HL7 MITA Data Analytics Sub-workgroup Out of Cycle HL7 WGM, 19 May, 2009, St. Paul, MN

1. HL7 MITA Data Analytics Sub-workgroup Out of Cycle HL7 WGM, 19 May, 2009, St. Paul, MN HealthLevel7

2. Presentation Overview • The Beginning – HL7 May 2008 • Progression Pre-Data Analytics - May 2008 until October 2008 • Progression Since Data Analytics – October 2008 to now • Data Analytics Artifacts to date • Next Steps • Lessons Learned (to date)

3. The Beginning – HL7 May 2008 • FM HL7 MITA Project kicked off in January 2008 at HL7 • Focus on Enroll Provider • No clear direction on how to proceed • HL7 May 2008 (Phoenix) – CAQH provides hundreds of data elements from its Universal Provider Database the (UPD) for the HL7 MITA Project – several states already use the UPD for credentialing • Volunteers from California Medicaid and Kansas Medicaid participating at the HL7 May 2008 meeting begin reviewing the CAQH UPD data elements for applicability to Medicaid. No data elements were removed, but many were added (final total over 1,000 data elements) • The HL7 MITA Project decided to seek feedback from the rest of the Medicaid community via NMEH and willing MMIS vendors.

4. Progression Pre-Data Analytics - May 2008 until October 2008 • Feedback from the document created at HL7 May 2008 was limited. Only a handful of states responded directly (CA, NM, SC, TX, VA). Feedback from MMIS vendors provided additional input. • No process was dictated in order move forward from that point. Minimal work was done to evaluate the state and vendor feedback. • HL7 MITA was still operating as one large group until the HL7 MITA meetings at the 2008 MMIS Conference (September). • A need to establish sub-workgroups in the HL7 MITA Project was established as critical to move forward with creating the artifacts necessary to ballot Enroll Provider. • Time from between the MMIS Conference until November 2008 focused on governance and the business process analysis of Enroll Provider. Some minor progress was made on the data elements worksheet.

5. Progression Since Data Analytics – October 2008 to now • Defining the Data Analytics Workgroup – officially approved at the HL7 January 2009 Workgroup Meeting • Posted in-progress artifacts to the MITA Wiki: http://mita.wikispaces.com/ • Meetings have been scheduled to occur weekly; actual experience has been slightly less. • The work on the spreadsheet has expanded substantially to define content, identify conceptual classes, incorporate modeling and business process work • A database has been established to facilitate analysis and communication to other groups • The Data Analytics artifacts have been compared against the HDF for alignment

6. Data Analytics Artifacts to date • HL7_MITA_Provider_Enrollment_Data_Analysis_v0_5a.xls • Aligns functionally to “Information Model Analysis” and “Glossary of Classes and Attributes” artifacts from the HDF • Attribute/class associations, attribute descriptions, comments for follow-up • Conceptual class descriptions, comments for follow up • Message inventory and descriptions • Message class identification • HL7 MITA Prov Enroll.mdb • Incorporates content of the Excel spreadsheet into a coherent database • Provides flexibility to add data content over time and re-use • Can use to show class relationships not possible in Excel • Hope to use to extend into Modeling and Vocabulary work.

7. Data Analytics Artifacts to date • Provider data statements V0.4.doc • A slightly more business-friendly abstraction of data analysis • Includes assumptions associated with the particular data analysis • Infers some “parent-child” relationships among classes • Some class optionality and cardinality statements included as a result of use of text descriptions, but not absolute • Provider Information Groups v1 markup.vsd • An early non-UML start at a logical data model • Color coding intended to reflect some relationships • A UML-based version (with no color) also available (not currently on wiki)

8. Next Steps • Complete class descriptions • Complete message descriptions • Review PDS Overview for class relationships • Establish class relationships • Establish class cardinality and optionality • Align classes and messages (re-examine cardinality and optionality) • Find classes to adopt “orphan” attributes • Identify “super-classes” that may need decomposition • Establish attribute cardinality, optionality, and data type • Move to complete Provider Management domain and Member Management data analysis

9. Lessons Learned • Start with identifying classes, worry about attributes much later • Work with modeling facilitator to get conceptual data model started much sooner • Have a harmonization session early on to gather intended messages/interactions that require data • Don’t worry too hard about HL7 alignment until the conceptual has gone through at least one round of review OR the business analyst driving the work is very experienced in HL7 • More participants are needed to go away and come back with iterations of data analytics work

10. Thank You Thank you to everyone that has participated in the Data Analytics Sub-workgroup so far; we encourage more people to share their knowledge and skills to move the group forward.