The amount of data employed by hospitals and health care organisations across the world is booming. As data-generating technologies proliferate throughout society and industry, hospitals must try to ensure this data is harnessed to achieve the best outcomes for patients. These IoT technologies include everything from sensors which monitor patient health and the condition of machines, to wearables and patients’ own mobile phones. The network of these machines means that clinicians have an overview of everything happening in the hospital, and can be alerted in real-time should an anomaly in the data reveal changes which need urgent attention.
This shift further towards data is radical for hospitals, thanks to its ability to support decisions made by doctors and ultimately improve patient outcomes. With the help of artificial intelligence (AI) and advanced algorithms, those professionals working in hospitals will soon see their capabilities advanced by data, in everything from the logistics of choosing which patient to prioritise to how best to support them through diagnosis and treatment. These technologies are changing the way society manages health care – leading to healthier citizens with a longer life expectancy.
Beginning to adopt new technologies
Healthcare providers and clinicians have never been slow to use technology to improve patient outcomes. They have, naturally, sometimes held back because of cost implications – MRI scanners are not cheap, for example. But they have always been quick to see the potential of new technology and to use it to improve patient care.
AI, however, has been slower to take off. Somehow, many hospitals and health care providers do not seem to be ready for decision-making supported by algorithms. Perhaps it’s a change of culture and a concern about the explainability of decisions supported by a "black box". Perhaps staff simply do not yet have the necessary skills and experience to take advantage of the insights locked into data. Whatever the reason, it has been a fairly slow start.
There is now, however, a groundswell towards data-driven decision making. A number of healthcare organisations have started to embrace AI and analytics. They have often begun with small-scale projects, but there is growing recognition that the future lies in personalised healthcare – and that this depends on data and analytics.
AI offers a unique combination of quality and safety for patients, better outcomes, and reduced costs. After all, getting the right medication or treatment quicker, with fewer side effects, is significantly cheaper than trying a number of expensive options first. It’s also far better for patients.
A shift in culture will take us into the future
Over the next three to five years, it seems likely that more and more healthcare providers will start to become data-driven organisations. This will, in most cases, require a change in culture. Providers must move towards acceptance of the process of using data to generate insights that then drive decisions. It’s likely that this acceptance will grow as organisations see what the early impact can be.
Providers will need to support the change in culture with changes in three other areas. The first is staff competence in using analytics and understanding the insights that emerge. It is vital that staff understand the recommendations from the decision engine and are able to explain these to patients and other staff. The second area is infrastructure. Hospitals will need suitable facilities and equipment to gather data and then analyse it.
A successful data strategy starts now
A successful data-driven hospital needs to centralise its data strategy for business operations and care.
This means that healthcare providers must develop strong data and model governance arrangements. Staff and managers alike need to be sure that data quality is high and the outputs from models remain appropriate. Models are only as good as the data that is fed into them. And insights are only as good as the models.
It is not reasonable to expect IT staff to be responsible for data that is input by clinicians. Clinicians, therefore, need to understand the benefits of high-quality data, and take responsibility for ensuring that patient data is correct. This is a bit of a vicious/virtuous cycle. Until people see the benefits of decisions driven by reliable data, it’s hard to persuade them that reliable data is important. However, without reliable data, it’s impossible to generate the necessary impact. A strong data strategy – covering collection, assurance, preparation and use – will go a long way to help.
History in the making
Hospitals may struggle to integrate these new technologies into a national system like the National Health Service in the UK, which is often stretched to its limit. It will take time and energy and financial investment not only to implement systems but to find out how to use them to the optimal benefit of patients and staff. However, the rewards to be reaped from boldly taking on the challenge are unprecedented, with potential to push patient outcomes to their very best since records began.
Throughout history, advancements in health care have been met with varying degrees of scepticism by their contemporaries. This modern adoption of AI and data-driven practices joins Semmelweisz’s revolutionary handwashing discovery and breakthroughs with test tube babies in the 1970s, as procedures which require a cultural shift in thinking if they are to make a positive difference in people’s lives.
Dr Joost Huiskens, health care consultant, SAS