Register your project for Clinical Record Interactive Search (CRIS)

What is CRIS?

Clinical Record Interactive Search (CRIS) provides a means of analysing de-identified data from the Oxford Health NHS Foundation Trust (OHFT) electronic patient records.  CRIS unlocks and transforms clinical data held in Trust systems to provide a rich and pseudonymised resource allowing researchers and clinicians to investigate hypotheses and identify patient cohorts. CRIS also provides an invaluable tool for service evaluation and clinical audit.

Oxford Health NHS Foundation Trust are also part of the CRIS Network.  This is a group of highly innovative NHS Mental Health Trusts who are working together to accelerate research work in dementia and mental health.  For further information on this network and its members please see the CRIS Network website.

Access to clinical information is clearly a sensitive issue and a security model was developed which has been considered and approved by the Oxford Health NHS Foundation Trust Caldicott Guardian and the Trust Executive.

Clinical Records

Trust Electronic Patient Record (EPR) systems hold a wealth of useful patient data. CRIS transforms this information into a pseudonymised database appropriate for research, service evaluation and clinical audit use.

Data Transformation

The transformation of data enables CRIS users to access the wealth of information recorded during patient care by healthcare professionals. This includes data recorded in coded and structured form, for example dates and numbers, plus data held in unstructured free text form, for example, within written assessments, progress notes and correspondence. After transformation, free text data can constitute a large part of the content of information held within CRIS, although this will depend on the amount of unstructured data held in the source EPR system.

The transformation process uses the patient’s EPR system identifier to derive a unique ID for each patient in the database. This ID does not allow CRIS users to identify patients. However, where patients have given appropriate consent, the ID can be used by authorised personnel to contact patients who have been identified as potential recruits to an ethics approved research project.

How can I access CRIS?

Access to CRIS requires either an NHS contract or a Research Passport.

If you have an NHS contract that is not with Oxford Health please contact the HR department within your own Trust and ask them to prepare an NHS to NHS Proforma.

Requests for access to CRIS should be emailed to Users are required to agree to the UK CRIS Terms and Conditions prior to being granted access to CRIS.

Once your right to access CRIS has been approved you can register your CRIS project.

Registering a CRIS Project

To register your CRIS research project please download the research registration form and email your completed application to A member of the CRIS team will then contact you to establish the feasibility of your CRIS question.  To assist you in determining your approach to interrogating the data we have produced a sample data plan which can be found here.

For a service evaluation or clinical audit, please visit the Trust Clinical Audit pages to download the relevant application form. To determine whether your project is Research, Service Evaluation or Clinical Audit please click here.

Additional information regarding the suggested content for the ‘Summary, Research and Scientific Justification’ fields, please see here for further information.

Once your project has passed feasibility your project will be formally registered on the CRIS system by a member of the CRIS team.  Your project will then be submitted to the CRIS Oversight Group to seek their approval.

Access to the CRIS Secure Environment – UKSeRP

Access to the CRIS facility is via a secure private network on a research platform with UKSeRP.  Once your right to access CRIS has been approved the CRIS Admin team will set up your UKSeRP user account.  This will enable you to apply for a CRIS user account, access to the CRIS facility along with statistical analysis software and your project files.

Creating a CRIS User account

In addition to a UKSeRP user account, see above, a CRIS user account will also be required by all project lead CRIS researchers.  This will enable the formal registration of your CRIS project to the CRIS system.

To obtain a CRIS user account, log on to UKSeRP and access CRIS via the UK-CRIS desktop icon.  From the CRIS home screen select ‘Register’ to submit a user application, which will be approved by a member of the CRIS Admin team.  The CRIS Admin team will register your CRIS project once it has passed feasibility and you will automatically be added as a project user.

CRIS Navigation Training

A training package which provides information regarding the navigation of CRIS and how to conduct a basic and advanced search is available via the CRIS Network website which includes forums, useful documentation and information relating to the CRIS Network.  It may be accessed from any computer. All CRIS Users should register for a CRIS Network account which will then allow them to view the training documentation.

Once registered you can log in and access the CRIS user training here.

