Artificial Intelligence (AI) is continuing to gain traction in the realm of healthcare and medicine. According to a study by the American Medical Association, 41 percent of physicians said they are both equally excited, and concerned, about the potential uses of AI in healthcare.
As AI capabilities continue to grow, there are a variety of ways AI can be used in a practice. Let us outline several AI applications that have the potential to positively impact both patients and providers.
As we begin to talk about the specific AI indications for healthcare, now and in the near future, it is useful to understand that these solutions fit into three groups and time horizons:
Solution Groups
- Existing Solutions With AI: Solutions that use AI now but will be greatly expanded.
- Existing Solutions Without AI: Solutions that currently do not use AI but will do so in the future.
- New Solutions / Technologies: Brand new solutions that will use AI.
Time Horizons
AI is moving quickly, and it is difficult to predict when these solutions will appear. These are the timelines we will use in this article to determine how AI could affect healthcare:
- Near Future: 1-3 Years
- Mid Future: 3-5 years
- Far Future: 5+ years
As mentioned, the influence of AI is becoming increasingly pervasive in healthcare. Here are various solution types, and some examples, for AI in this space.
Solution Group 1: Existing Solutions With AI
2D and 3D Imaging Analysis
- What This Is: The expansion of solutions with AI analysis of 2D and 3D images to assist in the diagnosis of healthcare pathology and existing conditions.
- Time Horizon: 1-3 years
- Specific Examples:
- Automation of diagnosis and treatment planning for medical and dental patients.
- Efficiency improvements enabling healthcare facilities to analyze images quicker, providing increased efficiency in handling more patients, more accurately.
- Assistance in identifying patients and helping to reduce medical errors and adverse events.
- Greater image resolution to help healthcare professionals determine signs that individuals cannot always see. This helps create enhanced speed and precision for diagnosing medical and dental disease.
- Helping to reduce the risk of healthcare emergencies, e.g., stroke.
Remote Patient Monitoring (RPM) and Medical Internet of Things (mIoT) Solutions
- What This Is: RPM refers to the use of technology to monitor patients’ health remotely outside of traditional clinical settings using IoT devices: wearable devices, sensors, mobile apps, and other digital tools to collect and transmit patient data, such as vital signs, symptoms, medication adherence, and activity levels, transmitted to healthcare providers, for analysis and intervention. AI can increase the utility of RPM/mIoT.
- Time Horizon: 1-3 years, 3-5 years, and 5+ years
- Specific Examples:
- Medical:
- Many sensor, cloud-connected mIoT devices that are near, worn by, or inside a patient’s body, including inside very small organs (blood vessels, inside the heart, lungs, gut, root canal tumors, etc.) can increasingly become AI-enabled, which can help improve and quicken analysis and precision.
- Example: Wearable ECG monitors/remote heart monitoring enhanced by AI can enable continuous and accurate monitoring of cardiac health, offering the potential for more accurate diagnostics, timely interventions, and personalized patient care.
- Dental:
- AI (“Smart”) toothbrushes equipped with sensors to monitor parameters such as oral hygiene habits (brushing frequency, technique), gum health bleeding, inflammation, and even teeth grinding patterns (bruxism) remotely. This data can be transmitted to the dental office, and integrated into the practice management software, for analysis and feedback.
- Medical:
Solution Group 2: Existing Solutions Without AI
2D and 3D Imaging Analysis
- What This Is:
- AI analyzes 2D and 3D images and assists in diagnosis of healthcare pathology and identifying existing conditions and landmarks.
- While this technology exists today, more advanced technology in the future can enable greater leaps in computer power, storage, bandwidth, etc.
- Time Horizon: 3-5 years
- Specific Examples:
- AI, Imaging, and Digital Production: AI in Imaging can enable advances in digital production, sometimes within the practice, e.g., with 3D printing.
- AI Embedded in Digital Equipment: AI embedded in imaging equipment can improve existing workflows and create new ones.
- Smart Treatment Rooms: Improvements in computer vision technology can watch the room to make sure processes and procedures are well followed.
- Generating Reports: AI tools can take the results of advanced image analysis and create EHR (Electronic Health Record) notes, facilitate communications with referring doctors, and generate reports for patients. Such reports can be posted automatically to the portal, and alert the patient that a new report is available.
- Telehealth: AI can enhance telehealth in a number of ways, especially when mIoT / RPM devices are connected. Examples of how this technology is, and can be, utilized in healthcare include:
- Enhancing the connectivity of remote diagnostic and therapeutic (mIoT) devices.
- AI analyzing the data being streamed in real-time, assisting the patient and provider in making telehealth sessions more valuable and personalized.
- AI-enabled RPM solutions connecting patients and providers during the telehealth session.
- Predictive analytics capabilities, making the telehealth solution more valuable.
- Improved access to care / reduced healthcare disparities: The ability to project the quality of healthcare consultations inexpensively and instantaneously, which can deliver improvements to individuals geographically and socio-economically isolated.
- Real-time AI-enabled translation services enhance real-time provider and patient communication.
