Medical Condition Cost Indexing Through Statistical Drug Linkage
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Solution Overview
Problem
The healthcare industry lacks a robust index to stabilize costs due to the absence of a futures market, and existing techniques for linking pharmaceuticals to medical conditions are flawed with false positives and negatives, leading to inaccurate cost analysis.
Innovation Solution
A method involving big data and machine learning to generate an index sensitive to the cost of treating medical conditions by filtering and weighting procedure codes, incorporating impact factors, and creating a drug and medical condition library to link pharmaceuticals accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a naïve technique is used to link pharmaceuticals to medical conditions by identifying all patients diagnosed with a condition and ranking pharmaceuticals by frequency of use, then the process is simple to implement, but the result contains false positives and false negatives and introduces significant noise into the analysis
Solution Approach 1:
The patent introduces an intermediary statistical analysis layer between the naïve frequency-counting approach and the final pharmaceutical-linkage determination. This intermediary layer calculates the likelihood of drug usage in patients with a specific condition versus patients without the condition, acting as a mediator that filters out false positives and false negatives while maintaining analytical accuracy
Solution Approach 2:
The patent replaces the simple mechanical counting mechanism (frequency-based ranking) with a statistical probability model. This substitution transforms the analysis from a straightforward but inaccurate mechanical process into a more sophisticated statistical system that accounts for background drug usage rates and condition-specific usage patterns
2Measurement precision
If a statistical-based analysis is used to determine the likelihood of seeing a particular drug among patients with a particular medical condition, then the accuracy of pharmaceutical-linkage analysis is improved, but the complexity of the analysis process increases
Solution Approach 1:
The patent segments the analysis process into distinct computational stages: (1) calculating the likelihood of drug usage in patients with the condition, (2) calculating the likelihood of drug usage in patients without the condition, and (3) comparing these likelihoods to determine significant linkages. This segmentation breaks down the complex statistical analysis into manageable, systematic steps that improve accuracy while maintaining process clarity
3Stability of the object's composition
If an index is created to represent healthcare costs for a futures market, then market stability is achieved, but the index must account for both services and pharmaceuticals which increases the complexity of index construction
Solution Approach 1:
The patent merges two separate cost components (healthcare services and pharmaceuticals) into a unified index structure. By combining these elements into a single comprehensive index that represents total healthcare costs, the system achieves market stability while systematically managing the complexity through integrated data processing and weighting mechanisms
Data Source
AI summary
Techniques for generating an index that is statistically sensitive to a cost of treating a medical condition are disclosed. Claim forms that are related to an identified medical condition are accessed. Codes are identified from within the claim forms. These codes are determined to be procedure codes. Pharmaceuticals for the procedure codes are identified, and a cost for those pharmaceuticals is determined. Each of the procedure codes is weighted based on whether each procedure code is directly related to the particular medical condition or is related to an identified co-morbidity of the particular medical condition. A cost for the weighted procedure codes is determined. The cost for the weighted procedure codes and the cost for the pharmaceuticals are used to determine a per capita cost for the medical condition. An index for the medical condition is generated based on the per capita cost.