A CENTRAL REGISTRY RELIABILITY STUDY
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1 A CENTRAL REGISTRY RELIABILITY STUDY Visual Editor TNM & Summary Stage Staging Skill Assessment Donna M. Hansen, CTR Auditor & Education Training Coordinator California Cancer Registry NAACCR June 16, 2016
2 2 Outline California Cancer Registry Study Rationale & Goals Study Design Reports & Dissemination of Results Study Results Analyses of Results Education Conclusions Next Steps
3 3 California Cancer Registry (CCR) & Our Regional Registries CalCARES California Cancer Registry kkkkkkk Cancer Prevention Institute of California Region 1/8 SEER Cancer Registry of Greater California Regions 2,3,4,5,6,7,10 SEER Cancer Surveillance Program Los Angeles Region 9 SEER CalCARES partners with California Department of Public Health (CDPH) to manage the operations of the state mandated California Cancer Registry (CCR)
4 4 Study Rationale Visual Editors (VE) on the front line Provide feedback to state registrars on TNM coding Some VE without any prior TNM experience Others, experience long ago Instructions for registry coding of AJCC TNM stage changing VE s expressed confidence in skills -not high
5 5 Assess TNM knowledge Study Goal Regional Registry Visual Editors Identify knowledge gaps Provide focused TNM Education Improve skills and boost confidence Visual Editors statewide were requested to participate Assess Summary Stage 2000 for same TNM cases
6 6 Pre-Study Requirements Each participant to complete AJCC Training materials: Registrar s Guide to Chapter One Explaining Blanks and X, Ambiguous Terminology and Support for AJCC Staging Completion of AJCC Curriculum Modules I-IV
7 7 Study Design- Eureka DMS Study designed to utilize Eureka DMS California Cancer Registry Data Management System Design included ability to: Populate Study Cases with Text Information Assign Cases to Individual Participants Receive Completed Cases Generate Reports for Analysis Timeline Module Development Collaboration CTR & Programmer Team Aug/Sept 2015 Testing in October 2015 Module went live November 2015
8 8 Study Design- Cases Scenarios 12 Case scenario s specially selected: Maximized TNM assessment and teaching value Understanding of AJCC rules Understanding on use of blanks, 88s and 99 Assess Summary Stage coding
9 9 Eureka Reliability Study Screen Populates Study Answers Study Coordinator populates case scenario text
10 10 Assigning Cases Define Testing Date Range Assign Users for study Assign cases to participants Test Title 6/1/16 6/30/16 User Names Hidden
11 11 Example: Participant Case List Screen Participant Case List Participant Name
12 12 Populated Case Scenario Screen Case scenario s visually mimic view normally seen in VE process Participant Reviews text Directly Enters TNM and Summary Stage Saves case as complete
13 13 Software Reports Reports developed to calculate discrepancies & accuracy by: Individual data item Individual case Individual Participant Each Region Statewide overall
14 14 Software Reports How Results Counted/Calculated Total Participants = 23 Total Cases = 12 Total Items per case = data items for each TNM case 230 errors possible per data item 2300 overall X 23 participants x 12 cases 1 data item for each Summary Stage case 276 errors possible overall x 23 participants x 12 cases Total Errors (Total Cases x Total Items per Case) x 100 = Percentage of errors
15 15 Software Reports Example Individual Results Pink cell indicates incorrect answer Overall 85.60%
16 16 Example Regional Report Software Reports
17 17 Individual Participant Dissemination of Results Personal Accuracy TNM Summary Stage Overall Regional Registry Management Results Specific to Region UCD Management CDPH Management Statewide and Regional Results
18 Study Results Distribution of Errors by TNM Category Clinical vs Pathologic (38%) Number/Percent of Errors (11%) n=230 Total Possible Errors per TNM category 38 (17%) 38 (17%) 51 (22%) 67 (29%) 60 (26%) 74 (32%) % Clin T Clin N Clin M Clin Stage Grp Clin Descrip Path T Path N Path M Path Stage Grp 7 (3%) Path Descripitor 42% TNM Category 58%
19 % Study Results TNM Stage Accuracy by Case All Regions Combined 95.00% 90.00% 85.00% 87.83% 90.00% 88.70% 86.09% 86.53% 93.92% 91.31% 90.00% Percent Accuracy 80.00% 75.00% 70.00% 76.09% 79.57% 73.52% 65.00% 60.00% 62.18% 55.00% 50.00% Study Cases
20 20 120% Study Results Summary Stage Accuracy by Case All Regions Combined 100% 100% 95.66% 93.75% 100% 100% 100% 91.31% 91.31% 82.61% 82.61% 82.61% 80% percentage accuracy 60% 40% 52.18% 20% 0% #1 Breast #2 Breast #3 Bladder #4 Colon #5 Endomet #6 Bladder #7 Prostate #8 Kidney #9 Prostate #10 Breast #11 Lung #12 Brain Study Cases
21 21 Study Results TNM Reliability Study Overall Accuracy 449 / 19.52% All Regions combined Accuracy 80.48% 1851 / 80.48% TNM Correct TNM Errors n=2300
22 22 Study Results Reliability Study Summary Stage Overall Accuracy 31/11.30% All Regions Combined 88.41% 245/ 88.41% Summary Stage Correct Summary Stage Errors n=276
23 23 Study Results 94% 92% Comparison TNM & SS2000 Accuracy by Region 93% 90% 90% 88% 88% 86% 85% 84% 83% 82% 81% 80% 78% 76% 74% Region A Region B Region C TNM SS2000
