The potential of collaborative work arrives strongly in the health management universe with the possible advent of the open health – a unified platform with integrated health information. Clinical histories, test results, physiological characteristics a click away form patients and health professionals. In the midst of legal, regulatory, marketing and ethical discussions, it is apparently undeniable that this movement tends to gain relevance given the possibilities of optimizing time and resources in health administration, as well as improving the experience of doctors and patients in saving lives and maintenance of well-being. Given this, how can you anticipate this trend and prepare your health structure for the open health? 

 Proposed in allusion to open banking, health ecosystems are more fragmented than those of the banking system, implying additional challenges for their implementation. More often than not, the same clinic or hospital has different systems that are incompatible with each other, depending on different suppliers, technologies used, tools and specific operating standards. At the same time, it also demands standardization in filling out forms, organizing data and making information available, whether simple, in image, video or other formats according to the representative drawing (Fig 1):

Fig 1. – Representation of systems without interconnection  

This data optimization tends to reduce the time used to measure characteristics and biological markers; facilitate the monitoring of health conditions (improving the journey of the patient and doctor); Save lifes; reduce complex healthcare expenses; and, even in a second moment, employ data medicine algorithms to predict the need for examinations and preventive consultations – such as, for example, to observe the evolution of comorbidities or the identification of neoplasms.  

Faced with the need to invest resources, time and, sometimes, adjustments in the organizational culture linked to the management of health data, the creation of small models of collection, storage, security, traffic and access to information would be recommended. This strategy tends to allow greater speed in the development of solutions, usability evaluations, measurement of results with the health teams and evaluations of scalability of the system to other centers or departments. But we still have some challenges to overcome:

• Health data is decentralized, spread across several systems, whether public or private.
• Because of this, there is a lack of standardization of this data for interoperability; 
• Assurance of the security of patient information, traffic and data storage.  
• LGPD (General Personal Data Protection Law), in which health data are considered extremely sensitive and are protected by other rules, such as the confidentiality rule between patient and health professional.

Such a transformation in the logic of using health information requires careful regulation and legal review, especially with regard to data access and portability to guarantee people’s privacy and determine the possibilities of using this asset aimed at maintaining health.  

At act digital, we have an initiative that aims to solve the challenges mentioned in one of our clients in the healthcare sector. Through an innovative approach, using Design Thinking, Agile, and Lean Inception, we align a shared business vision and make a highly scalable solution tangible through the use of technologies such as micro services, Big Data, associated with Machine Learning and Artificial Intelligence. Together with Cloud Computing, we solve information availability and security problems, reducing operating costs.  

In this way, several data sources are stored in a single location (Datalake), where data scientists/ engineers will work with raw data to generate unified and valued information for future uses. These processes are automated according to the creation of artificial intelligence, allowing this information to be consumed in various health sectors.