Semantic Health Description
AI-powered medical coding and auditing. Streamline manual inpatient auditing and coding processes, improve documentation quality, and free your team to focus their efforts on high-value tasks. Semantic Health drives improvements at leading hospitals. Semantic Health uses NLP and custom clinical AI algorithms, trained by our world-class AI teams on millions of records, to parse clinical and coded information. This allows our coding engines to better understand clinical context, incorporate changes in coding rules and guidelines, and suggest high quality coding and auditory opportunities with clear evidence to the clinical documentation. AI can optimize your revenue cycle and save you time by automating labor-intensive medical auditing and coding processes. Semantic Health provides hospitals and health systems with a supercharged platform for inpatient auditing that allows a 100% review of claims data prior to billing.
Semantic Health Alternatives
Centauri Health Solutions
Centauri Health Solutions, a healthcare technology and service company, is driven by the desire to make healthcare more efficient for our clients and provide compassionate support to those in need. Our software, powered by analytics, allows hospitals and health plans (Medicare and Medicaid, Exchange and Commercial), to manage their variable income through a custom-built workflow platform. Our tailored support for their members and patients gives them access to life-enhancing benefits. Our solutions include Risk Adjustment, Medical Record Retrieval and Medical Record Coding, Analytics, RAPS/EDPS Submissions, HEDIS®, and Stars Quality Program Management. Clinical Data Exchange, Eligibility, Enrollment, Eligibility, and Revenue Cycle Analytics. Referral Management & Analytics. Social Determinants of health.
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CodaMetrix
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Healthicity Audit Manager
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Now included — Audit Manager features built-in Tableau integration to provide in-depth analytics and reporting.
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Google Cloud Natural Language API
Machine learning can provide insightful text analysis that extracts, analyses, and stores text. AutoML allows you to create high-quality custom machine learning models without writing a single line. Natural Language API allows you to apply natural language understanding (NLU). To identify and label fields in a document, such as emails and chats, use entity analysis. Next, perform sentiment analysis to understand customer opinions and find UX and product insights. Natural Language with speech to text API extracts insights form audio. Vision API provides optical character recognition (OCR), which can be used to scan scanned documents. Translation API can understand sentiments in multiple languages. You can use custom entity extraction to identify domain-specific entities in documents. Many of these entities don't appear within standard language models. This allows you to save time and money by not having to do manual analysis. You can create your own machine learning custom models that can classify, extract and detect sentiment.
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Company Details
Company:
Semantic Health
Headquarters:
Canada
Website:
www.semantichealth.ai/
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Product Details
Platforms
SaaS
Type of Training
Documentation
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