24 24 Two Types of Errors: Coding Errors Analyses of Results Selection of incorrect AJCC TNM category (value) Assigned X when a valid TNM category available Descriptor error Incorrect assignment of M Data Entry Errors Non-use/incorrect use of blanks, 88, 99 to reflect stage in registry data fields
25 25 Analyses of Results 500 Types of TNM Errors Number of Errors % 52% All Errors Coding Errors Data Entry Errors
26 26 Analyses of Results Coding Errors = 48% Result of: Incorrect understanding of some AJCC principals Rules for classification Use of clinical info in path stage Assessment/timeframe rules for M assignment Tumor size errors-converting cm to mm Incorrect use of X AJCC T, N & M tables some layout differences between chapters TNM Subcategories not used when applicable Used incorrect TNM Subcategory Special AJCC rules for some circumstances Differ from general rules
27 27 Data Entry Errors = 52% Analyses of Results Modifications required for stage entry in registry fields Record layout does not allow AJCC stage composition entry Requires use of blanks in some scenarios Errors due to unclear understanding on when/how to use blanks to represent AJCC Stage in record layout. Use of 88 s when TNM not defined by AJCC Stage group 99. AJCC rules and other Standard Setter rules differ
28 28 Analyses of Results TNM Adjusted Accuracy IF Data Entry Errors Non-Existent Accuracy with Coding Errors Only 0/(orig 230) 219(9.5%) Adjusted Accuracy 90.50% 2081/(orig 1851) n=2300 TNM Correct Coding Errors Data Entry Errors
29 29 Identified Education Needs Clarification and training needed on: How to use blanks to represent an implied value in data entry How/when to use blanks when Info unknown or rules for classification not met How/when to use 88 s or 99 Correct way to use clinical information in pathologic stage Review of the M Rules Assessment method Timeframe How to represent AJCC stage composition in record layout 7 th Edition Manual Review Chapter specific rules Rules for Classification Surgical treatment and Pathologic stage TNM Subcategories clinical vs pathologic Summary Stage vs TNM Different rules Can t convert
30 30 Education Provided Education presentation developed Presented in person at regional offices or via live webinar Included: Overall Results- all regions combined. Customized regional results contrasted to overall results.
31 31 Education Provided Education included: Detailed Answer Key for each case AJCC Stage Composition AJCC Staging Rationale Data entry examples and rationale AJCC Curriculum Modules-where to find supporting info AJCC Manual-where to find rules/info Review of TNM rules for classification Special Rules situations Correct use of X, Blank, 88 or 99 with examples Summary Stage Answers & differences with TNM TNM Tips VE Tips Q&A s
32 Education Example 32 Case # 2 Breast Invasive tumor on Bx, no residual tumor on resection AJCC Stage Data Entry T N M Stage Group T N M Stage Group Clin ct1c cn0 cm0 IA Path pt1c pn0 cm0 IA Path T included clinical info Clin 1C 0 0 1A Path 1C 0 1A pm left blank to indicate implied value of cm0 to correctly represent stage in record layout Tip: Use the clinical tumor size info in this case (ct1c) which is assigned as a pt because path rules for classification were met by the definitive tumor resection. Case is not pt0 because we can incorporate the clinical ct1c info per AJCC rules. See AJCC Module II, Lesson 8, Slides 5,6,7
33 33 Education Provided Further Education provided: During timeframe of study, new values released by AJCC for TNM Additional education was provided to VE New 2016 allowable values for TNM categories reviewed Rationale for c & p prefixes Multiple Examples/Case scenario s Compared 2015 TNM stage/data entry to 2015 TNM stage/data entry Post study education continues
34 Education Example 2016 cases 34 For an in situ tumor: Bx DCIS & Surgery DCIS Correct stage composition now possible Breast/AJCC Stage Clin: ptis, cn0, cm0, Stage 0 Path: ptis, cn0, cm0, Stage 0 T N M Stage Group ptis Clin Path IS cn0 cm0 0 Must use blanks to correctly represent stage in record layout 2015 vs 2016 Data Entry Special In situ rule per AJCC pg. 12, table 1.8 T N M Stage Group Clin pis c0 c0 0 Path pis c0 c0 0 ptis, cn0, cm0 no longer blank - have values to complete correct clinical & path stage composition
35 35 TNM Reliability Study Met Established Goals Conclusions Assessment of Regional Registry VE skills TNM coding TNM data entry Summary Stage coding Identified Areas to Focus Education Increased understanding of TNM, Summary Stage principals Improved understanding of Registry Data Entry Boosted confidence of VE staff
36 36 Eureka DMS Conclusions Enhancement & Customizations possible Meet evolving registry needs Programmer & CTR Collaboration Successful Reliability Study Effective Education Tool
37 37 Next Steps Reliability Study Phase 2 Retest with new cases Using 2016 allowable values Timeline Goal Summer/Fall 2016 Compare results Phase I/Phase II Determine additional training needs
38 38 Acknowledgement Ghenadie Ciornii, BSIT, CPBI Bachelor of Science, IT Certified Professional Business Intelligence Programmer/Analyst California Cancer Registry UC Davis Institute of Population Health
39 39 Contact Info Donna M. Hansen, CTR Auditor & Education Training Coordinator California Cancer Registry UC Davis Institute of Population Health
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