Bar-coding in AP: OmniTrax as a Full Middleware Solution Rodney Schmidt, MD, PhD Professor of Pathology, Director of Medical Informatics (Pathology) University of Washington, SeattleSlide 2
Today\'s Story Lessons from OmniTrax Lean procedures and work process Deeper comprehension of barcoding Different levels of barcoding with various advantages Measures of advantages Quality and effectiveness Workflow subordinate! Current capacities Trade-offs utilizing a middleware arrangement Need for a scanner tag standardSlide 3
Disclosure Bar-coding programming created at UW (OmniTrax and OmniImage) has been authorized by UW to Pathway Pathology Consultants for PowerPath end-clients. Dr. Schmidt and his group have an income imparting consent to UW. Dr. Schmidt has a counseling concurrence with Thermo-Fisher for instructive talks. No other money related associations with equipment or programming makers.Slide 4
Expensive $23k/net station $10k/cutting station Software Workspaces change Wiring, organizing Time speculation Software quick Workspaces moderate Financing moderate Processes change Material dealing with QA Jobs change Workflow Change administration Pathologists influenced! Why standardized identification? Who needs the bother?!Slide 5
Why standardized tag? Blunder diminishment and patient security Errors naming things 1/300 (manual) to < 1/10,000,000 (datamatrix) Reduced medicinal legitimate obligation Custodial duty & stock control Self-intrigued reasons Helps you carry out your occupation quicker Reduced time squandered on mistake determination Indirect efficiencies in light of better learning about where things areSlide 6
What is Bar-coding? Naming Putting scanner tags on things Technically simple, shabby (a few strategies) Tracking Location redesigns; stock control Added work; needs programming; humble cost Driving Using standardized tags to speed up work process Disruptive innovation; costly; LIS interoperabilitySlide 7
Bringing Bar-coding to AP Track slides (2005) Eliminate the "lost slide" issue Ease gathering prep Specimen names (2006) Tissue disposes of and following Drive net photography Block creation and naming (2008) Automated JIT generation of barcoded pieces Gross room QA process and following Slide creation and naming (2008) Automated JIT production of barcoded slides Facilitate work process and QA Eliminate all manual naming (and mistakes) Facilitate work process – JIT data showSlide 8
Achieved Benefits Marked lessening in naming blunders Improved stock control (i.e. information of where things are) Direct reserve funds of ~ 3 FTE Indirect investment funds of >> 0.5 FTE Improved picture accumulation and administration (printed material, gross, miniaturized scale, EMs, IF, and so forth) Increased employment fulfillmentSlide 9
Bar-coding Options Buy LIS-particular Available? Competent? Purchase 3 rd party arrangement (middleware) Available? Proficient? Fabricate LIS-particular middleware Can be speedy. Venture. Manufacture LIS-freethinker middleware Most mind boggling; most controlSlide 10
Design Principles No checking without advantage User acknowledgment; insignificant preparing No manual information section Eliminate human mistakes Use standardized identifications to drive work process Efficiency Make nothing until it\'s required Eliminate taking care of and blunder openings No suspicions – just trust filter occasions Quality timestamps, areas, staff Leverage LIS-skeptic planSlide 11
Material recognizable proof (2005) Handwritten example marks Manual, disconnected tape naming Hand-composed slide namesSlide 12
Primary naming blunders (2004) ?Slide 13
Targets – Gross Room Foolproof marking No human naming/information section Reduced reliance on care staff Off-hours accessibility Redirection of bolster work force Reduced misuse of tapes Grossing venture at any rate as quick as present (Record timestamps) The unsupervised Resident!Slide 14
Receive example and enter information into the LIS Generate a bar coded mark for the example and lab ask for shape. Least additional keystrokes (one) Targets - AccessionSlide 15
Classic Grossing Workflow Accession examples Label examples * Label tapes * Group with examples * Move to organizing zone Move to gross seat * Lay out tapes * Fill tapes Request more tapes Store abundance with specs Handling steps Rack filled tapes Possible blunders * Reconcile with LIS Transport for preparing * QA stepsSlide 16
Accession examples Bar-code examples Scan/print tapes * Lay out tapes * Fill tapes Rack filled tapes * Transport for preparing Just-in-Time Printing Fewer dealing with steps Fewer (1) mistake openings Fewer QA forms Courtesy General DataSlide 17
Q&E BenefitsSlide 18
