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PERC: Envisioning the Next Generation of EPath NAACCR Annual Meeting June 10, 2008, Denver Jennifer Seiffert, MLIS, CTR, Northrop Grumman Contractor to.

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Presentation on theme: "PERC: Envisioning the Next Generation of EPath NAACCR Annual Meeting June 10, 2008, Denver Jennifer Seiffert, MLIS, CTR, Northrop Grumman Contractor to."— Presentation transcript:

1 PERC: Envisioning the Next Generation of EPath NAACCR Annual Meeting June 10, 2008, Denver Jennifer Seiffert, MLIS, CTR, Northrop Grumman Contractor to NPCR, CDC jenesei@comcast.net Joseph Rogers, NPCR, CDC jdr0@cdc.gov

2 Outline PERC History PERC Members PERC Goals Project Vision Cancer Care Ontario Activities

3 Note Presentation will emphasize Collaborative Staging (CS) because that is my role on PERC

4 History (1) PERT (Pathology Electronic Reporting Task Force) established in 2007 PERT grew out of several prior activities: –SNOMED Surgical Pathology Working Group Reviewed and updated the SNOMED Anatomic Pathology subset (took over a year) –College of American Pathologists (CAP) Cancer Committee

5 History (2) In 2008, PERT was upgraded to PERC –A full Committee of CAP –Reports to SNOMED STS [SNOMED Terminology Solutions] Oversight Committee

6 History (3) PERC has established two subcommittees: –Data Modeling (back end) group for modeling how CAP checklist data can best be collected electronically, interoperably, and mapped to other standards, including CS Includes CS and NAACCR representatives –User Interface (UI) (front end) group for modeling interface for pathologists entering checklist data electronically

7 History (4) Priority being given to UI work, getting standardized electronic checklists to pathologists and LIS vendors ASAP Decision has been made, for current work, to –Include mapping to CS for items with one-to-one non-algorithmic maps –Postpone mapping to CS items requiring reference to multiple data items or algorithms to 2nd phase of project after easy mappings done

8 PERC Members May 2008 John Madden, MD, PhD Co-Chair Duke University Monica de Baca, MD, Co-Chair Physicians Laboratory George Birdsong, MD Emory University Kenneth Gerlach, MPH, CTR CDC/NPCR Lori Havener, CTR NAACCR Mary Kennedy, MPH CAP Robert Knapp, MD Pathology Laboratory, P.C. Gemma Lee Cancer Care Ontario Andrea MacLean Cancer Care Ontario Richard Moldwin, MD,PhD CAP Douglas Murphy CAP Wendy Scharber, RHIT, CTR Registry Widgets Jennifer Seiffert, MLIS, CTR Collaborative Staging Mike Smith, MD CAP James Sorace, MD, MS ASPE, HHS Henry Travers, MD President, WASPaLM

9 PERC Goals (1) To advance the computerized representation of the CAP checklists –Create FRAMEWORK for electronic forms (standardized input) data repositories (retrievable output) –Ensure electronic versions accurately represent the CAP Cancer Committee’s intended meaning

10 PERC Goals (2) To create an electronic representation of the CAP Cancer Protocol checklists which –Is aligned with (upcoming) AJCC and Collaborative Staging Systems. –Allows for historical representation –Is amply designed for addition of medical specialties, coding, and/or staging systems

11 Project Vision (1) CAP provides software tools for computerized implementations of cancer checklists Path labs and vendors implement standardized checklist templates for synoptic cancer reports as part of full path reports

12 Project Vision (2) Central cancer registries receive standardized synoptic ePath and can automatically populate standard NAACCR items, including CS Registries consolidate ePath with other reports (clinical, demographic)

13 Aspects of Framework (1) Software application and database for creating and distributing computerized checklists Written specifically for PERC work Enables automated data capture Provides mapping to other standards incl. SNOMED, NAACCR, CS Facilitates reuse of data for CS, research, caBig, tissue banking, etc. Template Editor

14 Aspects of Framework (2) Consistency across checklists to improve accuracy. Examples: vascular invasion and lymphatic invasion standardized to “lymph/vascular invasion” mitotic activity vs. mitotic count tumor configuration vs. tumor features Standardizing “flavors of null” (indeterminate, no data, not reported, etc.)

