HAVEN

  • Research type

    Research Study

  • Full title

    Hospital Alerting Via Electronic Noticeboard

  • IRAS ID

    189622

  • Contact name

    Shahista Hussain

  • Contact email

    ouh.sponsorship@ouh.nhs.uk

  • Sponsor organisation

    University of Oxford

  • Clinicaltrials.gov Identifier

    WT-103703/Z/14/Z, Funder's reference number

  • Duration of Study in the UK

    2 years, 11 months, 31 days

  • Research summary

    Late recognition of deteriorating patients in hospitals causes treatment delays that result in increased mortality and morbidity. Despite widespread introduction of vital sign-based “early warning scores” deterioration of patients frequently goes unrecognised. Consequently, developing systems for early recognition of patients at risk of severe reversible deterioration has become a key goal for the NHS. The HAVEN Project aims to produce a hospital-wide IT system that enables a continuous risk assessment in all hospital patients, and predicts those at risk of deterioration.

    This IT system will use routinely stored electronic data from Oxford University Hospitals NHS Foundation Trust and Portsmouth Hospitals NHS Trust (including demographics, laboratory results and vital signs) to create this continuous risk assessment. At present, these different types of data are stored in different local databases, and are not integrated or displayed in a way that supports decision making or calculation of patient risk. The project will implement a system to gather the relevant data so that it can be used to gauge risk.

    Risk prediction algorithms will then be developed and validated, using the records of patients who were admitted to hospital and then admitted to an intensive care unit (ICU) after two or more days in hospital. The information about these patients illustrates the pathway from the first signs of deterioration on the ward to ICU admission.

    The algorithms will be used to create a prototype allowing clinicial staff to identify, rank, review and treat patients who, without acute medical intervention, will deteriorate requiring ICU admission. The prototype will be developed using Human Factors methods to determine the best way to present the information to support decision making.

    This project has potential to increase ICU bed capacity and save money by reducing the number of patients admitted from the ward because their deterioration was recognised quickly.

  • REC name

    South Central - Oxford C Research Ethics Committee

  • REC reference

    16/SC/0264

  • Date of REC Opinion

    13 Jun 2016

  • REC opinion

    Favourable Opinion