Transforming Healthcare Software Implementations with AI: Insights from the Puerto Rico Hospital Association Health IT Summit
I recently had the privilege of speaking at the Puerto Rico Hospital Association Health IT Summit, where I discussed how artificial intelligence is revolutionizing healthcare software implementations.
The Problem with Traditional Healthcare Software Implementations
In my presentation, I highlighted a critical challenge facing healthcare organizations today: traditional software implementations are often:
- Costly - requiring significant investment in consultants and staff time
- Time-consuming - frequently taking months or even years to complete
- Complex - demanding specialized knowledge across multiple domains
- Error-prone - with manual processes introducing data inconsistencies
Data migration emerged as one of the most critical pain points in these implementations. The process typically involves high-touch, manual work that not only drives up costs but also introduces security risks and potential errors that can impact patient care.
How AI is Transforming Implementation Processes
AI is transforming software implementations by automating key processes:
1. Data Classification
AI can automatically categorize and organize information from diverse sources, creating structure from unstructured data.
2. Data Mapping
Where data already exists but needs restructuring, AI can efficiently map information between different systems without requiring manual intervention.
3. Data Enrichment
For situations requiring inference and additional context-specific information, AI can enrich data by converting continuous variables to discrete ones and drawing connections between disparate data points.
Real-World Success: Baptist Health Case Study
To illustrate these benefits, I shared the experience of Baptist Health, which faced the challenge of consolidating multiple EHRs from over 200 care points, including hospitals, independent emergency departments, and ambulatory centers.
Their solution involved:
- Adopting an organization-wide EHR system (EPIC)
- Implementing an AI solution from drFirst to clean and normalize medication data during migration
The AI system processed millions of medication SIGs (instructions), ensuring information was converted into discrete data by interpreting clinical language.
Remarkable Results:
- Processed over 7 million medication SIGs
- Identified more than 3,000 additional high-risk medications across 1,700+ patient profiles
- Saved over 7 million clicks in the first 7 months after launch, dramatically reducing manual work
- Improved operational care by giving doctors access to complete patient medication data
AI Implementation at Equiply
I also shared how we're leveraging AI at my current startup, Equiply, to tackle similar challenges in medical equipment management:
The Challenge:
Providing financial insights on hospital medical equipment infrastructure requires consolidating data from multiple sources:
- Electronic Health Records (EHR)
- Computerized Maintenance Management Systems (CMMS)
- Fixed asset databases
- Manufacturer databases
Often, hospitals have only basic information like equipment serial numbers, but lack critical data such as:
- Manufacturing dates
- Warranty details
- Purchase information (cash, lease, financed)
- Departmental revenue projections
Our Solution:
We've developed an internal AI tool that helps merge, classify, enrich, and map data to specific formats, enabling us to provide critical financial analyses including:
- Lifecycle cost analysis
- Investment analysis
- Useful remaining life calculations
- Capital planning
- Replacement matrices
- Equipment prioritization
The Result:
Dramatically faster implementations that deliver immediate value to healthcare organizations.
Looking Forward
As AI continues to evolve, its impact on healthcare software implementations will only grow. The technology is streamlining workflows, improving data accuracy, and reducing costs—transforming what was once a painful process into a strategic advantage.
Healthcare organizations that embrace these AI-powered approaches will not only save time and money but also improve data quality, leading to better clinical decision-making and patient outcomes.
Connect and Continue the Conversation
If you're interested in discussing how AI can transform your healthcare software implementations or would like to learn more about our work at Equiply, please feel free to connect with me on LinkedIn or visit our website.