15 Aspects of Framework (3) Use appropriate dialog controls to improve accuracy Choose one: o Squamous cell carcinoma o Adenocarcinoma o Large cell carcinoma o Small cell carcinoma Choose as many as apply:  Embryonal carcinoma  Choriocarcinoma  Yolk sac tumor  Teratoma Group of Radio ButtonsCheck Boxes

16 Aspects of Framework (4) ___ Tumor 2cm or less without extra-parenchymal extension (T1). ___ Tumor 2cm but not more than 4cm without extracapsular extension (T2). ___ Tumor more than 4 cm and/or tumor having extra- parenchymal extension (T3). Tumor size: _______ cm Extraparenchymal extension Positive Negative Indeterminate Increased Atomicity Current Checklist FormatPossible modification CS algorithm could derive pT.

17 Aspects of Framework (5) ___ Cannot be assessed ___ Benign glands at surgical margin _X_ Margins uninvolved by invasive CA ___ Margin(s) involved by invasive CA ___ Unifocal ___ Multifocal ___ Apical ___ Bladder neck ___ Anterior ___ Lateral ___ Postero-lateral ___ Posterior ___ Other(s) (specify): ___ Cannot be assessed ___ Benign glands at surgical margin ___ Margins uninvolved by invasive CA _X_ Margin(s) involved by invasive CA ___ Unifocal _X__ Multifocal ___ Apical _X_ Bladder neck ___ Anterior _X_ Lateral ___ Postero-lateral ___ Posterior ___ Other(s) (specify): Context Sensitivity

18 NPCR’s Goal Increase quality of cancer surveillance data and efficiency of collection by increasing use of CAP checklists and synoptic reporting –How? Make them easier to use by pathologists, lab system vendors, registries

19 Project Vision Review(1) CAP provides software tools for computerized implementations of cancer checklists Path labs and vendors implement standardized checklist templates for synoptic cancer reports as part of full path reports

20 Project Vision Review (2) Central cancer registries receive standardized synoptic ePath and can automatically populate standard NAACCR items, including CS Registries consolidate ePath with other reports (clinical, demographic)

21 PERC Activities for 2008 Weekly teleconferences of each subgroup Goal to have model electronic data entry forms for selected checklists published in 2008, using TNM 6 th ed., for pathologists and LIS vendors to begin implementing Will probably recommend simple interim database approach for LIS vendors— limited mapping

22 Sample Early Draft Prototype of Lung Electronic Checklist Check boxes Optionality Radio buttons

23 Lung Draft Prototype Detail Pathologist checks all that apply Choices are nested, grouped 45 20 70 60 5540 70 75 56 70 65 45 60 71 Mapping to CS Extension available behind the scenes Database can be built behind the scenes Algorithm needed for combinations checked.

24 Cancer Care Ontario Activities Real-world test of some of the PERC concepts –90% of path reports in province of Ontario are received electronically –Modified CAP/CS aligned checklists implemented in participating hospitals –Central registry will capture CS items from synoptic reports mapped to CS and derive stage –Feasibility and accuracy will be assessed –Also testing a computerized path requisition form for surgeons to complete

25 Cancer Care Ontario Activities Collaborative Staging Colorectal Pilot Project. –Modified front end of checklist to align w/CS. –Pathologists complete checklist, data are extracted from hospital information system, CCO coders supplement staging data w/radiology, surgery and clinical info Other Sites to come: breast, lung, prostate, endometrium eSurgery and eRadiology feasibility assessment underway

26 Issues from Cancer Care Ontario (1) Multiple path reports on same patient/tumor –Need guidelines for pathologists—registry would prefer separate synoptic report for each reportable tumor –Need guidelines for registries, consolidating multiple reports from multiple specimens –Need to determine if reports pertain to stage AT DIAGNOSIS

27 Issues from Cancer Care Ontario (2) Determining which lab results to capture from multiple tests for SSFs/tumor markers Can algorithm be written to select the appropriate test results from lab information system? –Usually need highest value prior to treatment –Rules are site- and test-specific

28 Information about CDC’s Cancer Prevention & Control Programs www.cdc.gov/cancer The findings and conclusions in this presentation are those of the presenter, and do not necessarily represent the views of the Centers for Disease Control and Prevention.


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