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.
