Automating Anatomic Pathology
J. Mark Tuthill, MD
Division of Pathology Informatics, Henry Ford Hospital
Detroit, MI 48202
Disclosures
In accordance with ACCME guidelines, any individual in a position to influence and/or control the content of this ASCP CME activity has disclosed all relevant financial relationships within the past 12 months with commercial interests that provide products and/or services related to the content of this CME activity.
The individual below has responded that he/she has no relevant financial relationship(s) with commercial
interest(s) to disclose:
Objectives
• Describe how automation and the future of the Anatomic Pathology LIS (AP-LIS) are inextricably related
• List the areas of anatomic pathology that may be capable of being automating
• Enumerate some of the pre-requisites for anatomic pathology automation and LIS interfaces
• Present examples of evolving automation, their impact, and associated AP-LIS Requirements
What Can We Envision Automating?
The Big Picture
• Pre analytic
– Prior to receiving or analyzing the sample – Preparing samples for analysis
• Analytic
– The process of analyzing the tissue • Post analytic
– The reporting of diagnostic information – Preparing for additional analytic studies
What Can We Envision Automating?
The Big Picture
• Electronic order to AP-LIS
• Biopsy/Label (sample procurement)
• Transport including tracking and routing
• Accession
• Tissue Gross Exam
• Processing, including fixation
• Embedding
• Cutting/ Slide Labeling
• Routine Staining/Cover slipping
• Case Collation
• Delivery
• Microscopic Exam
• Special Stains/Re-cut Orders/materials retrieval
• Diagnosis
• Dictation
• Transcription
• Report Sign out
• Materials filing and storage
Imagine
automating and
integrating these
process using
computerization
and advanced
robotics!
What Can We Envision Automating?
The Big Picture
• Electronic order to AP-LIS
• Biopsy/Label (sample procurement)
• Transport including tracking and routing
• Accession
• Tissue Gross Exam
• Processing, including fixation
• Embedding
• Cutting/ Slide Labeling
• Routine Staining/Cover slipping
• Case Collation
• Delivery
• Microscopic Exam
• Special Stains/Re-cut Orders /materials retrieval
• Diagnosis
• Dictation
• Transcription
• Report Sign out
Automating Anatomic Pathology
Why has AP Automation Lagged Behind the
Clinical Pathology Laboratory?
• The variability of specimens
– Versus CP specimens which come in tubes, AP
sample vary with each surgery
• Required manual processes
– Manual dissection, embedding, sectioning • A lack of interest?
– Do anatomic pathologists lack exposure to the ideas of automation used in the clinical laboratory?
– Why change what works?
• The harsh environment
Prerequisites for Anatomic Pathology
Automation
• Sophisticated electronic medical records system
– Electronic orders interface for Anatomic Pathology • Bar code labeled assets with the laboratory
– Assets with unique identifiers
• Development of robotic technologies (a few examples) – Grossing
– Sectioning
– Tissue transport
– Storage systems: cassettes and slides – Sampling
Prerequisites for Anatomic Pathology
Automation
• Sophisticated electronic medical records systems
– Such systems will enable clinical orders to be sent to the anatomic pathology information system as well as supporting:
• Decision support
• Gathering of accurate and required information • Positive patient identification
• Generation of laboratory ready labels to the point of service
• Tracking of samples to the laboratory including monitoring of conditions
Prerequisites for Anatomic Pathology
Automation
• Electronic orders interface to the Anatomic Pathology Laboratory Information System (AP-LIS)
– Similar to the clinical laboratory, a flow of orders to the LIS will enable:
• Sample receipt • Tracking
• Routing
• Processing
• Automation of several elements of case accessioning
– Decrease errors
Prerequisites for Anatomic Pathology
Automation
• Bar code labeled assets within the laboratory
– This is most essential early prerequisite to achieve automation within the laboratory
– Bar coding of assets allows for: • Bar code driven workflow
• Identification error reduction due to mislabeling • Improved efficiency by reducing manual labeling • Automation of subsequent activities
– Integration whole slide imaging, interface devices
– This is the key requirement for all many automation requirement, and thus the AP-LIS
Prerequisites for Anatomic Pathology
Automation
• Bar code labeled assets within the laboratory
– In addition to simple bar coding of assets with a accession
