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

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Presentation on theme: "RE-ENGINEERED WORKFLOW IN THE AP LABORATORY: Costs and Benefits Erin Grimm, MD Rodney Schmidt, MD, Ph.D University of Washington Medical Center Seattle,"— Presentation transcript:

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 1.Review current workflow in Anatomic Pathology and the need for change 2.The UW Anatomic Pathology Automation Project A detailed look at each stepA detailed look at each step 3.Starting the automation process Building a business caseBuilding a business case 4.Questions for the future

4 The scope of the problem Histology laboratory workflow has not changed in decades Yet Volumes increaseVolumes increase Laboratories expandLaboratories expand uilding_histology_lab_1959.gif 1959

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

6 Problem #2 Errors Happen Patient ID errors occur in APPatient ID errors occur in AP 4.3 / 1000 surgical specimens 14.3 / 1000 surgical specimens / 1000 amended reports1.9 / 1000 amended reports 19.2% of amended reports were due to patient ID errors 219.2% of amended reports were due to patient ID errors 2 1.Makary MA et al. Surgical specimen identification errors…. Surgery 2007 Apr;141(4): Nakhleh RE, et al. Amended reports … Q-probes study of 1,667,547 accessioned cases... Arch Pathol Lab Med Apr;122(4):303-9.

7 Error rates Error Prevention Methods Real world Examples 1/100 Clear process Reliance on education/vigilance Errors filling out lab requisition Failure to give results to patients Suboptimal specimen 1/1,000 Clear process Systems for error identification and mitigation Mislabeled specimens 1/10,000 1/100,000 Advanced design + Automation Error ID/ mitigation Specimen loss Computer interface errors Achievable Error Rates Resar RK. Making noncatastrophic health care processes more reliable... Health Serv Res. 2006; 41: To go from 1/1,000  1/10,000 requires automation

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

9 Objectives 1.Review current workflow in Anatomic Pathology and the need for change 2.The UW Anatomic Pathology Automation Project A detailed look at each stepA detailed look at each step 3.Starting the automation process Building a business caseBuilding a business case 4.Questions for the future

10 UWMC Pathology 178 Faculty Members178 Faculty Members 40 faculty with clinical duties40 faculty with clinical duties 29 Residents and Clinical Fellows29 Residents and Clinical Fellows 35 Graduate Students35 Graduate Students $32 million in NIH grants (2006)$32 million in NIH grants (2006) A complex academic environment with: >36,000 surgical pathology cases/year>36,000 surgical pathology cases/year

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

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

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

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

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

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

17 Scanning benefits Benefits: Benefits: 3.8 hours/day saved for 26 pathologists and residents3.8 hours/day saved for 26 pathologists and residents Staff satisfaction:Staff satisfaction: 10.0/1010.0/10 Saved 0.25 min/caseSaved 0.25 min/case Current usage:Current usage: 10,614/month 1.Schmidt RA, et al. Integ. of scanned doc mangmt... Am J Clin Pathol Nov;126(5): Routbort M, Grimm E, Schmidt R. Optimized Document Management…. APIII 2006 Conference

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

19 Goal: Goal: 1.Provide real-time status and location of slides Benefits include: Providing real-time case progression informationProviding real-time case progression information Easier location of slides for conference/sendoutsEasier location of slides for conference/sendouts Facilitates workflow analysis via time-stampsFacilitates workflow analysis via time-stamps 2.Drives AP-LIS functionality Automates histology order completion and other processesAutomates histology order completion and other processes Slide Tracking Name

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

21 Slide Tracking Benefits FTE Savings FTE Savings Histology +0.5 FTE Reduced time hunting for mis-delivered slides +0.5 FTE Auto completion of outstanding orders when slide is scanned Office staff FTE Reduced time for conference preparation +.25 FTE Increased efficiency regarding send outs

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

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

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

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

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

27 Objectives 1.Review current workflow in Anatomic Pathology and the need for change 2.The UW Anatomic Pathology Automation Project A detailed look at each stepA detailed look at each step 3.Starting the automation process The business caseThe business case The issuesThe issues 4.Questions for the future

28 The Business Case 1.Efficiency More volume with same personnelMore volume with same personnel $ $3.00/case (slides, specimens)$ $3.00/case (slides, specimens) 2.Patient safety Optimize patient careOptimize patient care Prevent rare, catastrophic errorsPrevent rare, catastrophic errors 3.Compliance Custodial responsibility for patient materials (paperwork, slides, blocks, etc).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 1)This is disruptive technology! Use automation to change habits (prelabeling/preprinting)Use automation to change habits (prelabeling/preprinting) Don’t automate bad workflowDon’t automate bad workflow Each user must benefitEach user must benefit 2)Select carefully Hardware compatibilityHardware compatibility Software compatibilitySoftware compatibility Appropriate technology/solutionAppropriate 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 appReporting/billing in one app Lab/material handling in different appLab/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.More than just tracking – disruptive technology! Workflow changes. Allows processing of increased workloads with static FTE levelsAllows processing of increased workloads with static FTE levels Improves patient safetyImproves patient safety Quantifiable gains can be made by upgrading the most inefficient/error prone processes in your laboratoryQuantifiable gains can be made by upgrading the most inefficient/error prone processes in your laboratory

36 Thank you UW development team Erin Grimm, MD Rodney Schmidt, MD, Ph.D UW Program Operations Manager Dan Luff

37

38 Questions for the Future 2.What materials will be tracked? When does tracking start? Traditional materials: specimen/blocks/slidesTraditional materials: specimen/blocks/slides More specimen derivatives arise: ancillary lab tests, tissue banking, biorepositoriesMore specimen derivatives arise: ancillary lab tests, tissue banking, biorepositories ?? Will there be introduction of prelab tracking to reduce preanalytical errors?? Will there be introduction of prelab tracking to reduce preanalytical errors No current product is comprehensive


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