Sanctions Analyzer EPLS/CMS Integration
Sanctions Analyzer Big Picture • • • •
System Design EPLS Interface OIG Interface Why Build the Tool?
System Design • All source data to be matched is extracted automatically from our source systems. – Personnel (from HR system) – Physician/Clinician (from clinical system) – Vendors (from materials/financial system)
• EPLS/CMS/OIG • Matching • Presentation
Process Flow Personnel D ata
Physician D ata
Vendor D ata Match Analysis by C ompliance Office Personnel
C ompare to EPLS D ata
C ompare to OIG D ata Matched U sing First and Last N ame
Matched U sing First and Last N ame
R ecord information regarding matches made w ith system
Match C omparison using SSN (w here available )
Facility Level R ecording of Matches made using Systemized process D isplay of Matches from EPLS and OIG
EPLS COMPARISONS • EPLS/CMS Comparisons – First and Last Name (Personnel) – First and Last Names (Physician/Clinician) – Vendor Name – First 15 Characters of Vendor Name – Web Service Utilization (EPLS) – Process Automated for “Rough Matching”
EPLS Web Service Reporting • • • • • •
Publicly and Freely Available Tool Data Stored in System as to Match Retrieve XML for matches for Analysis Match Type and Sanctioning Agency Personnel Identifying Data for Matches Physician Numbering (NPI)
EPLS Web Service Reporting • “Rough Match” = Potential Match which needs to be investigated further • Clear matches based on SSN/ID Material • EPLS SSN Data Conclusive/Inconclusive – SSN Data is Hit or Miss on EPLS – Human Checking of EPLS SSN Matches
• Shortening Analysts Time Demands
EPLS Web Service
EPLS Web Service
EPLS Information •
https://www.epls.gov/EPLS%20Public%20Users%20Manual.pdf
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The EPLS Search Web Service is accessible over the Internet, and the EPLS Search Web Service Definition Language (WSDL) specification may be found at: • http://www.epls.gov/epls/services/EPLSSearchWebService?wsdl •
Assistance at GSA Federal Service Desk https://www.fsd.gov/
OIG Matching • • • • • • •
Download data from web Store OIG Data in SQL Database “Rough Matches” developed Match First and Last Name Match Vendor Name Match First 15 Characters of Vendor Name Process is internal only no web service
OIG Matching • • • •
OIG Matches presented Human interface for matches Clear matches based on SSN/ID Material Store Information regarding match
Benefits • Recording Match Yes/No Decisions • System automates “Rough Matches” • Analysts focus only on matches not entire population of Covenant Health • Web based interface • Focus on completion of monthly tasking • Storage of commentary
Benefits • • • • • •
Reduce Analysts Time Commitment Reduce Redundant Checks Reduce FTEs required to complete checks Records who completed check Recordable proof of compliance checks Reduction Equals Dollars
Sanctions Analyzer Summation • • • • • •
“Rough Matches” SSN Matches Provide Rough Matches to Users Human checking of Matches Match cleared - Revisit New Matches Reporting via Email
WEBSITE LINKS http://www.covenanthealth.com/ https://www.epls.gov/ https://www.epls.gov/epls/search.do http://oig.hhs.gov/exclusions/exclusions_list.asp