- This project will commence in September 2017 and run for 15 months.
- Run by East Kent Hospitals University NHS Foundation Trust, in partnership with the University of Kent.
- Aiming to streamline the non-elective patient pathway to improve health and social outcomes.
- Hospital datasetswill be combined to provide doctors, nurses and allied health professionals with predicted clinical and social outcomes for patients based on the previous experience of similar patients.
The health care setting is becoming more complex and hospital patients often have multiple health problems. Although increasing amounts of clinical, laboratory and risk-scoring data are available, interpreting these to establish a patient’s health and social care needs can be difficult.
This project run by East Kent Hospitals University NHS Foundation Trust seeks to provide context to the multiple data sources available with the aim of improving acute care and streamlining the non-elective patient pathway through the Trust.
This will be achieved by combining hospital datasets and using ‘patient matching’ to provide doctors, nurses and allied health professionals with predicted clinical and social outcomes based on the previous experience of similar patients. Examples include providing predicted death rate, intensive care unit use or length of stay in hospital.
A unique feature of this approach is that it provides data to the point of care early in (and throughout) the patient’s stay, in real time, using an existing mobile communication platform developed by the Trust.
Ensuring that patients receive the most appropriate care, in the most suitable environment, earlier in their hospital stay has the potential to improve outcomes and reduce length of stay.
This intelligent interpretation and application of data to provide an estimate of pre-defined outcomes has not been previously applied broadly in clinical settings.
The accuracy of the approach will be determined by comparing actual with predicted patient outcomes. The results could be of national significance, particularly in the context of increasing amounts of data being collected electronically.