EHR Cohort Aggregation for Medication Usage Research
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Solution Overview
Problem
Existing methods for gathering medication usage information post-regulatory approval face challenges due to incomplete or inaccessible pharmacy and insurance records, with each provider requiring separate consent and non-standardized data across entities.
Innovation Solution
An automated system using a coordination server that aggregates Electronic Health Records (EHRs) from multiple healthcare providers to identify and compile data for a cohort of patients based on predefined criteria, eliminating the need for individual consent and record access from pharmacies and insurance providers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If pharmacy records and insurance records are accessed to gather medication usage information, then data can be collected for research studies, but the records are incomplete or inaccessible and require separate consent from each patient and provider
Solution Approach 1:
The patent combines multiple data sources (pharmacy records, insurance records, EHR data) into a unified research database through the coordination server. This merging approach consolidates scattered medication usage information from multiple providers into a single accessible repository, eliminating the need to separately access and reconcile data from multiple independent sources.
Solution Approach 2:
The coordination server acts as an intermediary between researchers and healthcare providers' data systems. It receives de-identified data from multiple providers, processes it according to research protocols, and delivers results to researchers without requiring direct access to individual provider systems or patient consents for each data request.
2Reliability
If separate consent is obtained from each patient and provider for data sharing, then patient privacy is protected, but the efficiency of drug-related investigations is reduced
Solution Approach 1:
Patients provide consent for data sharing in advance during their routine healthcare visits, before any research studies are initiated. This preliminary consent is stored in the EHR system and allows future research data requests to proceed without additional patient involvement, eliminating the need for repeated consent processes for each study.
Solution Approach 2:
The system uses automatically generated de-identified data sets that are prepared and made available by the coordination server without requiring manual patient authorization for each research request. The automated processes handle data selection, de-identification, and delivery, making the system self-sufficient for routine research data needs.
3Ease of operation
If data is standardized across multiple insurers and providers, then data can be easily accessed and parsed, but each entity has its own data privacy policies and non-standardized systems
Solution Approach 1:
The coordination server transforms data from various providers into a standardized format by applying uniform de-identification rules, data structures, and coding standards. This parameter transformation allows data from diverse sources with different privacy policies and formats to be converted into a consistent, research-ready format that maintains necessary privacy protections while enabling efficient analysis.
Data Source
AI summary
Apparatus and method for supporting medication research. In an embodiment, an apparatus executes an algorithm to receive a request regarding a medication, obtain Electronic Health Record (EHR) data for a population of patients prescribed the medication within a target time period, perform electronic data processing on the EHR data for the population of the patients based on cohort criteria specified in the request to identify a cohort of the patients from the population, compile the EHR data for the cohort, and provide a report regarding the medication based on the compiled EHR data.