number or medical record number it will be critical for each asset to have an unique ID embedded in the bar code
– This will allow each block and each slide to be managed uniquely supporting
• Sophisticated routing • Tracking of assets
• Digital Pathology (unique ID on slides will be essential!) • Systems interfaces
• Without uniquely identified assets the clinical laboratory could not have achieved the level of automation currently experienced
Examples of Anatomic Pathology Automation
Examples of AP Automation
• Automation of histology orders (stain protocols) • Auto stainers and auto cover slippers
• Interfaced immunostain orders to automated immunostain platform
• Bar code labeling automation
– Automated production of cassettes at accessioning – Cassette driven generation of labeled slides
• Tracking, routing and storage • Automated tissue embedding • Automated microtome's
Examples of AP Automation
• Automated block sampling • Automated slide sampling
– Laser capture micro dissection
• Conveyor belt systems, tubes, roving robots • Slide collation robotics
• Automatic diagnostics
– Whole slide imaging algorithms for immunostains quantification
Examples of AP Automation
Histology Protocols
• Automated ordering histology protocols for different sample types at case accession
– When a particular part is accession the appropriate blocks and initial stain orders are generated
– Initial billing fee codes are applied
– Histology logs are electronic sent and printed providing early notification of work
• This has increases efficiency and allows for LEAN processes – Work is standardized
– Revenues were enhanced through better charge capture
• This is not easy and required iterative re-work and constant attention to defects to get the most satisfactory end result
Examples of AP Automation
Bar Code Labeling
• Essential first step to widespread AP automation – Note the impact of re-labeling in the automated
staining platform
• As previously stated the implications of bar code labeled cassettes drives all other processes
• By themselves, the impact of automation of cassette labeling following by label generation are profound
Examples of AP Automation
Bar code labeling • Bar code specified surgical pathology
– 2D bar codes were not available so we created a solution and integrated it using middleware
• Interfaced to CoPath eliminating dual entry
– Cassettes are etched at the time of accession – Uses predefined protocols
• Provides nicely formatted cassettes with 2D bar codes • Bar coded cassettes are used to create slides labels
“just in time” at the cutting bench – “Stainer shield”
Examples of AP Automation
Bar code labeling
• Phase 1: (Sunquest) Misys CopathPlus™ MHv 4.1 (Misys Healthcare, Raleigh, NC),
• Phase 2: Sunquest CoPath 6.0 (Sunquest Information Systems, Tucson, AZ)
– Custom interface to laser cassette etchers that use Labelase ™ software, both from General Data
(General Data, Cincinnati, OH)
– 2 Dimensional barcodes etched on the cassettes through a custom report: “HFH Label by scan” – Cassettes are read at the microtomy stations
• Bar code labels for slides are generated (now with 2D bar codes) placed on glass slides prior to
Historical Workflow
• After processing, sections were cut and mounted onto slides then hand labeled with the case accession
number and part designation
• Stains were performed based on electronic requests that were available at the histology department through the LIS
Historical Workflow
• After staining, paper labels were batch printed from the LIS and affixed onto the corresponding slides
23 COM A COM B COM C USB 2 RS232 serial ports on PC CoPath Sends on Com A
Labelase Listens to Com B
Formats Bar Code and Sends Data
USB Connect to Etcher
CoPath to Slide Etcher: Communication Pathway
Etcher Receives Data and Engraves
24
CoPath terminal
Barcode label printer -Lab tag
-Specimen containers
Lab tag scanner, bar code reader Cassette etcher- 2D barcode
Accession Station U-shaped Cell
CoPath terminal 2D Barcode reader -Individual cassettes Slide label printer
-Chemical resistant slide labels -Print 1 cassette not batch
25
Microtomy Station
26
This case is submitted in 3 specimen containers consisting of:
part A - sigmoid colon biopsy, part B - transverse colon biopsy and
part C - stomach biopsy with standing preorder for Helicobacter pylori immunostain. Protocol driven information is reflected in the slide labels dictating 2 levels cut for each part. The stomach biopsy protocol, part C,
calls for an additional 2 blanks slides to be cut, one for the immunostain & a 4th left unstained.
