As healthcare organisations grapple with responding to the endemic and adapting their operations to fulfil other aspects of their care mission, they must also begin to define and prepare for the future of care amid economic, regulatory, and social uncertainties. What might the post-Covid-19 landscape look like? How can health systems address a range of possible challenges? What are the opportunities to revolutionise care? To succeed in the future, healthcare leaders need to rethink what this crisis revealed and continue to drive these new movements in how we deliver care.
COVID-19 exposed vast weaknesses in health systems around the world and has exacerbated gaps in quality and service while highlighting the critical role of quality healthcare during an emergency. Though it has inflicted devastating health and economic costs, it has also created a once-in-a-generation chance for transformational health system changes.
Now, as healthcare organisations grapple with responding to the endemic and adapting their operations to fulfil other aspects of their care mission, they must begin to define and prepare for the future of care amid economic, regulatory, and social uncertainties.
What might the post-pandemic landscape look like? How can health systems address a range of possible challenges? What are the opportunities to revolutionise healthcare?
To succeed in the future, healthcare leaders need to rethink what this crisis revealed and continue to drive these new movements in how we deliver care, to “build back better”.
The pandemic not only brought with it a new level of stress for providers, but also for patients, and technology was the solution that calmed fears, provided relief, and most importantly, allowed for communication between providers and patients who needed care.
It seemed that almost overnight, technology provided access where access was limited, and the flexibility of telehealth increased the workflow efficiency for providers. More importantly, the world witnessed the “proof of concept” for how technology can positively impact the healthcare industry—at scale.
However, demographic, epidemiological, and socioeconomic trends show that even greater challenges lie ahead for health systems, especially in ASEAN. Populations are rising fast in some of the poorest countries and ageing rapidly in higher-income settings.
Many countries face a protracted epidemiological transition, where stunting coexists with obesity, and surging non-communicable disease burdens, such as cardiovascular disease and cancer, come atop persistent infectious threats.
Rising citizen expectations for healthcare have followed urbanisation and globalisation, even as climate change, economic crises, institutional fragility, and conflict threaten to overwhelm fragile health gains in many countries. It’s no surprise then that healthcare expenditure in the ASEAN region is on a pre-COVID path to grow by over 70 per cent between 2018 and 2025—with the fastest growth expected in emerging economies who can leapfrog into this new paradigm.
In seeking a sustainable solution to healthcare, countries in ASEAN have had to narrow their focus towards ensuring access to its citizens, both from a cost perspective as well as a geographic standpoint, while shifting their focus from treatment of disease to prevention.
While the utilisation of technology in healthcare is not new, the importance of intelligent applications of technology to improve efficiencies is critical, deploying it to improve patient care and to improve the lives of healthcare providers as healthcare demand rises.
As the world slowly emerges from the COVID-19 crisis, health systems will enter a period of critical risk and opportunity. Bold choices now can transform health systems for the decades to come, bringing goals like precision health within reach.
Where most medical therapies are designed with the average patient in mind, precision health1 aims to deliver a highly personalised course of treatment based on a patient’s genetic makeup, health history, family medical history and lifestyle choices.
By using healthcare artificial intelligence (AI) applications to better understand, monitor and predict a patient’s health journey, precision health can help with disease prevention and when diseases occur, enable clinicians to make more informed treatment decisions.
The key to the success of precision health is the use of healthcare AI technologies that can analyse massive sets of health data and distill actionable insight for the care of individual patients. GE Healthcare has developed intelligence platforms to support organisations on the path to precision health by enabling more than 50 healthcare applications and medical AI algorithms.
With technological advances, clinicians will have the opportunity to increasingly harness precision health in 2022 to treat various diseases and disorders. The solutions currently in development are expected to radically change care delivery models and improve outcomes for generations to come.
So how do we get there? The hard-earned wisdom earned during the pandemic has led to visions of a new, more resilient healthcare ecosystem—one that is Intelligently Efficient, leverages technology to reduce burnout, expands access with virtual care and improves data management to strengthen clinical decision-making.
Inefficiency in health systems is a global problem. The World Health Organization (WHO) estimates that 20-40 per cent of health systems’ resources are wasted, which undermines service delivery.
During the pandemic, healthcare institutions everywhere were forced to re-evaluate their operations. For some institutions, viewing efficiency as a process that improves every component of the care system and one that uplifts every individual who interacts with that system is already becoming a reality. These institutions strive for a state in which quality care flows seamlessly and efficiently for providers and patients, guided by relevant insights. A concept GE Healthcare has termed Intelligent Efficiency.
Any new technology must help clinicians diagnose earlier, better, and faster so that healthcare providers can achieve a more precise diagnosis. After all, operational efficiency can only be improved with real-time visibility.
