Innovations in computer science and data science are on track to revolutionize almost every sector of the economy — including critical fields like healthcare. Big data, AI and smart technology all provide organizations with better access to data than ever before, as well as new tools for extracting insights from available information. So what is disruptive technology? Disruptive technology in healthcare causes radical change and often results in new leadership. In another industry and time period, the lightbulb could be considered disruptive technology. In today’s healthcare market, telemedicine, or virtual healthcare, is one of the biggest recent disruptive innovations.
Over the next few years, these three technologies have the potential to significantly improve how healthcare providers treat patients.
1. Internet of Things (IoT) and Smart Technology
IoT and smart devices, which connect to the internet to transfer or receive data, could offer significant benefits for healthcare providers and health systems. And it’s another disruptive innovation example in healthcare.
Data from a device like a smartwatch, for example, could be accessed remotely, providing critical health information on patient vitals, like blood oxygen level or heart rate, for providers to care for patients, even when they’re off-site.
Smart devices can also continuously upload information to the cloud, allowing healthcare facilities to perform real-time analysis of that data or store it for future study using medical devices for disruptive innovation.
With the right design and patient permission, critical updates on patient health could be instantly stored in electronic health records (EHRs), reducing administrative overhead and ensuring that health records contain the most recent and relevant data possible for an overall business model innovations. For healthcare providers, this could ensure health records remain up-to-date and accessible. And, connected devices can enable providers to receive real-time alerts when critical health indicators are outside of normal ranges.
Many new smart EHRs are increasingly designed to interface with smart technology like IoT patient monitors, meaning that hospitals may easily integrate these two technologies with manufacturer-provided tools.
Wearables
While telehealth has many benefits, it has one major drawback — it’s difficult or impossible to track certain kinds of patient health data over the internet, like patient vitals.
New wearables may help to change this. Wearables are one of the most common types of IOTs, and these internet-connected, wearable biosensors can allow doctors to automatically track important health data after a patient has returned home. These sensors, often in the form of smartwatches or ECG monitors, can provide continuous monitoring for patients, doctors and other care providers.
There are many different diagnoses or diseases that can be better managed using wearables, even in neurological conditions like Parkinson’s disease. In typical treatment practice, these patients are required to monitor and record their condition — delegating work to the patient and providing data that is non-continuous and sometimes unreliable.
Wearables have also been used to track home recovery after patients have been discharged from a hospital following an ICU stay or surgery. The devices can help reduce or eliminate the need for follow-up visits, ensuring doctors can track patient health without requiring the patient to return to the hospital.
As they generate data, wearables can instantly store relevant information in patient health records, ensuring that anyone with access to their health records can view updates on a patient’s condition or progress. This kind of data could be helpful to both primary and specialty care providers and other health professionals like physical therapists.
2. AI and Big Data Analytics
AI and big data analytics enable data scientists to process massive amounts of data — more than conventional techniques can manage.
In the healthcare industry, AI-powered analysis may help uncover new treatments and assist care providers in decision-making.
Already, AI has been used in an experimental capacity to help doctors interpret MRIs, analyze CT scans and better understand patient data. A Google AI algorithm, for example, outperformed six expert radiologists in identifying breast cancer on mammograms, suggesting AI could significantly improve the accuracy of breast cancer screening in the future.
Other AI algorithms specialize in breaking down language and speech rather than numbers or visual information.
Natural language processing (NLP) is the use of AI to break down language that’s written naturally — how most people speak it.
These tools can enable new technology like Providertech’s AI-powered medical chatbots, which use NLP to facilitate text messaging-based communication between patients and AI. These AI chatbots can provide 24/7 and contactless access to medical information — and with a human-like conversational style that more conventional chatbots can’t offer.
This can help providers to take full advantage of telehealth by mitigating some of the technology’s drawbacks, allowing them to provide better care over the internet.
The bots can also be used to gather patient data, serving as a more user-friendly check-in questionnaire. Already, the bots have been used to help organizations screen patients for COVID-19.
In the future, hospitals could use similar technology to improve medical record keeping. An algorithm trained on EHR data could detect instances of upcoding, for example, or automatically summarize records, drawing out the most essential information in a patient’s medical history.
New algorithms could also help identify patient segments that medical organizations are failing to reach or help design strategies that may improve communication with underserved communities.
3. Personalized Medicine
With analysis of patient health and genetic data, it’s possible to tailor treatments to individual patients.
Information on a patient’s genetic and molecular profile can allow care providers to order tests or prioritize therapies more effectively.
As AI becomes more effective at analyzing language, doctors could also use language processing algorithms and EMRs to drive personalized medicine (or “precision medicine”).
New algorithms can comb through patients’ medical records to generate personalized recommendations based on information like previous responses to medication, family health history, genetics and risk factors.
For example, doctors are already using certain genetic markers to determine where to begin treatment. Genetics can influence how well a drug works and the side effects it may cause. Doctors can use genetic information and precision medicine platforms to more effectively prioritize treatments when multiple options are available.
How Innovative Technology May Transform Patient Care
New technology is on track to revolutionize patient care. Wearables and other smart devices will help to provide doctors with greater access to patient health data, helping to streamline hospital operations and make telehealth more practical.
At the same time, AI and big data analytics will help doctors make sense of the data and extract new insights that can be used to improve patient care
For healthcare organizations wanting to take advantage of these innovations, new communications technology is one of the best places to start. Learn more about how businesses like Providertech are integrating AI into new healthcare solutions that can help providers adopt this technology.
