RE-ENGINEERED WORKFLOW IN THE AP LABORATORY: Costs and Benefits

1. RE-ENGINEERED WORKFLOW IN THE AP LABORATORY:Costs and Benefits Erin Grimm, MD Rodney Schmidt, MD, Ph.D University of Washington Medical Center Seattle, WA

2. Disclosures • The UW-developed software (PowerTrax and ePathImage) is licensed through the University of Washington. • The speakers have no relationship with IMPAC Medical Systems, owners of PowerPath, or any of the other mentioned companies.

3. Objectives Review current workflow in Anatomic Pathology and the need for change The UW Anatomic Pathology Automation Project A detailed look at each step Starting the automation process Building a business case Questions for the future

4. The scope of the problem Histology laboratory workflow has not changed in decades Yet Volumes increase Laboratories expand 1959 http://history.library.ucsf.edu/imagelib/med_sci_building_histology_lab_1959.gif

5. Problem #1 Inefficiencies exist that cause waste Waste increases expense Labor costs Poor resource utilization

6. Problem #2 Errors Happen Patient ID errors occur in AP 4.3 / 1000 surgical specimens1 1.9 / 1000 amended reports 19.2% of amended reports were due to patient ID errors2 • Makary MA et al. Surgical specimen identification errors…. Surgery 2007 Apr;141(4):450-5 • Nakhleh RE, et al. Amended reports … Q-probes study of 1,667,547 accessioned cases ... Arch Pathol Lab Med. 1998 Apr;122(4):303-9.

7. Achievable Error Rates To go from 1/1,0001/10,000 requires automation Resar RK. Making noncatastrophic health care processes more reliable... Health Serv Res. 2006; 41:1677-1689.

8. A Dilemma What if 1% of tests were errors and 6% of the errors led to inappropriate care? 40,000 surgical cases / yr 1% are erroneous 400 erroneous surgical cases / yr 6% inappropriate care 24 care problems / yr(> 2 cases/month)

9. Objectives Review current workflow in Anatomic Pathology and the need for change The UW Anatomic Pathology Automation Project A detailed look at each step Starting the automation process Building a business case Questions for the future

10. UWMC Pathology 178 Faculty Members 40 faculty with clinical duties 29 Residents and Clinical Fellows 35 Graduate Students $32 million in NIH grants (2006) • A complex academic environment with: • >36,000 surgical pathology cases/year

11. UW Goal for Automation Resident/PA dictates gross description (Gross Room) Resident/PA requests additional blocks (Gross Room) Stickers with labels applied (Histology) Case accessioned Signout Cassettes preprinted and placed with specimen (Gross Room) Slides pre- labeled by hand (Histology) Pathologist calls up case to enters diagnosis (Offices) = Opportunity for transcription error 1) Decrease mislabeling opportunities

12. UW Goal for Automation 2) Streamline Workflow Save Labor (FTEs) Automate manual processes Ex. Histology order completion, specimen discard, image uploads Make location/progress of all assets (specimens, blocks, slides, and paperwork) visible and trackable in the AP-LIS Eliminate preprinting/prelabeling Initial phase Start with projects having ↑ Yield ↓ Developer hrs

13. Staged UW Automation Clinical Database (75 hrs) • Gross room • Photography (80 hrs) • Specimen container • disposal (50 hrs) Slide tracking (1500 hrs) Whole line automation 2005 2006 2007 2008 Document scanning with imaging suite (150 hrs) New Clinical Database (400 hrs) Cassette barcoding (500 hrs?) Approximate developer hours noted for each project

14. Technical info Custom software was written as a Windows application using Microsoft Visual Studio C#.Net and SQL Server UW Clients PowerPath Client PC Thin Client PowerPath Database UW Database SQL Server

15. Staged UW Automation Clinical Database (75 hrs) • Gross room • Photography (80 hrs) • Specimen container • disposal (50 hrs) Slide tracking (1500 hrs) Whole line automation 2005 2006 2007 2008 Document scanning with imaging suite (150 hrs) New Clinical Database (400 hrs) Cassette barcoding (500 hrs?) Approximate developer hours noted for each project

16. Document Scanning Goal Develop an electronic document management system All case-related paperwork is viewable from the case specific repository in our AP-LIS Workflow Paperwork is barcoded when accessioned Scanner reads paperwork barcode Document is scanned, accepted by office staff, and automatically uploaded to the image tab of the AP-LIS

17. Scanning benefits Benefits: 3.8 hours/day saved for 26 pathologists and residents Staff satisfaction: 10.0/10 Saved 0.25 min/case Current usage: 10,614/month • Schmidt RA, et al. Integ. of scanned doc mangmt... Am J Clin Pathol. 2006 Nov;126(5):678-83 • Routbort M, Grimm E, Schmidt R. Optimized Document Management…. APIII 2006 Conference

