artificial intelligence healthcare applications

Trendsetting Applications of AI in Healthcare

We live in a digital age, so it’s not surprising that the healthcare industry follows suit. From the data-driven insights of wearables to mobile apps that help manage chronic conditions, it’s clear that technology is changing healthcare forever.

But what exactly are people getting their hands on? As a long-time public health physician and leader on digital transformation in healthcare, here are some of the most exciting trends in digital health that I see shaping the industry right now.

Consumer AI

Many health systems have already chosen to incorporate artificial intelligence (AI) into their operations — and it’s not just for cost-saving purposes. With the help of AI, healthcare organizations can better tackle complex challenges related to population health management like declines in patient satisfaction, rates of readmission and rising costs of care.

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.

After all, personalization is key to providing better healthcare outcomes. What is also helping push consumer AI further into healthcare is its use as a popular application for wearables. Apps such as Google Fit and Apple HealthKit provide individuals with an in-depth picture of their health and wellness through tracking data, which can potentially help them better understand their conditions.

Challenges in working on improving the regulatory framework will persist. In what some experts describe as “digital trust,” these issues of privacy in health data will need to be addressed as innovations rapidly emerge in response to the needs for patient-centered care.

Big Health Data

The proliferation of wearable technology also helps contribute to the rise of big health data, an ever-increasing trove 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. 

There is also now a greater focus on developing big health data initiatives that enable secure exchange between healthcare providers and their patients, especially when it comes to cloud-based technologies that offer real-time tracking of patient health data.

Cloud Data

The adoption of cloud computing technologies is also helping to usher in a new era of digital transformation in healthcare. 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. This includes adopting solutions such as electronic health records (EHRs) since they allow healthcare providers to store, manage and share data more easily.

Cloud networks are also paving the way for better telehealth solutions like remote medical monitoring and mobile health services. In the future, I see virtual healthcare services as becoming an increasingly viable option for patients who want to stay at home.

Drug Discovery With Machine Learning

With the rise of big health data comes an increased emphasis on machine learning (ML) in healthcare. 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. An example of this is the use of ML to predict patient drug responses that can help identify which patients will benefit the most from a certain treatment.

This type of predictive analytics works well with genetic data and offers clues about how an individual will react in specific situations. Using predictive analytics in this way enables healthcare providers to deliver targeted care plans that are based on individual patient needs.

Personalized Genetic Testing

Genetic testing is another area where predictive analytics will play a major role in the future of consumer AI and healthcare. 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. For example, pharmacogenetic testing has recently been used to treat chronic pain in children, and the process can potentially save billions of dollars that go to ineffective drug therapies.

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. However, more research is needed to determine the benefit of this testing broadly in diverse populations.

Bottom Line

Digital health transformation will continue to gain momentum over the next few years, and healthcare providers are increasingly looking toward digital technologies for ways to improve patient care while determining the best practices in a regulatory framework.

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.

Author: Anita Gupta

Source: Forbes