In Asia-Pacific, an estimated 1.1 billion people are expected to be above 50 years old by the year 2025. This region is home to more than 50 per cent of the global population and they account for nearly two-thirds of the global disease burden from major chronic respiratory diseases.1 Ri
In Asia-Pacific, an estimated 1.1 billion people are expected to be above 50 years old by the year 2025. This region is home to more than 50 per cent of the global population and they account for nearly two-thirds of the global disease burden from major chronic respiratory diseases.1 Right now, the demand for healthcare outstrips the supply of skilled medical professionals. Supply is especially low in rural areas. In India, for example, 65 per cent of the population lives in rural areas, while only 2 per cent of doctors are available in the countryside.2 This poses major challenges for our healthcare systems. How can we make healthcare accessible to the growing and progressively ageing population? Digital technologies and big data will play a key role in tackling these challenges.
Digitalisation in healthcare holds great promise. It can help to overcome many of today's healthcare challenges, allowing providers to improve outcomes while saving resources and putting patients into better control and management of their own health. For this region in particular, it has the potential to make healthcare more accessible. Tele-consultancy is one example, where cost can be saved and access increased. Simply put, the patient does not need to be where the doctor is. Connecting digitally saves travel time, cost and burden for the patient who may not be fit to travel in the first place. A patient may be scanned on a CT scanner in a remote area while a skilled doctor elsewhere could then evaluate the data. Such a concept is meaningful in places where there are remote populations that do not easily have access to care, such as in the Philippines, Vietnam, India, or China to name a few. That means, high-end services and expert knowledge can be centralised and accessed remotely.
I believe Asia will be the place where Digitalisation happens faster than anywhere else in the world. There is a need for affordable and accessible healthcare, coupled with the availability of digital talent, government support, and openness to digital means. India, for example, has the highest proportion of digital talent3 in the world and the government is implementing various national policies to promote entrepreneurship and digital adoption. The digital boom in China has certainly transformed multiple industries, including healthcare. People are very open partly because there isn’t much history to destroy before introducing something new: for example, China went straight from cash to digital payments and skipped credit and debit cards for the most part.
At Siemens, we launched our fully integrated Siemens Digitalisation Hub in Singapore last year. It is the first of its kind in the world and the ideal place from which to serve the digital needs of our customers throughout Asia and beyond. The hub will support the digitalisation efforts of companies in Southeast Asia's urban infrastructure, industry, and healthcare sectors.
The ultimate goal of Artificial Intelligence (AI) is to assist in providing better care for patients by transforming data into knowledge and actionable insights. We have been involved in the field of Machine Learning since the 1990s. This is reflected by more than 500 patents in the field of machine learning, 75 basic patents in the field of "Deep Learning" and more than 40 AI-powered systems already in clinical routine. Developing solutions for managing this ever-increasing workload is a crucial task for the healthcare sector. Chinese hospitals can be extremely crowded and the workload of the doctors can be daunting–the average daily patient throughput for a CT can be 150 per day and the doctor may easily need to read around 20000 images per day. That is far more than double the amount of some other countries. Diagnostic experts and physicians need a new set of tools that can handle large volumes of medical data quickly and accurately. This would allow for more objective treatment decisions based on quantitative data and tailored to the needs of every patient. To provide this new toolset, we need to draw on the power of AI. A specific example is our AI-Rad Companion Chest CT,4 an intelligent software assistant for radiology, which can identify organs and potentially disease-relevant changes in the chest. AI-Rad Companion Chest CT is a tool that can simultaneously increase productivity and quality in diagnostic radiology.
Personally, I find the concept of a “Digital Twin” very exciting. Siemens Healthineers is pursuing an ambitious vision–that someday there will be digital twins of individual patients’ entire bodies. These digital companions are intended to be more than just sophisticated anatomical models. In addition to a patient’s clinical information, they could also contain cellular, molecular, and genetic information. If a patient’s physical condition is already known ahead of time, physicians could decide whether a specific drug would be likely to help and at what dosage it should be given. For example, computational modelling of heart function using Artificial Intelligence facilitates extensive, interdisciplinary integration of patients’ clinical data into a Digital Twin of their heart. The latter can then be used for prognosis and even therapy planning. The Digital Twin helps gain a better understanding of a patient’s disease, predict its course, and even test various types of intervention. The vision is of a life-long, smart Digital Twin that will learn continuously and stay up-to-date with each new batch of clinical data.
We believe that digitalisation and the associated networking of healthcare providers are essential for the transformation to value-based healthcare. With the Siemens Healthineers Digital Ecosystem, we are providing our customers with much deeper insights than previously possible into the key components that create both clinical and operational value. The main goal of our Digital Ecosystem is integrating and interconnecting data, participants, applications, and services. Imagine the sheer amount of available data. All of a sudden, healthcare providers will not only benefit from insights derived from five hundred but millions of cases. This can be efficient for example when it comes to the diagnosis of rare diseases–where it is crucial to amass a lot of data to identify the best way to diagnose and treat the patient.
Artificial Intelligence and digital means play a key role in the future of healthcare. With the support of AI, radiologists will be able to focus more on what matters: the diagnosis and its impact on the treatment of the patient. It will increase productivity, save resources, thereby enabling more access to care as well. In essence, AI has the potential to strengthen humankind, it will take over the tasks that machines can do for us, and enable us to focus on and spend our time on what really matters: the patient.
References:
1 MedTech Asia McKinsey report Dec2015
2 The World Bank
3 NASSCOM - Indian Start-Up Ecosystem Report (2016/2017/2018); NASSCOM - Accelerator/Incubator Report (2017); Capgemini - The Digital Talent Gap Report 2017); KOL Interviews
4 AI-Rad Companion is pending 510(k) clearance, and not yet commercially available in the United States and other countries
