Trinity Health Presenters: Self-Distribution and Supplier Collaboration Presenters: Jennifer Kleabir, Trinity Health Scott Gasiorek, Trinity Health

FACULTY DISCLOSURE The faculty reported the following financial relationships or relationships to products or devices they or their spouse/life partner have with commercial interests related to the content of this CE activity: Scott Gasiorek – No disclosures Jennifer Kleabir – No disclosures This slide is for internal use. Please do not alter.

Learning Objectives: Outline the dynamics of Master Data Management processes and procedures. Describe three challenges health systems face when measuring and managing data. Discuss how to achieve distribution and supplier collaboration.

Master Data Management

Current State Reference Data Challenges Multiple disparate system implementations have created challenges in linking key reference data items (ERP, EMR, Surgical Information Systems, etc.). Inability to link items across systems creates significant barriers to determining utilization, identifying cost per case, analyzing supply movement and reducing variation. Lack of integration across systems creates multiple maintenance points and redundant work across many functions.

Differences Between Systems

Current State Reference Data Challenges Different core item numbers Different MFG numbers and formatting Descriptions differ by noun majors, abbreviations and existence of attributes Cost information not passed or stored

Current State Data Maintenance Limited/poor integration between current ERP and SIS environments. Multiple teams managing the same item records across multiple systems Lack of master data management and standards promotes variation.

Future State Solution: MDM Enhance integration between supply chain and clinical systems Create an enterprise wide master item record with a unique numbering and classification scheme that can be centrally maintained and be the “source of truth” for all systems requiring item information Enhance the charge capture process Enhance reporting in support of gathering cost per case, reducing variation and utilization

The Tool: Informatica Informatica chosen as enterprise-wide solution for master data management Robust toolsets for data and entity mapping, schema definition and error handling Integrated with existing Informatica investment

Key Design / Build Steps Finalized vendor/item cross reference in support of consolidated item file. Design and built Informatica Data Director (IDD). Build included appropriate business rules and configuration differences between legacy ERP platforms and PeopleSoft. Match and merge rules created; Merge of east and west data complete for suppliers and items. Integrations completed with ERP platforms for suppliers and items. Discussions begun with internal teams supporting EMR/Surgical platforms (Cerner, Epic, McKesson) to establish vision for future state integration.

Tubing Example

Trinity Health DISC Network (Dedicated Integrated Service Center) Single delivery point for manufacturers

Our Collaborative Foundation Quality Reduce Inventory in field Lower our cost to serve Supply producing and receiving what is needed Demand sending the right signals Current State/ Future State Transactional Innovation How do we become better Strategy Alignment Define together Partnership Quality Quality Operations & Supply Chain Alignment Creativity & R & D Quality

How do we become more efficient? Tool and Resources How do we become more efficient? - Run current state vs. future state workshops with supplier - Understand current PO transaction behavior - Review supplier scorecarding and identify “quick fixes” - Ensure accountability on all parties

Scoring Methodology Categories Weight Sub-Categories Delivery Performance 35% On-Time Performance Average Days Overdue 25% 10% Order Management 30% Exceptions Back Orders Duplicates 15% 5% Quality Order Discrepancies (NCI’s) Recalls Returns Value & Support P/F Satisfaction Survey DISC ROI Contribution/Cost Savings Overall 100% This slide is for internal use. Please do not alter.

Overall Score Overall Score Order Management Quality Value & Support Delivery Performance

Source Specific Scores Q&A Slide Overall Score Order Management Quality Value & Support Delivery Performance

Overall 95.6% On-time Performance; Using 7 Day Lead-Time Delivery Performance Detail % On-time Talking Points Comments Percent On-time Overall 95.6% On-time Performance; Using 7 Day Lead-Time Poor Performers Overall Score Order Management Quality Value & Support Delivery Performance

X exceptions/ X PO lines Order Management Detail Exceptions Talking Points Comments Error Types Totals X exceptions/ X PO lines Overall Score Order Management Quality Value & Support Delivery Performance

Quality Detail Recalls Talking Points Comments Count 30 unique alerts received Score Each alert type is equally weighted, total divided by spend in $M Overall Score Order Management Quality Value & Support Delivery Performance

Q&A Slide