Healthcare Procedure Prior Authorization Prediction From Claims Analytics
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Solution Overview
Problem
Healthcare providers face complexity in determining whether a procedure requires prior authorization due to varying policies among different payors, often leading to manual inquiries that are time-consuming and potentially inaccurate, resulting in rejected claims.
Innovation Solution
A computer-implemented method processes historical claim and remittance information to generate metrics and thresholds for predicting whether prior authorization is required, using probabilistic analysis and statistical hypothesis testing to provide accurate recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual process is used to contact payor for prior authorization inquiry, then providers can obtain authorization information, but the process becomes time-consuming and potentially inaccurate
Solution Approach 1:
The system enables providers to self-determine prior authorization requirements through automated analysis of historical claim data and payor policies, eliminating the need to manually contact payors for each inquiry. The provider access device automatically queries the system and receives predictions based on processed historical information.
Solution Approach 2:
The system performs preliminary analysis of prior authorization requirements by processing historical claim and remittance information before actual procedures are performed. This advance preparation creates a knowledge base that enables quick, accurate determinations without time-consuming manual inquiries at the point of care.
2Reliability
If different payor policies are manually researched, then accurate authorization rules can be found, but the complexity of obtaining policies from various payor sites increases
Solution Approach 1:
The system serves multiple payors with different policies through a single unified platform. The historical claim data repository and analysis engine universally process information from various payors (Medicare, Medicaid, private insurers, HMOs, PPOs) and provide consistent predictive outputs across all payor types.
Solution Approach 2:
The system acts as an intermediary between providers and multiple payors, automatically managing the complexity of researching and interpreting different payor policies. Instead of providers directly navigating complicated payor websites and documents, the system mediates by processing historical data and generating predictions based on aggregated payor rule information.
3Productivity
If prior authorization is not obtained when required, then processing time is reduced, but claims are denied payment
Solution Approach 1:
The system incorporates feedback from historical remittance information showing actual payor responses to prior authorization requests. By analyzing patterns in historical claim outcomes, the system learns which procedures require authorization for each payor and provides increasingly accurate predictions, improving both productivity and payment success rates over time.
Solution Approach 2:
The system replaces the mechanical process of manual prior authorization inquiries with an automated electronic prediction system. This substitution eliminates the time-consuming manual workflow while maintaining high accuracy in determining authorization requirements, thereby improving both productivity and claim payment success.
Data Source
AI summary
A method includes processing, by one or more processors, historical claim and claim remittance information to extract prior authorization data; performing, by the one or more processors, a probabilistic analysis on the prior authorization data for a procedure to generate a first metric and a second metric, the first metric comprising a percentage of claims including the procedure in which prior authorization is applied for and the second metric comprising a percentage of claims including the procedure in which prior authorization was not applied for and were denied payment for not applying for prior authorization; determining, by the one or more processors, whether the first metric satisfies a first authorization threshold and the second metric satisfies a second authorization threshold, the first and second thresholds being associated with a prior authorization rule corresponding to the procedure; and generating, by the one or more processors, a recommendation on whether to obtain prior authorization before performing the procedure based on whether the first metric satisfies the first authorization threshold and the second metric satisfies the second authorization threshold.