Remember the days when health care delivery was confined to the four walls of the hospital and involved lengthy hospital stays?
Doctors and nurses often suffered “alarm fatigue” from pagers and paper was used to record patient health data and stored in overflowing storage departments, with clinicians spending valuable time deciphering hand-written clinical notes – when they could find them. And hospital leaders made critical operational decisions based on observations walking the floors.
Thankfully that’s a bygone era – or at least it’s getting there.
Driven by the need for a better patient experience, healthcare has experienced a huge shift and like other industries such as banking and retail, digital transformation in healthcare isn’t slowing down. As costly chronic care needs continue to grow and exert considerable pressure on health systems, and patients become more involved in managing their health using IT solutions, the future of the healthcare industry will centre on digitally-enabled models of care. So clinicians can care for patients, improve outcomes and save lives.
As we begin a new decade, there are four trends that will be imperative for the healthcare industry to deliver digital transformation of health at scale.
Lifestyle-related chronic diseases are our nation’s biggest health problem, with almost half of all Australians now living with a chronic disease such as cancer and diabetes. That’s up 42.5 per cent from just 10 years ago. In the face of these growing numbers, the healthcare industry is shifting its focus from acute care to the prevention and management of complex chronic health conditions.
A consumer-centric, prevention-focused approach means focusing on treating people before they become patients, rather than treating the diseases. The availability of public data, combined with the existing understanding of the wider factors of health, means that governments and health organisations can use digital tools to better identify risks and then help the behaviours of people most in need.
Digital health technologies offer new possibilities for people to use their data to meet their health needs and goals. For example, by tracking physical activity, alcohol use and stress levels on mobile apps and combining this with data from the GP such as blood pressure and cholesterol levels, people can be notified of potential health risks earlier and be directed to a range of relevant and effective interventions.
From an Australian perspective, this approach will require co-operation across the federal and state levels to implement an effective approach. Currently, the divide in responsibility for primary versus secondary care and current funding models are at odds with this proactive approach.
To unlock the power of digital technologies to deliver personalised health outcomes, information will need to be better connected, combined and shared across providers and public health agencies. Yet with hundreds of health IT systems used daily across hospitals, GP surgeries, care homes and community care facilities, gaining access to patient information isn’t as straightforward as it needs to be.
Open standards, secure identity and interoperability are critical to the safe and successful use of digital technology, ensuring that systems “talk to each other” and that data gets to the right place, at the right time. At its heart, interoperability is about making a health system better, more accessible and delivering services that are better connected and optimise patient outcomes.
To reach this potential, agreements in standards that are widely used and accepted is an important first step. The architecture must also be flexible and scalable enough to cope with more users and extra connected systems. That’s why government organisations like the NHS are pushing for a modern, internet-based, mobile first “plug and play” IT infrastructure, so providers can develop their own solutions to access patient information and move to an operational model that can rapidly respond to the insights generated.
The explosion of patient data creates new opportunities for how care is delivered. But at the same time, it has placed enormous pressure on clinicians. Currently, clinicians need to manually review, process and take action on tens of thousands of different data points each day, to determine a patient’s care needs.
Despite their initial promise, electronic medical records (EMRs) or electronic patient records (EPRs) have failed to help clinicians reduce their cognitive workload, as the information is not always presented in a meaningful and intuitive way. For example, they lack visualisation support tools to help identify patterns and trends in the data. This increased cognitive load on clinicians shifts the focus away from patient care and leads to longer hours and burnout.
Despite the availability of AI technology in the clinical environment, we haven’t seen effective, widespread use of AI at the point of care. But we are starting to see the potential for AI to help clinicians do their work faster, and also manage clinical risk in a proactive way, rather than a responsive or retrospective manner.
With the ability to process vast amounts of data, AI combined with natural language processing can be used to populate health records and support clinical decision-making by tracking trends and spotting patterns in the data. Soon we’ll see its application in advancing the prevention, treatment and diagnosis of complex and rare conditions and develop new drugs to treat these diseases. Governments and healthcare solution providers today are making significant investments to speed up the testing and adoption of AI solutions in health markets around the world.
For many years the healthcare industry has focussed on implementing solutions to capture data and often ignored the need to make that data accessible. Without access, we are not realising the value available and are missing an opportunity to apply learnings to future care delivery.
There are many intuitive analytics tools available today that mean you don’t need a mathematics or statistics degree to interpret the data. When data is visualised as meaningful information and is aligned with the user context, clinicians can better understand trends and can take immediate action. Joining data from multiple disparate sources and aligning it with clinical and business perspectives exponentially increases the insight that can be gained and applied to improve service delivery models.
Looking ahead, we expect these trends to transform how healthcare is delivered and address key challenges facing the industry. Embracing digital innovation and new technologies will be important. But it will also take collective accountability in healthcare organisations (from nurses right through to Boards), health technology providers and governments to deliver change that is truly transformational for patients and clinicians.
Kaye Hocking is General Manager, Marketing and Sales Support, at Alcidion