The amount of data collected and analyzed by hospitals and health care organizations across the world was already on the rise, but the global pandemic has sharpened the focus on data even more.
With trends changing not daily, but hourly, during the pandemic, health care professionals struggle to monitor larger intensive care capacities, track staff safety/fatigue and optimize every available resource. At the same time, decision makers must assimilate new research findings, adjust policies and do it all in real-time because acting quickly is a matter of life and death. During this crisis, it’s no wonder that health care leaders turn to analytics to help them make data-informed decisions quickly.
While the urgency of the pandemic may be pushing the health care industry to more rapidly adopt data and analytics for decision-making, no one knows what the new normal will look like. To get a better idea of where we’ll go from here, it may help to look at where the industry is with data and analytics overall today.
New sources of data
As data-generating technologies have proliferated throughout society and industry, leading hospitals are trying 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 radical shift further towards data has the ability to support decisions made by doctors and ultimately improve patient outcomes. With the help of artificial intelligence (AI) and advanced algorithms, medical professionals will soon see their capabilities advanced by data, in everything from the logistics of prioritizing which patients to treat 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.
Adopting new technologies
Health care 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 to help 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 in the data. Whatever the reason, it’s been a fairly slow start.
But even before the push of the pandemic, a groundswell towards data-driven decision making was beginning. A number of leading health care organizations have started to embrace AI and analytics. They’ve often begun with small-scale projects, but there’s growing recognition that the future lies in personalized health care – and that personalized medicine depends on data and advanced 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
Now that the COVID-19 crisis is ushering in higher levels of analytics use, it seems likely that over the next three to five years more and more health care providers will become data-driven organizations. This will, in most cases, require a change in culture. Providers must move towards using data to generate insights that then drive decisions. It’s likely that this acceptance will grow as organizations 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’s 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 analyze it. The third is a successful data strategy.
A successful data strategy starts now
A successful data-driven hospital needs to centralize its data strategy for business operations and care.
This means that health care providers must develop strong data and model governance. 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’s fed into them. And insights are only as good as the models.
A successful data-driven hospital needs to centralise its data strategy for business operations and care.
It’s not reasonable to expect IT staff to be responsible for data that’s 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
Throughout history, advancements in health care have been met with varying degrees of skepticism by their contemporaries. The modern adoption of AI and data-driven practices could join Semmelweisz’s revolutionary handwashing discovery and breakthroughs with test tube babies in the 1970s. They’re all procedures which require a cultural shift in thinking if they are to make a positive difference in people’s lives.
While the pandemic crisis may be pushing the health care industry to make that cultural shift more quickly, it will be interesting to see what happens during pandemic recovery and potential future outbreaks. My hope is that the new normal will include widespread AI adoption, because that will help improve patient care, reduce costs and achieve better outcomes.