US-20260124377-A1 - LONGITUDINAL HEALTH OUTCOME MONITORING USING AN INTELLIGENT INJECTION DEVICE PLATFORM

US20260124377A1US 20260124377 A1US20260124377 A1US 20260124377A1US-20260124377-A1

Abstract

Methods and systems are disclosed for using an intelligent injection device platform to perform longitudinal and other health outcome analyses. A device may include a database for storing treatment schedules, administration data, and biomarker measurements. A device may include a data collection system configured to collect biomarker data from connected monitoring devices. A device may include a compliance analysis module configured to calculate an adherence score by comparing actual administration timing and dosage to a prescribed treatment schedule. A device may include a research analytics module configured to analyze a relationship between medication regimen adherence and a patient outcome. A device may include a reporting system configured to generate an observational study report correlating a drug adherence pattern with a biomarker change and a clinical outcome.

Inventors

Jeremy Corbett

Assignees

DATADOSE, LLC

Dates

Publication Date: 20260507
Application Date: 20250829

Claims (20)

1 . A research platform for tracking medication usage and patient biomarkers comprising: a server configured to receive administration data received from a wireless module of intelligent injection devices used within a healthcare entity; a database for storing treatment schedules, the administration data received from the wireless module of the intelligent injection devices, and biomarker measurements; a data collection system configured to collect biomarker data from connected monitoring devices; a compliance analysis module configured to calculate an adherence score by comparing actual administration timing and dosage to a prescribed treatment schedule, wherein the actual administration timing and dosage is received from the wireless module of the intelligent injection devices; a research analytics module configured to analyze a relationship between medication regimen adherence and a patient outcome, wherein the medication regimen adherence is determined based upon, at least in part, the administration data received from the wireless module of the intelligent injection devices; a reporting system configured to generate an observational study report correlating a drug adherence pattern with a biomarker change and a clinical outcome, wherein the drug adherence pattern is determined based upon, at least in part, the administration data received from the wireless module of the intelligent injection devices; and adjusting one or more chamber valves of at least one intelligent injection device of the intelligent injection devices to control delivery of the dosage.
2 . The research platform of claim 1 , wherein the research analytics module uses sensor fusion to generate a prediction related to an instance of medical dosage administration.
3 . The research platform of claim 1 , wherein the compliance analysis module is configured to calculate a compliance score for an injection event based at least in part on a conformance of the administration data to at least one criterion of a treatment schedule, and compare the compliance score to a compliance threshold metric to categorize the injection event as compliant, non-compliant or indeterminate.
4 . The research platform of claim 1 , wherein the research analytics module comprises a generative AI system configured to generate a data story related to an intelligent injection device or to an instance of medical dosage administration.
5 . The research platform of claim 1 , wherein the research analytics module is configured to analyze patterns across a plurality of intelligent injection devices to identify an optimal dosage timing sequence for an improved patient outcome.
6 . The research platform of claim 1 , wherein the data collection system is configured to aggregate administration data from multiple intelligent injection devices across different locations to generate a population-level adherence metric.
7 . The research platform of claim 1 , wherein the research analytics module utilizes at least one machine learning algorithm trained on administration data from a plurality of intelligent injection devices to predict a patient compliance pattern or treatment outcome.
8 . The research platform of claim 1 , wherein the reporting system is configured to generate a longitudinal study tracking medication effectiveness across multiple intelligent injection devices over a time period to identify a treatment optimization strategy.
9 . The research platform of claim 1 , wherein the data collection system is configured to collect temperature and storage condition data from multiple intelligent injection devices to correlate pharmaceutical stability with patient outcomes.
10 . The research platform of claim 1 , wherein the research analytics module utilizes artificial intelligence to analyze administration timing data from multiple intelligent injection devices to identify personalized dosing schedules that maximize therapeutic efficacy.
11 . The research platform of claim 1 , wherein the compliance analysis module is configured to track a medication adherence pattern across multiple intelligent injection devices to identify an intervention point for improving patient compliance in chronic disease management.
12 . The research platform of claim 1 , wherein the reporting system is configured to generate a comparative effectiveness research report analyzing outcomes across different intelligent injection device types and administration protocols.
13 . The research platform of claim 1 , wherein the data collection system is configured to aggregate administration data from intelligent injection devices across multiple geographic regions to identify population-specific treatment response patterns and optimize regional healthcare delivery.
14 . The research platform of claim 1 , wherein the research analytics module utilizes predictive analytics to analyze historical administration data from multiple intelligent injection devices to forecast a future medication need.
15 . The research platform of claim 1 , wherein the reporting system is configured to generate a real-time research dashboard displaying aggregated analytics from multiple intelligent injection devices to support clinical decision-making and treatment protocol adjustments.
16 . A method of performing predictive analytics on population-level medication data comprising: aggregating administration data received wirelessly from a plurality of intelligent injection devices across a defined patient population spanning multiple healthcare providers, wherein the administration data includes data resulting from adjusting one or more chamber valves of at least one of the plurality of intelligent injection devices to control dosage delivery; collecting continuous physiological measurements from connected monitoring devices within the defined patient population; training a machine learning system on training datasets of intelligent injection device operation of the plurality of intelligent injection devices and outcome data resulting from usage of the plurality of intelligent injection devices; analyzing time-series data of medication adherence patterns correlated with biomarker trends, wherein the medication adherence patterns are determined from the administration data received from the plurality of intelligent injection devices; identifying a patient at risk of non-compliance based on historical adherence patterns determined from the administration data received from the plurality of intelligent injection devices and biomarker measurements; predicting optimal injection timing and dosage based on population-level physiological parameter analysis of the defined patient population; generating a cost-effectiveness analysis correlating medication compliance with a healthcare cost and clinical outcome, wherein correlating the medication compliance is based upon, at least in part, the administration data received from the plurality of intelligent injection devices; and providing a recommendation for a population health intervention based on a predictive analytics result, wherein the predictive analytics result is based upon, at least in part, the administration data received from the plurality of intelligent injection devices, the time-series data of medication adherence patterns correlated with the biomarker trends, the population-level physiological parameter analysis, and the cost-effectiveness analysis.
