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Transforming data into usable insights with a healthcare AI platform

More than 1.2 billion clinical documents are created each year, only to sit in electronic storage without being analyzed. Make use of all your data to better measure clinical activities, guide care, and make discoveries.

The Apixio Platform

More than 1.2 billion clinical documents are generated each year in the U.S., but there is very little analysis of that unstructured information. The Apixio Platform can mine textual data and combine its generated insights with available structured data to craft computable individual health profiles, or phenotypes. We analyze our assembled phenotypes in real-time using a flexible rules engine. This automates the execution of clinical guidelines, quality and risk measures, payment or reimbursement policies, and other operational and administrative rules, to support critical healthcare activities.

Step 1: Data Acquisition

We use a secure extraction process to capture free-text documents, scanned charts, and facsimiles, in addition to clinical structured data, claims and other administrative data, and more. These data are then handled in our Data Loader in preparation for our data and analytics pipelines.

Step 2: Data Processing

Our data pipelines process ingested information, run validation checks, and then assemble the data into Apixio Patient Object Models (APOMs) in preparation for our downstream analytic steps. During this stage, we use our optical character recognition (OCR) pipeline to translate the data in image files into machine-readable text.

Step 3: Data Analysis

Signals are generated from analysis of APOMs, which are then used by proprietary data algorithms and predictive models to generate insights. Processed data stored in APOMs include patient diseases, medications, procedures, encounters, biometric values, other data, and derived information from prior analyses.

Step 4: Phenotype Assembly

Information from AI algorithms are sorted and analyzed for discrepancies and then a robust patient phenotype is created. This phenotype is a rich, longitudinal picture of individual healthcare, which is the basis for our solutions.

Step 5: Application Use

Our solutions use data from phenotypes to execute specific rules to automate clinical, administrative, or operational activities.

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Our flexible data pipeline can ingest a variety of different file types, including PDFs, TIFs, JPGs, and EHR extracts.
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Apixio's InfoStream solution provides a comprehensive healthcare data acquisition and integration platform that ingests clinical and administrative data securely from various source systems and includes intelligent optical character recognition technology to turn images such as PDFs or facsimiles into machine-readable text.
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Text classifiers:
Data is run through our machine learning models, called classifiers, to extract relevant information. We use ensembles to combine related pieces of information into usable insights.
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Training data:
We use training data to teach our models what to look for when analyzing patient documents.
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Results API:
Patient events are bundled into packages to be routed to our applications.
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Patient events:
Our models generate a set of patient events tailored to the specific solution and client needs.
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Patient Phenotype
Information from AI algorithms are sorted and analyzed for discrepancies to then create a robust patient phenotype that is a rich, longitudinal picture of individual healthcare, which is the basis for our solutions.
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Care View
Apixio's Care View solution provides an easy-to-navigate summary of an individual's healthcare with valuable insights into risk, quality, outcomes, and clinical care.
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Quality
Apixio’s Quality Identifier solution uses proprietary AI algorithms to locate relevant clinical facts in medical charts. These facts are presented in an application where abstractors can easily confirm the evidence. Approved facts are then exported to quality measure engines. Apixio’s Risk Adjustment solutions use proven AI algorithms to support a comprehensive retrospective chart review experience for Medicare Advantage, Affordable Care Act, and Medicare Shared Savings programs.
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Risk Adjustment
Apixio’s Risk Adjustment solutions use proven AI algorithms to support a comprehensive retrospective chart review experience for Medicare Advantage, Affordable Care Act, and Medicare Shared Savings programs.
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Clinical Guidance
Our clinical guidance suite presents actionable insight for providers and other care team members to better care for their patients. Our AI algorithms curate text and coded data to produce enriched clinical summaries which can be easily searched along with helpful tips and predictions.
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Testimonial
Capital Blue Cross Health Plan

The efficiencies Apixio brings to our reviews are just incredible. Their machine learning technology leads you to the right information you need for coding.

Andrew Bloschichak MD, MBA
Senior Medical Director, Government Programs - Capital Blue Cross
Testimonial
network health

The coding team was wonderful to work with, and incorporated our specific coding guidelines when working on our project. When they noticed a trend in what we were rejecting, they shared a Coding Clinic we were unaware of for clarification on how to code the scenarios.

Josh Weisbrod
VP of Risk Adjustment
Testimonial
Scripps logo

By using Apixio, we’re improving our auditing bandwidth and enhancing the ability of our coders to focus on other chart audits and other projects that we couldn’t do before.

JoAnn Hayden
Scripps Health Plan Services
Case Study

Capital Blue Cross

Fast Facts: Second-Pass Coding 33,500 charts reviewed +5% RAF score increase between…

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Case Study

How a Veteran Coder Used Apixio’s HCC Identifier to Eliminate Data Entry Error and Double Productivity

Fast Facts Increased productivity from 3 charts per hour to 10 charts…

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Case Study

Sigma Health Plan

Fast Facts 70,000 lives reviewed 983 new HCC codes 98.5% coding accuracy…

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