1. SEER Auto-Consolidation Workgroup
Bobbi Jo Matt, BS, CTR, RHIT
NAACCR Annual Meeting
June 11, 2019

2. Objectives Goals Workflow/Process Accomplishments Work in Progress
Questions

3. The Workgroup Formed May 2017
Participants from SEER registries, NCI and IMS
Meets monthly via a Web call

4. Workgroup Goals
To develop a standardized process to identify tumor related data fields for potential auto-consolidation
To create and test standardized auto-consolidation logic for each data field
To define and develop a standard interpretation of the data item rules

6. The Process STEP 1: Select data items for potential auto-consolidation
Reporting Source selected
STEP 2: Identify all coding instructions applicable to consolidating the data item (Reference: SEER – STORE – AJCC – NAACCR)
Priority order for codes -> 1, 2, 8, 4, 3, 5, 6, 7
STEP 3: Identify any data items that may be used in the manual decision-making process
Class of Case

7. The Process cont.
STEP 4: Develop logic to identify the best value from the source records
Information from step 2 & 3 incorporated into logic
The priority order for codes
Class of Case
Example: Comparing Reporting Source field
If incoming record has value of ‘1’ -> a value of 1 will overwrite ‘2’ unless the ‘2’ is coming from analytic source and ‘1’ is coming from non-analytic source

8. The Process cont. STEP 5: Develop methods to test logic
STEP 6: Conduct test
Executed across all registries
Use manually consolidated data as the “gold standard” to:
Identify weaknesses in proposed logic
Shows ambiguity in guidelines

9. The Process cont. STEP 7: Analyze results
Did the auto-consolidated value match the manually consolidate value?
Did the logic correctly identify the correct source record value – manual review missed?
STEP 8: Make adjustments based on analysis
Source records don’t have data field under review
DCO’s vs MDO’s

10. The Process cont. STEP 9: Re-Test (Step 6) STEP 10: Implementation
Registry specific decision
Timing
Customize logic or Opt out
Type of Reporting Source
All registry’s choice to just do based on priority order and run on new cases

12. Accomplishments Implemented into SEER*DMS Diagnostic Confirmation
Type of Reporting Source
Implemented into SEER*DMS
Diagnostic Confirmation
Logic developed & Analyzed
IMS testing and should be in production soon
Determined further training is needed for Heme/Lymph tumors
Lymph Vascular Invasion (LVI)
Logic developed
IMS testing in progress

13. Accomplishments cont.
Implemented automated solution to select known over unknown values
2018 SSDI’s
Mets at Diagnosis (6 data fields)
Marital Status at Diagnosis
Primary Payer at Diagnosis
Developed priority list for drafting automation logic for required data fields
Grouped data fields together

14. In Progress Develop logic for Known over Known:
Marital Status at Diagnosis
Primary Payer at Diagnosis
Mets at Diagnosis (6 data fields)

15. Discussion Topics Class of Case Trust in the Source Record
Used frequently in consolidating
Not required by all standard setters
Not consistently coded
Trust in the Source Record
While an abstract may pass edits, there may be inconsistencies within the abstract that are not identified by edits
Inconsistencies, unless corrected, may inadvertently be selected as the correct code during auto-consolidation

16. Source Record Validation - Sub-Workgroup
Created in response to the discussion on trust in the source record
Purpose is to develop logic for ensuring the source records are accurate
Participants are the same as Auto-Consolidation workgroup
Group meets every other month (alternating with Auto- Consolidation workgroup)

17. Source Record Validation - Goals
Phase 1
Define a minimal set of edits for source records (beyond existing record edits)
Define strategies for handling fields with coding errors and/or edit failures

18. Source Record Validation - Goals cont.
Phase 2
Concurrent with defining auto-consolidation logic, run queries to evaluate common issues in the data items used as input to the logic
Identify global fixes for data items (as appropriate)
Define rules for targeted visual editing
Discuss development of a workflow to reject records with errors and/or provide feedback to registries

19. Source Record Validation – Future topics
Determining how Class of Case is used and what role it plays in auto-consolidation
Data items from new data sources in regards to consolidation
Claims
Pharmacy
etc.

20. Auto-Consolidate Workgroup
Linda Coyle, IMS
Suzanne Adams, IMS
Frances Ross, CTR, Kentucky
Cheryl Moody, BA, CTR, California
Kacey Wigren, CTR, RHIT, Utah