EHR2PHR DCT: Data platform infrastructure for clinical research.
A Patient-Centric Platform for Real-Time Interoperability, Connecting AI, ML, and NLP Analytics with Research Data in Centralized and Decentralized Clinical Trials.
EHR2PHR DCT Empowering Clinical Research for: pharmaceutical companies, hospitals participating in clinical trials, scientific investigation organizations and CROs.
EHR2PHR DCT Clinical Data Warehouse (CDW) is a real time database that harmonizes and consolidates data from a variety of clinical sources to present a unified view of a single patient.
EHR2PHR DCT makes a difference through analytics and Machine Learning (ML) and Artificial Intelligence (AI)-driven applications, based on diverse data from across the care continuum.
EHR2PHR DCT provides an opportunity to change how research studies are conducted, enabling a single point of connection to any number of data sources.
The EHR2PHR DCT platform is advancing clinical trials and observational studies into the next generation: Real World Trials. Our Personal Electronic Health Record (PEHR) centralizes medical records within each patient's unique personal EHR
Predictive Care Analytics providers (AI and ML) are connected with EHR2PHR DCT Platform, using big data to spot warning signs and anomalies in patterns so that preventive actions can be taken.
EHR2PHR DCT aggregates Real World Data, patient data from different electronic medical record (EMR) systems, eCOA, hospital records, connected diagnosis labs, DNA sequencing, imaging institutions, devices, wearables, ePRO, telehealth and home healthcare visits.
Life sciences and pharmaceutical companies can gain great value by using Real-World Data : EHR2PHR DCT connects the world’s health data to improve patient outcomes, linking study data with RWD.
EHR2PHR DCT
patient-centric platform provides interoperability and bridges AI, ML and NLP analytics in Real-Time, accelerating the discovery of Real-World Data in either centralized or decentralized clinical trials.
CT + SMART PEHR = RWE DCT
DCT +(AI + ML + NLP)= Safer CT
DCT +(AI + ML + NLP)= Shorter CT
DCT +(AI + ML + NLP)= Cost-effective CT
OUR CLIENTS
CLINICAL TRIAL TYPES
Features
- Digital process with AI and ML for participant selection.
- eConsent and digital enrollment.
- Cloud Healthcare Infrastructure with security and compliance best practices.
- Interoperability: collecting and storing data from diverse sources (integrations), generating personal and unified health records.
- Real-world & self-reported data capture, with the ability to “bring your own device” (BYOD).
- Participant digital data capture system (ePRO - Electronic Patient-Reported Outcomes, eCOA- Electronic Clinical Outcome Assessment)
- Real-time access to participant data capture
- Evidence generation platform
- Artificial Intelligence and Machine Learning capabilities for patient EHR followup, processing, and external AI & ML analysis integration.
- De-identified healthcare data
- Data discrepancy management
- Hundreds of third-party wearable, App and sensor integrations
- Virtual visits and telemedicine integrations
- Execution of fully decentralized trials
Outcomes
For Hospitals
Smart Data Lake is a centralized repository of raw data from various sources within the healthcare industry.
It is designed to store and manage vast amounts of structured and unstructured data in its native format, including
medical records, clinical trial data, claims data, patient-generated data, and other health-related information.
SMART DATA FABRIC combines the features of a data lake and a data warehouse, along with modern data management technologies such as data virtualization, data APIs, and microservices. It enables healthcare organizations to integrate and manage data in real-time, and provides a flexible and scalable platform for analytics, machine learning, and other advanced data processing applications.
