Personalized Medicine. A New Healthcare Paradigm Based on ICT Tools

During the last decades, the ICT revolution has dramatically transformed the way people and companies operate. The continuous development of ICT tools, not only has helped organizations to improve their productivity, but also has created completely brand new industries.

However, the healthcare industry has not historically embraced such technologies as fast as others. Traditionally, and in a classic product adoption lifecycle context, healthcare organizations used to be part either of the late majority or the laggards segments. Among others, the most important reasons of the slow deployment are:

  • existence of a high bureaucratic system with a wide number of actors involved in decision making.
  • difficulty to cope with high volumes of heterogeneous data
  • high costs involved in the storage and the analysis of the information.
  • legal issues concerning personal data management and data compilation
  • patient´s mistrust about data management of sensitive information.
  • lack of IT literacy of some segments of the healthcare workforce.

Historically, the main stakeholders of the healthcare system have not had big reasons for changing a classic, bureaucratic and highly profitable system. Large corporations have been interested in maintaining a corrective based and scale intensive model, focus in general diagnosis and treatments. On top of that, public administrations have contributed to create massive public systems whose efficiency is increasingly being questioned.

However, during the last few years, two main forces are producing a turning point, enabling a rapid implementation of ICT tools in healthcare sector. Today, the industry is considered to have a high potential for implementing such solutions. This revolution is generating a paradigm shift, from a traditional medical system, to a personalized medicine approach. A model centered in patient´s particular characteristics.

In developed countries, Governments are deploying a “push strategy” to change the situation. This is the first driver that is speeding up the pace at which the industry is evolving towards technological based models. Since an economic point of view, classic healthcare systems are no longer sustainable. Public institutions are seeing the new personalized medicine paradigm as an opportunity to create better solutions at a considerable lower cost. An example of this approach is the Horizon 2020 Healthcare framework developed by the European Union, funded with more than M€ 450 for the period 2014-20.

The second driver that is enabling this transformation is technology. New text mining and cognitive computing processes are allowing doctors and researchers to use unstructured data. This kind of data can be extracted from papers and other plain text documents and, analyzed as a whole, can provide useful information when diagnosing or treating a patient. Moreover, the cost of computer power needed to analyze huge amounts of data is becoming available at a reasonable cost, allowing activities that could not be imagined only a decade ago.

Data is nowadays present everywhere. Healthcare is a data intensive industry that uses knowledge to transform symptoms and pre-tested hypothesis in diagnostics and treatments. Nowadays, there exists an affordable technology capable of measuring and analyzing the data of the patient on an individual basis allowing, not only to create on-demand treatments, but to develop specific plans to predict and prevent diseases in advance.

The battle of Personalized Medicine has begun. A new dynamic and highly heterogeneous industry is being formed. Pharmaceutical, ICT, Insurance, Telecommunication, Consumer Electronics, are only a few of the sectors that are interested in creating specific divisions to develop products and services in the eHealth market. Based on its core competences, they will offer value propositions that will vary. However, most of them will have to implement big data platforms to turn raw data into meaningful value.

Francisco Parra, Research Analyst @ Delfos Research.

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