果冻影院

The team, led at 果冻影院H by聽Drs Steve Harris,聽Tim Bonnici and Mark White,聽were highly commended by Health Data Research UK and were placed in the top 3 nationally for their Team of the Year award.

During the pandemic, 果冻影院H became one of the intensive care unit (ICU) surge centres, supporting a network of five north London hospitals. This meant expanding our own ICU beds and staff, and deploying a mobile transfer team to retrieve critically ill Covid-19 patients from smaller, overstretched ICUs.

To help manage critical care beds, staff and equipment, the 果冻影院H team rapidly prototyped and rolled out a live 鈥榮itrep鈥� bed management tool which reported in near real time.

The tool supported 434 critically ill patients across north London and helped enable 162 patients to be transferred to the 果冻影院H surge centre from overstretched units across north London. It allowed staff to be allocated where they were most needed and ensured transfer beds were always kept available.

The tool was deployed to new 鈥榮urge鈥� ICUs at the National Hospital for Neurology and Neurosurgery and at Westmoreland Street, and to specialist emergency and respiratory wards as the pandemic progressed. It became the 鈥榞o to鈥� bed management tool and remains in use at 果冻影院H today.

The tool is based on the Experimental Medicine Application Platform (EMAP),聽which through the generous support of 果冻影院H Charity聽was developed by a multidisciplinary team at 果冻影院H in the two years leading up to the pandemic. EMAP鈥檚 aim is to make health care data available for research and innovation in near real time, to speed up clinical decision making and help resource management across entire hospitals.聽

Traditionally insights from data have lagged behind 鈥� with hospitals working on the basis of data that is days or sometimes months old.

EMAP was developed thanks to a collaboration between clinicians, researchers, and software engineers, with the support of the 果冻影院H Biomedical Research Centre and 果冻影院H Charity.

Dr Harris said: 鈥淲e don鈥檛 just want an EHR, we want a system which enables digital health technology interventions, which allows your machine learning or AI to actually do something at the bedside to directly improve patient care or support the processes around that care.鈥�

Key characteristics of the EMAP team include its diversity, including not just software engineers and clinicians but a healthcare designer and a behavioural scientist 鈥� who play an invaluable role in looking at how users actually relate to dashboards.

Members also get to understand each other鈥檚 worlds with engineers spending time on the critical care unit and clinicians receiving data science and software design training.

EMAP is now being used to look at antibiotic stewardship, managing anti-microbial resistance, identify patients with heart failure patients, and provide ward-level forecasts of bed demand.

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