Advantages and Integration of Multi-vendor LIS Environments

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Advantages and Integration of Multi-vendor LIS
Environments
Pathology Informatics 2010 Mark Routbort, MD,
PhD University of Texas MD Anderson Cancer
Center Houston, Texas
Disclosures No financial relationshipsMostly
satisfied customerHave previously served as a
member of IMPAC PowerPath Advisory Board
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Anatomy of the laboratory information system
General lab resulting
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Anatomy of the laboratory information system
Inbound integrationorders, ADT
Phlebotomy/specimen collection
General lab resulting
Outbound integrationEMR, fax/print, outreach
Billing
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Anatomy of the laboratory information system
Labs
Inbound integrationorders, ADT
Anatomic pathology
Phlebotomy/specimen collection
Transplant/HLA
General lab resulting
Microbiology
Outbound integrationEMR, fax/print, outreach
Transfusion
Cytogenetics
Billing
Molecular diagnostics
Flow cytometry
Proteomics
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Anatomy of the laboratory information system
Cross-cuttingfeatures
Labs
Inbound integrationorders, ADT
Anatomic pathology
In-lab workflow
Phlebotomy/specimen collection
Digitization
Transplant/HLA
Data analysis
General lab resulting
Image analysis
Microbiology
QA/QI
Outbound integrationEMR, fax/print, outreach
Transfusion
Procedure/EDM
Cytogenetics
Billing
Rules
Integrated reports
Molecular diagnostics
Synoptic data
Flow cytometry
Asset management
Proteomics
Automation
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The allegorical elephant

• How you define a laboratory information system
  depends to some extent on what you are trying to
  do, or what your biggest current problems are
• If you want your laboratory information system to
  do all of the above
• Very good
• Very ambitious

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A tsunami of clinical diagnosticand biomedical
research data
Example Diagnostic bonemarrow biopsy

• Hematologic lab values
• Morphology
• Clot
• Core
• Smears
• Cytochemical/special
• Immunohistochemistry
• Flow cytometry
• Cytogenetics
• Molecular

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Dealing with complexity

• Break up problems into their constituent
  elements
• Classify and subclassify
• Compartmentalize and subspecialize

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BM report Mostly hand-filled, includes CBC data
Test requisition
BM diff Custom application
Historical data ClinicStation or PowerPath
Flow CERNER
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However, in support of clinical diagnostic work,
data integration is needed at multiple levels

• Within a single modality over time (historical
  record)
• Across labs for pathologic diagnoses and
  pharmacodiagnostics
• Across the patient record for clinicopathologic
  correlation and optimal diagnostic efficiency

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What is an integrated application platform?

• Microsoft Office suite as example
• Consistent look and feel
• From user perspective, ease of use of application
  is enhanced by consistent user interface
  paradigms
• From vendor perspective, branding and
  differentiation are considerations as well
• Data communication and updates between components
• Static cut and paste as minimal example
• Linked objects with dynamic updating

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Multi-vendor integration advantages

• Allows a best of breed selection process
• Can enable lab-by-lab system upgrades
• Anatomic versus clinical lab system
• Transfusion medicine donor and recipient
• Integration of new or rapidly evolving
  technologies
• Digital pathology
• Proteomic/molecular
• Facilitate subspecialty lab data analysis
• Cytogenetics
• Flow cytometry
• Molecular diagnostics

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General integration approacheswith multiple
systems

• Cross-system data reports
• Terminal scripting
• Health Level 7 interchange
• XML/Web Services
• Form based data exporting and importing
• Application programming interfaces
• Application integration
• Simulating a single vendor experience single
  sign-on and context synchronization
• Functional integration

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Cross system reportsRelational databases enable
a granular, extensibledata-centric model of the
real world
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Cross system reports
Data from outside system (institutional ADT
database)
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Terminal scripting

• For terminal/host based LIS integrations
• Programmatically emulate a set of keystrokes
  imitating what a user would do at a terminal
  keyboard

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Terminal scripting
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Terminal scripting
Doesnt have to be (shouldnt be) dumb

• Dumb timed set of keystrokes played back in
  equal time regardless of host response
• Intelligent
• Read host response and react appropriately
• Handles branching logic
• Handles delays on the part of the host
• Handles errors gracefully with logging and
  alerting
• Can abstract data from host windows (screen
  scraping)

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Terminal scripting uses at MD Anderson

• Provide single sign on functionality for
  pathologists lightweight
• Shortcut to flow cytometry test verification
  function for pathologists lightweight
• Used to automatically update a patient flag in
  our CERNER system based on data from our MAK
  Progesa transfusion medicine system to enable
  intersystem rules based on recent blood typing
  results much more complex

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MAK Progesa to CERNER PathnetScripted Updates

• Runs as a Windows service
• Unattended
• Auto start
• No direct user interface
• Incorporates logging and alerting logic

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MAK to CERNER Test Harness
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Terminal scripting lessons

• Difficulty of set up is linked to complexity of
  process being automated
• Branching logic?
• Errors possible?
• Interactive or unattended?
• Potentially sensitive to changes in the
  underlying systems
• Can solve certain problems that cant be
  addressed effectively in other ways

