Clinical Trial Participant Engagement
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The document discusses a clinical trial data platform called Quahog LTI that aims to address issues with patient non-adherence in clinical trials such as prolonged trials and patient drop-outs. The platform provides real-time monitoring of patient data from connected devices and an intelligent bot to engage patients. This allows for instant issue resolution, improved data quality and reliability, and faster time to market. Key features include automated data collection and analysis, custom reporting and segmentation, and rule-based notifications and workflows to streamline clinical trials.
Clinical Trial Participant Engagement
- 1. Clinical Trial Optimization With Automated Real-Time Data Collection and Engagement
- 2. Problem Statement Patient non-adherence leading cause for Clinical trial prolongation and re-enrolment
- 3. Identifying Gaps Patient Compliance Unsatisfactory Issue Resolution Periodic Site Visits seems stressful Data Variability Drop Out Re-recruitment Delayed OutcomeInaccurate Outcome
- 4. Fixing the gaps for better results Better Patient Compliance Instant Issue Handling Integrating Device/Home kits Data Completeness Continuity Outcome generation as planned Accurate Outcome Better Patient/Participant Engagement Real-time alerts and monitoring Patient Engagement Device Data Integration
- 5. Mapping the Participant’s Journey The key to success is Monitoring and Engagement
- 6. Outcome of the Solution Improved Patient Compliance Data Reliability Faster time to Market Process Automation Areas of improvement
- 7. The Solution Quahog LTI Clinical Trial Data Platform An integrated data platform that provides trial administrators to manage patients and monitor their outcomes in real-time The platform provides Data Connectors Data Management Analytics & ML Module Workflow Module Bot Module
- 9. Platform - Advantages Using Quahog LTI platform, Clinical trial data logs containing patient data are synced to a secure cloud database, allowing in real-time monitoring which is necessary to measure outcomes and address adverse events quickly. In addition, it eliminates human error, reduces costs and saves precious time thus expediting time-to-market. Data Reliability As data collection is automated it minimizes manual entries, thus reducing human errors. As data is integrated, data compliance is enhanced for better accuracy in results Improves Patient Compliance Bots assisting patients to ensure routine is maintained and resolving patient queries. Clinical trial administrators are alerted instantly in case they need personal attention thus reducing trial fall-outs. Faster Time to Market Streaming data and real-time analysis allows in faster learning, thus reducing weeks between trial phases. The knowledge graph allows in full pattern extraction allow in conducting root cause analysis and in prediction of possible side effects, enabling deeper insights into the trials Cost Saving Data collection is automated which minimizes data input by patients or trial administrators, thus saving costs.
- 10. Integrated Clinical Trial Data Flow DATA COLLECTION DATA ANALYSIS AND INSIGHT AUTOMATION INTELLIGENT BOT PARTICIPANT FOOD DOSAGE BURN SLEEP REPORTS PERSONALIZATION TRIAL ADMINISTRATOR
- 11. Data Automation
- 12. Easier for the Trial Admin The platform enables the trial admin with the following features • Single Participant View with time-series timeline • Custom Segment Monitoring for Specific Behavioral Study • Rule based Triggers for Notifications • Trigger based Workflows • Bot Engagement and NLP Libraries • Custom Report Building • Custom Segmentation • User Permissions
- 13. Unified Participant Screen showing data over time helpful in analyzing changes in behavior highlighting influencing factors
- 14. An interface to create participant segments based on multiple parameter to analyze cohort behavior
- 15. Custom Time-series reports and Relationship graphs for temporal and spatial analysis of trial entities
- 16. Setting up rule types to ensure triggers and notifications for deviations and anomalies in patterns
- 17. Based on rules, users can trigger workflows based on rules to engage patients using automated targeting messages
- 18. Areas of Bot Engagement For better patient compliance
- 19. Automated Features The platform comes with built-in workflows for data organization, analysis and engagement • Creating Unified Patient Stack • Explicit Data Graph • Machine Learning Pipelines • NLP based Data Query
- 20. Data Unification The platform ensures data reliability by collecting and integrating data by each participant, creating a N=1 stack for highly accurate analysis Based on the relationship between nodes in the data graph, data is auto-organized, ready to process through ML workflows
- 21. Custom Knowledge Graph for Behavior Analysis of Trial Entities http://www.quahoglife.com/mgraph2.html
- 22. Machine Learning Pipelines for Predictions and Recommendation
- 23. Integrated NER and SRL Logic for making it easier to look for reports or patterns using keyword queries
- 24. In short, Quahog LTI Clinical Trial Data Platform offers 1. An integrated data platform for analyzing n=1 patient behaviour 2. Platform capable of integrating with external devices for data 3. A patient mobile app that is integrated with the platform 4. An machine learning platform to predict and recommend 5. An engagement platform that can trigger alerts and notification 6. A bot to engage patients 7. A back end monitor for clinical trial managers