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What is Omda Compos?

The successful assessment of pharmaceutical treatments and their associated protocols relies heavily on the efficient collection and dissemination of comprehensive, timely, and high-quality information. In response to this need, the Omda Compos suite has been meticulously designed to optimize the management and seamless sharing of medical data within the clinical environment. This state-of-the-art platform ensures that both users and applications engaged in clinical trials and registries can quickly access essential information, thereby promoting enhanced collaboration and effective utilization of data. Central to the Compos platform is the Omda Compos QR, which incorporates an advanced database architecture, data warehousing capabilities, user management features, and other fundamental components that maintain data integrity from the initial collection stage through to analysis. It is essential to uphold streamlined user access and efficient logging practices for any clinical registry or trial. The Omda Compos QR delineates user roles to manage access to specific sites, which further bolsters security and governance over the data management lifecycle. By focusing on these critical elements, the platform not only aids researchers but also elevates the standard of clinical data management. Furthermore, the integration of these functionalities ensures a more robust, reliable framework for advancing clinical research.

What is Clinical Extract?

Clinical Extract can efficiently obtain research data from any electronic health record system that utilizes a certified bulk FHIR API, including well-known platforms such as Epic, Oracle Health (Cerner), athenahealth, eClinicalWorks, MEDITECH, NextGen, and Veradigm. The tool functions as a SMART Backend Services client within your existing infrastructure, employing read-only permissions and enabling the export of only the specified study group through a Group $export. It converts NDJSON into a detailed CSV format, complete with a data dictionary that correlates each column to its corresponding FHIR element, all while ensuring that patient data stays securely within your environment. Tailored specifically for cancer and clinical registries, it supports coded case and abstraction fields in line with the NAACCR layout and addresses the requirements of research informatics teams and ethical brokers by providing study-specific data collections alongside an IRB-compliant data dictionary. Additionally, it aids research sites in evaluating clinical trial feasibility based on established coded criteria. Among its key capabilities are a cohort builder, roster extraction using FHIR $match, and the creation of both the CSV and data dictionary, plus a specialized oncology perspective that highlights biomarkers and TNM stage as distinctly labeled columns for straightforward analysis. This holistic method significantly improves the accessibility and applicability of essential health data for a variety of research initiatives, thereby streamlining the overall research process. Ultimately, Clinical Extract serves as a vital resource for enhancing the efficiency and effectiveness of health data research.

Media

Media

No images available

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

On-Prem
Linux

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

Omda

Date Founded

1999

Company Location

Norway

Company Website

omda.com/solutions/health-analytics/omda-compos/

Company Facts

Organization Name

Saga IT

Date Founded

2016

Company Location

United States

Company Website

clinicalextract.com

Categories and Features

Healthcare Analytics

Not specified

Categories and Features

Healthcare Analytics

Not specified

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