

Solving the toughest Healthcare AI Problems

HiPaaS enabled Realtime monitoring of Sepsis after Bone Marrow Transplant. As a result mortality rate was reduced by 3%.
​
-
Realtime feed from EPIC about Meds, Vitals, Labs data
-
Filter data based on BMT metrics
-
Run Integrated AI Algorithm to predict Sepsis probability
-
Return probability to Hospital floor for real time adjustments to meds and treatment
​


HIPAAS IMPROVED OUTCOMES with COMPREHENSIVE DIABETICS AND KIDNEY CARE
-
Long term Care Monitoring via App and Chat features
-
Integrated MEDS, LABs Order and Results
-
Integrated REFERRALS ( nephrologist )
-
Genomics Testing ( Check Fabry disease )
-
Track the patient’s Diabetes and Hypertension
-
Decide on Dialysis regimen
-
Regular Blood tests to check the efficiency
-
Dialysis device data storage
-
Donor application integration and monitoring
-
ICU Request for transplant procedure
-
Post care and monitoring


HIPAAS DELIVERED PATIENT APP TO MANAGE NURSING HOME SELECTION
-
Long term care or Shifting to nursing home from Hospital care.
-
Select right nursing home based on CMS defined criteria
-
Read ranking and reviews of Nursing Homes before hand.


HIPAAS ENABLED WORKFLOW TO MANAGE GENETIC HOME KIT TESTING FOR CANCER
-
Online Doctor prescription based order for kit
-
Kit delivery
-
Testing and Kit shipping
-
Deliver Results


HiPaaS enabled 90 Day Mortality Rate Monitoring.
-
Realtime feed from EPIC about Meds, Vitals, Labs data
-
Filter data and calculate 90 day mortality rate
-
Return probability to Hospital with care plan and treatment


HIPAAS DELIVERED PATIENT APP FOCUSED ON BREAST CANCER CARE
-
Continuous monitoring of care plan & results
-
Self test instructions
-
Integrated order of labs and visits
-
Integrated Chat
-
Context driven notifications and alerts
-
Integrated with MyChart


HIPAAS DELIVERED INTERACTIVE PATIENT APP TO MANAGE CARE PLAN
-
Continuous monitoring of care plan & results
-
Integrated order of Meds, labs and visits
-
Integrated Chat
-
Context driven notifications and alerts
-
Integrated with MyChart


HiPaaS Healthcare AI Features

Enable evidence-based AI algorithms
Implement various critical condition surveillance solutions to monitor sepsis, mortality, and patient safety data. Detect signs of clinical decompensation that could be life threatening or warrant urgent transfer to a higher level of care and then trigger alerts to appropriate care team members. Plug in the trained AI model in real time to receive the data and provide results

Define AI Models
Define or integrate existing Models using python framework

Filter Clinical Stream with Required indicators for AI model
Filter the data stream with key indicators required for the model

Connect to EHR in Real Time - Clinical Streaming
Integrate with EHR like Epic, Cerner and others to receive real time HL7 stream of data

Integrate results back with EHR
Either send HL7 data back to EHR or call API or update database to reflect the results in EHR

Improve Critical Care
Enable earlier intervention on deteriorating patients, improve their chance of survival, and reduce the need for higher-cost care.
Automatically notify caregivers to potential clinical decompensation, thereby reducing the burden on care teams.
Provide the research and evidence-base for predictive AI algorithms and associated interventions.

Load Terabytes, PetaBytes of data improve AI Model
Scale and Performance: AI needs data in petabytes and current solutions to load data are not scalable and take lot of time. HiPaaS is highly scalable and we have successfully converted large sets of healthcare data like medical records, lab results, encounters, and patient demographics of Terabytes size each. HiPaaS converter is auto scalable using AWS serverless fargate architecture. Performance is key, we are continuously optimizing to convert data faster (e.g. 5-10 GB in few minutes). Recently, we were able to transforms 10+TB or observations data in few days.

Test the AI Model with real data
Quality data is vital for achieving accurate and reliable outcomes in healthcare AI applications. Robust and well-curated datasets help in reducing errors, false positives/negatives, and bias within AI models. At HiPaaS, we have developed required validations, lookups, crosswalks which will check, clean the data before converting. Codes like ICD10, ICD9, Snomed, Ionic are mapped and can be configured based on source data. Furthermore, HiPaaS also handle data entry mistakes (e.g. decimal "." can be entered in 5 different ways).

Train the AI Model
There are various formats, standards , types and sources of healthcare data. Mainframe systems, public healthcare domain data and old EHR systems data is often available in custom csv files. EHR's like EPIC, Cerner and others provide CCDA, FHIR and/or HL7 data feeds. Payers and Insurance companies often have EDI X12 data related to claims and authorizations. To further complicate things, the data sets can be a point in time or over series of timeframes. HiPaaS has inbuilt mappers for standard formats and a mapping tool for custom data formats.

Enable Production Grade AI Model for Hospitals for Critical or Chronic care
HiPaaS enables production grade, highly available infrastructure for deployment of AI Models
HiPaaS AI Modeling Tool
-
HiPaaS provides out of box 40+ indicators that can be configured to train the AI model.
-
Train the model by providing large amount of data
-
Test the model in simulation mode by streaming production real time data

Data Conversion and Enrichment
Convert and enrich the legacy data. Unlock healthcare data and feed to model
Real time clinical streaming can be further filtered and enriched based to get targeted values for the model

