Artificial Intelligence in Healthcare

Data: a key enabler for transformation

We live in a world where data is abundant and social networks proliferate. Ironically, information to support medical decision-making is frequently unavailable and, when it exists, it’s usually enclosed in silos of un-related information. Data fragmentation and lack of interoperability are healthcare challenges in today’s connected world. 

SARS-COV_2 pandemic highlighted the vulnerabilities of health systems around the world, showing how unprepared we are for contingency events. Evidenced the importance of building resilient health systems, teaching us the relevance of improving data collection and exchange to ensure that the right information is provided to the right people at the right time.

Future vision: data improves medical decision making

The attempt to maximize operational efficiency with limited resources still poses tremendous challenges. If the limited resource is the availability of solid organs for transplantation and operational efficiency of the programs, measure lives saved, the task in hands is even more daunting.   It’s clear that data is a key enabler for transformation, a facilitator that will help optimizing health service supporting, for example, paradigms shifts, from a treatment to a prevention model, from a single protocol to a personalized approach of the disease and of the patients. 

In Solid Organs Donation and Transplantation, the challenge to address organ scarcity requires data, more precisely, demands the collection and sharing of sensitive medical data through the entire treatment pathway, describing patient and donor initial medical conditions, the cycle of care, including treatments, processes, costs, and final outcomes, to support, in the future, medical team’s decision making. 

Unfortunately, solving the data scarcity challenge it’s only a part of the equation.  Medical teams must make complex decisions, combining ethical and medical variables, to achieve a decision on, for example, the allocation of an organ to a specific patient, ensuring a balance between utility (the best use of the organ) and equity (equal access for all the patients in the waiting list).  This is where Artificial Intelligence may help, by assisting medical doctors in situations where they deal with ambiguity and complexity. 

The role of Artificial Intelligence (A.I)

Artificial Intelligence is a promising way to manage complexity[2], ensuring relevant productivity and efficiency gains.

It is being used in two key areas in organizations across the world:  support organ allocation, and paired kidney donation.

  • Allocation: The most common allocation algorithm uses a point scoring system to allocate organs. In these systems, different points are considered for each criterion. The donated organ is allocated to the patient who earns the highest score. The most relevant challenge in designing these systems is identifying effective factors and weighting them to get the best utility and equity outcomes[3]
  • Paired key donation:  it is one of the great success stories of artificial intelligence. The reason is simple: it takes an incredibly complex problem and solves it faster and with fewer involuntary errors than humans, and as a result, helps to save more lives[4]. This method is currently used in the USA, but also in the UK, Canada, and the Netherlands.

Next steps: establish the basics

Organizations and Governments need to start by ensuring data collection. Data is the pillar of knowledge; so, data must be properly collected and systematized in a database for future scientific use.

Data exchange is the next step, to ensure that the right information is provided to the right people at the right time. 

But, as we have discussed, as some medical decisions are simply too complex and require too much time to properly analyze all variables, whether medical, ethical, or moral, ensuring a proper balance between utility and equity, A.I. behaves as a facilitator.

The value of AI in kidney matching and allocation is also to avoid bias, or how to reduce it. But we cannot forget that algorithms only perform well as the data they are trained on and processes set by their developers. AI can only be as good as data and data is created by humans, with their bias and prejudice. 

A.I. was one of the 2020 topics of the year, addressed both by researchers, and regulatory bodies. UNESCO has produced the first draft of a recommendation on ethics for A.I.[5], while the European Commission has created approaches on A.I. and A.I. ethics, with recommendations for member countries[6].

How can TransplantHUB contribute to the use of Artificial Intelligence in healthcare? 

TransplantHUB was conceived, by design and default, to answer to the transplantation digitalization hurdles. 

First and most significantly, TransplantHUB is a software for collection and exchange of information that encloses the information for clinical transplantation practice and health-services but also for clinical audits.

 The clinical information of the patient with end-stage organ failure encompasses a treatment lifecycle; from relevant medical history to tests, clinical exams and lab results, procedures, therapies, inpatient and outpatient clinics to outcomes, and even costing systems. 

The objective is clear: to support and accelerate medical decisions, while simultaneously creating the basis to identify and ensure the implementation of Best Practices and support of clinical medical research.

Reflecting upon the key issues of donation and transplantation, we decided to develop a tool to help medical teams to address one of their biggest challenges: the identification of possible donors, our Possible Donors Detection module.

We proceed by developing, using Artificial Intelligence in Healthcare, an organ allocation motor, with a catch: it’s fully customizable, so that it may be adjusted to a country-specific legislation and model on the subject.

We have developed a tool aiming to support medical teams to the best of our abilities, in their day-to-day life, simplifying and accelerating decision processes,  nevertheless, the patient’s care and final decision on diagnosis and treatment is the privilege of health professionals. 

Our motto is simple: “Better decisions. Less time. More lives saved”.

To find out more about how we may help, please contact us and we’ll be more than happy to manage a demo meeting and demonstrate, further, its developments.

Health at a Glance: Europe 2020, State of Health in the EU Cycle, December 2020, OCDE / European Union

Can AI Fairly Decide Who Gets an Organ Transplant?, by Boris Babic, I. Glenn Cohen, Theodoros Evgeniou, Sara Gerke, and Nikos Trichakis, December 01, 2020,, accessed on 28th of December 2020

 Identification and weighting of kidney allocation criteria: a novel multi-expert fuzzy method, Nasrin Taherkhani, Mohammad Mehdi Sepehri , Shadi Shafaghi and Toktam Khatibi, BMC Medical Informatics and Decision Making, 6 September 2019,, accessed on 28th December 2020.

How AI changed organ donation in the USA, Quartz,, September 2018, accessed on December 29th 2020. 

FIRST DRAFT OF THE RECOMMENDATION ON THE ETHICS OF ARTIFICIAL INTELLIGENCE, Ad Hoc Expert Group (AHEG) for the preparation of a draft text of a recommendation on the ethics of artificial intelligence, UNESCO, September 7th 2020,;queryId=basket-anon%3A7a202f62-c919-4f67-bf67-96dcf8110e64, accessed on 28th December 2020, 

On Artificial Intelligence – A European approach to excellence and trust 

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