Customer / Patient Service
- What This Is:
- Use of AI bots (voice and text/web) to field and respond expertly, naturally, and automatically to customer and patient inquiries.
- AI sentiment analysis determines if/when to drop the communication from a bot to a person.
- Time Horizon: 1-3 years, 3-5 years
- Specific Examples:
- Business and software customers can use this to pay their bill, process order cancelations, make modifications and additions, change shipping options, and make inquiries about their bill, prescription refills, and the status of an order.
- Patients can make, confirm, or change appointments.
- Real-time AI-enabled translation enables the company to assist customers in their natural language, including instantaneous translation.
Business Process Automation (BPO)
- What This Is:
- AI that is used to reduce or eliminate certain internal business processes, especially those that are very resource-intensive and repetitive.
- Time Horizon: 1-3 years
- Specific Examples:
- AI partially or completely taking over repetitive, manual processes: Healthcare administrative teams today are doing procedures that are very resource-intensive – e.g., Claims, reports, ordering, etc. that are made more efficient with AI.
Patient Tools
- What This Is: A world of tools enabling patients to take charge of/understand their health and options better, and participate in the management of their care.
- Time Horizon: 1-3 years, 3-5 years
- Specific Examples:
- DIY patient/customer services, such as scheduling, billing/invoicing, inquiries, and prescription refills.
- Assist a patient in finding the best doctor for their needs in terms of expertise, price, insurance network, reimbursement, geography, language, etc.
- Simulation tools that educate patients and help them visualize treatments and outcomes.
- Real-time translation tools.
- A myriad of AI-enabled IoT devices and software to help patients track their health, and act.
- Virtual Health Assistants: Tools to help patients understand and manage their health, such as personalized health advice, medication reminders, appointment scheduling, symptom monitoring, improving patient engagement, and adherence to treatment plans.
Smart Inventory
- What This Is: Analytical and computer vision AI to determine and maintain proper inventory levels in healthcare practices.
- Time Horizon: 3-5 years
- Specific Examples:
- Precise AI tools to provide visibility to, and ways to maintain/manage, inventory and auto-replenishment.
- Through predictive analytics, AI algorithms analyze historical sales data, market trends, and other relevant factors to predict future demand accurately.
- Automate the replenishment process by determining optimal reorder points and quantities, reducing the risk of stockouts or overstock situations.
Sales Assistance
- What This Is: GenAI (Generative AI) to enable practices to search for products they are interested in and receive easy-to-follow, structured responses including information tables and videos.
- Time Horizon: 1-3 years
- Specific Examples:
- Customers using GenAI to conduct product, services, and solutions research to use on e-commerce sites, trade shows, social media, and other communications.
- Customers ask questions and make requests using a GenAI bot with the response being rich and structured feedback, including educational videos, to help customers educate themselves on various products, solutions, and services and do comparisons of features, pricing, etc.
- Gather information about customers doing research: Healthcare businesses can know who is asking what questions, helping their marketing and sales teams follow up on these inquiries, make recommendations, cross, upsell, etc.
Solution Group 3: New Technologies / Solutions
Precision and Personalized Healthcare
- What This Is: AI to help quickly and accurately diagnose, treatment plan and deliver customized, precise therapeutic care and medications.
- Time Horizon: 3-5 years, 5+ years
- Specific Examples:
- Couple and analyze a patient’s health tests, genetics, etc., to more quickly get to an accurate diagnosis, select the optimal therapeutic regimen, including the right medicines, and monitor progress.
- AI to select patients for clinical trials.
In the coming months and years, the furious pace of development of new groundbreaking solutions can increasingly change the face of diagnosis and delivery, as well as the business of healthcare. Each of these solutions has an opportunity to positively impact both providers and patients.
About Bruce Lieberthal Chief Innovation Officer, Henry Schein, Inc.
Bruce serves as the Chief Innovation Officer for Henry Schein, Inc., reporting to Chris Pendergast, Henry Schein’s Global Chief Technology Officer. In this role, he is at the nexus of evaluating hundreds of cutting-edge solutions and technologies, advising the many medical and dental business units of Henry Schein on important emerging trends and helping connect the company’s global sales, marketing and distribution capabilities with important new products that help its customers run better practices and deliver excellent patient care. Previously, from 2009 until 2015, he was the Vice President, Emerging Technologies for Henry Schein, Inc., reporting to the president of Henry Schein’s Global Practice Solutions Group. He started at Henry Schein as the Director of Product Management to the leadership team in Utah when Discus Dental Software was acquired by Henry Schein, Inc. in May 2007 and was promoted, in 2008, to Vice-President of Product Management and Development, managing all of Henry Schein Practice Solutions’ software lines and development teams. Bruce was the founder of Direct Vision Software, the General Manager of Discus Dental Software and has been a leader in dental technology for almost 35 years. He graduated from SUNY Buffalo’s School of Dentistry in 1983, practiced dentistry for 14 years between 1984 and 1997, and brings much knowledge to the Henry Schein team.