Healthcare AI – 2023 Health IT Predictions

As we head into 2023, we wanted to kick off the new year with a series of 2023 Health IT predictions.  We asked the Healthcare IT Today community to submit their predictions and we received a wide ranging set of responses that we grouped into a number of themes.  Check out our communities predictions below and be sure to add your own thoughts and/or places you disagree with these predictions in the comments and on social media.

All of this year’s 2023 health IT predictions:

And now, check out our community’s healthcare AI predictions.

Evangelos Hytopoulos, Sr. Director of Data Science at iRhythm Technologies
There is no doubt that AI has become mainstream in many areas. In medicine, AI approaches are currently both developed and deployed at a rapid rate, fueled by the dearth of data that already exist from different modalities (genetic, genomic, images, EHR, etc.), as well as the continuous streams of data that are provided by wearables.

The majority of models today are based on supervised learning, where labels are combined with measurements to teach an algorithm to predict unseen data. However, it takes a lot of effort to create a labeled data set and as a result, usually only a subset of the data can be labeled – thus limiting the learning capacity of the current models. In upcoming years, we can expect to see AI approaches that are based on the use of self-supervised and generative AI algorithms in order to facilitate the incorporation of a larger volume of data in model training. Supervised learning is capable of learning important features of the underlying measurements that are a richer representation of the data.

The advantage of generative algorithms is the creation of synthetic data – labels coming from a different signal domain and the important features are learned from the domain of interest. In both cases, proper validation will be required to prove the validity of the algorithms and the lack of any bias in its predictions.

Gabriel Mecklenburg, Co-founder at Hinge Health
Approximately 1.71 billion people suffer from musculoskeletal (MSK) conditions like neck, back, or joint pain worldwide. It is a global crisis with a severe human and economic toll. With AI, we have the opportunity and tools in hand to transform the digital health experience for billions impacted by chronic pain.

AI is already being used to build immersive 3D experiences in theme parks and video games. Applying those same technologies to heal patients is like giving care providers a superpower they never had before. For example, AI technology can now help identify and track many unique joints and reference points on the body using just the phone camera. That allows care providers to track reps, and provide real-time instructions and feedback on the exercise form. The AI picks up all kinds of subtle movements the human eye cannot.

By harnessing this data and feeding instructions back to the patient in real-time, we can deliver personalized, responsive, and immersive healthcare AI is clearly the future of motion tracking for health and fitness, but it’s still extremely hard to do well. Many apps will work if you’re a white person with an average body and a late-model iPhone with a big screen. However, equitable access means that AI-powered care experiences must work on low-end phones, for people of all shapes and colors, and in real environments. We must ensure AI is used to bridge the care gap, not widen it.

Dave Bennett, CEO at pCare
The most significant potential with AI and Digital Health lies in precision medicine. So, within my Medicare Advantage population for example, I split out patients with diabetes, find out who is due for an annual eye exam and then send them a message to match their communication preferences. This is population health in action.

With advances in AI, I can now get into the realm of precision medicine – which is much more targeted. With the ability to model and train millions of records, we can now find patients who look more like me (or any given person), so the care recommendation is much closer to 1:1.

Tathagata Dasgupta, Founder and President at 4D Path
Digital technology, including Artificial Intelligence (AI), will continue to transform pathology services by increasing their efficiency and advancing the field toward fulfilling the promise of precision medicine. In oncology, AI-powered diagnostic solutions will enable a faster, more accurate, more efficient approach to personalized cancer diagnoses. Furthermore, such diagnoses could ultimately provide biomarker profiling and prognostication information to accelerate and democratize precision medicine for optimized patient care. Because widespread clinical adoption is required to unlock such possibilities for patients, a science-driven, biologically explainable solution is needed that is both easy to integrate in the current standard of care and simple to validate using orthogonal experiments.

Yaniv Hakim, CEO & Co-founder at CommBox
The deployment of automation and AI in healthcare organizations will expand in 2023 to handle the growing demand for digital healthcare services, especially in times of shortages of medical staff. Utilizing AI helps healthcare enterprises automate approximately 50% of repetitive requests from patients. In 2023, AI will continue to eliminate the loads on medical staff and better handle the shortage in the health systems.

In 2023, we will see AI handling more patient requests such as providing basic medical information and answering questions, asking for prescriptions, scheduling appointments, processing requests across the supply chain, etc. AI chatbots with machine learning capabilities will fill in for humans wherever it’s possible, freeing medical personnel to care for patients on-site.

In IT, AI will enable healthcare providers to automate and speed up medical staff requests – solve internet malfunctions, connect medical and computer equipment, etc. Furthermore, AI will allow healthcare providers to process and segment big data, generate insights and improve healthcare services.

Digital Healthcare Healthcare providers will need to invest more in digital solutions in 2023 in order to keep up with the growing demand for digital healthcare. We’re seeing that 80% of patients already want to contact healthcare providers on messaging channels, so it’s becoming a must-have in today’s digital reality.

Personalization will play a major role in digital healthcare in 2023. 88% of patients rate personalized healthcare as important, so providers will have to invest more in incorporating data into their digital experiences. In countries that still suffer from the results of Covid-19, digital healthcare will continue to enable remote medical services and add new services to reduce exposure to sickness.

