AI in Practice Management II
AI can also be used to automate certain aspects of pre-visit planning to make physician care encounters more efficient and rewarding for patients and physicians. This would improve the overall workflow at the physician’s office as patients can be checked in faster, physicians can view prioritized information to make visits more efficient and follow-ups can […]
AI in Practice Management I
AI can help providers and their practices to improve operations like scheduling and patient check-ins and check-outs. AI-powered scheduling software could make life easier for patients and their medical providers. It will be able to analyze previous scheduling patterns for each patient and provide suggestions for the best date, time, provider and location for the […]
AI in Prior Authorizations
One of the key areas on the administrative side of healthcare is prior authorization. This is when clinicians need to get an approval from the insurance company to perform a service like an MRI for the patient. Insurance companies use prior authorization to control costs by preventing unnecessary procedures. This is always a point of […]
AI in Administration and Operations II
More than 40% of submitted claims aren’t paid electronically or automatically upon their first submission. The AI applications in this area include more accurate coding from processing provider documentation and identifying the relevant billable medical codes. There are now algorithms which can tap into historical data and use it to predict whether a claim will […]
AI in Administration and Operations I
Most of the administrative functions in healthcare are done electronically nowadays, making AI the perfect tool to “figure out” what to do and to perform activities like completing forms, sending information and scheduling follow-ups. This would bring three economic improvements to the process: first, it would mean fewer healthcare resources, including the time of doctors […]
What are the consequences of a fragmented healthcare system?
THE US HEALTHCARE ECONOMY is valued at almost $4 trillion. If it was a country, it would have the fifth largest economy in the world, and it equates to nearly half of what the entire world spends on healthcare. We can argue about whether that’s a good thing or not and what percentage of it […]
AI in Pharma Medical Affairs and Commercial
Machine learning can also accelerate the regulatory submission process, as the massive amounts of data generated during clinical trials can be captured and effectively shared to collaborate between investigators, contract research organizations (CROs) and sponsor organizations. In pharmacovigilance, huge amounts of structured and unstructured data need to be reviewed so that we can provide oversight. […]
AI in Clinical Trial Operations
AI can introduce key intelligent automation to different processes in the actual running of trial operations. Some examples of this include using AI in monitoring medication adherence, creating digital twins and synthetic arms that help reduce the number of patients needed, and identifying optimal patients for recruitment by analyzing clinical information. Non-adherence often leads […]
Patient Stratification for Clinical Trials
Here, we’re talking about technologies that help with finding, screening, selecting, recruiting and keeping study patients. A variety of AI technologies can assist in this process. You can use NLP on clinical notes as a first pass to find patients with the right stage of disease once you know their diagnosis from the ICD-10 codes. […]
AI in Clinical Trials III
A technique called adaptive design, which relies on a more flexible approach to clinical trials, has become a key trend for researchers tackling COVID-19. Traditional studies are more rigid about endpoints and dosing regimens, while adaptive designs allow researchers to make modifications as the trial progresses. One of the biggest ongoing challenges is that of […]