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Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
Healthcare Analytics with WebSphere Message Broker
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Healthcare Analytics with WebSphere Message Broker

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An introduction to the analytics capabilities in the Message Broker Healthcare Connectivity Pack (HL7, CDA and DICOM)

An introduction to the analytics capabilities in the Message Broker Healthcare Connectivity Pack (HL7, CDA and DICOM)

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  • 1. © 2012 IBM CorporationHealthcare Connectivity PackHealthcare AnalyticsAnt Phillipsantphill@uk.ibm.com
  • 2. © 2012 IBM CorporationUse RestrictionsThe Program is capable of being used as a medical device data system to transfer, store, and convert data from oneformat to another. The Program may occasionally transmit data to bedside medical devices (e.g., for polling and telemetry).However, the Program itself is not a medical device.The following uses of the Program are prohibited:a. use to control any bedside medical device for clinical, therapeutic or treatment purposes (for example, but withoutlimitation, the administration of medication, anaesthetics, saline solutions and the like);b. use for active patient monitoring (i.e., where the Program is used as the sole means of monitoring life-critical patient data, e.g. heart rates);c. use for decision support (i.e., where the Program is used as the main basis to determine patient-specific treatment orimmediate clinical action); ord. use in any active monitoring that depends on the timeliness of data transmission.Indemnity to IBMLicensee will indemnify International Business Machines Corporation and its affiliated companies against any and all thirdparty claims and liability arising directly or indirectly from any use of the Program by or for Licensee for a use or purposethat is prohibited by the provisions of the foregoing section, "Use Restrictions".As of December 11th2012, WebSphere Message Broker Connectivity Pack for Healthcare is currently available for purchasethrough the Passport Advantage program only for use in the following specific countries :Australia; Austria; Canada; Chile; China; Colombia; Denmark, Finland; Germany; Italy; Malaysia, Mexico; Netherlands; New Zealand; Norway; Poland;Portugal, Singapore; Spain, Switzerland; Sweden, United Kingdom; United States of AmericaFor the current list of licensed geographies please see the following URL:http://www-01.ibm.com/software/integration/wbimessagebroker/healthcare/license/index.htmlImportant Disclaimer and Availability InformationWebSphere Message Broker Connectivity Pack for Healthcare
  • 3. © 2012 IBM CorporationWhere Does It Fit?3
  • 4. © 2012 IBM Corporation4Big Data The healthcare world is increasingly reliant on data for business insight– Analytics can provide dramatic real world cost savings and efficiency improvements– It is an enabling technology allowing scarce resources to be used more effectively– Analytics works at many levels across the healthcare continuum– Small departments all the way up to population management and health economics IBM Integration Bus is an outstanding source for analytics applications– Huge amounts of healthcare data flow through IBM Integration Bus every day– Using the integration engine to feed downstream applications makes great sense– Covers three key healthcare standards: CDA, DICOM and HL7 (v2) Tooling simplifies many scenarios when working with healthcare data– Understand what clinical information is present in the data– Extract the relevant clinical information and remove the noise– Feed the information to downstream databases and applications– Validate the incoming data meets the appropriate standard
  • 5. © 2012 IBM Corporation5Data Analysis Profiles The knowledge of a standard is encapsulated in a Data Analysis Profile– Healthcare Connectivity Pack provides profiles for CDA, DICOM and HL7 (v2)– The profile specifies how to identify interesting data in source documents– It also contains zero or more glossaries where medical terms are stored (LOINC) Your starting point is to create a Data Analysis project in your workspace– It is a design project where you explore data and select relevant data for extraction– You select the type of data you will work with when you create the project– Add the data you want to extract from the source documents into a target model– The target model generates the IBM Integration Bus artifacts (map, subflow, validation)
  • 6. © 2012 IBM CorporationHealthcare AnalyticsCDA/CCD
