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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.

What is Altis Labs Nota?

Altis Labs has introduced Nota, a groundbreaking platform aimed at improving the efficiency of therapeutic research and development in the clinical field. By leveraging artificial intelligence, Nota assesses imaging data to forecast patient outcomes, enabling sponsors to better concentrate on their most viable therapies. This cutting-edge tool equips researchers with the ability to utilize imaging data from clinical trials, access predictive biomarkers, and accelerate research initiatives on a broader scale. With Altis' cloud-based software that employs deep learning techniques, biopharma companies can achieve comprehensive outcome predictions at the levels of individual images, patients, and entire cohorts, thereby enhancing the design of clinical trials and boosting confidence in predicting clinical endpoints. The insights provided by Nota hold the potential to significantly shorten development timelines, reduce drug development costs, and increase the likelihood of success in clinical trials across diverse therapeutic areas. Furthermore, Nota signifies a major leap forward in the fusion of technology with clinical research, ultimately paving the way for more streamlined and effective drug development methodologies. This innovation not only promises to transform the landscape of clinical trials but also aims to improve patient outcomes in the long run.

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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

On-Prem
Linux

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Not specified

Company Facts

Organization Name

Saga IT

Date Founded

2016

Company Location

United States

Company Website

clinicalextract.com

Company Facts

Organization Name

Altis Labs

Date Founded

2019

Company Location

Canada

Company Website

www.altislabs.com/news/altis-labs-announces-launch-of-nota-a-clinical-information-platform-to-accelerate-therapeutic-r-d

Categories and Features

Healthcare Analytics

Not specified

Categories and Features

Healthcare AI

Not specified

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