Five Trends in Digital Health Transformation
Digital health transformation will continue to gain momentum over the next few years, and healthcare providers are increasingly looking to digital technologies for ways to improve patient care while determining the best practices in a regulatory framework. These five trends in digital health transformation are changing the way people approach healthcare.
- Consumer AI: Health systems are now incorporating artificial intelligence (AI) into their operations in order to better tackle complex challenges related to population health management. Apart from this, consumer AI also has a significant role in improving the current state of healthcare. At home, for instance, AI can help patients better understand their symptoms and treatments by making personalized recommendations generated from an individual’s own unique biological data.
- Big Health Data: Big health data is an ever-increasing world of information that can offer businesses and healthcare providers useful insights about patient care. For instance, big health data can be used to better predict the onset of chronic conditions among patients who are predisposed to them. It can also create more efficient and effective clinical pathways and improve hospital management operations. This aligns with recent calls to take the emphasis off people’s medical records and on overall health plans, as well as utilizing data to deliver information over simply supporting transactions.
- Cloud Data: Cloud computing enables rapid data access and processing, which can help healthcare providers make more informed, real-time decisions. Healthcare organizations are also starting to use cloud-based technologies for better information management. And lastly, cloud networks are paving the way for better telehealth solutions like remote medical monitoring and mobile health services.
- Drug Discovery With Machine Learning: ML refers to predictive analytics to sift through huge amounts of medical data and identify patterns that can be used to improve patient outcomes. In the coming years, I predict we’ll see a bigger focus on applying ML technologies to drug discovery, drug development and pharmaceutical industry processes. Using predictive analytics in this way enables healthcare providers to deliver targeted care plans that are based on individual patient needs.
- Personalized Genetic Testing: With genetic testing, healthcare providers can analyze an individual’s DNA to create a model that predicts how they are likely to respond to certain drugs or treatments. Using this type of advanced predictive analytics enables drug developers to develop personalized treatment plans that could potentially improve the lives of patients with certain conditions. With the proliferation of this technology and service, consumers will have more options for genetic testing, and these tests can give healthcare providers access to even greater amounts of data in order to improve patient outcomes and treat patients more effectively.
As more people worldwide get access to smart technology in their homes, health-related apps and services, including telehealth solutions, will continue to become an increasingly viable option for patients who want to stay home but still get quality healthcare. And as innovation continues to move ahead, global policies and regulations will have to determine how best to use these technologies to ensure safety and efficacy.
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