHSDS is a complex relational data set which collects record-level data on NHS-funded specialist mental health, learning disabilities and autism services. As a secondary uses data set it intends to re-use clinical and operational data for purposes other than direct patient care.

The MHSDS is unique in its coverage, because it covers not only services provided in hospitals, but also in outpatient clinics and in the community, where the majority of people in contact with these services are treated. MHSDS brings together key information from Adult and Children's mental health, learning disabilities or autism spectrum disorder, CYP-IAPT and early intervention care pathway that has been captured on clinical systems as part of patient care.

From April 2019 data, the MHSDS is collected via the Strategic Data Collection Service (SDCS) Cloud service using the MHSDS v4.0 (or later) Intermediate Database (IDB). Prior to this, MHSDS data was collected via the Bureau Service Portal.

Unlike the Bureau Service Portal, the SDCS Cloud an internet-facing service that does not require an N3 or HSCN connection, making it easier for providers to submit data and therefore enabling better coverage in published statistics. This new service stores MHSDS data in cloud-based infrastructure.

Detailed guidance is available to support providers in making submissions via the SDCS Cloud. This includes detailed technical and user guidance. New providers must complete a defined process to gain access to the SDCS Cloud. It also uses two-factor authentication as the secure method of confirming user identity using a combination of two different factors.

Data Processing

From April 2019 data, the MHSDS data are processed using NHS Digital’s new Data Processing Services (DPS). DPS uses modern technologies and processes to collect, process and access data more efficiently.

Find out more about our Data Processing Services (DPS) here.

CCG derivation

The methodology for deriving Clinical Commissioning Group (CCG) was updated for the 2019-20 reporting year. There are two major changes; the removal of the submitted organisation identifier (when OrgCodeGPPrac IS not null then OrgCodeGPPrac) and the removal of the exclusion code for submitted organisation identifier (and OrgCodeGPPrac <> '-1').

The organisation identifier field, submitted by providers, allows unvalidated entry of a CCG codes; and the contents of this field supersede any other CCG information in the dataset when assigning a CCG to a patient.

It was found that the data provided in this field varies greatly and can include a number of non-current CCG values; these values result in the patients being assigned to Unknown CCG. Removing this step means that the CCG assigned to a record is derived within MHSDS from postcode information and, as such, will be a valid current CCG.

Analysis conducted, comparing statistics based on the current methodology with that of the updated methodology produces, shows a significant decrease in the number of unknown CCGs being reported using the updated methodology. Analysis also showed that, when the organisation identifier field was valid, there was little difference between this and the derived CCG.

The data quality of this field is currently not of a standard that improves the measure; the data quality of this field, and other fields like it, will need to be improved before it can be reliably used to assign valid CCGs.

Children and Young People Receiving Second Contact With Services measure methodology and limitations

This publication reports the number of children and young people receiving at least two contacts (including indirect contacts) and where their first contact occurs before their 18th birthday and their second contact occurs during the reporting period.

The methodology for this measure was updated for the 2019-20 reporting year with one major change – the inclusion of XenZone/ Kooth data following the approval of NHS England – this change has brought with it a number of small changes to capture their activity.

For XenZone/ Kooth:

The updated code is available in the metadata file.

Important limitations of this methodology

The major limitation of including the XenZone/ Kooth data within the measure is the risk of double counting and the unknown level of double counting.

The MHSDS uses an algorithm using patient information to produce a unique identifier for each patient; this identifier is then used to identify a patient with two contacts with a service. XenZone/ Kooth is a provider of an anonymous online service; this means our usual method of identifying patients (and those that have two contacts) does not function for XenZone/ Kooth submitted data.

As such we may identify a patient as having two contacts and then also identify the same patient as having two contacts with XenZone/ Kooth because we cannot determine that they are the same patient.

There is currently no estimation of the scale of this double counting. NHS Digital are investigating possible methods to estimate or quantify this.

As a result, this measure is to be treated as experimental and used with caution, considering this limitation.

Delayed transfers of care measures methodology

The existing measure MHS26 Days of delayed discharge in RP has been updated to bring it in line with NHS England guidance.

The measure now excludes the first midnight of the delay period which was not previously the case. Additional breakdowns have also been included for delay reason, delay attribution and Local Authority (LA) of responsibility. Providers are asked to supply this data; where a valid LA code has been supplied, this is used, if there is no LA code or the supplied code is invalid then the LA is derived from the persons address, if this is not available then it is classed as unknown.

