Why digital transformation of healthcare is a team sport

By: Ymke de Jong

Ymke de Jong — Data & AI Partnerships Lead

There’s no arguing that digital transformation has helped revolutionized many industries. Thanks to big data, artificial intelligence, the cloud, the internet of things, and other technological advances, sectors such as transportation, entertainment, hospitality, and banking have become much more personalized, efficient, and less costly. The healthcare industry also stands to make similar benefits from digital transformation, which is of high need, seeing the current aging population and a shortage of medical staff and increasing costs [1].

Healthcare and data

At the heart of most digital transformations is the improved ability to collect and process quality data. Companies like Uber, Netflix, and Airbnb have transformed traditional industries by leveraging this capability and merging it with artificial intelligence algorithms to create insights and experiences.

Healthcare has an abundance of data and it is growing exponentially every day[3]. Today, health data generation has expanded beyond hospitals to our homes, mobile devices, wearables, etc. However, in most cases, health data is not ready to be mined and used to improve the work of care givers. “We are drowning in information, while starving for wisdom.” This famous quote by biologist E.O. Wilson exposes the challenges of data science; we have access to more and more data, but often lag behind when it comes to fulfilling the promises as seen in other industries.

What are the barriers?

Healthcare leaders are aware that a successful approach to digital transformation requires overcoming a number of obstacles. Research done and explained in the Philips Health Index 2022 shows that 46% of leaders in hospital setting view data more of a burden than an asset. A few arguments identified in this research to support this feeling of burden are:

● Technology infrastructure limitations

● Siloed data

● Data security and policy

● Staff knowledge and mindset

It is worrisome to see that most of these barriers have been a constant presence for healthcare leaders since the Future Health Index research began in 2016.

At the same time, there is a lot of AI research being done in the healthcare sector. The number of publications on AI in healthcare is rising exponentially and the academic results are amazing, but only a small part of it finds its way into hospitals and into the hands of clinicians[2,5]. Scalability turns out to be difficult due to small datasets that are collected from few sources, data compatibility problems and regulatory hurdles. This leads to one of the major challenges currently: the risk of unknown bias present into AI models used in healthcare, for example when they haven’t been trained on diverse data from different and diverse populations.

What is the solution?

Fortunately, several trends are helping develop solutions that move to responsible AI solutions at scale. All those trends have a common enabler: work together!

Include clinicians in every step of the innovation

AI is not a solutions itself; it needs to be adopted and embraced by care givers and/or patients in order to deliver the full potential. The technology needs to be migrated into the workflow and fully thrusted. To truly accelerate the digital transformation, we need to make sure to include care givers from the start of the development process. Working in cross sector ecosystems is not an option, it is a must for digital transformation in healthcare to succeed.

Create data standards and interoperable platforms together

Creating all our own data standard will lead to a jungle of standards. Working together with leading institutes to develop open data standards is key to ensure interoperability today and in the future. One of our initiatives at Philips is the HealthSuite Digital Platform, a unified platform embracing those open standards where data from different sources is aggregated, standardized, and made accessible to everyone at a health organization. This platform reduces the data engineering effort required to create solutions that can help in different stages of diagnosis and care.

Team up to build digital trust by safeguiding data privacy and security

Academic institutes lead the way in data sharing for innovation purposes. One example is FAIR, a framework that was kickstarted in the U.S. in 2016 and ensures that research data is accessible and interoperable across different institutions and research labs. At Philips, we participated in the development of the MIMIC dataset, an open ICU dataset that is freely available to all researchers. Another promising direction is the pioneering of next-generation AI methods often developed by academic institutes such as federated learning, which has been designed to train ML models without the need to transfer sensitive data to a centralized location. This methodology is nicely shown in the European ecosystem initiative Gaia-X[4].

Joining forces through strategic partnerships and ecosystem collaborations

An example of an ecosystem embracing digital innovation is the Eindhoven MedTech Innovation Center, a large-scale research collaboration effort between Philips, the Eindhoven University of Technology, the Catharina Hospital, the Maxima Medical Center, and the Kempenhaeghe Sleep Center. By bringing together clinical, industry, and knowledge institutions, we’ve been able to create a fast track to clinical innovation. One of the products of this collaboration is the Healthdot, a wearable device that is placed on the chest and measures heartrate and respiratory rate. The testing of the wearable was kickstarted in 2018 with a study of post-surgery patients at the Catharina Hospital. In 2021, it reached mainstream practice and is helping reduce clinician load by releasing patients earlier and monitoring their vital signs remotely.

To summarize, digital transformation holds a large promise for the healthcare industry, but we must overcome its hurdles. By working together, we can accelerate the time to clinical practice and make sure our latest innovations can help improve care and health for everyone.

1. “Philips-Ai-Position-Paper.Pdf.” Accessed June 2, 2022.

2. Sande, Davy van de, Michel E. van Genderen, Joost Huiskens, Diederik Gommers, and Jasper van Bommel. “Moving from Bytes to Bedside: A Systematic Review on the Use of Artificial Intelligence in the Intensive Care Unit.” Intensive Care Medicine 47, no. 7 (July 2021): 750–60.

3. “RBC Capital Markets | Navigating the Changing Face of Healthcare Episode.” Accessed June 2, 2022.

4. “Gaia-X.” Accessed June 9, 2022.

5. “2021.11.23.21266758v1.Full.Pdf.” Accessed June 9, 2022.

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