Healthcare data is data of a medical nature and/or data relating to the broad determinants of health in respect of the state of health of a given individual, consisting of information about the past, present or future physical or mental health of the person concerned, including information regarding the patient’s registration for the provision of healthcare services.
Governments consider healthcare data to be particularly sensitive, as it makes it possible to identify an individual on the basis of specific, private information. The majority of legislation, therefore, protects the personal nature of certain data.
This is why, in France, it is known as “personal healthcare data”, which is defined by Art. 2 of the French Law on Computer Technology and Freedom as “any information relating to an identified individual or who may be identified, directly or indirectly, by referring to an identification number or to one or more items relating to him/her.” It should be noted that medical data is no longer considered “personal” when it has been anonymised so that it would no longer be possible to re-identify the patient.
Each day, tens of thousands of items of healthcare data are created, mainly by medical diagnostic or monitoring equipment. For example, scanning a single organ for one second is estimated to produce 10 gigabytes of data and that the amount of medical imaging is increasing overall by 20-40% per year.
So, healthcare professionals and healthcare establishments face a major issue: how to host and store the data they generate every day, and how to ensure its sustainability and security. In addition, this data, and in particular the interpretation, analysis and cross-referencing of it, represents an economic mother lode of unprecedented proportions and a major challenge for society in terms of research, public health and prevention as well as the economic efficiency of our social-health systems.
- Equipment for the remote monitoring of patients generates an average of 1,000 measurements per second, i.e. 86,400 measurements per day.
- 16,000 hospitals worldwide collect patient data.
- 1 X-ray in 5 is unnecessary repetition of an examination already performed, which represents a waste of $20 billion every year.
- 65% of patients think that the security of their healthcare data is more important than the ease with which they can access it.
In practical terms, how can we manage data and make it meaningful while keeping it secure?
France was one of the first European Union Member States to introduce specific regulations to ensure that personal medical data is hosted safely and appropriately. These provisions aim to organise and provide a framework for the submission, storage and retrieval of personal healthcare data under conditions that guarantee it remains confidential and secure.
The legislation works on the assumption that medical data is highly sensitive for many people, if not most. Therefore, decree no. 2006-6 of the Code de la Santé Publique (the French Public Health Code) governs data hosting and requires healthcare professionals and healthcare establishments to use the services of an accredited hosting service provider if they outsource the hosting of personal healthcare data “collected or produced within the framework of prevention, diagnosis or care activities.” If they opt to host their patients’ data on their own systems, they are not required to be accredited, but they do need to ensure the data can be stored and kept confidential for 20 years.
Tweets about it...
Healthcare Data Une liste Twitter par @OrangeHCare
🔐 Vous avez jusqu'à la fin du mois de mai 2020 pour contribuer au projet de loi sur l’identification et l’authentification des usagers du système de santé, dans le but de finaliser le texte et de publier l’ordonnance d’ici la fin de l'année 🗓
Orange Healthcare has made data protection its priority.
With that in mind, Orange became the first telecommunications operator in France to become an accredited provider of hosting services for personal healthcare data,
following a long and thorough screening process that covered a wide
variety of criteria, from access to data, authority and control, to risk
As a trusted third party, Orange Healthcare offers its expertise in the hosting, storage and archiving of personal healthcare data to healthcare establishments. Its Flexible Computing Santé service uses Cloud Computing technology to enable healthcare establishments and professionals to store hosted data and access it remotely on demand. This solution is completely tailored to the establishments’ actual needs and can be adapted over time to changes in these needs, to guarantee performance and flexibility.
But beyond the hosting of this data, Orange Healthcare is convinced that data analysis is a crucial factor in diagnosis and prevention.
Applying Big Data techniques to the world of healthcare results in the
emergence of new practices in epidemiology, preventative and
personalised medicine, or even in the development of new patient support
Orange Healthcare plays a leading role in this field and at the end of 2014 it set up, together with several high-profile partners, the Healthcare Data Institute, a think tank focusing on Big Data in healthcare.
Big Data in healthcare; uncovering the potential of medical data
This is a subject that goes beyond the ongoing debate on data protection, and its potential for transforming the healthcare sector is under-estimated. Indeed, the use of personal data on health and social interaction is a key issue for research, public health and prevention, as well as for the economic efficiency of our social health models.
But above all else, it is the interpretation, analysis and cross-referencing of this data by those who have come to be known as “data scientists” that could revolutionise healthcare in the future:
By making it easier to access healthcare and medical information and enabling them, once they are more aware, to take control of their healthcare data and, therefore, of their day-to-day health
By making it possible for them to use targeting techniques and diagnostic assistance tools to select more suitable treatments and to provide the right treatment at the right time, to the patient most likely to respond to it.
By optimising care pathways and their effectiveness and by analysing data on a national scale, which would make it possible to anticipate healthcare needs (estimates suggest that Big Data in healthcare could enable the United States to make savings of $300-$450 billion).
By making it possible to speed up its research and development cycles, but also by maximising the effectiveness of treatments by targeting the patients treated.
Orange Healthcare is particularly committed to this emerging field and, together with a range of partners, set up the Healthcare Data Institute in late 2014. Since then, it has contributed to the thinking on and the advancement of the potential applications of Big Data principles in the healthcare field. As such, having helped to gather more than 7 million items of healthcare data during the mHealth Grand Tour 2015, Orange Healthcare is supporting the researchers who are analysing this data for the purposes of developing good practice for the management of diabetes during physical exercise.
Healthcare data terms
Personal healthcare data is defined by Art. 2 of the French Law on Computer Technology and Freedom as “any information relating to an identified individual or who may be identified, directly or indirectly, by referring to an identification number or to one or more items relating to him/her.”
Abbreviated to: “Cloud” – means exploiting the calculation power or storage capacity of remote servers, through the intermediary of a network, usually the internet. Therefore, it involves delocalisation of the IT infrastructure.
Means data sets that are so huge that they are difficult to work with using traditional database management or information management tools.
A professional in the management and fine analysis of Big Data for the strategic and operational purposes of a company. They use statistical techniques and IT tools to structure, synthesise and interpret information. But whereas a data analyst generally examines data from a single source (e.g. CRM), a data scientist examines and analyses to a higher level data extracted from many fragmented sources.