What does a motorsport championship have in common with patient care? It's how data underpin the outcome for both. 

Over a race weekend, the McLaren-Honda team captures more than 12 billion real-time data points from 300 sensors located on each car, these sensors help the team behind the driver measure and improve performance. Similarly in today's healthcare, data underpin patients' treatments – from multiple monitoring systems that provide an insight into a patients' condition in ICU or surgery, to daily records of patients' sugar level and blood pressure that can help clinicians fine-tune medication dosages.

The similarities on the race track and in the hospital are not lost on like-minded individuals looking for answers to better healthcare. Dr Jai Rao, Consultant, Department of Neurosurgery, NNI, started pursuing a cross-industry collaboration with McLaren Applied Technologies, the company behind the predictive data analytics technology used by Formula One teams, when he realised in a chance meeting two years ago that McLaren's data analytics suit for motorsports could also be applied in the healthcare setting.

"We want to interpret variability to be more predictive rather than reactive. We should be able to anticipate when to provide treatment, rather than wait for the condition to actually declare itself."

- Dr Jai Rao, Consultant, Dept of Neurosurgery, NNI

On 2 November 2016, NNI and McLaren Applied Technologies signed a memorandum of understanding to explore translation of motorsports predictive analytics to neurological care.

At the occasion, Assoc Prof Ng Wai Hoe, Medical Director of NNI, shared, "We have lots of health data we can acquire from the patients. The question is, how do we make use of it? With the capability for data analytics provided by McLaren, we can make sense of the data we have and use it to improve protocols."

"This highly configurable, companion technology platform is inspired by racing, and can be designed to engage, capture and measure improvements in health outcomes," Lim Kok Leong, Regional Director of McLaren Applied Technologies, APAC, said.

Potential application for brain injuries

Gait is a commonly-measured parameter in the treatment of chronic brain disease patients, such as normal pressure hydrocephalus, and a significant factor in determining the success of its treatment.

The current method of diagnosis and follow-up treatment for normal pressure hyrocephalus relies on timing a patient for a walking test and other assessment methods such as going through the patient's history, ordering CT scans and MRI scans. The data collected through these methods are limited, given the short span of a clinical consultation.

To counter that, new technology developed with McLaren can offer continuous monitoring through wearable devices sensing heart rate, blood pressure or even the muscular skeletal system in real time.  Dr Rao said, "We can pinpoint the best time to intervene by monitoring a patient at home. Consistent monitoring also eliminates possible inaccuracies due to patient anxiety during clinical tests."

Another area where the technology can be applied is in Traumatic Brain Injuries (TBI). Dr Rao explained, "A TBI patient is typically set-up with multiple monitoring systems to observe his recovery. But we need to reinvent the current system to personalise treatments based on each patient's health data, because no two TBI patients are alike."

He continued, "We want to interpret variability to be more predictive rather than reactive. We should be able to anticipate when to provide treatment, rather than wait for the condition to actually declare itself."

A new perspective

The application of personalised activity-based monitoring, predictive analytics and data management technology can advance neurological care exponentially by forecasting treatments and raising care outcomes beyond brain injuries.

Dr Rao said, "We hope to predict outcomes. When the data shows that the patient's condition is worsening, clinicians can intervene before it's too late."

He added, "Our five-year collaboration with McLaren Applied Technologies has potential to help patients across the neurological continuum and even other diseases."

How does predictive data analytics work in healthcare?

Step 1. High quality data is captured through sensors (for example, in the ICU or in patient's home).

Step 2. McLaren's predictive data analytics technology analyses the information and predicts possible outcomes using simulation and modelling.

Step 3. Health providers use the information and make decisions to intervene, provide preventative measures or prepare for the eventual outcome.

Step 4. The loop is closed by recording the response to intervention, and using the data to refine the software's algorithms and optimise future treatments.