Security Requirements of CRIS use

CRIS can only be accessed from the OHFT network.  Data from CRIS must be kept within the OHFT firewall and can only be saved on the CRIS shared drive on OHFT computers. CRIS data CANNOT be saved on personal or encrypted USB sticks. CRIS data must not be emailed from OHFT machines to your personal email or a University email. Please be aware that additional permission is required for derived data to be analysed outside of the OHFT firewall, from the CRIS Oversight Group.  CRIS researchers are only permitted to access their own CRIS Project folders and files located either within the CRIS Remote Desktop or the G:OxfordshireCRIS Projects.  Access is not permitted to other projects folders and files.  Please also note that currently SPSS and R are the only statistical programmes that are available within the Research and Development Team.

The security model includes regular audits of searches carried out using CRIS (all searches by all users are recorded and can be audited). For this to be possible, we keep a record of all projects carried out involving CRIS analysis along with general specification of the type of searches which will be required.

Ethics and research governance approval assume anonymity of the data analysed.  As with any dataset, there is the potential within this database to compromise anonymity by generating unique variable combinations or rare categories. CRIS users are asked to consider whether this issue may occur and strategies to avoid compromising anonymity.  Alternatively they may wish to obtain specific ethics approval for an analysis where this risk is likely to be significant. Searching under clinicians’ names are a sensitive issue; this type of information in research would have to be justified.

CRIS Application Approval Process

The CRIS Oversight Group, led by the Trust Caldicott Guardian will review all requests to use CRIS as a de-identified database. It is important for the Trust to demonstrate that OHFT clinical data are used responsibly and for projects with demonstrable research and clinical importance.

The future of CRIS, as with other aspects of OHFT research, depends on successful bids for future funding. This in turn requires evidence of use of the database, hence the need to keep a record of individual projects.

The CRIS Oversight Group has a role in facilitating CRIS analyses and to advise on how best to extract robust data. The database is potentially complex and users will be encouraged to collaborate and share expertise and hands-on experience. The information submitted in the project application form will be used to provide a database for this purpose to assist future researchers.

Collaborations and Grant Applications for CRIS use

All work, which requires the use of CRIS must be reviewed and approved by the CRIS Oversight Group.  This should be taken in to account when completing any applications or considering a collaboration, which require the use of CRIS data.  Failure to inform the CRIS Oversight Group of a grant, research application or collaboration may result in the project being declined.

Need further help?

If you have any questions please email

CRIS search ideas - Top 10's

Below are links to the Top 10 priorities for future research in mental health, agreed by the Priority Setting Partnerships (PSP).  Why not consider conducting a CRIS search to answer one of these questions.

James Lind brings patients, carers and clinicians together in Priority Setting Partnerships (PSPs) to identify and prioritise the Top 10 uncertainties, or unanswered questions, about the effects of treatments.

The aim of this is to make sure that health research funders are aware of the issues that matter most to patients and clinicians.





Eating Disorders


CRIS privacy and GDPR

How are patient details protected?

CRIS information is held securely with strict arrangements about who can access the information.  This will include Trust staff, clinicians and approved researchers.  The information will only be used for the purpose of health and care research, service evaluation, clinical audit or to contact you about future opportunities to participate in research.

Where there is a risk that you can be identified your data will only be used in research that has been independently reviewed by an ethics committee.  For further information on ‘patient information and health and care research’ see the Health Research Authority (HRA) or for CRIS specific information see our CRIS Privacy Notice

Ongoing CRIS projects

Below are links to the CRIS projects currently being led by researchers at Oxford Health BRC.

Each project includes a lay summary and are arranged by their relevant research theme.  For completed and published CRIS projects please view our publications tab.


  • New Mind 2
  • Prediction of death, nursing home use and admission in the older population using routinely collected data
  • Validation of UK Biobank Data for Mental Health Outcomes: A Pilot Study Using Secondary Care Electronic Health Records
  • Enabling earlier and more accurate diagnosis in Alzheimer’s disease (AD)
  • ORCHARD-CRIS Dementia
  • Care factors in early and late-stage dementia disease


  • Body Dysmorphic Disorder (BDD) and its association with suicidal ideation (forming ideas or images), self-harm and suicide.

Mood disorders

  • A feasibility study on an automated identification of potential patients with treatment resistant depression (TRD) for studies being run in Oxford.
  • Prevalence of Treatment Resistant Depression (TRD) in Child and Adolescent Mental Health Services (CAMHS) for 11-18 year olds
  • Difficult to Treat Depression


  • Patients with psychosis who are parents to children under nineteen
  • Measuring the fidelity of Early Intervention in Psychosis interventions using Natural Language Processing to improve the prediction of relapse in First Episode Psychosis
  • A study estimating long-term rates of relapse, patterns of health outcomes, mental health service use, and moderating factors in patients with psychosis.


