The implementation of outcomes and costs measurement methods is the starting point for assessing and increasing value in healthcare. Remote monitoring of outcomes, self-management care, process optimization in healthcare delivery, prediction analysis for prevention of complications and data interoperability are some of the domains where digital health plays a major role in innovation towards VBHC. By resorting to measurement methods, innovation through digital health will support long-term and sustained outcomes in Healthcare.

Measuring long-term outcomes

VBHC has started with a focus on the design of clinical pathways for specific medical conditions and cycles of care. The ambition to have standardized outcomes that can be used for benchmarking takes a further step: collect and aggregate health data from each patient, in a specific cohort, from various healthcare delivery services, towards valid benchmarking analysis. Furthermore, the ambition for long-term and sustained outcomes takes a second step: collect health data from both inpatient and outpatient stages of clinical pathways.

Following the Triple Value model, at the population level, the outcomes’ collection goes far beyond care cycle: it will need innovation on monitoring technologies that pervasively collect health outcomes from groups of citizens and engage them for increasing value in Health. This is particularly challenging for groups of patients with long-term complex conditions. As Erik Janssen writes in an opinion article:

“The question we must ask ourselves is: how can we leverage these new technologies and innovations to start delivering on outcomes and experiences that matter, so patients with severe, chronic conditions can start to live longer and better lives?”.


The actual growth of digital health or, in other words, eHealth, through a new generation of connectivity (5G), mobile technologies (e.g. smartphones, wearables, IoT devices and apps) and modern data science platforms are bringing tremendous opportunities to Healthcare. Undoubtedly, digital health technologies are enablers for VBHC since they offer pervasive means to collect outcomes and costs, as well as to assess value and support new processes for value improvement.

Challenges to digital transformation

It is, though, important to design technologies in a way that facilitates the measurement of outcomes and costs, as technologies are not mandatory to increase value in healthcare. Low accessibility, acceptance and adherence to technologies are among various human factors that lead to a slow rate in digital transformation for Healthcare. Also, health data security, privacy and trust are a challenge to be tackled in this digital transformation. Compliance with the actual guidelines and regulations seem to be insufficient to guarantee high confidence for healthcare systems and may hinder technology innovation due to fear. A serious commitment to regulations and transparency of data usage from technology developers and healthcare providers are important to engage users of healthcare systems to join digital innovation.

Transdisciplinarity for technology design 

Contribution from multiple knowledge domains is an essential key to enable technology to drive the purpose of increasing value in healthcare, by supporting long term and sustained outcomes with minimal waste. Medical sciences, economic-social sciences, law and linguistics must work collaboratively with technology developers to unravel the potential of digital transformation for increased value in Healthcare.

— About the author —

As CEO, Ana Rita is the scientific head of VOH.CoLAB, developing strong collaborative and multidisciplinary networks with companies and academia to implement real-world pilots with the full engagement of practitioners and patients, validating tools and methods and leveraging the healthcare transformation and citizens’ quality of life.


How can We Successfully Converge the Health and Technology Ecosystems to Create Value for Patients?   

Gray, M. & Jani, A. Promoting triple value healthcare in countries with universal healthcare. Healthcare Papers (2016).

Leung, T. I. & van Merode, G. G. Value-Based Health Care Supported by Data Science. in Fundamentals of Clinical Data Science 193–212 (Springer International Publishing, 2019). doi:10.1007/978-3-319-99713-1_14

Elf, M. et al. The case of value-based healthcare for people living with complex long-term conditions. BMC Health Serv. Res. (2017). doi:10.1186/s12913-016-1957-6