Data Science in health market
The cloud imperative in healthcare
Two years ago, organizations were experimenting in the public cloud. Now their focus is on migrating legacy technology to the cloud and transforming data and applications using capabilities that aren’t available in their existing infrastructure solutions. Yesterday, cloud was about aspiration. Today, it is about scale.
Cloud is a disruptive force fueling innovation in the industry. Healthtech players with cloud solutions continue to grow as market influencers. In addition, the big three cloud hyperscalers— Microsoft, Amazon and Google—have healthcare in their sights and are investing in innovation.
The intersection between digital technology and healthcare experiences has certainly accelerated with the COVID-19 pandemic, and leading the future of care will demand rethinking core assumptions about the intersection of people and technology. People’s perceptions of and relationships with technology are changing, and to adapt, healthcare payers and providers need to redesign digital experiences.
Maintaining Medical Journals all in the same place across different hospitals and clinics.
In Sweden this practice started a few years ago, but recently newer implementations on the current database makes possible for citizens to have access to their own medical journal as well a more strick control over pescriptions and medicine prescription.
Data Warehousing can provide controlled data to different actors in the health market without invading privacy from the patient.
Data mutation occurs in real time and all periphericals that require that specific data are updated in real time. On the other side the fetching of data from the system is stricly restricted to the operations of the peripherical might need in order to protect the privacy from the patient. These transfers are done under an active webhook in order to keep the data in realtime.
Step 2. Data prediction
Data warehousing has been a trend since 2016 and most of the hospitalar management systems are using it. Nevertheles at nortb we decided to take a step further and research how to combine predicative analysis within the process, by expanding the above diagram and including two more servers while turning the process cyclic, increased the data cycle efficiency almost in 40%.
Real Time Data
between all units.
between patients with common denominators.
And advising patients to seek a doctor.
We included an analytical server that models different variables related to human body denominators or test results in real time, creating thus a structured comparison based on the different model-chains by relating sets of the most similar cases. This unique server only function is to send a set of different scenarios to the predicative server where different statistical models are calculated.
The Predicative server in the other side compares the received scenarios with the patient history and in case of a comparison between different scenarios achieves a rate of more than 85%, the patient is warned to seek medical help as well the same data information is sent to the medical unit where the patient is registered. Upon triggering an alarm in the system, the information is redirected to any access point (medical centers, hospitals, pharmacies, etc...) which makes the data cycle be complete. A full controll is achieved, assuring an active supervision over the patient medical status.
Data Distribution & storage
Data takes the most important role nowadays. Increased hacker attacks made the three major providers adopt different measures arouund data storage and data handling. One of the most important shifts in data warehousing in recent times has been the emergence of the cloud data warehouse. Previously, setting up a data warehouse required a huge investment in IT resources to build and manage a specially designed on-premise data center. Now, several cloud computing vendors offer data warehousing functions as a service (DWaaS), accessible via an Internet connection. This model negates the costly capital expenditure and management required for an on-premise data warehouse.
The evolution of cloud computing in healthcare has revolutionized how the computing is abstracted and utilized on remote third party infrastructure. Introducing the cloud services in the health sector not only facilitates the exchange of electronic medical records among the hospitals and clinics, but also enables the cloud to act as a medical record storage center. Moreover, shifting to the cloud environment relieves the healthcare organizations of the tedious tasks of infrastructure management and also minimizes development and maintenance costs. Because of probable disclosure of medical records stored and exchanged in the cloud, the patients’ privacy concerns should essentially be considered when designing the security and privacy mechanisms. Security strength defines the success of any network service. This survey paper aims to discuss, analyze security challenges and available solutions in cloud computing. Various approaches have been used to preserve the security of the health information in the cloud environment.
From the back office to the doctor’s office, we help clients deliver more effective, efficient and affordable healthcare with Insight Driven Health.
Data Driven Health
Data Driven Health is the new program of nortb's innovation-led approach to more effective, efficient and affordable healthcare.
Our servers operate at the intersection of business and technology to combine real-world experience, clinical and business insights and new, enabling intelligent technologies to deliver the power of Data Driven Health in a demanding new digital world.
That's why the some healthcare providers choose nortb for a wide range of end-to-end services that help them become the intelligent healthcare enterprises of the future—from the back office to the doctor's office.
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