Fadwa Ouardani, Senior Associate at XAnge

The State of Data in 2023: Health Tech Industry

There is a big potential in the European health data economy over the next 10 years. The European eHealth market is projected to jump from €3.6 billion to €7.5 billion in the next five years. VC deals in Europe rose from €7.4 billion to $12.2 billion in 2021 and likely dived in 2022. Globally, Digital health investments reached an all-time high of over €52,7 billion in 2021 but then took a dive in the first quarter of 2022. The global value of health data was also growing and was expected to reach $34.27 billion last year, with a compound annual growth rate of 22%.

European Healthcare at a glance

The EU plans to save €5.5 billion over the next ten years due to better access to and exchange of health data in healthcare. An additional €5.4 billion in savings for the EU is possible due to the better use of health data for research, innovation, and policy making. This will contribute to an additional market growth between 20-30%.

When discussing growth and opportunities in healthcare, we must look at the unifying building block that is one of the keys to unlocking market growth: data.

The Benefits of Big Data in Healthcare

According to the professor of genomics and pioneer Eric J. Topol, a “Gutenberg moment” in healthcare is approached through dramatic technological advancements. Healthcare is experiencing a revolution as the printing press did in the 15th century. We are about to experience a shift in power from doctors to patients. He emphasizes the age of patient-centered medicine, in which patients generate medical data using their own digital devices and communicate via their smartphones. This shift will have several benefits:

  • Big data will allow practitioners and hospitals to transition from a reactive, treatment-based approach to a more integrated, preventive model. This might lead to a dramatic shift in public health spending. In the US, about 80% of health spending went toward care and treatment. By 2040, 60% of health expenditures will go toward improving health and well-being.
  • The intelligent use of data also can speed the development of tailored approaches for greater patient engagement, which could lead to better compliance. The holy grail is a 360° view of the patient. A complete understanding of all medical, social, and environmental information associated with an individual would lead to a “perfect machinery for treatment and prevention”.
  • The analysis of big data helps providers develop best practices based on solid evidence. This is one of the primary drivers of the European Commission’s Health Data Space.

The State of Collaboration in Healthcare

When it comes to data collaboration in the healthcare industry, there are two major topics to consider:

  1. The amount of data is skyrocketing: According to a study by the International Data Corporation, the data generation growth rate in the healthcare sector is expected to exceed that of any other industry sector through 2025. IDC predicts that the global amount of data will grow from 33 Zettabytes in 2018 to 175 Zettabytes by 2025. This is driven by data-aggregating initiatives in the healthcare sector, including electronic healthcare records created by public and private healthcare providers, biobank collections, and information generated by medical devices, social media, and data platform companies.
  2. Players in healthcare are slow to adapt: As you’ll see below, all relevant players in the healthcare space are very slow to adapt to technological advancements, data aggregation and management, and interdisciplinary collaboration. While this is mainly driven by the sensitive nature of healthcare, it also means a slower adaptation of best practices and new concepts to improve the treatment of patients.

Challenges to Data Collaboration

When we look at the current state of collaboration in hospitals, we are far from the ideal. Data is often scattered and needs to be aggregated to have value for third parties. There are also challenges in sharing data within and between institutions.


  • Privacy Restrictions Privacy restrictions imposed by federal law regulate the release of medical information and make it hard for new partnerships to form and for startups to use the data aggregated in hospitals and laboratories. With very limited financing, it’s hard to comply with the rise of regulations.
  • Short-staffed Healthcare systems might want to improve their big data tools but lack staff members. But data and IT experts are just a small part of the workforce. The World Health Organization (WHO) estimates we need and additional 18 million health workers to achieve universal healthcare by 2030 in low and lower-middle-income countries.
  • Fragmentation Data fragmentation and the lack of uniform digitization impede efficiency, with some data overlooked because it’s stuck in silos. The decentralized nature of healthcare systems makes unified approaches difficult. AI and other technologies can only operate with digital information, but many organizations are still paper-based.

Opportunities for Startups in the Healthcare space

It took ten years and €4.6 billion to sequence the first genome. By now, the cost of genome sequencing has dropped extremely low from €26.7 million in 2004 to less than €1.000. There is a growing number of startups and organizations that stand for the opportunities that come with the rapid technological advancements.