An associated VODIM measure has also been created to indicate the use of appropriate LA codes. NHS digital are working with providers where known data quality issues exist.

72 hour follow up measures methodology

Three new measure have been created for 72 hour follow up:

  • MHS78 Discharges from adult acute beds eligible for 72 hour follow up in the reporting period
  • MHS79 Discharges from adult acute beds followed up within 72 hours in the reporting period
  • MHS80 Proportion of discharges from adult acute beds eligible for 72 hour follow up - followed up in the reporting period

Those eligible for follow up are defined as having been in an acute bed and have been discharged to home or a new ward in the last three days of the previous month and all but the last three days of this reporting month.  All measures are available at national, provider and CCG of GP Practice or Residence level. In this instance provider is classed as ‘Provider of Responsibility’ as it is the responsibility of the provider to ‘follow up’ the patients moved from the acute bed not the individual site. Note patients who have died are excluded from this measure.

Restrictive interventions measures methodology

Two new measures have been added to the monthly release, these are available in standalone files available in the monthly release: 

  • MHS76 Count of people subject to restrictive interventions
  • MHS77 Count of restrictive interventions

Previously restrictive interventions were reported on in the Mental Health Annual Bulletin and in the Learning Disability Services Monthly Statistics.

The two new measures apply to all patients in MHSDS. Both measures include breakdowns by provider, provider type, CCG by restrictive intervention type. The person count measure also includes breakdowns by patient demographics; age group, ethnicity and gender. Note as a person can be subject to more than one restrictive intervention the sum of types of restraint can be greater than the total number of people.

Approach to collection of ward stay information to inform inpatient activity analysis

There are distinct types of ward configuration and service provision within mental health, learning disabilities and autistic spectrum disorder inpatient services that cater for people with distinct needs. It is important to be able to understand this variation, particularly in context to different pathways of care, to ensure that inpatient capacity is effectively used to deliver mental health services. This is relevant in a wide number of strategic and operational areas in mental health services including; understanding Out of Area Placements, Delayed Transfers of Care, length of stay, and ensuring an optimal balance of care between inpatient and community-based services.


This has introduced the case for specifying a comprehensive list of ‘hospital bed types’ to define this element of variation within the system.

Development of ‘hospital bed type’ categories


The NHS Benchmarking Network (NHSBN) has been collecting inpatient activity by bed type for a number of years and the adult mental health categories used were agreed via a consensus exercise, led by the NHS Confederation Mental Health Network in 2012. These suggested categories are now familiar with providers and are used as a currency in national benchmarking assessments.


Categories for children and young people’s inpatient mental health services have been identified and are described further in NHS England’s Child and Adolescent Mental Health Services (CAMHS) Tier 4 Report (https://www.england.nhs.uk/wp-content/uploads/2014/07/camhs-tier-4-rep.pdf ) as well as being used in NHS England’s specialised commissioning contract specifications.


Whilst learning disability wards broadly map to the NHSBN categories, work is in progress by NHS England to consult and define further where required.

Development of central derivations


Using the provided ‘hospital bed type’ categories and associated definitions, NHS Digital commenced development of derivations aiming to centrally derive this information using existing data within the MHSDS. The continued collection of Ward Setting Type, Ward Security Level, Clinical Care Intensity and Treatment Function Code allow a detailed understanding of the configuration of the inpatient ward and the service delivered.

NHS Digital is currently using these derivations to produce information from MHSDS about people in adult acute inpatient care (including adult acute and Psychiatric Intensive Care Unit (PICU) beds) and specialised adult inpatient services (secure beds plus specialist mother and baby and eating disorder units). The derivation uses methods developed through consultation with provider organisations in 2014 and used in some experimental analysis from the Mental Health and Learning Disabilities Data Set (MHLDDS).


A need exists to consolidate reporting requirements to ensure that burden is minimised for data submitters.

Identifying and agreeing a solution for national reporting


Two options of obtaining the required information through the MHSDS in the long term were put forward for consideration and agreement for national reporting:
1.    Option 1 - Direct collection of Hospital Bed Type for adult and CYP mental health and learning disabilities
2.    Option 2 - Central derivation of such categories using existing defined properties of the Ward and service provision

Consultation outcome


NHS Digital consulted on MHSDS v2.0 requirements with a wide range of stakeholders throughout 2016 through public consultations, events and workshops. NHS England has also provided feedback from separate NHS Benchmarking Network consultations.