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Information transfer Health Level 7 (HL7)

• Messaging standard for health care inter-systems
  communication at the highest level - application
  of the Open Systems Interconnection or OSI
  Model of networking
• Founded 1987, versions 2.1, 2.2, 2.3 from
  1990-1999, in wide use for communicating lab and
  pathology results (version 2.x)
• ANSI standard

CBC (Supergroup) result message examples -
Partial result message  MSH\ESILABINVISION
_PMSHIS20050331155000-0600ORUR012980822T2.
1PID100000000099999900000TESTMICKEYN1940
0313FWUNK000010501880256428827901PV1
1ODICTDICT731HIS0000361WALTERS,
RONALD S. MR20050301144
200-060020050402155000-0600OBR155002800101477
5200001550550028025032847925032847900000000101550
0312CBCCOMPLETE BLOOD CNT/DIF/PLTRT20050331152
000-060020050331154200-0600PCCGSSO, CELIA
G.20050331154300-06000000361WALTERS,
RONALD S. M10000509003089GLAP2005033
11520RTOBX001NM5500009WBCWHITE BLOOD CELL
COUNT 2.4K/UL 4.0-
11.0LF0000000000000022520020050331155000.00
00-0600IIMINSTRUMENT PERFORMED IDPCNDAACOSTA,
NOEL D.OBX002NM5500018RBCRED BLOOD CELL
COUNT 3.03M/UL 4.00-
5.50LF0000000000000022520020050331155000.00
00-0600IIMINSTRUMENT PERFORMED IDPCNDAACOSTA,
NOEL D.
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HL7 version 2.x strengths (weaknesses)
Efficient, well-defined message model Difficult to human-read Extensions must be through overloading of fields
Vocabulary independent Syntactic interoperability Vocabulary independent Lack of semantic interoperability
Widely implemented Lowest common denominator Widely implemented Lowest common denominator
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Common uses of HL7 to interface lab systems

• ADT interfaces
• Allow systems to get a direct copy of patient
  demographic data and hospital/outpatient status
• Orders interfaces
• Allow intersystems direct creation of orders
• For instance, order entry in the EMR for lab
  draws with transmission to the LIS
• Results interfaces
• Communication of lab test status and resulting to
  systems connected to the LIS

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HL7 between lab information system components

• Can be effective and reliable in the covered
  domains
• Uncovered areas of integration out of scope
• Non-textual data is awkward
• Most common example is incorporation of reference
  lab testing (e.g. Quest Diagnostics, Mayo) into
  local LIS to eliminate manual entry of send-out
  tests
• Other scenarios are possible but less common
• Incorporation of lab data stream into pathology
  system
• HL7 is generally a push model for integration

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Traditional EMR-centric (push) model for
pathology result reporting HL7-based delivery of
pathology reportsconverted from editor like
Microsoft Word to ASCII
Pathologist
Self, transcriptionist, resident entry
DIAGNOSIS Metastatic adenocarcinoma.
Format conversion to ASCII text
HL7
Interfaceengine
HL7
HIS Viewer
Transmission of complex data over HL7 generally
requires transformation (parsing) to ASCII text
Clinician
Custom display logic
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Report as seen by pathologist
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Report parsed into HL7 and received by the
HIS/EMR Integrity of semantic content is at risk
in any transformation process
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Push model generally means multiple copies
Should everyone have their own copy of the data?

• Complexity of the message processing
• Maintenance of the data model
• Maintenance and stewardship of the data,
  including compliance issues
• Multiple potential conflicting sources of truth

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An alternative Service-oriented architecture

• A perspective of software architecture that
  defines the use of services to support the
  requirements of software users.
• In SOA, resources such as lab data are made
  available as independent services that can be
  accessed without knowledge of their underlying
  platform implementation
• While SOA does not dictate a specific
  implementation framework (e.g. CORBA, RPC, DCOM,
  Web Services), Web Services as the
  implementational strategy leverages W3C standards
  along with corresponding deep penetrance of
  description, analysis, and transformational tools
• Key features of the SOA/Web Services perspective
• Schema and documentation is instrinsic to, not
  extrinisic from, service definition (WSDL web
  service description language)
• Schema and data are XSD/XML
• WSDL permits the automated generation of platform
  specific proxy classes for consuming systems

Ref http//en.wikipedia.org/wiki/Service-oriented
_architecture
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XML

• eXtended Markup Language
• W3C specification for data modeling
• Human and machine readable
• Self-describing

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SPiDR at MD Anderson Shared pathology
information data repository

• Middleware service for querying of path lab
  data
• Implementation
• HL7 listeners -gt population of relational
  database with normalized model of laboratory data
• For some systems (APLIS - PowerPath), direct
  database replication with implementation of
  text-indexes for case finding
• Multiple back-end databases running on multiple
  servers
• Supports multiple internal database models
  integrating data sources over time
• Multiple mirrored servers allows the same data to
  be queried transactionally (get me all the lab
  data on patient X) or analytically (find me all
  the patients with recent diagnoses of chronic
  myelogenous leukemia with bcr/abl translocation
  loads above X) without risking transactional
  performance
• Web services interface
• Annotated, streamlined XML schema for LabData
• Leverages W3C standards

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Internal data model

• Fully relational
• Process-aware
• Temporal
• Multiple data sources multiple databases

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• Internal data model is complex, normalized, and
  may vary according to source system
• Includes temporal elements to support
  point-in-time state reconstruction (regulatory)
• Much more complexity than most consumers need!