  • Feasibility, acceptability and validation of OxMIS, a novel suicide risk assessment tool: using natural language processing in CRIS for external validation

Multi morbidity

  • Diabetes in Mental Health
  • Rare side effects of psychotropics bone marrow toxicity and dysphagia

General psychiatry

  • Discriminating N-Methyl-D-Aspartate Receptor-antibody encephalitis (NMDAR-Ab-E) from primary psychosis


Peer Reviewed


Puntis S, Whiting D, Pappa S, Lennox B. Development and external validation of an admission risk prediction model after treatment from early intervention in psychosis services. Translation Psychiatry. 2021 Jan 11; 11(1):1-11

Puntis S, Oliver D, Fusar-Poli P. Third external replication of an individualised transdiagnostic prediction model for the automatic detection of individuals at risk of psychosis using electronic health records. Schizophrenia Research. 2021 Feb 01; 228:403-409


Gligic L, Kormilitzin A, Goldberg P, Nevado-Holgado A. Named entity recognition in electronic health records using transfer learning bootstrapped Neural Networks. Neural Networks 2020 Jan: 121:132-9. doi:10.1016/j.neunet.2019.08.032

Goodday SM, Kormilitzin A, Vaci N, Liu Q, Cipriani A, Smith T, Nevado-Holgado A. Maximizing the use of social and behavioural information from secondary care mental health electronic health records. Journal of Biomedical Informatics 2020 Jul: 107:103429. doi:10.1016/j.jbi.2020.103429

Iqbal E, Govind R, Romero A, Dzahini O, Broadbent M, Stewart R, Smith T, Kim C-H, Werbeloff N, MacCabe J, Dobson R, Ibrahim Z, De Luca V. The side effect profile of Clozapine in real world data of three large mental health hospitals. PLOS ONE. 2020 Dec 08. doi:10.1371/journal.pone.0243437

McDonald K, Smith T, Broadbent M, Patel R, Geddes JR, Saunders KEA. Prevalence and incidence of clinical outcomes in patients presenting to secondary mental health care with mood instability and sleep disturbance. European Psychiatry 2020 Apr 27: 63:e59. doi:10.1192/j.eurpsy.2020.39

Vaci N, Koychev I, Kim CH, Kormilitzin A, Liu Q, Lucas C, Dehghan A, Nenadic G, Nevado-Holgado A. Real-world effectiveness, its predictors and onset of action of cholinesterase inhibitors and memantine in dementia: retrospective health record study. The British Journal of Psychiatry 2020 Jul 27: 1–7. doi:10.1192/bjp.2020.136.Epub ahead of print

Vaci N, Liu Q, Kormilitzin A, Crescenzo FD, Kurtulmus A, Harvey J, O’Dell B, Innocent S, Tomlinson A, Cipriani A, Nevado-Holgado A. Natural language processing for structuring clinical text data on depression using UK-CRIS. Evidence-Based Mental Health 2020: 23:21–6. doi:10.1136/ebmental-2019-300134

Walker S, Potts J, Martos L, Barrera A, Hancock M, Bell S, Geddes J, Cipriani A and Henshall C. Consent to discuss participation in research: a pilot study. Evidence Based Mental Health 2020;23:77-82. doi:10.1136/ebmental-2019-300116



Senior M, Burghart M, Yu R, Kormilitzin A, Liu Q, Vaci N, Nevado-Holgado A, Pandit S, Zlodre J, Fasel S. Identifying Predictors of Suicide in Severe Mental Illness: A Feasibility Study of a Clinical Prediction Rule (Oxford Mental Illness and Suicide Tool or OxMIS). Frontiers in Psychiatry 2020 Apr 15: doi:10.3389/fpsyt.2020.00268


Breilmann J, Girlanda F, Guaiana G, Barbui C, Cipriani A, Castellazzi M, Bighelli I, Davies S, Furukawa T, Koesters M. Benzodiazepines versus placebo for panic disorder in adults. The Cochrane database of systematic reviews 2019 March 28: doi: 10.1002/14651858.CD010677.pub2


Hofer M, Kormilitzin A, Goldberg P, Nevado-Holgado A. Few-shot Learning for Named Entity Recognition in Medical Text. DeepAI 2018 Mar 11.

Page last reviewed: 21 September, 2021