17 . The method of claim 16 , wherein aggregating administration data includes collecting temperature sensor data from the plurality of intelligent injection devices to correlate pharmaceutical storage conditions with medication efficacy in population-level studies.
18 . The method of claim 16 , wherein collecting continuous physiological measurements includes integrating data from wearable devices associated with the plurality of intelligent injection devices to enhance longitudinal patient monitoring.
19 . The method of claim 16 , wherein the cost-effectiveness analysis includes transaction intelligence data from intelligent injection devices for use in a healthcare billing process.
20 . An intelligent injection device research data platform comprising: a network of intelligent injection devices deployed across a healthcare entity; integration of the network of intelligent injection devices with an electronic medical record system for comprehensive patient data collection; a digital twin module configured to model a patient response based on medication administration data received from the network of intelligent injection devices and biomarker measurement, wherein the medication administration data includes data resulting from adjusting one or more chamber valves of at least one of the intelligent injection devices to control dosage delivery; a machine learning system trained on datasets of medication administration patterns from administration data of prior intelligent injection devices and corresponding biomarker changes; a research compliance module configured to ensure data collection for at least the network of intelligent injection devices meets an institutional review board requirement; and a data governance system configured to maintain patient privacy while enabling research analysis of patient medication usage patterns and health outcomes associated with the network of intelligent injection devices.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS This application is a continuation-in-part of U.S. patent application Ser. No. 19/281,005, filed on Jul. 25, 2025, which is a continuation of U.S. patent application Ser. No. 19/031,862, filed on Jan. 18, 2025, which is a continuation of U.S. patent application Ser. No. 19/030,829, filed on Jan. 17, 2025, which claims the benefit of U.S. provisional application no. 63/715,505, filed on Nov. 1, 2024, which are all hereby incorporated by reference in their entirety. FIELD The present disclosure relates generally to a management platform for injection devices, such as syringes, and, more particularly, to data reporting regarding administration completion of an injectable pharmaceutical. Understanding administration of drugs and their interaction in the healthcare ecosystem are important in delivering beneficial patient care. Applicant appreciates that regular pharmaceutical therapy and a need for real time data management related to both timing of and compliance in dosing bundled with increased information sharing across the care continuum can provide valuable insight for improving care and, in turn, reducing fraud, waste, and abuse. SUMMARY In some aspects, the techniques described herein relate to a research platform for tracking medication usage and patient biomarkers including: a server configured to receive administration data from intelligent injection devices used within a healthcare entity; a database for storing treatment schedules, administration data, and biomarker measurements; a data collection system configured to collect biomarker data [dependent: including glucose levels, weight measurements, and physiological parameters] from connected monitoring devices; a compliance analysis module configured to calculate an adherence score by comparing actual administration timing and dosage to a prescribed treatment schedule; a research analytics module configured to analyze a relationship between medication regimen adherence and a patient outcome; and a reporting system configured to generate an observational study report correlating a drug adherence pattern with a biomarker change and a clinical outcome. In some aspects, the techniques described herein relate to a research platform, wherein the research analytics module uses sensor fusion to generate a prediction related to an instance of medical dosage administration. In some aspects, the techniques described herein relate to a research platform, wherein the compliance analysis module is configured to calculate a compliance score for an injection event based at least in part on a conformance of the administration data to at least one criterion of a treatment schedule, and compare the compliance score to a compliance threshold metric to categorize the injection event as compliant, non-compliant or indeterminate. In some aspects, the techniques described herein relate to a research platform, wherein the research analytics module includes a generative AI system configured to generate a data story related to an intelligent injection device or to an instance of medical dosage administration. In some aspects, the techniques described herein relate to a research platform, wherein the research analytics module is configured to analyze patterns across a plurality of intelligent injection devices to identify an optimal dosage timing sequence for an improved patient outcome. In some aspects, the techniques described herein relate to a research platform, wherein the data collection system is configured to aggregate administration data from multiple intelligent injection devices across different locations to generate a population-level adherence metric. In some aspects, the techniques described herein relate to a research platform, wherein the research analytics module utilizes at least one machine learning algorithm trained on administration data from a plurality of intelligent injection devices to predict a patient compliance pattern or treatment outcome. In some aspects, the techniques described herein relate to a research platform, wherein the reporting system is configured to generate a longitudinal study tracking medication effectiveness across multiple intelligent injection devices over a time period to identify a treatment optimization strategy. In some aspects, the techniques described herein relate to a research platform, wherein the data collection system is configured to collect temperature and storage condition data from multiple intelligent injection devices to correlate pharmaceutical stability with patient outcomes. In some aspects, the techniques described herein relate to a research platform, wherein the research analytics module utilizes artificial intelligence to analyze administration timing data from multiple intelligent injection devices to identify personalized dosing schedules that maximize therapeutic efficacy. In some aspects, the techniques described herein relate to a research platform, wherein the