1 4 3 2 Barcode Specified Work Processes
Problems Encountered
• Issues:
– Label was misaligned
• Reasons for barcode variance:
– Label size (limited real-estate for essential information and bar code) – Stock alignment
• Printer mechanical problems:
– Each printer had to be adjusted individually and frequently on a daily basis
• Bottom line:
– with code 128 (linear bar code) tolerances were too tight to succeed Occurred 50% of
Problems Encountered
•
Impact:
– Up to
20%
of case slides could not be pinged
by pathologists on a daily basis
– Resulted in increased sign-out delays, slower
turnaround time, and frustration (through
failed reads)
• Required subsequent manual entry of cases into the LIS by pathologists
Solution
• We replaced linear barcodes with 2D bar codes as part of an upgrade of our LIS
– This included replacement of the old labeling subsystem with 'real-time labeling‘
– Native Sunquest CoPath solution ( They got it!)
• The new functionality in the LIS allowed seamless, automated slide label printing in real-time as each
Benefits of Real Time Labeling:
• Prints a 2D bar code vs. a 1D linear label
• 2D bar codes require little space on the label and are 99-100% readable
• 2D bar codes in the upgrade created a Unique ID (part, block, slide) as an internal identifier that is used for specimen tracking
• Requires no keystrokes to run, as labels print automatically and the block is automatically verified
Outcome
• With 'real-time labeling' the batch printing process has now been entirely eliminated
• Specimen misidentification rates have been further reduced
• Workflow efficacy in the histology lab has increased as cassette reading defects have been eliminated
– Barcode reading defects required the histotechnologist to manually type in cases numbers, leading to increased risk of patient misidentification
Results: Misidentification Rates
Baseline Linear Bar Codes (Jan. 2007) 2D Bar Codes (June 2012) 45 18 1 0 5 10 15 20 25 30 35 40 45 Number Mis-ID Defects Percent of Cases 1.67% 0.62% 0.02%Dirty Laundry and Bar Codes
• Bar codes will fail to read!
– Cassettes and slides have more problems than paper • Root causes are multi-factorial
– Unique ID issues and workflow; a whole new world!
» Cassette rework, re-run protocols – Cassette colors impact reading
– Processing impacts bar codes
– Maintenance of etcher and printers
• Need for inline bar code analyzer as per the cereal box factory
• Perhaps the most commonly automated process in the current AP lab
– Included automated cover slipping
• This saves hundreds of man hours per year
• Has more consistent results versus manual staining and cover slipping
• Interfaces with AP LIS will further enhance productivity and decrease errors
Examples of AP Automation
Automated Immunostaining
Interface Design
• The completed project was rolled out in four phases:
• Phase 1: A unidirectional HL7 interface was created
between CoPath version 4.1 and the Dako autostainer Link 48 platforms
– Allowed IHC orders placed in CoPath to be directly transmitted and received by the DakoLink instrument control software
Automated Staining Platforms
Design• Phase 2: Our CoPath information system was upgraded
to version 6.0 which provided the capability to uniquely identify and track case assets
– The upgrade allowed CoPath to assign unique
identifiers to each and every case asset (i.e. parts, blocks, and slides)
– With this in place, unique slide IDs (linked to IHC orders in the AP-LIS) were transmitted to Dako autostainer control software
– Dako autostainer instruments could then read and utilize native CoPath labels
Unique Asset Identification
• As each asset in a case is created in the AP-LIS, the
system gives each one a unique tag, associated with the case accession number
– This unique ID is permanent and stored in the stored in the AP-LIS
• As new stains are ordered, a unique ID is assigned
– This is encoded into a Data Matrix barcode printed on the slide label to be used for the stain order
Design
• Phase 3: A bi-directional HL7 interface was
implemented between CoPath version 6.0 and the Dako Automated IHC platforms
– This allowed slide status information (i.e. pending, complete) to be transmitted from the autostainers and back to CoPath
• Phase 4: A bi-directional HL7 interface was
implemented between Sunquest CoPathPlus version 6.0 and the Dako Automated Special Stains platforms
