Can humans and machines work together for better health care?

Can humans and machines work together for better health care?

Healthcare is becoming an information-driven industry. Increasingly people wear monitors in their daily life to track their health. We have started using Artificial Intelligence (AI) and genomics to diagnose disease with a precision that was unheard of just a couple of years ago. Hospitals are getting equipped with machines of extraordinary capabilities to treat patients in a highly targeted and non–invasive ways, being guided by augmented reality and robotics. It’s clear that technology is greatly impacting the way we practice medicine and organize healthcare. There’s no doubt that in ten years from now, it will be profoundly different from what we experience today.

It’s tempting to think machines are taking over in the age of connectivity and machine intelligence but I think the opposite is happening. Humans – patients, healthcare professionals, business leaders and politicians – will be enhancing their capabilities by using smart machines and software, like they have done with earlier technologies, but they will continue to rely on their empathy, knowledge, experience and judgement. 

Even though many want technology to play a greater role, they also fear that machines could potentially replace humans.

The new Future Health Index report, a digital healthcare research study commissioned by Philips, builds on the data, perceptions and experiences from 33,000 people in 19 countries and gathers advisory inputs from experts from leading academic and global non-profit organizations. It reveals an intriguing contrast in people’s attitudes – even though many want technology to play a greater role, they also fear that machines could potentially replace humans. At the same time people around the world are asking for user-friendly and more connected care – something that we can only achieve through open, highly secured, data streams. It’s up to healthcare professionals and IT professionals to bridge the gaps and facilitate behaviour changes so that we can truly reap the enormous benefits of digital healthcare.

From the survey we gleaned that many healthcare professionals believe that wearable technologies will add to their workload, lead to greater costs and create unreliable sets of data. One cardiologist interviewed in Germany for the research even stated: ‘Doctors might be against technology because they think it will take away their jobs and they will become a peripheral figure.’

The application of new technologies always comes with challenges and disruption. We need to fully engage clinicians along the route of innovation to ensure these technologies result in meaningful and validated tools that can be integrated into clinical workflows with the aim to both improve care operations and patient outcomes.

We can use technologies to make healthcare more personalized and deliver it 24/7 at the most appropriate location.

Connected care technologies supported by Artificial Intelligence (AI) can help find patterns in the massive amounts of health data, to gain deeper insights and create a more complete patient picture (or “digital twin” in IT jargon), identifying key determinants of one’s health. We can use technologies to make healthcare more personalized and deliver it 24/7 at the most appropriate location. It can ensure we have the right care professionals available at the right time. And it will also help us to make our health systems more impactful and cost efficient.

The first steps are taken – as I’ve written about before when describing hospitals of the future, as sensing and adaptive networks. Forward looking institutions, like Kaiser Permanente, have integrated physical and virtual spaces to embrace patient-centricity, real-time data interpretation, while enabling the human touch at the right time and place. Leaders are creating systems that drive better health outcomes at lower cost.

In designing these new systems we need to address the concerns of medical professionals. When I spoke at the AI Summit in London last month, I shared my views on the challenges in the development and application of technologies such as Artificial Intelligence, of which there are many; from raw data quality, to interoperability and security. One of the most prevalent is the need for transparency in AI systems for healthcare. They cannot just be these ‘all-knowing’ entities working their magic in the shadows. Clinicians will have to be involved in co-design and review cycles. Regulators will look for clinical evidence. Any healthcare AI will always be a combination of data-driven and knowledge-layered learning. Machine learning should be interpretable so that medical professionals can understand its working, validate and accept outcomes, and explain these to their patients.

Healthcare will always require an empathetic and trustful human element, no matter how sophisticated technologies become. Many of the skills of a healthcare practitioner are irreplaceable. For instance, in our report only 11% of the general population surveyed saw the potential for remote appointments with artificially intelligent doctors.

Feedback suggests that the general population understands that connected care technology – from electronic records to health apps and remote monitors – can play an important role in advancing efforts to prevent or control chronic disease. Clearly, the more data that they can share in a responsible, secure manner, the more valuable that data will be for their own health. AI-driven holograms of doctors are too sci-fi right now, but we do currently have access to telehealth technologies to support chronic condition management – technologies that are already using AI for real-time assessment of a patient’s acuity, which will ultimately form the basis of these futuristic health developments.

