this is the ALGORITHMIC ai layer with a blended data science and DOMAIN EXPERTISE approach.
We create scalable and highly repeatable best-practice data analysis models, using community-driven machine learning algorithms, to automatically analyze massive amounts of claim data and provide prescriptive insights and actions for every claim, in seconds. Our decision engines are 100X faster and for 70% less cost than traditional manual and point-solution approaches.get a demo
THE APPROACH THAT IS 70% LESS COST, 100X FASTER THAN MANUAL ANALYSIS AND HAS ALREADY DRIVEN OVER $300 MILLION IN VALUE TO DATE.view case studies below
AI AND MACHINE LEARNING DECISION ENGINES FOR RCM.
Our decision engines are purposely built to replicate human intelligence and reduce the time between analysis and decision availability and increasing the ability to share information across multiple platforms and tools.
Assess and predict insurance claim denial risk and segment receivables with best follow-up tactic.
Assess patient payment risk without FICO scores and segment receivables by engagement tactic.
Understand claim touch efficiency and staffing alignment while measuring overall performance.
Automatically identify, audit and mitigate upstream root-causes.
Ensure KPI benchmarks, cash flow forecasts and bad debt reserve methodologies are appropriately predicted.
Automatically assign the right portfolio of accounts to be placed to outsource vendors.
Integrate social determinants with one or more data sources to provide operational insights into patient financial behavior.
Line-level parse and auto-analyze 835/837 in near-time to provide deep insights into payer responses.
easy access to best practice decisions.
Our decision catalog gives you access to a robust library of pre-crafted expert insights on 50+ decision types that span front, middle and back-office operational processes. request decision catalog
you grow smarter as your data grows.
Forget multiple excel sheets or ad-hoc databases; we make extracting and storing your data -asset accessible and understandable. From transactional, charges to 837 to 277, our engines make it easy to drive meaningful analysis from raw data sources.
We like sharing our data, so our enriched insights are produced in file formats that will work across your platforms and tools.
Whether we run our algorithms on your internal servers or in our cloud, every algorithm output can be shared accurately, via ETL, API or HL7, eliminating redundant and time-consuming interoperability challenges.
LEVERAGE THE POWER OF THE COMMUNITY TO ENHANCE BEST PRACTICE KNOWLEDGE SHARING.
Our smart revenue cycle community amplifies the effects of cross-provider learning which allows us to works through problems, learn, and helps each other save time and money along the way.
Just like current community benchmarking, our smart community learns from each other by applying our decision engines in a hub approach that leverages meta-outcome learnings of each provider to drive improved process variation, risk decision, claim recommendation by making the algorithms smarter over time.
We help fill in gaps in your data when you might need additional information from the broader community.
Traditional benchmarks are to macro-level, so we use our community model to benchmark more granularly at the service line, payer and process level.
Access to improved process variation, risk decision, claim recommendation by making the algorithms smarter over time.
Our approach allows us to learn about performance issues from the community (i.e., elevated payer and service line risk.)
built to embed insights across multiple platforms, tools and people.
We use our expert services to help deploy our content across multiple platforms and tools to help you deliver stories and prescriptive insights for action in the way you need them to drive tangible ROI – We call it embedded intelligence.
Augment best-practice process improvement analysis, reports, and strategies with targeted, pinpoint accuracy.
We are EMR agnostic and rather than mimic system rules, we deploy enriched data files, inside other platforms databases.
Expertly crafted user stories summarized in easy to read stories that are used in existing visual tools.explore embedded intelligence