  • Lifen raised € 50M (€20M in 2019) and showed continued growth in France, with more than 600 healthcare institution clients using its services to support over 2 million patients monthly. Expects to recruit over 200 new employees over the next 18 months.
  • MyPL provides multidisciplinary Cancer care. MyPL follows a patient-centered approach and has developed a set of solutions that improve the outcome of cancer treatment and provide patients with the appropriate management tools.
  • Galeon built the first Electronic Health Record on the Blockchain to gather highly structured medical data.
  • Health Data Hub The French government introduced 2019 the Health Data Hub. It’s a public structure that will enable project coordinators to easily access non-nominative data hosted on a secure platform in compliance with regulations and citizens’ rights. The goal is to improve the quality of care and patient support.
  • Kiro improves the communication of lab test reports between clinical laboratories, health professionals, and patients. The platform makes the results of medical reports easier to understand and personal. The startup raised €2 million in 2019. Today, the company works with more than 230 laboratories in France that serve millions of patients.According to the company, “90% of our customers say they are satisfied with Kiro. So much so that they are more inclined to accept the digitization of their test results.” The more patient-friendly reports have another positive side effect. The laboratories receive ⅓ fewer follow-up calls with questions from patients about their test results.
  • European Health Data Space: The EU introduced the European Health Data Space in 2022. The EHDS is an ecosystem of rules, common standards and practices, infrastructures, and a governance framework that will give citizens digital access and control of their health data. The EU wants to foster a “single market for electronic health record systems, relevant medical devices, and high-risk AI systems.”

Data Ownership in Healthcare

Like everything else in healthcare, the question of data ownership is very complex. Today, health data belongs to both the patient and the health professionals. There is a difficult balance to strike.

On the one hand, AI software needs huge data sets to learn and train, as their accuracy depends mostly on the size and quality of this data set. On the other hand, outcries over data misuse or the exposure of millions of sensitive health reports are plenty, like when the Royal Free Hospital in London granted access to 1.6 million health records to Google’s AI subsidiary, DeepMind, to help the company develop an app that analyses test result data for patients.

An interesting idea to rethink the concept of data ownership in healthcare comes from Kathleen Liddell, David A. Simon, and Anneke Lucassen. The team proposes in a paper to move away from “ownership” towards a discussion about protecting individuals whose health information is processed, legitimate data use/users, and a healthy and well-functioning data economy.

Many questions still need to be discussed in order to move forward on this matter:

  • How can healthcare providers balance protecting patient privacy with sharing information to benefit the patient and the broader healthcare system?
  • Who owns the collected data that is collected? The hospital? The state? The patient?
  • How should healthcare providers and policymakers address the social determinants of health, such as poverty, housing, and access to education, that can profoundly impact health outcomes?
  • How can the healthcare system ensure everyone has access to the care they need, regardless of their ability to pay?
  • How can healthcare providers obtain informed consent from patients, especially when patients may not fully understand a treatment’s potential risks and benefits?

The questions are an open debate, and I don’t think we will solve them anytime soon. What is certain is that we need to ensure very strong anonymization of our data. The good news is: one part of the solution can already be provided in certain cases by the use of synthetic data.

Synthetic Data

Synthetic data, simply put, is fake data generated from actual data. The method preserves the properties and statistical information of the original data while also protecting the privacy of individuals. The space is growing fast, and companies like Sarus let data scientists and analysts work on confidential datasets without accessing them directly.

Broadly speaking, there are three types of Synthetic Data: Fully synthetic data, where all records and variables in the data set are created from the synthesizer model; Partially synthetic data, where only some variables are synthesized, and the rest retain their original values; and Hybrid synthetic data, where some records are synthesized, and some original records are included.

Besides preserving the privacy of patients, Synthetic data could significantly improve interoperability standards in the sharing of health data. But to get there, we need to ensure that the data is not identifiable.

Investing in the future of health tech

Big data has the potential to revolutionize the healthcare industry and bring a shift in power from doctors to patients. Big data allows for a more integrated, preventive model of healthcare, leading to improved spending on health and well-being. At XAnge, we focus on making technology accessible to billions of people. If you are building a startup in the space or want to contribute to its growth, get in touch – our inbox is always open.


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