The general population’s understanding of connected care technology is another area for consideration. Only about a quarter polled (24%) consider themselves knowledgeable about connected care technology, which is understandable given that its infancy in medical practice. The rate was even lower in developed markets and particularly Europe, falling to 9% in Italy and 8% in Germany. Even where there is higher overall perception, such as in the United Arab Emirates, only about half (48%) of the general population polled claimed to be knowledgeable about connected technologies. Today the only place where patients are continually monitored with medical grade devices is in the Intensive Care Unit. At Philips we have a mission to make continuous monitoring ubiquitous, in the general ward, at home, and ultimately, wherever you are.

So, more needs to be done not just to introduce connected care technology, but to encourage people to use it through education, training and daily engagement. About a third (31%) of respondents said they’d be more likely to use technology if they had better training on how to use it, 44% said they would be more likely to use it if their healthcare practitioner had recommended to do so and 29% would be more likely to use it if it had been paid for by their insurer.

For both the general population and healthcare professionals to make strides towards more connected care, we need to demonstrate that skills and capabilities are truly being enhanced through technology. Jobs are not always going to be lost, but some will be made more specialized – a growing demand for more and also differently skilled workers will flow from this. And because preventative medicine will help to keep patients out of hospital through greater use of digital technology, resources can be concentrated on those who will benefit from them most.

Many health professionals are already using the power of advanced analytics and AI, when they use Philips Guardian predictive patient management software or Illumeo’s intelligent radiology station. Perhaps inspiration can be found in arenas beyond healthcare, where investment in progressive technology – especially the internet of things and AI – have positively transformed working practices.

Challenging unfounded fears with positive use cases will act as the catalyst in creating healthcare systems that are fit to tackle the challenges of the 21st century. It is time to fully embrace digital technologies as a driver for better patient outcomes and lower operational costs.




Elena Pupazan

Circular Economy, Digital Innovation, Impact Venture Building, VC & EU funding, Collaborative Entrepreneurship

7 年

Healthcare is a critical human and life service and we need to innovate very responsibly and ethical here both from interfering with some natural processes of life as well as the human rights in the socio-economic context. I trust the intentions (especially of Philips) and understand the added value but the cost to pay might be priceless. Could we also address sooner than later the boundaries and implications? We need to mind that the exciting innovation is possible thanks to the patient data access and insights. This is private property of the customer of extreme high value. How does the industry act on customer's patient data ownership, privacy management, usage consent and monetization?

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Ben Jeddou

Product Specialty| ??'

7 年

That's true. We live in an era where Machines are exceeding all Human expectations. They're getting too close to Think, Act, Listen, Speak, Feel, Understand and Learn like us. Some of them (pointing to the IBM Watson Cognitive tremendous machine) are even outperforming teachers, doctors, architects, in their daily Jobs. However, looking on the bright side of it, these tools can be put in Context of advancing Humanity & saving Earth. (e.g. countering Climate Change effects, fighting epidemics, personalizing education ..and so on) ? access full article here, https://startup1956.com/cognitive-computing-machines-exceeding-human-expectations

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Nhung ??ng

Qu?c Duy Nhà cung c?p máy ch? bi?n g? và day chuy?n s?n uy tín ch?t l??ng nh?t t?i tphcm - Thi?t b? v?t t? ngành g?

7 年
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Jen Jen Chen

Physician on the outside, product on the inside

7 年

Yes! Crucial to have MDs work hand in hand with developers/engineers to address the right problems in healthcare. Also need to consider that we can't really train any ML to address the more complicated aspects (like thinking like MDs in ddx) until medical data is fully shared and accessible

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Teresa Slankard

Associate Program Manager of Post Acute at ConvaTec

7 年

The Key is simplifying the bedside carepaths to align to the needed documentation metrics. So many times experts create the pathways that make bedside care too complicated and as a result you have non-compliance which results to inaccuracy in regard to data. Easier Pathways also create better education retention and confidence which will then lead to success in healthcare

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