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Digital health also requires care

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The global digital health market is experiencing a boom: with spectacular growth, it could reach $660 billion by 2025. Investors have poured an unprecedented amount of money into the sector in 2020, a year of record funding for startups in the area. Among the 399 healthcare executives heard in a recent Accenture study, 81% said the pace of their organizations’ digital transformation is accelerating.

One segment that has grown a lot is digital therapeutics (DTx), defined Digital Therapeutics Alliance as a “new category of medicine”, characterized by delivering medical interventions directly to patients using wearable devices, sensors, and evidence-based software to treat, manage and prevent a broad spectrum of diseases and disorders.

To keep up with the changes and the digital health market itself, the team at The Medical Futurist decided to put the most important companies in a giant infographic. It points out the TOP100 digital health companies in 2021, according to the entity.

Source: The Medical Futurist

All participants in healthcare systems can benefit from the contributions of digital health – to improve outcomes, increase patient convenience and reduce costs – but there is still much work to be done to bring digital health into the mainstream.

Privacy and security

Of course, considering that DTx is a fully digital option, they bring with them a plethora of relevant privacy and security issues. These technologies will increasingly handle sensitive data and become victims of malicious third parties. As such, their design and clinical applications must take these issues into consideration and strengthen cybersecurity measures as much as other health monitoring services, local, within medical institutions, and remote.

Modern hospitals are highly digitized. The availability of patient data is at the heart of this digitalization. Traditional IT systems and medical IT work together in an integrated manner and require a central monitoring solution. 

Remote health monitoring systems, meanwhile, have increasingly become a reliable solution for providing personalized, less intrusive, and patient-friendly healthcare services.

As with all technology solutions, an end-to-end risk assessment must be carried out taking into account the specific characteristics, configurations, and variations that each organization or operation presents, although there is much in common between them.

Technically, any such health monitoring system has four layers:

  1. Sensitive layer: this layer is responsible for reading patient information. For example, it is possible to program it so that a doctor can track the patient’s geographical location (important for patients with amnesia), as well as blood pressure and sugar levels.
  2. Network layer: Once the patient information has been received, it needs to be transferred. This is where the network layer comes in. This part is responsible for the fast transfer of data from the patient’s device to the doctor. All medical devices require a classic IT infrastructure for communication. This infrastructure takes care of the data transfer and provides the hardware for the system network. It requires cables, switches, servers, and storage systems, as well as WIFI and its access points. Therefore, to ensure security and privacy the medical devices and systems require comprehensive IT monitoring. Device availability, data transfer, and application performance must be kept under continuous observation.
  3. Data processing layer: at this stage, the analysis of the information takes place. The system can draw a quick conclusion about a patient’s condition, because it is powered by AI, and quickly notify a doctor if the patient needs immediate help. Also, with the artificial intelligence built into the HMS, it is possible to make predictions that a patient may get worse, even if everything seems normal.
  4. App layer: after processing the data, the doctor receives a message in an app installed on his smartphone, tablet, or PC. By knowing everything that is happening to the patient, the doctor can make an informed decision about future treatment, allowing the patient to go home or change the course of treatment if necessary. In addition, the most advanced health monitoring system can be powered by deep machine learning, so the doctor can also receive AI-based suggestions on the diagnosis and course of action to be performed.

For too long, healthcare institutions and authorities have protected our health data. Protected as physical records and in IT systems, this medical information was not even accessible to us. With the digitization of healthcare, these authorities have to double down on the secure management of sensitive data, as healthcare is increasingly moving from the clinic to the home, where people are treated via telehealth services and monitored for signs and symptoms with the help of smartwatches, apps and other technologies that can be connected to a wireless network and/or can apply algorithms to the data collected. Are these health authorities up to the task?

Medical information is already among the most valuable items on the black market. It allows counterfeiters to file false insurance claims and even purchase medical equipment illegally. This valuable commodity is leading to an increased incidence of compromised health records. Predictions indicate that the amount of digital data in 2025 will be 175 zettabytes or 175 trillion gigabytes. And the contribution of digital health tools to this very significant block of data is not negligible.

Today’s systems are more complex than ten years ago and have many new components. Likewise, more processes are running on a typical computer than ever before. To ensure smooth operation, you need to continuously check the operating parameters of your equipment so you can respond proactively.

This is why system monitoring tools have become a necessity. They allow administrators to spend their time on more productive and rewarding tasks while the tool monitors the system and alerts the administrator when something is wrong, usually before it becomes a real problem. This gives the administrator enough time to react and correct the problem. Especially for administrators of digital health systems.

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