The health tech revolution creates incredible opportunities for all stakeholders in the healthcare system. New AI-enabled tools are popping up so rapidly that the industry is seeing explosive growth. A new study from Precedence Research values the healthcare IT market at $880 billion, and expects it to reach $3.7 trillion within 10 years.
But just having more tools isn’t enough to guarantee results or bring about a healthier society. That’s why many of us in this field have been focusing on building the next stage in at-home care: making the industry more patient-centric. Big advancements were made over the past year, and even more can be expected in the year ahead.
More predictive and assistive
Numerous tools have been created to help people track key health metrics or gauge symptoms, from cardiothoracic to respiratory care and much more. People suffering from atrial fibrillation (AFib), hypertension, diabetes, obesity, and other conditions increasingly have the ability to check vitals without a visit to the doctor.
The new wave advances early detection abilities. These tools can now provide more proactive insights about each patient. And because they collect longitudinal data, they can spot subtle changes over time. For example, machine learning systems may recognize that a patient’s ECGs (electrocardiograms) appear clinically normal in isolation, but are also showing signs of potential degradation — before the patient is symptomatic, and before doctors would usually spot those patterns under traditional methods.
These tools can alert patients and connect them with experts to discuss the findings. This makes preventive care more viable. Prevention is more effective than treatment after a disease has progressed, and saves large sums of money in healthcare costs. This is particularly true in my field, heart health. Heart disease remains the leading cause of death worldwide and in the United States (even though the number of heart attacks has decreased). An estimated 80% of heart disease is preventable. But it can be difficult to detect, which makes monitoring — especially for people at higher risk — especially important.
Harmonization boosts holistic health
The proliferation of digital health tools means that people are now collecting data about more aspects of their own wellbeing. In addition to ECGs, they may be tracking blood pressure, blood oxygen, glucose levels, physical activity and more. When combined, the power of these tools is greater than the sum of its parts.
Through “sensor fusion” — combining data from different sources — this technology can stitch together a more contextualized, holistic understanding of each patient’s health. This kind of harmonization is one of the most exciting advancements in the field. Maximizing its potential requires cooperation; the more these tools share data, the better their results will be. This requires companies to develop more partnerships and data-sharing agreements.
Electronic health records (EHRs) are also an important part of the picture. They’re filled with vital information, from a patient’s history to genetic factors, traumas, surgeries, and allergic reactions. The more this data is combined with findings from digital health tools, the more actionable information can be provided.
All of this can be done without sacrificing privacy. Strides are being made in anonymization, pseudonymization, and advanced encryption techniques to help. For example, in training and validating tools, there should be no personally identifiable information (PII).
Understandable, empathetic, and safe
To serve patients, these tools must be consumer-centric and user-friendly. That’s why the latest advancements in natural language processing (NLP) are so significant. AI health technologies can now speak in ways that help patients understand findings and feel more comfortable.
Through sentiment analysis, the best tools adjust output to provide a greater sense of empathy. They understand patients’ questions and concerns, and adjust their responses to be most understandable and resonant for the individual. Our research has found that many users want these voices to come across as supportive in addition to being informative.
A quality tool must also be clinically validated and backed up by extensive research across large and diverse populations. And guardrails must be in place, preventing the tool from offering any guidance that could harm a patient, and ensuring that the tool doesn’t overstep its mandate. For example, a digital health tool can’t clinically diagnose a condition; only a licensed practitioner can do so.
The new era of AI in healthcare is promising. While remote patient monitoring (RPM) cannot yet replace human doctors, it can be an always-present assistant to help people be proactive in managing and tracking their own health. It reduces dependence on an overstressed healthcare system.The more it’s used to its greatest capacity, the more lives it will save.
Photo: lorenzoantonucci, Getty Images
Al Woo is chief product officer at AliveCor, the leading provider of FDA-cleared personal electrocardiogram (ECG) technology. Alivecor is transforming cardiology with its medical-grade AI-powered solutions. Al and his team manage a portfolio of innovative devices and services for consumer and clinical markets. These include Kardia devices, the most clinically validated personal ECGs. Their latest innovation, Kardia 12L, designed exclusively for healthcare professionals, is a 12-lead ECG system that expands access to clinical grade ECG diagnostic capabilities across a variety of acute care settings.
AliveCor’s enterprise platform allows third-party providers to manage their patients’ and customers’ heart conditions simply using state-of-the-art tools, addressing gaps in care and improving the treatment experience for patients across a range of disease areas. Before joining AliveCor, Al was principal product manager with Alexa Voice Service at Amazon and director of product marketing at Synaptics. He received his engineering degree from the Massachusetts Institute of Technology.
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