HIPAA Compliance

We create a HIPPA complaint store before all processing your Health care data, we follow all the checklists to become HIPPA complaint.

HIPAA Compliance Checklist

Technical Safeguards:

Implementation SpecificationFurther Information
Access controlThis not only means assigning a centrally-controlled unique username and PIN code for each user, but also establishing procedures to govern the release or disclosure of ePHI during an emergency.
Activity logs and audit controlsThe audit controls required under the technical safeguards are there to register attempted access to ePHI and record what is done with that data once it has been accessed.
Automatic log-off of PCs and devicesThis function logs authorized personnel off of the device they are using to access or communicate ePHI after a predefined period of time. This prevents unauthorized access of ePHI should the device be left unattended.

Physical Safeguard:

Implementation SpecificationFurther Information
Policies for the use/positioning of workstationsPolicies must be devised and implemented to restrict the use of workstations that have access to ePHI, to specify the protective surrounding of a workstation and govern how functions are to be performed on the workstations.

Policies and procedures for mobile devicesIf users are allowed to access ePHI from their mobile devices, policies must be devised and implemented to govern how ePHI is removed from the devices if the user leaves the organization or the device is re-used, sold, etc.
Facility access controls must be implementedControls who has physical access to the location where ePHI is stored and includes software engineers, cleaners, etc. The procedures must also include safeguards to prevent unauthorized physical access, tampering, and theft.

Administrative Safeguards:

Implementation SpecificationFurther Information
Security management processImplement policies and procedures to prevent, detect, contain, and correct security violations.
Conducting risk assessmentsThe main task is the compilation of a risk assessment to identify every area in which ePHI is being used, and to determine all of the ways in which breaches of ePHI could occur.
Developing a contingency planIn the event of an emergency, a contingency plan must be ready to enable the continuation of critical business processes while protecting the integrity of ePHI while an organization operates in emergency mode.
Restricting third-party accessIt is vital to ensure ePHI is not accessed by unauthorized parent organizations and subcontractors, and that Business Associate Agreements are signed with business partners who will have access to ePHI.

Data processing & warehousing

We do not put restrictions on your data sources, we accept a wide range of health care data sources such as EHR, Databases (SQL/NoSQL),  File systems, Cloud storages, API and many more. We take the data from your raw Data source irrespective of their standard’s & formats FHIR/HL7/any.  We store all the historical data too in the data warehouse

Data quality & Modeling

– Generate data quality report on your raw data

– Convert the raw data to PREDERA DATA MODEL

– Prepare features required for ML Model & store them in a unified feature store

– Reuse the same features to build multiple models

– Predera’s DATA MODEL is built on top of the OMOP data model and extended using FHIR standards. OMOP is an observational database used to perform analytics & machine learning on top of health care data.

Predera AIQ

Predera AIQ is an intelligent automation engine for machine learning teams, to drastically cut down on the challenges faced today in building, deploying and managing models.

Under the hood, AIQ uses machine learning to help manage machine learning, so Data Scientists can focus on experimentation.

Here’s what AIQ gives your out of the box

– Build ML Experiments/Models

– Track all your Experiments/Models at one place

– Schedule to train your models automatically

– Deploy and scale models at any time

– Monitor the performance of your model

– Read & Review each and every prediction

– Provide your feedback on a prediction

Collaborate:

Never lose another AI/ML experiment, artifact, metrics and lineage. We collect it all – seamlessly for all your platforms and data science programming languages, so you and your team can collaborate better

Build:

A Smart Operations Engine that brings the complex art of taking your experimental models to deployment at scale on a variety of infrastructure, all with one single click

Monitor:

Monitor Data Science and Machine Learning models in production in a reliable, scalable and explainable way, so your data scientists spend less time debugging them

Autofix:

With an integrated approach to managing model deployments, we not only act as your dashboard and insights for model challenges but can take actions on your behalf for fixing issues in production