18. Staged UW Automation Clinical Database (75 hrs) • Gross room • Photography (80 hrs) • Specimen container • disposal (50 hrs) Slide barcoding (1500 hrs) Whole line automation 2005 2006 2007 2008 Document scanning with imaging suite (150 hrs) New Clinical Database (400 hrs) Cassette barcoding (500 hrs?) Approximate developer hours noted for each project

19. Slide Tracking Goal: Provide real-time status and location of slides Benefits include: Providing real-time case progression information Easier location of slides for conference/sendouts Facilitates workflow analysis via time-stamps Drives AP-LIS functionality Automates histology order completion and other processes Name

20. Slide Tracking Workflow Histology Pathology Offices Sendouts Faculty signout File Room Pull for conference Resident review Histology work order completes with scanning Deliver Ship

21. Slide Tracking Benefits FTE Savings

22. Staged UW Automation Clinical Database (75 hrs) • Gross room • Photography (80 hrs) • Specimen container • disposal (50 hrs) Slide tracking (1500 hrs) Whole line automation 2005 2006 2007 2008 Document scanning with imaging suite (150 hrs) New Clinical Database (400 hrs) Cassette barcoding (500 hrs?) Approximate developer hours noted for each project

23. Gross Photography Gross photography • Photo is automatically imported into case-specific AP-LIS image tab Results • Improved Quality Focus 50.1%  77.8% • Quantity Increased 310 photo/mo  503/mo • Labor Savings • Resident/PA > 1 min/case by • Office Staff 1 FTE (bulk image upload) • IT help requests 1.7/mo  0.5/mo • Cost Savings • Eliminated cost of darkroom materials • Eliminated kodachrome storage

24. Specimen Discard Workflow Device scans specimen barcode Handheld device queries AP-LIS If case signout occurred <2wks prior If case signout occurred >2wks prior

25. Staged UW Automation Clinical Database (75 hrs) • Gross room • Photography (80 hrs) • Specimen container • disposal (50 hrs) Slide tracking (1500 hrs) Whole line automation 2005 2006 2007 2008 Document scanning with imaging suite (150 hrs) New Clinical Database (400 hrs) Cassette barcoding (500 hrs?) Approximate developer hours noted for each project

26. Cassette barcoding Goals: Streamline workflow Cassette barcode drives gross room and histology workflow Eliminate cassette preprinting Eliminates work for accessioners Eliminates an error-prone step Enable resident/PA to obtain cassettes without interruptions Photo Courtesy of General Data

27. Objectives Review current workflow in Anatomic Pathology and the need for change The UW Anatomic Pathology Automation Project A detailed look at each step Starting the automation process The business case The issues Questions for the future

28. The Business Case Efficiency More volume with same personnel $2.50 - $3.00/case (slides, specimens) Patient safety Optimize patient care Prevent rare, catastrophic errors Compliance Custodial responsibility for patient materials (paperwork, slides, blocks, etc).

29. Buy vs. Build Decision • “Buy” is now possible • Some LIS vendors (IMPAC, CoPath, et al) • Others (RA Lamb, Dako, Ventana, UW) • Others in development • Most are expensive (S/W and H/W) • No current product is comprehensive

30. Hardware • Label printers – inexpensive • Bar-code readers – inexpensive • Cassette printers – expensive (most) • Slide printers – expensive For distributed JIT workflow, we need “personal” cassette printers and slide printers that are as inexpensive, reliable, and ubiquitous as label printers.

31. Key Considerations This is disruptive technology! Use automation to change habits (prelabeling/preprinting) Don’t automate bad workflow Each user must benefit Select carefully Hardware compatibility Software compatibility Appropriate technology/solution

32. Questions Where are the boundaries for the AP-LIS? Who provides bar-coding solutions? Major automation providers are not AP-LIS vendors (Dako, Ventana, RA Lamb, UW) • Implicit challenge to LIS vendor “lock-in” • Reporting/billing in one app • Lab/material handling in different app

33. Questions Where are the boundaries for the AP-LIS? What will be tracked? • Traditional: Specimens, blocks, slides • New derivatives: Cells, DNA, tissue banks, ancillary labs, biorepositories • Pre-lab tracking: From OR, offices • Reduce ID (pre-analytic) errors

34. Questions How much of the financial benefits will labs be able to retain? • Hardware? • Implementation? • Software? • Purchase/support pricing model • Per-item metering

35. Conclusions Bar-coding automation More than just tracking – disruptive technology! Workflow changes. Allows processing of increased workloads with static FTE levels Improves patient safety Quantifiable gains can be made by upgrading the most inefficient/error prone processes in your laboratory

36. Thank you UW development team UW Program Operations Manager Dan Luff Erin Grimm, MD grimme@u.washington.edu Rodney Schmidt, MD, Ph.D schmidtr@u.washington.edu

38. Questions for the Future What materials will be tracked? When does tracking start? Traditional materials: specimen/blocks/slides More specimen derivatives arise: ancillary lab tests, tissue banking, biorepositories ?? Will there be introduction of prelab tracking to reduce preanalytical errors No current product is comprehensive