Patient monitoring via connected devices generates huge volumes of data.
To extract usable information from this unprocessed and unorganised data, healthcare providers are increasingly turning to big data analytics and other analytics solutions, according to Frost & Sullivan.
In particular, predictive analytics is becoming important because it can not only show the current state of the patient’s health but also predict future illnesses. The success of this and other technologies attracted $566.3m (£431.5m) in healthcare data analytics investment in 2018.
“As mHealth rapidly gains traction, wearables, telehealth, social media and patient engagement are expected to find adoption among more than half of the population in developed economies by 2025,” said Sowmya Rajagopalan, advanced medical technologies global director at Frost & Sullivan.
The research and analysis firm forecasts that the patient monitoring market will be worth more than $350bn (£266.7bn) by 2025, with the focus moving beyond device sales to solutions.
“In the future, patient monitoring data will be combined with concurrent streams from numerous other sensors, as almost every life function will be monitored and its data captured and stored,” Rajagopalan said. “The data explosion can be harnessed and employed through technologies such as Artificial Intelligence (AI), machine learning, etc., to deliver targeted, outcome-based therapies.”
Patient monitoring solution developers will also look to incorporate disruptive technologies such as:
- Brain-computer interface (BCI): BCI monitors and measures health metrics and uses the information to analyse a person’s psychological state or emotional, cognitive state.
- Wearables/embedded/biosensors: This technology is being driven by an increase in the chronic disease population and shift from treatment to prevention. Continuous glucose monitors, blood pressure monitors, pulse oximeters, and electrocardiogram monitors are some of the main applications.
- Smart prosthetics/smart implants: These are used for patient management after surgery and for rehabilitation. They help in measuring the key parameters to support monitoring and early intervention to avoid readmission or complexities.
- Nanorobotics/digital medicine: Digital pills and nanorobots are designed to monitor medicine intake to address the issue of non-adherence.
- Advanced materials/smart fabrics: This emerging field focuses on wound management, cardiac monitoring and mental illness.
All these technologies provide real-time, measurable value to patients and healthcare institution. Future innovations will be aimed at mass personalisation and availability, Frost & Sullivan predicts.
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Tags: AI, big data analytics, healthcare data analytics, patient monitoring data