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Central Hall, York University

Mental Health Services Data Set (MHSDS)


The current issues with COVID-19 have produced a fast-moving situation which continues to challenge the organisation of many events internationally.  We have therefore had to carefully consider the best way of dealing with this short course.  With many countries now facing lockdowns for unknown lengths of time, it is with great regret that we have taken the decision to postpone this course to a future date (dates to be confirmed). 

We sincerely apologise for any inconvenience caused in these extraordinary circumstances, and we look forward to continuing to provide our short course offerings to you in the future.



The Mental Health Services Data Set (MHSDS) is a mandatory dataset, which should record all contacts with secondary and specialist mental health services in England. The MHSDS covers services provided in hospitals, outpatient clinics and in the community, where the majority of patients are treated, and covers care for children, young people and adults. Data submission is mandatory for NHS funded care, irrespective of whether the service provider is from the NHS or the independent sector. 

MHSDS can be linked to the Hospital Episode Statistics (HES), the dataset covering hospital admissions in the English NHS. Note that in the same week, the Centre for Health Economics (CHE) will be offering a course about Analysing Patient-Level Data using Hospital Episode Statistics (HES).

The MHSDS was introduced in 2016 and replaced the Mental Health and Learning Disabilities Data Set (MHLDDS), changing the structure of the datasets and, for the first time, includes records on Child and Adolescent Mental Health Services (CAMHS). 

The MHSDS can be used for commissioning, audits, research, service planning, monitoring policies, performance management, benchmarking and payment systems. Users include policy makers, commissioners and researchers. 

The complexity of the data model makes the use of MHSDS particularly challenging. The datasets in the MHSDS present issues common to other health datasets (e.g. HES), such as complex coding, missing data, duplicates and costing challenges. Additionally, the data are not immediately amenable to analysis, which means that one of the first decisions to make is how to bring together the relevant information from the different datasets. Therefore, the use of the MHSDS requires a significant investment in learning about the data before being able to undertake meaningful analyses that can be relevant to the different potential uses and users of the data. 

Please note that the unique structure of the dataset might make it harder to translate the knowledge acquired to another dataset in a different country.

Researchers at the University of York who use MHSDS will introduce participants to the ways they have found to overcome the data challenges described above and will stimulate discussion to determine whether there are alternative ways of analysing the data. We will highlight data quality issues throughout the workshop and discuss their implications. There will be two hands-on sessions using an artificial dataset, where participants will be able to see what the cleaned and re-structured data look like and try some analyses on it. Stata code for the data preparation (not covered in the hands-on session) and the analyses will be provided. 

There will also be presentations by a policymaker, a mental health provider and a mental health commissioner on how the data are collected, quality checked and used.


The workshop aims for participants to understand:

  • how the MHSDS data are collected
  • the MHSDS data structure and how to manipulate it
  • how to identify patient groups
  • how to analyse key variables
  • the costing of mental health services using Reference Costs
  • the limitations of the data


This workshop is open to people working in the public sector, academia (including PhD students) and the private sector. It is suitable for analysts working in the NHS, commissioning organisations, health care researchers and consultancy companies. 

Whilst overseas applicants may be interested in this workshop, they should be aware that the exercises relate directly to the unique MHSDS, which is created for, and used in, England. 

Participants should have some knowledge of basic introductory statistics and familiarity with computer software (e.g. SAS, Stata, SPSS). In this workshop, we will be using Stata but other software users should not be discouraged. Code can be easily translated from one software to another. For more information about Stata and Stata resources please visit the Stata tab.

Workshop dates

Workshop dates

  • To be announced


Workshop programme

Preliminary Programme 

Day 1:  (11:00 – 17:30 + Dinner)

  • 10:40 – 11:00 Registration
  • Session 1         Workshop introduction and welcome
  • Session 2         Introduction to the dataset
  • Lunch
  • Session 3         Data collection and use by mental health providers
  • Session 4         Data use by mental health commissioners
  • Session 5         Discussion
  • Session 6         Data Overview
  • Dinner (19.00) 

Day 2: (09:30 – 16:00)

  • Session 7             How to identify patient groups (part 1)
  • Session 8              How to identify patient groups (part 2)
  • Session 9             Activity in the MHSDS and its cost
  • Lunch
  • Session 10           Application 1: Waiting Time Targets
  • Session 11           Application 2: Inequalities
  • Session 12           Closing Session. 16:00 Workshop finishes



The tutors for this workshop are researchers at the Centre for Health Economics, University of York

Maria Jose Aragon (Research Fellow)
Leonardo Koeser (Research Fellow)
Claire de Oliveira (Reader in Health Economics)
Rowena Jacobs (Professor)
Speakers from NHS Digital/NHS England - NHS Improvement, Clinical Commissioning Group, Commissioning Support Unit, Mental Health Trust



Before you register on this workshop, please ensure you have secured the appropriate funding from your Organisation.
Registration is done online by Credit/Debit Card for instant payment and a guaranteed secured place on this workshop (please note the University of York does not accept American Express cards).

If you or your Organisation cannot pay by credit/debit card, please email the workshop co-ordinator:

We regret that we cannot reserve or hold workshop places in advance of booking or payment.  


This workshop is supported by the Health Foundation. The Health Foundation is an independent charity committed to bringing about better health and health care for people in the UK.  

Fees are fully inclusive of tuition, lunches, workshop dinner and materials, but do not include accommodation. VAT is not payable. Transferring between workshops is not possible.

Fees £100

Cancellations and alterations

A full refund of workshop fees (less 10% administrative charge) will be made for cancellations received in writing at least one month prior to the workshop. Substitutes can be made but please email new delegate's details when known to Cancellations made less than one month prior to the workshops are non-refundable/non-changeable.

In the unlikely event that, due to unforeseen circumstances, the workshop has to be cancelled by the University of York, our liability is limited to the refund of workshop fees. We recommend delegates have adequate insurance cover to claim any travel or personal expenses.


Once registered, the workshop administrator will give further information about accommodation available on campus and in York in your registration confirmation. There are a large number of hotels and guest houses in York, and workshop participants will be personally responsible for making their own accommodation arrangements.


There is an abundance of Stata resources including the official Stata documentation, Stata books, the Stata Journal, the Stata Blog and Web resources. 

Different tutorials and lecture notes emphasise different coding aspects (data analysis, statistical analysis, etc.). While you can choose the one that looks most suitable for your programming background, we recommend the following because they emphasise data analysis and are simple.

Who to contact

Workshop dates

  • To be announced