Judy Jiao, Chief Information Officer at National Government Services
AI is revolutionizing and enhancing the progress of business operations in our modernizing society — Today, there are a wide range of AI-enabled products, services, and custom solutions available for companies to adopt. What used to be a highly sophisticated field has flourished into one with endless possibilities featuring cost-effective and impactful implementations.

Intelligent call centers are comprised of chatbots equipped with natural language processing, speech recognition, and text analysis. Image analysis technology aids healthcare providers in their vital decision-making to treat patients. Targeted insights are generated by scanning through social media and customer interactions to help companies further develop their marketing strategy. Frauds are detected through analyzing patterns and predicting future behaviors.

Leaders must understand what AI can do for their business — Since AI can offer a wide range of features and has a long list of tools available in the market, one must understand the specific business needs of the company and evaluate the AI solutions available to address them. Is it increasing sales efficiency? Reducing fraud? Replacing tedious, manual steps? Finding prevalence? Predicting future behaviors? Setting strategic goals for AI to tackle is crucial for it to succeed. Start with one or two areas with a clear focus and intention for the implementation. Identify what tools are readily available and what needs to be custom built.

It’s crucial to align data strategy with AI initiatives —Data strategy is an enabler of AI initiatives. Today, AI experts are shifting from big data to advocating for more relevant, wide data to give good context (e.g. metadata). These data give meaningful and multi-dimensional information which enables AI solutions to be more actionable. To achieve a positive AI outcome, the data needs to be high quality. Therefore, data governance and management is essential for data strategy. In addition, to reduce information overload, shift from data insights to decision insights with AI enabled data solutions.

AI will be embedded into existing systems and processes — When AI is embedded well into business, end users should feel that this is a natural part of their operations. Alternatives are suggested, processes are automated, customers are served with good insights, incidents are predicted and prevented, and solutions are optimized. Utility and value will increase accordingly as they become part of normal business operations and processes.

The implementation of AI-enabled Robot Process Automation (RPA) solutions will increase —AI solutions usually have a high return on investment. When business processes interact with human beings to perform routine, repetitive, and time-consuming tasks, AI-enabled RPA can drastically improve user experience and productivity. The implementation of these solutions usually does not require a software engineer or data scientist, which greatly expands the talent pool to implement them. In addition, the cost of implementation is increasingly manageable as many available solutions are relatively easy to put into place and turnaround time is short.

Punit Soni, CEO at Suki
Voice interfaces will cross 70%+ adoption in health settings from the current 30% or so backed by natural language, large language model systems and consumer mobile app interfaces. Investments in healthcare tech startups will continue but focus on revenue will intensify. This coupled with long healthcare sales cycles will mean a quite a few will run out of cash and shut down. Meanwhile, the Chief AI office will become a position in health systems differentiated from CIO and Data/digital executives.

Ophir Tanz, Founder & CEO at Pearl
In 2023, we can expect accelerating adoption of patient-facing AI solutions in dentistry to create an appetite among patients for AI that will catalyze more rapid adoption of the technology in other medical sectors. In the dental industry, clinical AI technologies — particularly radiologic aids which assist dentists in their evaluation of patient x-rays — are seeing exponential rates of adoption, with per-office AI implementation growing at a rate of 300-400% month-over-month in 2022. These AI systems offer key advantages, including that they both enable greater radiologic accuracy (dentists using AI, read x-rays 37% more accurately) and offer patients an objective, easier-to-understand lens through which to understand x-ray diagnoses.

Patients privilege these advantages with not only fascination and engagement, but also their trust. The millions of patients who experience medical AI for the first time at their dentist this year will bring an appetite for AI to subsequent interactions with medical providers in different fields. Other areas of healthcare will take time to respond to consumer interest in AI, but 2023 will mark the beginning of a new wave of medical Ai innovation, catalyzed by patient demand.

Carlene MacMillan, MD, VP, Clinical Innovation at Osmind
We see enormous opportunity for partially AI-generated progress notes to help streamline clinician experiences and allow them to focus more fully on patient care. WIth a low barrier to entry, we anticipate seeing more companies in this space emerge in the year ahead in healthcare and other industries. For healthcare, adoptees should pay special attention to HIPAA and other privacy standards, as this may feel invasive in early stages.

Be sure to check out all of Healthcare IT Today’s healthcare AI content and all of our other 2023 healthcare IT predictions.

About the author

John Lynn

John Lynn is the Founder of HealthcareScene.com, a network of leading Healthcare IT resources. The flagship blog, Healthcare IT Today, contains over 13,000 articles with over half of the articles written by John. These EMR and Healthcare IT related articles have been viewed over 20 million times.

John manages Healthcare IT Central, the leading career Health IT job board. He also organizes the first of its kind conference and community focused on healthcare marketing, Healthcare and IT Marketing Conference, and a healthcare IT conference, EXPO.health, focused on practical healthcare IT innovation. John is an advisor to multiple healthcare IT companies. John is highly involved in social media, and in addition to his blogs can be found on Twitter: @techguy.

   

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