Proprietary Computational Models System
A Framework that Adjusts to the Needs of Your Practice & Providers
We leave the mediocre blanket approaches to our competitors and offer automated software that is personal and hyper-focused on you and your practice.
Instead of forcing you to adjust to our systems, we created systems that adjust to you, and focus on designing a user-friendly means of setting up smart filters, practice rules, management options, and easy to access (and use) features that enhance your daily efficiency.
Focused Simplification
AI Pattern Analysis
Revenue Efficiency
Our Six Primary Rules Engine Focuses
Focus #1: Accurately identifying the tools, insights, and assistance you need (or will need)
Focus #2: Providing everything you need at the time you need it in a useful manner
Focus #3: Making what you need easily accessible to you in a helpful manner
Focus #4: Properly customizing our solutions to your particular practice and needs
Focus #5: Effectively filtering and grouping our data sets by real-world priority and timing
Focus #6: Refining the process over time based on patterns to further enhance productivity
Machine Learning for Medical Billing
Claimocity deploys a series of advanced analytics, deep-dive statistical analyses, and machine learning algorithms to take hospital-based patient billing and revenue processes to the next level, giving hospitalists and hospital physicians the tools they need to not only manage but exceed even their own rigorous expectations.
The simple truth is that the insurance company generated and controlled billing processes are confusing, mystifying, and in general, a complete mystery to most physicians. Even billing experts with decades of experience encounter issues, so what can a doctor who has devoted his or her life to medicine instead of billing hope to accomplish in the face of such overwhelming odds.
Insurance plans vary by provider and insurer, each with their own set of rules, contract rates, historical payout averages, denial rates, and contextual nuances that impact payouts and create a web of gray areas and claim hurdles that making coding and billing an arduous process to sift through with high efficiency. This leads to under coding errors for safety reasons or over coding errors to generate higher short term revenue streams despite the long term risks.
Medical Coding Machine Learning
The Claimocity medical coding machine learning uses advanced analytics to learn patterns, assess historical data, analyze individual billing and coding choices, and enhance the accuracy, efficiency, and financial productivity that drives consistent improvements and growth.
Over time the pattern analysis gathers more personalized data for your practice, improving the decision-making capacities, reducing errors, improving revenue streams, and systematically getting rid of the impediments to rigorous bottom-line improvements for everyone in your practice.
Medical Billing Software Rules Engine Hospital Uses
What is a medical billing rules engine? The bigger answer is as complex as the billing process. The simple answer is that each practice is different, requiring a different set of parameters based on the facilities they work in, the number of physicians covering each other, the type of patients being seen, the time frames between visits, whether there is an intake visit or a discharge necessary within the specialty, whether gaps means that a visit has been missed or just unbilled, and so on. A smart rules engine allows for a level of specification and individualization that personalizes the practice management and revenue software to your practice’s specific needs and improve the performance over time.
