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What is Healthcare Data Analytics?

A significant portion, over 70%, of healthcare information resides in clinical documents like patient charts, discharge summaries, clinician notes, and reports, which enables our advanced Natural Language Processing and AI Engine to extract crucial concepts, attributes, and contextual details that enhance business insights, refine billing processes, evaluate and categorize patient risks, compute quality metrics, and collect patient sentiment and outcome information. By leveraging previously underutilized data sources, you can greatly advance your clinical research or business intelligence initiatives. Our extensive database encompasses thousands of clinical concepts, such as genomic biomarkers, symptoms, side effects, and medications, which facilitates the identification of disease characteristics and risk factors from clinical documents, thus improving patient stratification and raising the quality of care provided. Additionally, we prioritize the anonymity of data subjects by implementing effective document de-identification techniques, ensuring their privacy while still maintaining the data's utility. This dual focus on privacy and comprehensive data empowers healthcare organizations to make well-informed decisions grounded in the most extensive information available, ultimately leading to better patient outcomes and a more efficient healthcare system.

What is Azure Text Analytics?

Harness natural language processing to gain valuable insights from unstructured text without requiring any machine learning knowledge, by utilizing an array of features from the Cognitive Services for Language. Elevate your understanding of customer emotions through sentiment analysis and identify key phrases and entities such as people, places, and organizations to uncover common themes and patterns. Use specialized, pretrained models to classify medical terminology specific to various fields. Evaluate text across multiple languages and reveal essential concepts within the content, which include key phrases and named entities that highlight individuals, events, and organizations. Delve into customer feedback regarding your brand while examining sentiments linked to specific topics through opinion mining techniques. Additionally, derive critical insights from unstructured clinical documents, including doctors' notes, electronic health records, and patient intake forms, by applying text analytics tailored for healthcare settings, ultimately enhancing patient care and informing decision-making processes. By integrating these advanced capabilities, organizations can stay ahead of trends and better meet the needs of their stakeholders.

Media

Media

Integrations Supported

Azure Marketplace
TAS Insight Engine
Unremot

Integrations Supported

Azure Marketplace
TAS Insight Engine
Unremot

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Inspirata

Date Founded

2014

Company Location

United States

Company Website

www.inspirata.com/solutions/healthcare-data-analytics/

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

azure.microsoft.com/en-us/services/cognitive-services/text-analytics/

Categories and Features

Population Health Management (PHM)

Analytics
Cost-of-Care Analysis
Data Storage
EMR/EHR Integration
Patient Engagement
Patient Identification
Patient Risk Stratification
Patient-Reported Outcomes
Payment Bundling
Predictive Alerts
Test & Treatment Reminders
Utilization Tracking

Categories and Features

Natural Language Processing

Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization

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