MDM Optimization

Your master data is dynamic and your data sources are changing and expanding. MDM Optimization will proactively analyze the impact of new data sources and growing data volumes on your master data accuracy.

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IMT’s MDM Optimization applies over 20 years of implementation knowledge and proven best practices to deliver immediate results.

Our expert team works with your data experts in an efficient and collaborative process to ensure improved match accuracy and reduced stewardship effort.

This interactive and iterative process examines the quality and composition of record matches to establish more precise task management and linkages for the data in your environment. By improving MDM’s ability to automatically match/link records, future task volume and manual resolution efforts are significantly reduced.

Proactively analyze the impact of data changes and new sources on your master data

New sources

Geographic
expansion

Data composition
changes

We use the client registry to review all the different source system records that come in, and assemble them into one patient view. We work hand in hand with each source on their data quality, and the things they can’t do for themselves. we point out their issues and work with them to resolve duplicates and create linkages across sources.

Advent Health reduced data stewardship task volume by 60% with MDM Optimization.

The Enterprise Master Person Index has been invaluable in linking our various computer applications together to ensure all person data is matched across our enterprise. It is the heart of our patient portal which allows patients to locate all their information regardless of which system it is in.

MDM Optimization Reduces Task Volumes for Large US Healthcare System

A large US healthcare organization with more than 150 hospitals and 2000 care delivery sites improved match accuracy and reduced task volumes by 62% for a highly integrated, high volume EMPI with IMT’s MDM Optimization Services. Learn more about how IMT performed thorough analysis against real data to measure the benefits and impact of optimization prior to implementation.

How It Works

Proven statistical techniques are applied against automated and clerical review thresholds.

Business and technical users evaluate pair-wise comparisons generated from pattern analysis of new and existing weights and algorithms.

New thresholds leverage past stewardship decisions to reduce current and future task volumes.

Assess the impact of new data sources to mitigate false positives before data is loaded.

IMT MDM Optimization Enables Your
MDM Program to be

Optimized

Recommends adjustments to false positive filters, weights, and thresholds

Reliable

Decreases the chance of human errors and increases quality of decisions

Intelligent

Leverages historical data resolution outcomes from stewards for future decisions

Transparent

Know why and how a task was generated for future auditing or research

Modernized

Takes advantage of new standardization and comparison functions for enhanced match accuracy

Automated

Recommends auto-resolution of tasks based on analysis of existing outcomes

Resources

Case Study

Extending The Enterprise ID with IMT Threshold Analysis™

AdventHealth streamlined their EMPI extending a “Know Me” commitment and their promise to help people feel whole: body, mind and spirit.

Blog

How to Enrich your Data in IBM MDM SE

After successfully implementing the IBM InfoSphere Master Data Management solution, our customers start to use the master data for person identification and matching across the enterprise. This is typically coupled with adding new types of data sources that contribute to their master data sets. But that can make linking more challenging, as each source varies in completeness and correctness.

Case Study

IMT MDM Optimization Reduces Task Volumes for Large US Healthcare System

IMT helps Large US organization with highly integrated, high volume EMPI improve accuracy and reduce task volume by 62%.

Blog

Ready to Apply the ProjectUS@ Address Standardization Recommendations?

How to improve address data for better patient matching and data exchange – per ONC Recommendations

Fact Sheets

Threshold Analysis and Algorithm Optimization

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Ready to learn more? Find out how MDM Optimization can help you improve data quality, prepare for new sources, and reduce current and future task volumes.

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