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External (service) model

• Service oriented question
• What are the lab results?
• External model for consumers
• State but not process aware
• Significant denormalization to facilitate
  comprehensibility and broad applicability
• For instance, patient demographic data is
  represented at the test level

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Service model of lab data

• Tests
• A lab test, which may be in varying stages of
  completion (status), and which may or may not
  have associated granular result details
  (TestDetail) or additional metadata about the
  test itself (TestInfo)
• Examples Complete blood count, GI panel, PSA
• Lab tests include information about the entity on
  which they were performed - generally, a patient
  - which represents a flattening of the typical
  HL7 hierarchy
• TestDetails
• TestDetails are granular data elements
  representing specific result components for a
  Test
• Examples Hematocrit (within CBC test), bilirubin
  (within GI panel), PSA level (within PSA test).
• TestInfo
• A collection of information about the test itself
  which does not readily fit into a flat Test
  structure
• Examples General result level comments not
  associated with a specific TestDetail,
  cancellation or other process explanations, order
  level comments.

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Demonstration
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Data export and import strategies

• XML is powerful but not often the starting point
  for non-relational data
• How to better get specialty lab diagnostic data
  in to the LIS?
• Flow cytometry, molecular diagnostics,
  cytogenetics
• All share fairly complex workflows (non-linear)
  and have a high degree of dependence on
  non-integrated analysis tools
• Data points transcribed in lab from different
  analysis packages into LIS
• Domain data model is volatile and different than
  LIS data model
• It is common for these labs to use worksheets or
  specialized data analysis packages to create
  summary data reports, which are subsequently
  manually transcribed into the LIS and stored as
  paper support documents

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Getting the data inFlow cytometric analysis

• Problems
• Multiple data analysis packages are required by
  lab CellQuest, FloJo, Excel, Diva, etc.
• LIS not designed, nor should it be, for raw
  list-mode data or complex analysis
• This dichotomy results in separation of the
  original diagnostic data from the LIS and
  cumbersome and error prone transcription from the
  analysis data to the LIS
• Conclusions
• Even if acquisition and analysis resides outside
  the LIS, there should be automatic import of both
  the original analysis results and the structured
  data from the analysis
• The LIS should be the place where the data comes
  together

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Sample CellQuest analysis
Multidimensionalscattergrams
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Sample CellQuest analysis
Summary front sheet
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Steps

• Define a schema for diagnostic flow cytometric
  analysis data
• Define a web service/WSDL (and get our LIS vendor
  to implement it!) for automatic data import using
  this schema
• Develop an import tool
• Reading raw PDF files to extract data elements
• Transformation into schema compliant XML
• Use web service to import analysis XML as well as
  an ectronic copy of the visual data

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FlowAnalysis schema
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FlowAnalysis schema
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The import tool
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The import tool
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The end result in the LIS
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Pre-vendor integration electronic flow PDFs to
replace paper printouts
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Application programming interfaces (APIs)

• An interface implemented by a software program
  that enables it to interact with other software
• Functional integration is enabled by APIs
• Ideally, well-documented publicly available
• Can be an extremely powerful paradigm
• It is also possible to create wrapper
  interfaces that use techniques such as Windows
  automation to simulate a native API
• E.g. LaunchApplication, LoginUser, OpenCase

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Use of APIs to incorporate digital imagesand
digital slides in a simple viewer
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Application integration

• Simulating a single vendor experience single
  sign-on and context synchronization
• Functional integration
• Bar coding support cross-application
• Automatic initiation of common tasks
• Accessioning a case
• Starting a dictation
• Functional build-out

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PathStation at MD Anderson An enterprise
application integrationengine for the
laboratorian/pathologist
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Design considerations for a unifiedmulti-vendor
environment

• Single sign on for every application
• Intelligent context synchronization
• Use of bar codes to drive workflow in a
  user/station appropriate manner
• Integration with both internal applications
  (CERNER, PowerPath, dictation/transcription,
  Aperio) and external (EMR)
• Platform for functional expansion

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Brief demonstration
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Conclusions

• Multiple vendor based systems can present a
  relatively integrated end user experience if
  appropriately connected
• This approach can provide some of the benefits of
  incremental or best-of-breed implementations with
  the benefit of a unified application
• A robust tool set is needed
• There are many middleware providers, developers,
  and automation toolkits available in the
  marketplace in support
• Dont take no for an answer if it seems like it
  should be doable, it almost certainly is

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Acknowledgements

• Shibu Ninan PathStation lead developer
• Leslie Nesbitt project manager
• Trey Elliot, Sanjivkumar Dave, Cathy Price,
  Mohammed Gomah, James Fleming- SPiDR
• Mike Riben Medical Director, Path Informatics