0
%
Reduction in execution time across the classification exercise
0
+
Diagnostic tests reviewed, classified, and structured into a database
$
0
B+
AUM of the global PE firm served
From 120 Hours to 50: AI-Powered Diagnostic Data Classification for a Global PE Firm
About the Client
A global private equity firm navigating highly technical healthcare data
A global PE firm managing $750B+ in assets engaged TresVista to interpret and standardize highly technical diagnostic data across a large test set, enabling consistent classification and reliable decision-making at scale.
Business Challenge
Two compounding barriers to accurate classification
• Clinical complexity at scale
Hundreds of diagnostic tests required clinical interpretation and consistent classification, creating significant complexity in ensuring accuracy and standardization across the full dataset
• Manual review bottleneck
Interpreting domain-specific clinical sources, validating rationale, and structuring outputs into clear utilization buckets made manual review extremely time-intensive
Strategic Approach
TresVista's Solution: Structured AI synthesis, anchored by clinical validation
TresVista built a structured AI-assisted workflow using ChatGPT Enterprise, combining a purpose-built prompt framework with rigorous analyst oversight to ensure clinical accuracy and output consistency across all classifications.
01
Diagnostic data review
TresVista systematically reviewed each diagnostic test against clinical reports, healthcare research publications, and diagnostic test databases to establish a consistent evidence base
02
AI-assisted research synthesis
ChatGPT Enterprise, guided by a structured prompt framework, was used to synthesize complex clinical source material and generate first-pass interpretations for each test category
03
Utilization bucketing
TresVista classified each diagnostic test into defined utilization buckets, ensuring outputs were structured, comparable, and directly actionable for the client's investment analysis
04
Output validation
TresVista analysts reviewed and validated all AI-generated outputs against source material, applying clinical judgment to confirm rationale accuracy before final delivery
TresVista Impact
A structured database. Faster delivery. Deeper analysis.
Before
120+
hours
After
~50
hours
~70 hrs
Saved
~70 hrs Saved per engagement
Reinvested in deeper analytical work.
Outcome
- Reviewed and classified approximately 300 diagnostic tests, delivering a structured database with clear utilization buckets and documented supporting rationale for each classification
- 60% reduction in execution time, cutting manual effort from 120+ hours to approximately 50 hours while maintaining clinical accuracy and classification consistency throughout
- Time freed for deeper analysis, allowing the client's deal team to shift focus from data processing to investment evaluation and sector-level insight development
Tools & Technologies
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