Healthcare Solutions

iHealth AI Solution - Deep Machine Learning Automation of EHR

iHealth AI EHR In-Basket Triage & Inbound Translation

Physicians are suffering and they need help!
iHealth AI Triage protects physicians from a flood of messages from patients and eliminates use of human triage dispatchers who review patients messages and route to appropriate pools (e.g. RN, APC, pharmacists, MA, CSA, etc.).
iHealth AI Triage intercepts all messages from patients & call center agents to physicians, analyzes a content of messages by Natural Language Processing (NLP), processes messages and routes each message to proper role pool.
iHealth AI Translate detects message language and translates inbound & outbound messages to/from English when needed.

Benefits:

In-Basket AI will reduce the amount of time the physician needs to allocate to EHR in-basket work and therefore free up time to see patients and increase job satisfaction.
In-Basket AI will reduce the amount of non-physician work in physician in-baskets by systematically looking at the in-basket messages and triage them efficiently to the right clinical staff job.
In-Basket AI will drastically reduce the cost of message translation (from & to patients).
In-Basket AI can be a key element in several organizational strategic deployment initiatives e.g. Primary Care Transformation, Population Health, and Joy of Work.

iHealth AI enables:

To fully automate in-basket community message routing and reduce number of in-basket triage human dispatchers to zero (0) human resources.
To create a cognitive platform which will reduce by up to fifty percent (50%) the number of human resources required to process patients’ messages, which include customer service agents (CSAs), medical assistants (MAs), pharmacists, registered nurses (RNs), advanced practice clinicians (APCs).
To build a cognitive knowledge base from patient messages and healthcare provider staff responses for Population Health Management to better understand the needs of patients and deploy the appropriate level of resources to patients.

iHealth AI Natural Language Processing:

iHealth AI Deep Learning uses Azure Cognitive Services, AzureML BERT/XLNet & NMT
BERT and XLNet were created by Google and Carnegie Mellon University; Open Sourced; Incorporated into Google Search; available in Microsoft Azure.
Google, Microsoft, Facebook and Amazon have all adopted BERT and XLNet for Natural Language Processing standard.
Microsoft, MIT, Harvard University, Carnegie Mellon University performed joint pilots with ClinicalBERT / BioBERT / XLNet with results much better than all other NLP technologies.

iHealth AI Azure Cloud deployment:

AzureML iHealth AI cloud solution
- Uses elastic scalability of Azure AKS and APP Services and Cosmos DB. With a single configuration change a throughput of the solution can be increased on a fly by 100 times above any workload requirements.
AzureML iHealth AI hybrid solution
- Healthcare Provider’s SQL server to store messages and other data, but run processing in Azure cloud.

EHR and Microsoft Azure:

Microsoft Azure is certified for EHR deployments.
Microsoft Azure is currently hosting EHR deployments.
Microsoft Azure FHIR SDK is a certified interface with EHR.
EHR does not require any additional interoperability testing, vetting, confirmation, certification or feedback.

Business Continuity, Disaster Recovery and Availability:

AzureML iHealth AI cloud solution
- Microsoft Azure fault tolerant globally distributed architecture.
- Maintenance and upgrade of Azure services do not interrupt services.
AzureML iHealth AI hybrid solution
- Healthcare Provider’s SQL Server to store messages and other data, but run processing in Azure.

For detail information see iHealth AI Workflow Video: