How to Understand Workflow in Your Automated Laboratory, Then Act on Opportunities to Boost

Productivity, Slash TAT, and Improve Quality

Chris Christopher Csquared Global Solutions, LLC

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Preface

• Lab Automation Market continues to grow • Shortage of Skilled Labor • Ability to Standardize Work, Reduce Errors, and

Achieve Predictable TAT’s

• Most often, lab’s do not achieve the full potential of Automation – WHY?

Technavio's analysts forecast the global laboratory automation market to grow at a CAGR of 5.48% over the period 2014-2019.

Global Laboratory Automation Market 2015-2019

In the face of rising demand and limited resources, Labs are compelled to work smarter…

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Learning Objective:

1. Production Insights - Review the major operational differences before and after the installation of lab automation.

2. Optimization - Review the scope, process, and factors to consider to optimize workflows in an automated environment

3. Strategies - Explore potential solutions to common operational bottlenecks of automated tracks

Gain insights into how to maximize the performance of automated laboratories

Take Aways:

Ex: Free Standing Instruments

Ex: Track Connected

Instruments

Pre Lab Automation Management Challenges

• Extremely difficult to Achieve Standard Work and Guarantee TAT’s

• Highly dependent upon Labor to meet Lab Goals for Quality and TAT

• Difficult to Minimize Waste • # Specimen Touches • Unpredictable Wait Times • Lost Instrument Throughput Capacity due

to Loading Variations • Specimen Transportation varies on Type

and Priority of Orders • Justifying New Capital Investments

Operations • Manual specimen receipt, sorting, aliquoting,

routing, and storing • Workflows organized by Department & Benches • Heavy Reliance on Instruments to Increase

Productivity

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Post Lab Automation Management Challenges

• Extremely difficult to Achieve a Balanced System (Maximum Efficiency)

• How to manage STATs • Staffing -- New Job Description Requirements

• Line Manager • Lean Water Spider

• What is the best time for PMs? Backup? • What happens IF…? • Justifying New Capital Investments

Operations • Automated specimen receipt, sorting, routing,

aliquoting, and storage • Organized by Automation Line & Non-Connected

Instrument / Benches • Heavy Reliance on Automation to Increase

Productivity • Consolidation of Workstations

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Recapping Sample Archiving Sample Location & Retrieval Sample Disposal Sendouts

Auto Verification Result Review & Validation Decision Support Result Reporting

Specimen Collection Sample Sorting Physical Sample Transport Centrifugation Decapping

Order Entry Accessioning Equipment Monitoring Remote Service

Key Considerations that Impact Production

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Varies by Hour of Day

Day 1 Day 2

1) Data Analytics -- Factors to Consider for Optimization • Frequency (arrival in lab) • Test Orders (chemistry, IA, hematology, coag, etc.) • Test Density (# tests per tube) • Priority

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2) Layout -- Factors to Consider for Optimization • # of Sample Touches (potential errors) • Configuration of Modules • # and Type of Instruments (capacity) • Instrument Menu Configuration • Specimen Travel Distance (waste) • Priority Management (STATs) • Staffing Requirements • Turn around Times • Space (T-Turns, U-Turns)

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3) Throughput Analysis -- Factors to Consider for Optimization • Instruments - Tube and Test Throughput • Changes to Instrument Throughput when connected to a track • Test Mix (ISE, photometric, etc.) • Module Throughput

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4) System Constraints -- Factors to Consider for Optimization • Sample Processing (Labor) • Sample Routing • Instrument Buffer Size • Throughput (Instruments & Modules) • Repeat Tests • Results Validation • Track Design / Instrument Connectivity • Tube Type

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5) Labor -- Factors to Consider for Optimization • Staffing by Function • Demand • Required Skill Sets • Line Management • Flow Control

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Optimization of Lab Automation

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Scope: Boost Productivity, Slash Cost, & Improve Quality

Focus: Maximize the Productivity of the Automation Line 1. Pre Visit Data Analytics – Collect & Process Data from LIS, Middle ware, &

Track 2. Observations – Monitor Flow & Processing; Interview Staff & Vendor Support

Personnel 3. Production Analysis – Study Sample Throughput, Utilization, Capacity, Turn

Around Time; Identify System Constraints 4. Operations – Explore Configurations, Setup, Staffing, etc. 5. Findings & Recommendations – Present to Leadership 6. Implementation and Validation – Confirmation of Changes

Six Step Process

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Executive Introduction &

Overview

Remote Data Analysis

Staff Interviews

Vendor Interviews

DAY I - Operational Assessment

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Data Analysis

1st Pass Findings & Recommendations

Day 2 – Observations & Data Collection

Day 3 Preliminary

Report

Validation & Final Report

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Optimization Goals & Deliverables

Management’s Expectations • Identify actions that will reduce cost and become

more efficient • Determine if the instruments and automation are

used in the correct way • Evaluate repeats, maintenance, and Quality Control

processes • Determine what we should be asking ourselves right

now concerning the future

Focus:

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Monday Tuesday Wednesday Thursday Hour of Day

Midnight Midnight Midnight

0

50

100

150

200

250

300

350

400

450

12 14 16 18 20 22 0 2 4 6 8 10 12 14 16 18 20 22 0 2 4 6 8 10 12 14 16 18 20 22 0 2 4 6 8 10 12 14

Immulite 2000-2

ADVIA 1800-2

ADVIA 1800-1

Centaur-2

Centaur-1

Tubes Processed by Hour on the Track

Online Instruments

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Data Analytics “Automation Line Error Analysis”

Advia 1800-1 What might be impacting Production / Throughput?

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Data Analytics “Automation Line Error Analysis”

Advia 1800-1 What might be impacting Production / Throughput? * WARNING * Data by itself IS NOT conclusive in

Identifying Problems, Constraints, or Opportunities in a complex environment.

Data must be used in conjunction with observations and interviews in order to

provide a clear picture of operations.

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Best Practices Observed

Instrument Maintenance – instruments on the line were well maintained using a dedicated technical team member to provide all maintenance activities, reagent preparation, calibration, and quality control. Specimen Management – full utilization of the refrigerated storage and retrieval system. Extra collection tubes were managed with a software program designed to simplify the storage and retrieval of specimens as needed. Team Work – Throughout the entire production process, there were numerous examples of workers helping others in time of need to clear backlogs or to increase throughput. The staff within Specimen Processing was exemplary in team work.

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Flow of Specimens • Tube Entry Points on the Line

• Priority Load – Single or Multiple Tubes • Batch Load (Bulk Input Module)

• Automated specimen receipt, sorting, routing, aliquoting, and storage

• Organized by Connected & Non-Connected Instruments

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0

50

100

150

200

250

300

350

400

450

11 13 15 17 19 21 23 1 3 5 7 9 11 13 15 17 19 21 23 1 3 5 7 9 11 13 15 17 19 21 23 1 3 5 7 9

Immulite 2000-2

ADVIA 1800-2

ADVIA 1800-1

Centaur-2

Centaur-1

Events Impacting Production

Day 1 Day 2 Day 3 Day 4

Instruments on Track

Hour of Day

Midnight Midnight Midnight

Chem-1 Off Line due to Reagent Additions IA-1 down 22

LIS Issue

Findings

Pre-Analytical Analytical Post-

Analytical

1420 1240

8985

8606

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20,444 Total Test Results Two-Day Average by Instrument

Centaur-1

Centaur-2

ADVIA 1800-1

ADVIA 1800-2

Immulite 2000-2

2.1 1.9

14.4

12.2

1.6

Test Density

Centaur-1

Centaur-2

ADVIA 1800-1

ADVIA 1800-2

Immulite 2000-2

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Pre-Analytical Analytical Post-Analytical Nov 9 – 1,260 Accessions

Observations: • Overall staff quality is very high with clear evidence of team

work • Skill sets for the Order Entry and Sample Processing differ • Timing cycles for the two processes can vary widely creating

large queues (Order Entry cycles take less time on average than processing depending upon type of samples received, tests ordered, etc.)

• Pickup of tubes from processing for the Automation Line was inconsistent and not predictable

Findings

Specimen Receipt, Order Entry, & Processing

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Findings

Pre-Analytical Analytical Post-Analytical Specimen Receipt, Order Entry, & Processing

Order Entry Specimen Processing 1) Removal of bag contents (sample tubes &

test requests) 2) Enter patient demographics into LIS 3) Perform first quality check - Match name

on tube with test request 4) Enter tests ordered 5) Stamp request with individual who is

performing this step 6) Print barcode labels 7) Place labels in bag with tubes 8) Place bag into box designated for

Processing

1) Go and pick up box from holding rack (may pick up several boxes at one time)

2) Empty bag with tubes and labels 3) Place barcode label on request and stamp

request with individual doing the processing

4) Place labels on tubes 5) Pour off urines 6) Make aliquots as needed 7) Print extra labels if needed 8) Place tubes in racks at processing bench

Day 2 – 1,326 Accessions Day 1 – 1,260 Accessions

Orders are grouped into Batches of 20 for processing

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Findings

Pre-Analytical Analytical Post-Analytical Nov 9 – 1,260 Accessions

Specimen Receipt, Order Entry, & Processing

Samples that are ready for the Analytical Phase are transported by two primary modes:

• Priority Orders are carried by the Processor to the appropriate workstation

• Routine Orders for the Automation Line are picked up by a technical staff who transports the racks to a workspace near the I/O module. Sample tubes are then picked up, inspected, and placed into Automation racks. The Automation racks are then place into the I/O module for analysis.

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Pre-Analytical Analytical Post-Analytical Nov 9 – 1,260 Accessions

Recommendations Specimen Receipt, Order Entry, & Processing

Pre-analytical Objectives - streamline front-end process to reduce wait times, establish continuous flow of specimens, and increase production output of the Aptio Automation line. 1. Enhance Cycle Time -- Reconfigure Specimen Processing into workstations

consisting of “Two-person Teams” with each team fully processing one requisition at a time (piece work) including quality checks

2. Improve Efficiency -- Reduce the number of Sample Touches by loading the chemistry I/A tubes designated for the Automation Line into the Automation Racks

3. Improve Productivity – Shift Aliquoting to the Track Automated Aliquoter. Place hematology tubes into a bucket that can be emptied directly into the Bulk Input Module

4. Enhance Labor Allocation -- Use a non-technical staff as a Lean “Water Spider” to manage, transport, load, and unload the Automation Racks with the objective to create a continuous flow of specimens

Justifications: • Faster specimen ordering and processing • Enables team building and rotation • Significantly reduces manual aliquoting and potential errors • Improved productivity and use of technical resources 27

Findings

Pre-Analytical Analytical Post-Analytical Production Summary ~ 2,400 tubes are received per business day that could be processed on the Automation line.

For the 24 hour period • 1,105 tubes routed to chemistry • 1,031 tubes routed to immunoassay

Peak Hour Production: ~ 400 Tubes on the Track ~ 100 Tubes on Hematology

Peak Hour Summary

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Findings

Pre-Analytical Analytical Post-Analytical Production Summary Peak Capacity Analysis

Chemistry Peak Hour:

183 Tubes Immunochemistry Peak Hour:

170 Tubes Hematology Peak Hour:

161 Tubes

Throughput and Capacity by Category

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Findings

Pre-Analytical Analytical Post-Analytical Production Summary Load Balancing Good

Tube Production by Instrument

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Findings

Pre-Analytical Analytical Post-Analytical

• Sampling Rate - Maximum number of tubes that can be sampled per hour

• Test Density – Number of tests ordered per tube

• Mix and Type of Test Ordered – one, two, three, four or more cycle times per test

• Instrument configuration – auto repeat and auto dilution features

Constraints that Impact Production

Production Summary Capacity to Meet Workload Good +

Test Production and Utilization by Instrument

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Findings

Pre-Analytical Analytical Post-Analytical Production Summary Capacity to Meet Workload Good

IA #1 Peak Hour: ~185 Tests

IA #1 Peak Utilization: 78%

IA #2 Peak Hour: ~180 Tests

IA #2 Peak Utilization: 79%

High Risk of Not Meeting TAT Goal if either IA is Off Line for >3 hours

Test Production and Utilization by Instrument

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Findings

Pre-Analytical Analytical Post-Analytical Production Summary Errors can have a Huge Impact on Production

Error Analysis

ResultDay 11

Count of ErrorColorCode Column Labels Row Labels Green Pink Red Red+ Yellow Grand Total A00-1 1 50 284 335 A00-2 1 169 155 325 A20 LAS-1 2 2 A20 LAS-2 2 2 A20 LAS-3 2 2 Aliquoter-1 1 34 35 Bulk IO-1 1 1 C-1 4 662 666 C-2 4 176 180 C-3 2 2 C-1 13 1 14 Decapper-1 14 1 7 22 Desealer-1 49 49 Dream Process Controller-1 3 3 Dream Process Controller-2 85 2 87 Immulite 2000-1 1 2 3 Immulite 2000-2 32 6 139 177 IO Module-1 150 1 1990 2141 Power Supply Controller-1 1 1 Recapper-1 2 2 RSM-1 40 1 29 70 Sealer-1 74 64 76 214 Tube Buffer Module-1 1 1 Tube Buffer Module-2 1 1 Tube Buffer Module-3 3 3 Tube Buffer Module-4 3 3 Grand Total 414 1 313 1 3612 4341

Observations: • Barcode Labels not secured to Tube • Samples making multiple laps around track • Instrument taken off line • Multiple tubes with same barcode loaded on track • Tube missed gate • Output Rack Full • Front Loading Instruments • Instruments out of Reagents

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Row Labels Green Pink Red Red+ Yellow Foil Lost 34 33 Emptying Queue 10 Overdue Carrier 5 Tip Drop Failure 5 Analyzer Red State during Sampling Request 2 1 Communication Error during Sampling Request 2 Pick Failure Not Reported 2 Sample Complete Message Not Arrived 2 Unknown Test Code 579 Output Rack Missing or Full 292 Sampling Not Successful 188 Test Not Aspirated 123 Sample Tube Not Processed 52 Error During Sampling 41 Reagent or Consumable Empty (Analyzer Error 01) 41 No Sealer Available 40 Unreadable Sample ID 39 No Ancillary (Analyzer Error 03) 33 Reagent or Consumable Empty 33 Test Not Aspirated;FolateBA 31 Sorting Rack Missing or Full 26 No Mitigation Reagent (Analyzer Error 06) 25 Empty Secondary Sample Tube Due To Clot Detected In Primary Sample Tube 20 Test Not Aspirated;VitD 20 Tube Not Detected 20 Foil To Waste Check Failed 19 No Request or SID Mismatch (Analyzer Error 4E) 18 Low Mitigation Reagent (Analyzer Error 07) 17 Empty Secondary Sample Tube Due To Insufficient Fluid In Primary Sample Tube 16 No Aliquoter Available 15 Clot Detected (Analyzer Error 56) 13

Findings

Pre-Analytical Analytical Post-Analytical Production Summary Errors can have a Huge Impact on Production

Error Analysis

Many Errors are Preventable

Prevention Tactics: 1) Training 2) Line Management 34

Recommendations

Pre-Analytical Analytical Post-Analytical

Automation Configuration, Setup, and Operation

ACTION Justifications Establish a LINE Manager or coordinator to oversee all production on the Automation

Establishes continuous flow -- Faster response times for managing issues that would impede production -- Minimizes batching

Connect Hematology to the Automation Line Increased productively by ~ 1 FTE -- Reduces labor requirements to load, calibrate, and run QC

Add a 3rd IA to the Line Increases line capacity by minimizing today’s IA constraint -- Provides a backup for the six-year old Centaurs that are on the line -- Improves overall system reliability

Continue the switching of Reagents to Concentrated Reagents Maximizes Instrument Production -- Reduces price of service

Upgrade Chemistry Instruments Maximizes uptime of the automation

Increase size of Instrument Buffer to 10 Minimizes Tube Travel on Track

Establish new procedures that minimize the number of repeats on the line. Ex: automate Folate dilutions

Maximizes Instrument Production

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Findings

Pre-Analytical Analytical Post-Analytical

Auto Verification of Test Results

Observations: • Presently, the Middleware is used as a ‘pass through’ for

Test Results for chemistry, immunochemistry, and hematology

• ~ 0.7 FTE is required to manage verification of test results

Opportunities: Fast Track to Auto Verification 1. Use Middleware rules to perform Auto Verification for

connected instruments 2. Establish rules within the LIS to all ‘pass through’ for Test

Results for chemistry, immunochemistry, and hematology that meet Auto Verification Rules

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Findings

Pre-Analytical Analytical Post-Analytical

Sample Storage

Observations: • Presently, the Online Automation Refrigerated

Storage Module is used to manage tube storage for Chemistry and Immunochemistry tubes

• The Capacity of the RSM is ~15,000 tubes • The RSM significantly reduces the # of touches which

in turn, reduces labor and potential errors • Chemistry Tubes are stored up to 14 days

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1. Established Continuous Flow – Workload completed ~ 2 hours faster 2. Improved Efficiency -- Reduced the overall number of Sample Touches by ~1

(lowering labor requirements and potential errors) 3. Improved Productivity – Reduced FTEs by a net of 1 .7 4. Enhanced Labor Allocation – Better utilization of Technical and Non-technical

staff 5. Increased User Knowledge – Use of Online Automation Training 6. Increased Capacity of IA -- with 3rd IA instrument

Learning Objective:

1. Production Insights - Review the major operational differences before and after the installation of lab automation.

2. Optimization - Review the scope, process, and requirements to optimize workflows in an automated environment

3. Strategies - Explore potential solutions to common operational bottlenecks of automated tracks

Gain insights into how to maximize the performance of automated laboratories

Take Aways:

In Summary for This Session

Thank you for your participation in this breakout. Chris Christopher Csquared Global Solutions, LLC 803.792.2212 40