From feedback presented, a preferred solution was not directly identifiable and both methods provided a mixture of opinion across stakeholder groups. For example, direct collection would provide a more transparent analysis method but could produce ambiguities in the data set where the bed type is not consistent with other recorded properties such as Ward Security Level.


In the absence of a single preferred solution, a recommendation was made by the Independent Standards Assurance Service (ISAS) to provisionally dual run both solutions as a pilot exercise. This approach was agreed with senior representatives of NHS England, DH and NHS Digital and subsequently accepted by the Standardisation Committee for Care Information (SCCI); SCCI was superseded by the Data Coordination Board (DCB) on 1 April 2017.

MHSDS v2.0 Approach – ‘dual running’ pilot


In order to ascertain explicitly the best solution to collect the required information for all three service areas and to ensure the resulting categories are comprehensive and fit for purpose, both identified solutions have been ‘dual run’ for a limited period of time within the MHSDS.

Discharges from adult acute beds followed up within 72 hours


New statistics regarding discharges from adult acute beds followed up within 72 hours were introduced in the Performance April, Provisional May 2020 edition of this publication series. The new statistics are:


•    MHS78: Discharges from adult acute beds eligible for 72 hour follow up in the reporting period
•    MHS79: Discharges from adult acute beds followed up within 72 hours in the reporting period
•    MHS80: Proportion of discharges from adult acute beds eligible for 72 hour follow up - followed up in the reporting period


An assessment was carried out as part of developing these statistics to determine which option for determining ‘hospital bed types’ would be the most appropriate method. It was determined that the directly collected hospital bed type information was the most appropriate method, and as such this has been implemented for these statistics.

Future developments


All other statistics in this publication series relating to hospital bed types are still based on centrally derived categories using existing defined properties of the ward and service provision. These statistics will be assessed individually in future and will be migrated to using the directly collected hospital bed type information if the assessment finds it is appropriate to do so.


Further development of the directly collected hospital bed type information may be required before all statistics in this publication series relating to hospital bed types can be migrated to this method. For example, the relevance of the currently available categories when applied learning disabilities and autism inpatient services may need further investigation.


NHS Digital will provide updates on these developments in future editions of this publication series.

Data validation

MHSDS data is validated in stages.

Firstly, the data is validated at the point of submission, for each provider. If file-level validation checks are not passed the provider will receive a file-level rejection report. If file-level rejection is passed, the data are successfully submitted but the provider will still receive a report containing details of field-level errors and warnings. These can be investigated, corrected and further submissions can be made within the submission window.

For submitted data, NHS Digital publishes two types of data quality reports in this publication series. By publishing data from both ‘provisional’ and ‘performance’ submissions, providers can review issues identified in a ‘provisional’ submission and investigate and resolve them for a ‘performance’ submission.

The first type of report is a coverage report. This shows the number of records successfully submitted by each provider, for each data table in the MHSDS. When viewed in time-series format in our Power BI reports, this also provides intelligence on the consistency of submissions and enables outliers to be identified.

The second type of report is a ‘VODIM’ report. This classifies each record into five categories; Valid, Other, Default, Invalid, Missing. NHS Digital is expanding the number of items for which VODIM reporting is available. This file also includes a number of Integrity measures. This information is also available as a Power BI report.

In addition to these reports NHS digital also publishes a Submission Report that provides additional information, especially around the use of the Multiple Submission Window Model. 

Dissemination

These statistics are disseminated via the NHS Digital website.

Monthly statistics are disseminated from data collected in ‘provisional’ and ‘performance’ submission windows for each month. At reporting year end, monthly statistics will be disseminated as a 'final' version from the latest submitted data throughout the year collected as part of the Multiple Submission Window Model. The ‘provisional’ data are designated as provisional and the ‘performance’ as performance data.

The data are also disseminated in the annual Mental Health Bulletin, which contains reporting based on a financial year reporting period and additional analysis where resources permit.

Review

The statistics presented in this publication are currently designated as experimental statistics and, as such, remain under constant review; although major changes to methodologies are made between reporting years in order to preserve time-series. 

The Mental Health Analysis team welcomes any comments or feedback on the publication so please send any such communications to enquiries@nhsdigital.nhs.uk with ‘Mental Health Monthly Statistics’ in the subject.

Last edited: 15 July 2020 4:08 pm