With more patients, fewer open beds, and workflow chokepoints, hospitals, and health systems in ASEAN for example are turning to single data infrastructure software known as “command centres,” featuring real-time decision support tools.
These hospitals would now be able to see unprecedented orchestration of patient care activity in real-time, using apps or “tiles” on a central dashboard. Enabled by AI—including machine learning, natural language processing (NLP), computer vision, and other modes—tiles are built for specialised use cases related to patient flow, quality, risk management and system optimisation.
This can lead to substantial savings for hospitals as the result of operating at maximum capacity, improving metrics such as a decrease in the average length of stay, and reduced emergency room diversion.
In the COVID-19 era, burnout has become an issue across healthcare professions, with GE Healthcare research revealing that nearly two-thirds of doctors surveyed still cite excessive bureaucratic demands as the primary cause for burnout, more than one-third pointed to long hours, and eight per cent of doctors said the stress of treating Covid-19 patients was the primary cause of their burnout.
And although electronic health records – a frequently cited contributor to burnout in other studies – certainly made the list of culprits, clinicians also pointed to chaotic workplaces, after-hours workloads and too many bureaucratic tasks as major factors.
But when technology works for clinicians by surfacing actionable data on command, healthcare has a stronger chance to hold on to the people who keep the system running smoothly.
In using an ultrasound, for instance, examining the central nervous system of a foetus can require multiple keystrokes. But a deep learning model built into the device can cut the number of keystrokes by 78 per cent, streamlining the process, reducing the opportunity for error, and limiting repetitive tasks.
Technology for MR and CT also leverages AI to make imaging faster for both technicians and patients. Intelligent MR slice prescription software uses deep learning algorithms to automatically detect and prescribe slices for routine and challenging knee and brain exams, delivering consistent and quantifiable results. It automates the workflow and optimises technologist efficiency and reproducible planning to ensure exam consistency for the same patient follow-up.
All this helps to take time off clinicians’ plates and makes things more efficient, so they can focus on what truly matters: patient care.
In Asia, where healthcare systems have long been familiar with SARS outbreaks, hospitals were the quickest to deploy telehealth and remotemonitoring technologies in the face of COVID-19.
The COVID-19 pandemic has now led to examining the necessary frameworks for supporting the wider adoption of telemedicine worldwide. Under-utilised care paths like telemedicine have become popular, sparking new urgency around using digital technology to improve workflows and make systems more productive.
Remote monitoring solutions are fast emerging as a reliable and cost-effective technology to connect ICUs using a hub and spoke model. There are two types of remote monitoring, one connects remote hospitals to those in metropolitan city centres, and the other allows monitoring of ICU beds across the floors of a hospital building at a single location. It enables clinicians advanced consultation, care, and monitoring of their critically ill patients without having to physically transfer them to a super-specialty hospital. This reduces the risk of clinical deterioration.
A MOH Telemedicine Centre has been deployed extensively in Vietnam since the onset of the pandemic. Using the solution to enable remote monitoring and efficient care for critically ill patients remotely across the country, it extended the critical care expertise of clinicians in the capital city to patients in rural communities where specialists are not otherwise available.
Healthcare systems everywhere are overwhelmed by the amount of data they collect, where research shows that a typical hospital generates enough data per year to fill 20 million four-drawer filing cabinets where 97 per cent of that data never gets used
And many don’t have the means to turn that information into the valuable insights they need for more efficient care.
The effective use of data requires changing the way it is stored and used today. Experts say healthcare leaders must revamp the protocols and technologies that silo data and prevent information from informing action. Data integration strengthens clinical decision-making and patient outcomes by providing easilyaccessible and expeditious insights to healthcare professionals when they need it.
Hospitals must craft plans to manage and capitalise on unstructured data, a challenge that existing technology can mitigate. They must look to invest in digital technologies that will help aggregate their data, applying AI and analytics.
These new intelligence platforms have been designed specifically to meet the need to take advantage of that data in new and significant ways. One solution is the implementation of cloud-based systems that can effectively and safely manage the exchange of relevant, real-time data to clinicians across the hospital enterprise, while anonymising patient data when required. Such systems are being deployed to streamline data gathering and boost patient privacy and data security.
With actionable data, the application of technologies like AI across the entire patient journey can help achieve precision healthcare that’s integrated, efficient, and highly personalised.
The COVID-19 pandemic brought many trials and tribulations to an already overburdened sphere. But having earned battlefield stripes on the front line during the Covid-19 surge also brought an opportunity for those leaders who were able to modernise and improve their healthcare ecosystems, accelerating transformations in the making and offering a glimpse into the future of healthcare.
The transition to a more holistic health ecosystem is about improving outcomes by finding new ways to reach and treat patients while creating capacity for providers and making precision health a reality. To achieve this, health systems must continue to prioritise digital innovation. It will be essential for responding to patients’ expectations for greater expediency, access, and convenience.