According to CDC, Americans visit doctor’s offices and ERs more than a billion times per year! Half a billion of those are primary care visits.
Primary care providers represent by far the single largest group of AI end users among healthcare professionals.
So why are family physicians not utilizing AI yet? Two key reasons:
- Digital health companies are not run by doctors. They run by technology people or, in Babylon’s case, by investment bankers and marketing executives. They develop shiny and flashy software that they try to sell. However, the software doesn’t solve primary care physicians’ problems. In fact, so far AI can have the opposite effect by overwhelming clinicians with noninterpretable data and nonactionable prediction.
- For the Big Tech, AI is a large-scale academic exercise. They seem to forget that they are building a tool to help primary care physicians, not to run a study for their next publication.
Two recently published articles – “A Clinician’s Guide to Artificial Intelligence (AI): Why and How Primary Care Should Lead the Health Care AI Revolution,” by Steven Lin, MD and “Advancing Primary Care with Artificial Intelligence and Machine Learning,” by Zhou Yang et al – are listing 15 needs of primary care AI has to address to change the lives of physicians and patients.
First 10 are primary care needs AI can and will solve. The last 5 are AI’s best practices in primary care that must be addressed. Many of these 15 are available on the latest WellAI for Medical Providers app.
Risk Prediction and Intervention
In the U.S., hospital costs for potentially preventable conditions account for 1 in every 10 dollars of total expenditures. With AI, it is possible to take EHR data and calculate risk to patients based on demographics, comorbidities, medications, labs, imaging, and social determinants of health. Being proactive with the patient health would reduce preventable ED visits, hospitalizations, and death.
Population Health Management
AI can assist with identifying and closing care gaps that would otherwise take primary care providers (PCPs) 7 to 8 hours to do every working day. Digital alerts and suggestions for cancer screenings and other preventive services are the ways to do future population health.
Medical Advice and Triage
What if you could have patients self-triage and identify whether they are critical care? What if you knew in advance if patients should come to your facility, connect to telemedicine, or have direct interaction with a nurse, scheduler, or physician? There is a way to not only identify critical care patients before they arrive, but also direct non-critical care patients to the right care level needed while eliminating pressure on medical staff. WellAI for Medical Providers offers all these right now.
Risk-Adjusted Paneling and Resourcing
Remote Patient Monitoring
One in 5 Americans now has a device that tracks vital signs or other health measures. WellAI for Medical Providers offers not only support for chronic care management by enabling ongoing patient centered diagnostics and instant recording to EMR systems and transcription, but also enables one-click connectivity to the care team. The care team will be able to instantly receive a report regarding the health status of the patient and respond accordingly – with a message, a call, a telehealth session, or other directive. It is a critical component to home health and remote patient monitoring solutions. WellAI’s solution reduces cost by preventing un-necessary ER visits, un-necessary care team visits, and drives efficiency with respect to the application of care.
Digital Health Coaching
Tech companies have learned how to leverage personal health data by pairing mobile devices with AI-powered coaches that can help patients self-manage some of the costliest chronic diseases, such as diabetes, obesity, hypertension, and depression.
Chart Review and Documentation
For every 1 hour clinicians spend in front of patients, they spend another 2 hours behind the computer, mostly on chart review and documentation. WellAI for Medical Providers “reads” EHR patient records. It extracts and highlights symptoms and automatically assigns ICD-10 codes creating accurate and immediate billing execution. It can be used for medical transcription accurately capturing and highlighting patient symptoms, prescriptions, and important patient attributes. This technology has the potential to unshackle clinicians from the EHR and allow them to pay more attention to their patients.
In extensive backtests, WellAI for Medical Providers has diagnose with 83% accuracy, on average, across more than 500 health conditions and 2,400 vignettes. Patients and care providers can communicate more effectively even before they arrive at the care facility – and determine if they even need to see a doctor in-person. The WellAI solution has a unique pediatric diagnostic capability. The WellAI dermatology model can accurately predicts, based on patient’s skin image on the iPhone, whether a melanoma is benign or malignant. The “benign” prediction reduces anxiety. The “malignant” prediction could catch skin cancer early.
WellAI for Medical Providers can help PCPs with clinical decision-making at the point of care. Imagine a clinician speaking with a patient, or a nurse texting a patient; there is an AI listening in and generating a note; that AI is also predicting the clinical decisions that the clinician might need to make based on the live conversation and providing clinical insights and recommendations in real time.
WellAI for Medical Providers can automate repetitive clerical tasks that are suffocating practices like billing, coding, and prior authorizations. It can also automate certain aspects of intervisit care planning to make actual visits more efficient and rewarding for both patients and clinicians alike. Some have proposed new models of primary care, powered by humans and augmentable by AI, focused on care between office visits, recognizing that health care is moving out of the 4 walls of the examination room and into the virtual space, especially in the post-COVID-19 era.
There is a real risk of not including RWD (Real World Data) from primary care transactions for AI/ML training, testing, or validation. Most existing AI/ML algorithms are usually trained on hospital data focusing on narrowly defined clinical conditions. Therefore, they are often not applicable to the ambulatory setting with much higher volumes of encounters. WellAI for Medical Providers, on the other hand, has been trained on all 69 NIH medical categories (also known as UMLS semantic types) using the constantly updated dataset of 30+ million medical studies.
There should be a mindset shift for AI/ML developers to move beyond developing AI/ML algorithm using primary care delivery transaction data to developing AI/ML for primary care delivery transformation and quality improvement. Most AI/ML technologies are built without clinical collaborators in the field and do not use data from a local setting where PCPs practice. WellAI for Medical Providers, on the other hand, is augmenting the scientific knowledge of 30+ million medical studies with the patient data from the PCP practice, to deliver a better outcome for the patients.
Algorithm Marketing Authorization and Reimbursement
It will be critical to test and monitor the safety and effectiveness of AI/ML algorithms before and after they enter the market, and primary care plays a critical role in marketing authorization. The FDA acknowledged that traditional regulatory pathways might not be efficient or appropriate to meet the demand of the rapid iteration of AI/ML software. The agency issued the first action plan on AI/ML-based Software as Medical Device (SaMD) in 2021. The action plan calls for further discussion on how AI/ML-based technologies interact with people, including their transparency for users and enhancing trust.
Social Justice and Health Equity
Reduction of healthcare inequities is at the heart of WellAI. WellAI was created with a vision to eliminate the information asymmetry – in particular, WellAI offers access to scientific second opinion tools to the underprivileged, uninsured, people of low income and those who would like to be self-triaged before going to the doctor’s office. WellAI’s applications are easily deployed across many different populations – all that is needed is a smartphone or browser. The application puts sophisticated diagnostic validation in the hands of even the most remote patients and enables them to have one-click access to providers as and when needed, it can integrate with and enhance remote-patient monitoring solutions. WellAI’s data scientists are keeping abreast of recent research on racial and gender biases in data science.
Relying on AI/ML algorithms for risk adjustment could help reimburse the PCPs more fairly to reflect the heterogeneity of patient populations and communities to improve health equity. AI/ML algorithms have distinct advantages over traditional methods in capturing complicated, nonlinear relationships between chronic diseases and health care expenditures or quality measures.
The future of health technology is knocking on the door. Medical providers just need to open that door ever so slightly.
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