The healthcare sector often lags behind other industries when it comes to technology adoption and implementation. The complexity and fragmented internal structure of healthcare organisations limit their ability to adopt IT that is consistent across the organisation.
Not only do different departments have different refresh cycles for legacy systems, they also require investment at different times. For example, the radiology department might be due an IT refresh this year, while the cardiac team is two years away from doing the same thing. Indeed, these internal teams will tend not to share infrastructure for common needs such as document storage, with the resulting siloes leading to a great deal of redundancy and waste.
Hospitals are now taking increasing interest in modern, shared IT resources, including cloud, due to limitations on physical space and the need to manage and reduce costs. As ever, security concerns, regulation and compliance will impact what they can do.
At the same time, increasing the quality of patient care while keeping costs down is difficult. Even if medicine and surgical procedures have become more sophisticated, the systems supporting the patient experience are limited – whether it’s struggling to share X-rays over an ageing PACS system or difficulty in prescribing the right medication for a patient with a very specific medical history and set of symptoms.
Given the context provided by these challenges, precision healthcare, in which better use of data and applications of analytics can enable much more personalised patient care, is likely to be the next wave of innovation to impact the sector.
As well as the potential to improve patient care, precision healthcare is gaining traction due to the scope it has to meet the increasing cost challenges within healthcare.
Consider a clinical trial in which a combination of two drugs is successfully used to treat a type of cancer. While the majority of patients respond positively to the treatment, a significant proportion fails to respond to the therapy, while also experiencing unpleasant side effects.
Precision healthcare would identify which patients would be most likely to benefit from the therapy, meaning fewer people are subjected to the side effects. There are also significant cost savings through minimising the number of occasions where treatment is given to people unlikely to benefit. The level of savings is clear when you consider that a typical early phase trial in oncology can cost $120,000 per patient in 2014, according to global contract research organisation Clinipace Worldwide.
In order to deliver precision healthcare, hospitals need to draw on insights from vast volumes of patient and genomics data. And this will require healthcare IT systems and data to be better aligned and integrated. There are also operational challenges that clinicians and healthcare IT professionals face each day, such as sharing data efficiently to improve the quality of patient care and reducing ‘data overload’ when physicians are confronted with a plethora of data points for each individual patient.
If hospital chiefs are to tackle these challenges and deliver precision healthcare they must take the following steps to modernise their IT infrastructure by:
- End the siloes -In most healthcare organizations, storage is typically deployed and managed by different departments. This may lead to spare capacity for some sets of data while other storage instances need to be upgraded continuously. With a siloed approach to storage, extra capacity cannot be shared, impacting CAPEX and OPEX costs. Reducing this cost burden requires a major effort to consolidate and re-architect the organisation’s underlying infrastructure. To do this, hospital IT leaders need to get past any concerns they have about single points of failure, and, as a result, systems need to be built with better resilience in mind. Patient data must also be consolidated without sacrificing the performance delivered by dedicated departmental systems. By having more than one point of failure, as well as strong back-up, business continuity and disaster recovery plans in place, hospitals will have more confidence in consolidation, and thus be better equipped to deliver precision healthcare.
- Expand the data lake to make better decisions – For many hospital IT leaders, often ‘data’ is synonymous with PACS data – historically one of the biggest data hogs in medical IT. In addition, there are now numerous devices and platforms to monitor and track people’s health. Increasingly, we need to incorporate data from other healthcare applications and draw it all together for analytics to deliver the level of insight needed for precision medicine. For example, clinicians need to access data from genomics research, medical Internet of Things devices, and even from social media. Crucial to pulling this information together in a usable way and therefore providing more personalised care, are data lakes, which aggregate huge volumes of unstructured data of different types and formats and to make it readily accessible by advanced analytics tools. Scale out solutions can also play an important role in giving the flexibility that hospitals need to cope with changing data volumes.
- Build a secure collaborative platform – Healthcare CEOs must streamline the process of looking at data from different sources and from outside their own organisation. Using cloud resources can help facilitate the sharing across organizational boundaries. This will also help bring in additional types of data, as mentioned previously, allowing hospitals to link information beyond their current systems, and drawing on insights from the latest However, by increasing the number of channels through which data can be accessed, hospitals could potentially expose information assets to potential risk. They must therefore have clearly-defined cloud security architectures in place that address existing security and compliance requirements with new policies, processes and technology. Advancements in software and APIs to new data sources will allow medical professionals to use these shared datasets to provide more predictive care, offering a better service to patients and improving quality of care.
- Turn data into an asset – With medical health records being retained for decades, organisations need the capability to store, manage and analyse vast amounts of data. Healthcare organisations must turn the data they have into an asset for services and patient care delivery – and they can do this by using analytics to gain new insights. Identifying the most important information, at the right time, will be key in delivering precision data. The only way to store this vast amount of data and make it available for analytics is through an expanded data lake complemented by managed cloud resources in their – or a local, compliant provider’s – care. By integrating on-premise systems with the cloud, hospitals will be able to move data between environments (in compliance with data protection requirements), ensuring it can be easily accessed when needed, without using precious in-house resources when not required. The arrival of private, rapidly-scalable cloud services makes building your own cloud capability extremely cost-effective as a hospital or hospital group. Going through the analytics process and working in a data lake will also help to reduce the amount of duplicate data stored, lowering operational costs further.
The insight generated by data is of paramount importance, so hospitals must make data accessible to analytics applications that can turn reams of data into insight in real time. This means supporting healthcare applications with multiple siloes in a data lake, utilising third party data, building a platform that supports secure collaboration and data sharing, and, fundamentally, changing the patient experience.
Data is an asset that healthcare organisations can use to help provide precision care, but the challenge is learning to cope with its unprecedented growth, and overcome the sector’s legacy siloes. With a growing and ageing population, alongside the persistent threat and high costs of chronic disease, transformation can’t come soon enough.