Histology – Embedding Target View basic data about square and example Efficient work process Block examine: Embedding directions Number of bits of tissue Specimen information (Record timestamps)Slide 19
Histology – Cutting Targets Present basic data (piece, example) Eliminate manual slide naming Block/slide confirmation Multiple work processes No messiness Efficient Touch-screens; no consoles Block filter: JIT slide printing/naming Info show Slide check: Block/slide coordinateSlide 20
Cutting - Benefits Elimination of hand marking Much quicker than manual naming for squares with many slides Fewer piece/slide confuses Overall throughput expanded ~10%Slide 21
Slide Life Cycle Histology Pathology Offices Sendouts Faculty signout File Pull for gathering Resident audit Histology work arrange finishes with filtering Deliver ShipSlide 22
Slides – Benefits Less staff time searching for slides Faster to discover last area than make a telephone bring Fewer contentions about whether slides were conveyed Fewer recuts? Enhanced occupation fulfillment ** Saved me 30 min the primary day! ** Overall investment funds > 2.0 FTE!Slide 23
Slides Benefits FTE SavingsSlide 24
Imaging Gross photographs Photomics Documents EM/IF HPV work process Reflex testing Digene/Luminex Specimen administration Discards Locations Winscribe robotization Barcodes Enable…Slide 25
Targets - Specimens Discards Accurate Efficient Documented Track area Drive photographySlide 26
Specimen Discard Workflow Device examines example standardized tag Handheld gadget inquiries AP-LIS If case signout happened <2wks earlier If case signout happened >2wks earlier If note on Req Data tab, posted warning and note showSlide 27
Barcoding Benefits Direct staff (FTE) 2.0 Slide conveyance and following 0.75 Cassette printing 0.1 Specimen disposes of 0.1 Document checking TBD Fluorescence picture import ~$150,000/yr accepting $50,000/FTESlide 28
Barcoding Benefits Indirect faculty (FTE) 0.5 Scanned counsel report accessibility 1 TBD Scanned Req frames TBD Slide area information (e.g. Pathologists) Reduced loss of materials Slide/Block following Specimen disposes of 1 Schmidt, RA, et al. Am J Clin Pathol 126:678-83, 2006Slide 29
Barcoding Benefits Error Reduction Elimination of all manual naming strides! Lessened naming mistakes Specimens Blocks ~988/yr to almost 0 "How could you figure out how to do that?!" Slides Gross photographs Scanned records PhotomicrographsSlide 30
OmniTrax – What\'s new? Interface demonstrate for collaborating with LIS More clients OHSU NYU HPV work process actualized Gross/Histo improvements (Cytology bolster) (Immunostainer interfaces) Leica Bond 3 BioCare intelliPATH (Archives following port) (Slide following port)Slide 31
Advantages Leverage the force of center frameworks Deliver specialty usefulness Avoid duplication of center capacities If you assemble your own: Independence and control Open equipment choices Portability between LISs Short bug/settle cycle Implement capacities you require Tune and refine prn Disadvantages Ongoing interoperability LIS overhauls Might change LISs Negotiate interfaces Extract information Write information LIS information show poor Too straightforward Missing ideas If you fabricate your own: Ongoing bolster commitment Middleware Software that scaffolds a human to at least one noteworthy frameworksSlide 32
UI/application UI/application UI/application Business objects LIS Agent Database QA Reports Basic Architecture OmniTraxSlide 33
UI/application UI/application UI/application UI/application Business objects LIS Agent IIS Web application Agent LIS Database Reports Local Extensions OmniTrax Web application ReportsSlide 34
Growth and Complexity as of Sept 7, 2010 Version 1: 22 tables Version 4: 48 tables Lab Framework Client DLL – 22,850 lines (around 460 printed pages) OmniTrax Server – 11,554 lines (around 235 pages) Agent – 4199 lines (85 pages) Gross Room Manager – 4754 lines (97 pages) Histology Manager – 5133 lines (104 pages) That\'s equal to: Les Miserables All three Lord of the Rings booksSlide 35
Need for a Standard Problems Multiple scanner tags from diff. offices on same thing No "doling out expert" in standardized tag Interpreted diversely by various programming Some restrictive uses APIII center gathering recommendations (2008) The scanner tag ought to contain just an identifier (e.g. "tag"); programming decides utilize The standardized identification ought to contain something proportional to a "relegating expert". ID | application | establishment 12356789 | OmniTrax | UWPath98195Slide 36
Why scanner tag?Slide 37
Phil Nguyen Kevin Fleming Rosy Changchien Chris Magnusson Victor Tobias General Data Thermo-Fisher Accu-Place Dr. Erin Grimm Dan Luff Steve Rath Pam Selz Kim Simmons All the Techs and Office Folks! Affirmations
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