Predictive Outcomes for Implantable Medical Devices
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Clinicians face challenges in determining optimal operating parameters for implantable medical devices (IMDs) due to the vast number of programmable settings and the dynamic nature of best medical practices, which can be time-consuming and underutilize valuable data stored in medical databases.
Innovation Solution
A system and method that utilizes a centralized database to compare individual patient data with historical data from a medical database, sorting matching datasets by therapy interventions to generate predictive outcomes reports for clinicians, including device-related, patient-related, and cost-related outcomes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If clinicians manually evaluate multiple programmable parameter settings for IMDs, then treatment decisions can be made, but the process becomes time-consuming and inefficient
Solution Approach 1:
The system pre-processes and stores outcome data from multiple patients with different IMD parameter settings in a database. When a clinician needs to determine optimal parameters, the system has already compiled the necessary comparative data, eliminating the need for manual evaluation of multiple settings and significantly reducing the time required for treatment decisions.
Solution Approach 2:
The patent introduces an intermediary system comprising a database and computer that mediates between the clinician and the complex IMD parameter selection process. This intermediary automatically retrieves and compares outcome data from similar patients, providing evidence-based recommendations that simplify the clinician's decision-making process while maintaining thoroughness.
2Loss of information
If extensive patient data is stored in medical databases, then valuable information is available, but the data remains under-utilized and does not effectively improve clinical decision-making
Solution Approach 1:
The system implements feedback by automatically querying the database for outcome data from patients with similar characteristics and treatment histories. This feedback loop provides clinicians with evidence-based outcomes from comparable cases, enabling them to make more informed decisions while fully utilizing the stored database information.
Solution Approach 2:
The patent introduces an intermediary system comprising a database and computer that mediates between the clinician and the complex IMD parameter selection process. This intermediary automatically retrieves and compares outcome data from similar patients, providing evidence-based recommendations that simplify the clinician's decision-making process while maintaining thoroughness.
3Reliability
If clinicians rely on individual patient data or small groups, then treatment decisions can be made, but the best medical practices remain dynamic and difficult to ascertain
Solution Approach 1:
The system pre-processes and stores outcome data from multiple patients with different IMD parameter settings in a database. When a clinician needs to determine optimal parameters, the system has already compiled the necessary comparative data, eliminating the need for manual evaluation of multiple settings and significantly reducing the time required for treatment decisions.
Solution Approach 2:
The patent introduces an intermediary system comprising a database and computer that mediates between the clinician and the complex IMD parameter selection process. This intermediary automatically retrieves and compares outcome data from similar patients, providing evidence-based recommendations that simplify the clinician's decision-making process while maintaining thoroughness.
Data Source
AI summary
A system and associated method receives, by a database coupled to a communication network, patient medical data from multiple data sources including data retrieved from implantable medical devices implanted in patients. A processor accesses the database to generate a dataset from the medical data having at least one data characteristic matching a corresponding data characteristic of a patient group of at least one patient. At least one subset of the dataset is identified that had a therapy intervention subsequent to a time point that the subset had the matching data characteristic(s). An outcome of the subset is determined and a predictive outcome for the patient group is produced based on the outcome of at least one subset.


