A highly granular dataset of 11,267 deliberate self-poisoning admissions curated by PIONEER. The data includes demography, diagnostic codes (ICD-10 & SNOMED-CT), presenting symptoms, procedures (OPCS4 & SNOMED-CT, prescriptions, referrals, follow-ups, and outcomes. The current dataset includes admissions from 03-12-2015 to 30-12-2023 but can be expanded to assess other timelines of interest. This dataset provides a clear understanding of self-poisoning in relation to different patient characteristics. The data also provides the type of drug taken (narcotic, non-opiod etc) and where (home, street, industrial areas etc) . Furthermore, assessments can be made on the impact of mental health service referrals and the likelihood of readmission with a subsequent overdose.

Geography: The West Midlands (WM) has a population of 6 million & includes a diverse ethnic & socio-economic mix. UHB is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & > 120 ITU bed capacity. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”.

Data set availability:  Data access is available via the PIONEER Hub for projects which will benefit the public or patients.  This can be by developing a new understanding of disease, by providing insights into how to improve care, or by developing new models, tools, treatments, or care processes.  Data access can be provided to NHS, academic, commercial, policy and third sector organisations.  Applications from SMEs are welcome.  There is a single data access process, with public oversight provided by our public review committee, the Data Trust Committee.  Contact [email protected] or visit www.pioneerdatahub.co.uk for more details.

Available supplementary data: Matched controls; ambulance and community data. Unstructured data (images).  We can provide the dataset in OMOP and other common data models and can build synthetic data to meet bespoke requirements.

Available supplementary support: Analytics, model build, validation & refinement; A.I. support.  Data partner support for ETL (extract, transform & load) processes.  Bespoke and “off the shelf” Trusted Research Environment (TRE) build and run.  Consultancy with clinical, patient & end-user and purchaser access/ support.  Support for regulatory requirements.  Cohort discovery. Data-driven trials and “fast screen” services to assess population size.

Further information including technical details, coverage, format and standards, provenance and related resources can be found on the link below: