Healthcare processes can be automated with ElinarAI. Many tasks that have been this far out of automation scope requiring highly skilled personnel can be automated with production proven ElinarAI. This results increased effectiveness of staff and overall process.
Industry
Healthcare industry (public and private hospitals, insurance providers and related segments) has multitude of processes that are currently heavily competent human labor driven. Some examples of these processes are:
- Claim opening
- Patient on-boarding
- Information transfer
- Medical referral routing
- Medical Research
- Population screening based on Medical History
Challenge
With large number of deep expert knowledge driven processes Heath Care Industry has been “out-of-scope” for advanced process automation. Decision makers have strong, opinions regarding assisting highly trained and experienced specialists with AI. Industry has seen just a few prominent diagnostic aids in relation to imaging.
Most processes follow 80/20 or 90/10 rule. Experts spend large portion of their time (80-90%) with trivial cases and fairly small amount of time and effort with cases that truly matters. This is no good. Humans deserve better.
Robotic Process Automation (RPA) can help…a bit; complex cases cannot be automated using RPA alone as robots rely on human cognition to do complex information extraction, classification and understanding of hidden signals.
Solution
ElinarAI enables healthcare industry to shift expertise from trivial to where it matters. Process with 91% of cases classified as “trivial” or “easy” can see up-to 80% automation level. AI extracts process specific information from written text and rules-based engine then proposes outcomes for case handlers acceptance.
ElinarAI can be applied into virtually any process where humans are required to understand and act upon complex information like Medical Records. Using a combination of classical Text Analytics, Language Models that are trained on huge amounts of general and in-domain texts and Deep Transfer Learning ElinarAI makes sense of complex written documents. ElinarAI extracts the information needed to automate underlying business processes.
This extracted information can then be acted upon using RPA or it can be fed directly to Business Rules Engine or Business Process Automation solution like IBM CloudPak for Automation.
When working with diagnostics or population health issues ElinarAI can provide analytical insight into IBM Watson Explorer where researcher or analyst can uncover deep relations between different entities like spinal issues and profession.
Technology
ElinarAI is a” Document AI”; it has been designed and optimized from ground-up to work with unstructured data like Medical Records. ElinarAI combines traditional text analytics with state-of-the-art Deep Transfer Learning. Underlying models have been trained with huge amounts of general and topic specific data (for example medical texts). This gives ElinarAI a major advantage when automating the extraction, classification and understanding of medical concepts. Actual production AIs benefit from underlying Deep Learning generated Language Modes; Using transfer learning ElinarAI offer significantly higher accuracy compared to models that do not have extensive background on Medical Texts.
ElinarAI is secure: ElinarAI processing pipeline removes privacy information from data at very early stage of the data processing pipeline; Privacy information is not relevant for AI to understand underlying reasons that caused patient scoliosis. Thus, all data processed by AI is heavily pseudonymized offering extra security during processing.
Use of Ultra-Powerful and highly secure IBM Power HPC AI optimized servers enable us to use larger models providing another increase in accuracy while keeping sensitive data secure. New AI capabilities in IBM Power 10 enable ultra-fast enterprise grade inferencing with latest security features like transparent memory encryption ensures that medical data processed by the AI are safe during each processing step.
