The healthcare system has seen a move towards the digitisation of medical data over the past decade. Where it had previously been commonplace to store medical records in the form of handwritten or typed reports, the advancement of computer systems has precipitated the digitisation of clinical exams and medical records. Electronic health records (EHRs) have been beneficial in making patient data much more readily accessible, increasing efficiency as well as reducing the possibility of errors in prescriptions and examination results. The adoption of EHRs has increased substantially in recent years and this, paired with the development and usage of new health-monitoring devices and related software, has resulted in a huge amount of data being generated. This data can subsequently be analysed to provide key insights and novel strategies for healthcare. For instance, one can observe what treatments are most effective for particular conditions, identify patterns related to side-effects or hospital readmissions, and gain other important information that can help patients and reduce costs.
The financial incentive of improved patient outcomes has encouraged healthcare providers to share more data that can be analysed. As a result, the global healthcare analytics market has seen significant growth, being valued at 11.6 billion USD in 2018 and projected to reach 81.21 billion USD by s, exhibiting a Compound Annual Growth Rate (CAGR) of 27.5 percent during this period. North America currently has the largest share in the market (see Figure 1).
The value of big data analysis should not be underestimated: its applications can improve processes and enhance patient care, ultimately saving lives. Efficient staffing is one way in which big data can be of great importance. Having too many workers carries the risk of unnecessary labour costs, whereas understaffing can result in poor customer service, which may be fatal to patients. Therefore, having the right number of staff on shift is crucial. Analysis sing a dataset containing years’ worth of hospital admissions records can reveal relevant patterns in admission rates, which can then be applied to find the most accurate algorithms that predict future admission trends.
Data analysis is not only beneficial to healthcare providers and to cost-cutting but can also optimise the services delivered to patients. Wearable technologies continuously collect patients’ health data and send it to the Cloud, giving doctors crucial information about the health of the general public, which allows them to adapt their delivery strategies accordingly. Propeller Health, for example, is a company that uses inhalers with GPS-enabled trackers to identify asthma trends on an individual level, sending patients a personal forecast and medication reminders, as well as looking at larger population trends.
Another successful healthcare analytics firm is Flatiron Health, which uses big data and its cloud-based software platform to help hospitals, researchers and physicians across the US in their fight against cancer. Founded in 2012, Flatiron Health uses advanced algorithms as well as machine learning to convert unstructured oncology data from lab reports, audio files and digital copies of hand-written notes into structured data. It pulls out relevant insights from a mass of information to generate real-world evidence to improve cancer treatments. Multinational healthcare giant Roche acquired Flatiron Health for 2.1 billion USD in 2018, indicating the increasing importance of data processing in order to obtain insights that result in advantages such as reduced trial costs.
However, there are challenges associated with healthcare big data. Patient confidentiality is a key issue that may hinder its development, as various laws govern what patient information can be released with or without consent. The healthcare industry is also one of the most susceptible to data breaches, which poses an additional concern, and as such, it is critical that organisations implement security solutions by applying effective encryption schemes to protect their data. If these issues are addressed, big data initiatives have the potential to revolutionise healthcare. The companies that are able to develop innovative data capabilities and promote data transparency will gain a competitive advantage and drive the healthcare industry forward.
By Hortense Comon
Sector Head: Hermione Scott