The NHS established four guidelines to follow in its digital technologies to strengthen its medical and hospital services. The aim is that, over time, all the needs that users and companies require for the optimal exercise of their functions and in relation to the quality of health can be met.
The NHS continues to innovate its services to deliver better quality by reducing the margins of error and biases involved in upgrading to new technologies demanded by digital health users.
The new tools being developed by the NHS require a solid and renewed digital foundation. In the past, they tried an innovation program that did not deliver the expected results as it did not gain acceptance from doctors and patients since the implementations and public policies they addressed did not focus on the actual needs and priorities of the user, leaving it aside; for this reason the British Health System learned the lesson from this failed case in 2002.
Now, the commitment to creating digital health-based technology is to include 4 basic principles that ensure its proper functioning and proper handling.
These four digital principles are:
- Meet the needs of users: to build trust and use of these software and platforms.
- Ensure privacy and security: using a data bank that can be backed up by specific systems with high standards of protection.
- Be open and interoperable: allows the flow of data and the integration of the different systems that work with a large amount of information.
- Be inclusive: make it attractive to new generations and recognize that there is a full spectrum of people in terms not only of their access to digital technologies, but also their ability to use them.
An example of this new vision lies in the Netherlands, where Skin Vision developed a mobile app to capture images of moles and analyze them using the cloud to store them and, within 30 seconds, determine the risk of skin cancer.
In the process a dermatologist checks the images and patients who are at high risk of this problem receive advice within 48 hours.
Images are also added to a library, helping library prevent the onset of cancer by using machine learning and updating its knowledge patterns for detection. Currently its accuracy is more than 90 percent.
The conclusion reached was that patient-centered models in a total and comprehensive way are beneficial in achieving "digital maturity".
