What new features could Komodo Health add to its Sentinel platform to improve real-world evidence generation?

Introduction

To improve real-world evidence generation on Komodo Health's Sentinel platform, we need to identify and implement new features that enhance data collection, analysis, and insights delivery. I'll approach this by examining user needs, current pain points, and potential solutions, keeping in mind the evolving landscape of healthcare data analytics.

Step 1

Clarifying Questions (5 mins)

• Looking at Komodo Health's position in the healthcare analytics market, I'm curious about the primary use cases for Sentinel. Could you share the top 2-3 ways customers are currently using the platform for real-world evidence generation?

Why it matters: Helps focus our improvement efforts on the most impactful areas Expected answer: Clinical trial optimization, post-market surveillance, and comparative effectiveness research Impact on approach: Would prioritize features that enhance these specific use cases

• Considering the rapidly evolving nature of healthcare data, I'm wondering about the current data sources integrated into Sentinel. What types of data are we currently leveraging, and are there any significant gaps or areas where customers are requesting more comprehensive coverage?

Why it matters: Identifies potential areas for expansion in data collection and integration Expected answer: Claims data, EHR data, and some social determinants of health data, with gaps in genomic and patient-reported outcomes Impact on approach: Would focus on features that address data gaps or improve integration of diverse data types

• Given the increasing importance of AI and machine learning in healthcare analytics, I'm interested in understanding Sentinel's current capabilities in this area. To what extent are we currently employing AI/ML techniques for real-world evidence generation, and what has been the customer feedback on these features?

Why it matters: Determines the potential for AI-driven feature enhancements Expected answer: Basic predictive analytics are in place, but customers are seeking more advanced AI capabilities Impact on approach: Would prioritize AI-powered features that can significantly enhance evidence generation

• Considering the competitive landscape, I'm curious about our differentiators. What unique capabilities does Sentinel currently offer that set it apart from other real-world evidence platforms in the market?

Why it matters: Helps identify areas to further strengthen our competitive advantage Expected answer: Comprehensive longitudinal patient journeys and proprietary data linkage techniques Impact on approach: Would focus on features that build upon and enhance these differentiators