Six Benefits of Implementing a Big Data Strategy in Healthcare

Six Benefits of Implementing a Big Data Strategy in Healthcare

Posted on December 16, 2015 by TheStorageChap in Big Data and Analytics, Healthcare

Following on from my colleagues post “Why many healthcare organizations find it difficult to capitalize big data and how to escape the trap” I wanted to use this post to discuss six benefits of implementing a big data strategy in healthcare. The post is timely, as this is my first day back doing work related activity following a recent spinal operation in which I got to experience healthcare from the trenches.

Pressures on the health sector to improve efficiency, productivity and patient care with limited budgets and an aging population, continue to grow. One of the ways it can overcome these challenges is making better use of its data. For example imagine if you could use data analytics to find out patients at risk of readmission (3% – 11%), and then take the necessary precautions to help prevent this from happening.

By combining structured and semi-structured data from various sources, such as public records from social services data, doctor’s notes and medical records, information on diet from weekly food shopping bills and exercise details from patient gym memberships right through to R&D data including information from clinical trials data, the healthcare sector could make this vision a reality.

Here are the six benefits I believe will be key for implementing big data in healthcare:

  1. Prevent costly emergency hospital readmissions by using a specific algorithm to scan each patient’s electronic health record. Looking at data elements such as blood-pressure readings and blood-glucose levels, hospitals are able to see which patients are at higher risk of diseases such as heart failure. As a result they can then better target intensive follow-up care to those patients who need it most, rather than discharging at-risk people who might require expensive emergency readmissions.
  2. Predict and resolve diseases before they happen – with personal genomics whereby an individual’s genetic make-up is broken down and recorded to identify risk-markers for specific diseases. Companies like 23andMe have already been using this data to forewarn customers which chronic diseases they are more prone to. And the UK’s NHS is in the midst of its 100,000 genome pilot project, so it can establish how best to use genomic data in national health care. Early, pre-emptive treatment can be more effective and far less expensive than tackling the disease head on.
  3. Predict patient behaviour and provide preventative actions. By integrating data across the entire healthcare system, including content from different government and private services, medical professionals will be able to gain a much deeper understanding of individual patients; which in turn will allow them to predict likely behaviours and then recommend preventative measures. Insurance companies are already doing this by using the data generated by wearable devices such as activity trackers to determine how active people are being, and then to reward or incentivise healthier behaviour.
  4. Reduce fatalities in intensive care by using real-time streaming data to catch changes in a patient’s condition sooner before something irreversible happens. Hospital ICUs create about 100,000 different data points per patient per second, which makes it very hard for clinicians to keep up with nuanced changes in a patient’s condition. According to the Society of Critical Care Medicine this challenge may contribute to the 10-29% mortality rate in ICUs. Linking this complex data up to an AI system which is able to digest it at this speed significantly reduces that risk, while also helping to develop a financially and operationally sustainable bench-to-bed paradigm.
  5. Help reduce the volume of acute health incidents by capturing and analysing real-time data from medical monitors that automatically send alerts before issues occur. This technology is particularly useful when caring for an elderly population who may not require constant hospitalisation, but are at risk from falls, heart attacks and emergencies in the home. Hospitals can equip patients with devices which automatically alert community care-workers when there is a warning sign which usually preludes a serious incident i.e. an inconsistent heart rhythm before a fully-blow heart attack and collapse. By alerting community care-workers ahead of time they’re able to offer preventative treatment, which improves the patients quality of life and takes some of the pressure off of general hospitals by reducing the need for admission.
  6. Optimise care and administrative processes. Aside from the patient-focused cost and efficiency savings highlighted above, healthcare organisations can also gain a lot as a “business” in their own right by analysing data to reveal where incremental improvements can be made internally. One of the UK’s biggest supermarket chains used big data to cut its annual refrigeration cooling costs by 20% – the same principle could of course be applied to hospitals storing refrigerated vaccines and supplies. Or perhaps using emergency patient admission times to calculate more accurately when certain types of staff will be needed more than others and plan shift schedules accordingly i.e. Mondays are when there is often a surge of mental health admissions but fewer paediatric cases.

In my recent stay in hospital I was amazed by the use of paper and pen at every stage. From collecting pre-admission clinical data, monitoring patient vital signs and manually checking drug allocation against name and date of birth, there is a huge opportunity to digitise the data collected to streamline processes, free medical staff from mundane processes  and most importantly improve patient safety.

EMC research has shown that of all of the data available to organisations on average only 3% is being prepared for analysis, of that data only 0.5% is actually being analysed and less than 0.5% of that is actually being operationalised. Like many other industry verticals, Healthcare is just making use of the tip of the data iceberg, so clearly the potential of what is  hidden below the surface of the water is huge.

The key to getting the most value from their data is for healthcare organisations to better understand the art of the possible and to ensure they have the right infrastructure to support, share and analyse it.

What do you think? Feel free to tweet me or leave a comment below.