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What is Miya Precision?

Miya Precision stands as a groundbreaking clinical solution founded on a FHIR-event platform, accommodating a variety of clinical and operational applications. By seamlessly integrating with existing healthcare IT investments, it fosters a cohesive system of engagement that complements clinical workflows. This innovative platform equips clinicians with actionable insights, enhancing patient care by consolidating data from numerous sources. By leveraging clinical decision support and artificial intelligence, it provides practical insights that can significantly impact patient outcomes. The information is presented through a user-friendly interface that highlights essential actions for efficient decision-making. Moreover, the FHIR-based event platform aggregates inputs from different systems to offer consolidated, meaningful information. Ultimately, it delivers a longitudinal patient record that synthesizes contributions from all systems into a clear and accessible overview, thereby promoting better healthcare delivery. This holistic approach not only simplifies processes but also boosts the overall efficiency of clinical operations, ensuring that healthcare professionals can focus more on patient care. As a result, Miya Precision stands out as a vital tool in today's healthcare landscape, championing improved outcomes for patients and providers alike.

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

NextGate
Novari Health

Integrations Supported

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

Not specified

Training Options

Documentation Hub

Company Facts

Organization Name

Alcidion

Date Founded

2000

Company Location

Australia

Company Website

www.alcidion.com/products/miya-precision/

Company Facts

Organization Name

Saga IT

Date Founded

2016

Company Location

United States

Company Website

clinicalextract.com

Categories and Features

Patient Case Management

Activity Tracking
Assessment Notes
Medical History Records
Patient Records
Treatment Planning

Categories and Features

Healthcare Analytics

Not specified

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