Electronic System-MD for Psychiatric Medication Assessment
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Solution Overview
Problem
Current methods for evaluating psychiatric medication effectiveness are time-consuming, lack systematic comparison across patients, and are limited by biased pharmaceutical company studies and inability to represent real-world patient populations, with no efficient way to track medication changes over time.
Innovation Solution
The CelestHealth System-MD electronically monitors and compares psychiatric medication effectiveness across patients using the Behavioral Health Measure-20 questionnaire, providing immediate feedback on mental health scores and medication changes, and generates Medication Outcome Graphs and Medication Effect Graphs to assess individual and group medication efficacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If manual or electronic recording of mental health scores and medication data is used, then data can be collected and stored, but significant time and effort are required to associate questionnaire scores with medication administration and changes
Solution Approach 1:
The system automatically associates mental health scores with medication administration data without requiring manual intervention. The electronic system self-updates by linking questionnaire scores recorded at each visit with the medication data already in the database, eliminating the need for physicians or staff to manually perform this association.
Solution Approach 2:
The manual mechanical process of recording and associating data is replaced with an automated electronic system. The system uses computational algorithms to automatically link mental health scores with medication information, substituting human effort with automated information processing.
2Measurement precision
If visual scanning of notes or spreadsheets is used to detect changes in mental health over time, then changes can be identified, but the process is time-consuming and inefficient
Solution Approach 1:
The visual scanning process is replaced with automated computational analysis. The electronic system automatically compares mental health scores across multiple visits using algorithms, instantly identifying changes and trends without requiring human visual inspection of notes or spreadsheets.
Solution Approach 2:
The system provides automated feedback by continuously monitoring mental health scores and comparing them against baseline measurements. When changes occur, the system generates notifications or reports that immediately inform physicians of medication effectiveness, creating a closed-loop feedback system that enhances productivity.
3Reliability
If randomized clinical trials are used to evaluate medication effectiveness, then systematic comparison can be made, but the studies are biased by pharmaceutical companies and do not represent real-world patient populations
Solution Approach 1:
The system serves multiple functions: it evaluates medication effectiveness for individual patients, compares outcomes across diverse patient populations, and generates aggregate data that reflects real-world practice. This universal approach replaces single-purpose clinical trials with a multi-functional evaluation system that handles both individual and population-level assessment.
Solution Approach 2:
Instead of starting with controlled clinical trials and then attempting to apply results to real-world settings, the system inverts the approach by directly collecting data from real-world practice. It gathers mental health scores and medication data from actual patient visits, thereby capturing genuine real-world effectiveness without the biases of pharmaceutical-sponsored trials.
4Loss of information
If physicians rely on academic journals publishing RCT results, then medication effectiveness information is available, but physicians lack the time, staff, or statistical resources to assess effectiveness independently
Solution Approach 1:
The system performs statistical analysis automatically without requiring physicians to have statistical expertise or dedicated staff. The electronic system self-calculates effectiveness metrics by comparing patient outcomes across visits and populations, eliminating the need for external statistical resources.
Solution Approach 2:
Complex statistical analysis procedures are replaced with automated computational algorithms embedded in the electronic system. The system handles all statistical computations internally, substituting the need for manual statistical work with automated information processing capabilities.
Data Source
AI summary
Disclosed is a method of efficiently assessing the effectiveness of psychiatric medications as administered by physicians and more specifically to a methodology that compares the effectiveness of different medications across groups of patients based on changes in mental health scores using electronic systems. Additionally, the invention delineates when changes in medications are made during the course of medical visits for a single patient.