FCID Utilization
• The DAKOLink software uses the AP-LIS unique ID as FCID
CoPath – Dako Interface
CoPath – Dako New Workflow
1. Stains are ordered in CoPathPlus.
2. Stain orders are released to the interface on demand or scheduled.
3. Interface creates an HL7 message and delivers to Dako
4. Message is routed to instrument. Slide labels print from CoPath.
5. Slides are cut in the laboratory and Slide labels print from CoPath and labels are applied to slides.
6. Slides are placed into the instrument. Label is
scanned by instrument which indicates the reagent stain workup.
New workflow after deployment of the
automated stainer interface
Stains Ordered
Slide are cut & labeled Creates HL7 message Slides placed onto instruments Slide labels scanned Slides processed CoPath Interface IHC Special stains
From CoPath Printer to Slides to Dako
Bypassing Dako Relabeling
Results: Phases 1-2
Activity Number of Slides Time
Pick up and sort slides from histology 12.0 mins.
Look up patient name in CoPath and record on sheet 7.0 mins.
Daily QC sheet 11.0 mins
Program Stainer: Enter name, acc#, path. initials, stain orders
IHC Autostainer #1 44 slides 11.5 mins.
- Label slides and place in rack 7.0 mins.
IHC Autostainer #2 32 sildes 10.5 mins.
- Label slides and place on rack 5.5 mins.
IHC Autostainer #3 36 slides 10.0 mins.
- Label Slides and place on rack 5.5 mins.
Approximate time saved per run: 56.5 mins. Assuming 2.0 runs per day X 56.5 minutes = 1.88 hours
Results: Phase 4
Special Stain Times per Run (with three runs per day)
Activity Time
Sort slides and compare to logs 5.0 mins.
Pull controls 1.0 min.
Deparaffinize 15.0 mins
Dry Slides 1.0 min.
Program Stainer: Enter name, acc#, path. initials, stain orders) 7.75 mins.
Assign carousel stations 1.0 min.
Approximate time saved per run: 7.75 mins. Assuming 3.0 runs per day X 7.75 minutes = 0.39 hrs.
Results
• With elimination of relabeling the slides and dual order entry through automation markedly decreases assay run time
– This saves upward of ~700 hours of manual effort per year while eliminating errors, and improving laboratory throughput
• Increases order accuracy by reducing keystroke errors.
• Enhances operational efficiency by automating processes. • Enforces safe, consistent, efficient handling of specimen.
AP Orders Interface
• Project initiated to transmit AP orders from our EMR to CoPath
• This will solve several problems:
– Elimination of unsolicited results as orders will be fulfilled in the EMR
– Proper encounter selection – Routing to provider inboxes – Better tracking or AP tissue – More efficient accessioning
• ADT, MD, Part Type, ICD, Clinical History and ask at order entry questions will be transmitted from EMR to CoPath
AP Orders Interface
• Project initiated to transmit AP orders from our EMR to CoPath
• Estimated impact in preliminary time studies
– 1.5 minute average decrease in case accession – 100,000 cases as a baseline for our math
• Savings of 2500 hours
• Minimum of $50,000, direct cost savings
• Doesn’t address complexities of mis-accessioned cases and required resolution
– Elimination of defect in encounter selection alone will have huge impact
Conclusions
• More aspects of anatomic pathology can be automated than are typically envisioned
• Automation of AP process have significant cost savings • Automation of manual process eliminates defects,
improves efficiency, and frees up time for value added tasks
• Elimination of defects results in improved patient safety • Electronic orders interfaces to CoPath will markedly
impact the accession process as well as clinical customer satisfaction and patient safety
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–
Automating Anatomic Pathology
Questions?
J. Mark Tuthill, MD
Division of Pathology Informatics, Henry Ford Hospital
Detroit, MI 48202