  • 7. © 2012 IBM Corporation7CDA Introduction Clinical documents are derived from the foundational HL7 v3 standards– Arguably the most successful part of the HL7 v3 initiative– Based on an underlying Reference Implementation Model (RIM)– Clinical document specifications are derived (cloned) from the RIM This technology has been piloted at several sites worldwide– Guan Dong Hospital of Traditional Chinese Medicine– Largest modern hospital enterprise in South China– Over 10,000 patients visit per day (in excess of 2000 beds)– 4 million patient-visit per year across one central hospital and four branches– Pilot project included a data warehouse for clinical studies CDA is gaining use worldwide as healthcare seeks to join systems up– Clinical Document Architecture (CDA) standard is tremendously flexible– CDAs can model a wide variety of clinical information both coded and narrative– More than 100 implementation guides have been written for CDAs alone! Our aim is to simplify the creation and consumption of clinical documents– Often this is with a view to extracting clinical information into a database– Simplifies the use of analytics to gain insight into healthcare data– Wide variety of uses such as patient similarity searches and public health studies
  • 8. © 2012 IBM Corporation8Clinical Document Data Analysis Understanding your clinical documents is the vital first step– Recursive nature of CDAs makes working from the schema very difficult– component, section, entry and entryRelationship to mention just a few!– Great flexibility in representing and modelling rich clinical statements The Healthcare Connectivity Pack understands clinical documents– IBM Integration Bus is configured with a CDA Data Analysis Profile– Load example documents representing your implementation guide(s)– Pre-configured with CDA, C-CDA, CCD, HITSP (C32 and C83) template IDs– A glossary of LOINC terms is built-in so that codes are understandableImport your source documents into aData Analysis project – the summarypage shows you how many documentswere loaded, validation issues, andinformation about missing LOINCcodes
  • 9. © 2012 IBM Corporation9Navigating Documents Data Analysis Profile identifies key sections in the clinical document– Navigate easily from the logical model to your source documents– Multiple example documents can be loaded into your Data Analysis project– Cardinality of the clinical data can be explored across the document setThe Data Analysisproject shows you themeaning of differentparts of your documentsSearch for clinicalconcepts across allyour source documentsSee where the relevantinformation is actuallystored in your documents
  • 10. © 2012 IBM Corporation10Target Model The target model represents the information you want extracted– The goal is to identify and map out the relevant clinical information– The Data Analysis Profile creates an XML schema for the target model– Typically large amounts of the clinical document is not relevant Simply drag-and-drop your clinical data onto the target model– By default all attributes and elements are assumed to be required– Refine the target model by removing unnecessary data and renaming elements– Often this refinement means removing structural attributes like classCodeThe target model contains justthe information you want toextract from the sourcedocuments – the tooling createsan XML schema to represent thissimplified model
  • 11. © 2012 IBM Corporation11Generation Generate the map, XSD, XSLT and subflow from the target model– The XSD defines a schema for the data specified in the target model– The map (MSL) extracts data in CDAs into the target model– As with XML schemas, maps can be deployed direct to IBM Integration Bus The XPATH expression shows what has been mapped automatically– Clearly building this kind of expression by hand would be tedious (at best!)
  • 12. © 2012 IBM CorporationHealthcare AnalyticsDICOM
  • 13. © 2012 IBM CorporationDICOM Introduction DICOM is a widely adopted integration standard for medical imaging– All modern imaging systems support DICOM (CT, MRI, Ultrasound, X-Ray etc)– DICOM includes a file format definition and a network communications protocol– Communication protocol uses TCP/IP to communicate between systems– Standard is maintained by National Electrical Manufacturers Association (NEMA) Enables the integration between PACS, workstations and modalities– PACS stands for Picture Archiving and Communication Systems– A modality is the source machine type (CT, MRI, Ultrasound, X-Ray etc) Medical imaging has traditionally been a separate function in hospitals– This is quickly changing as hospital systems become more integrated– IHE is also active in this space – for example scheduled workflow (SWF) scenarios– Scheduled workflows require close integration between HL7 and DICOM systems13
  • 14. © 2012 IBM CorporationExternal Expert / Second Opinion14 In many geographies radiology skills are in critically short supply– IBM Integration Bus can be used to route DICOM images to external experts– Routing based on data in the DICOM image (for example, a SNOMED code)– Solves the larger integration picture such as email notification to physicians
  • 15. © 2012 IBM CorporationPre-Fetch on Admission15 Preparing studies in advance when patients are admitted to hospital– Flexible routing options to retrieve studies and send them to the right specialists– Routing based on data in the DICOM image (for example, a SNOMED code)– Requires a mixture of DICOM commands including C-FIND, C-MOVE and C-STORE
  • 16. © 2012 IBM CorporationDICOM Nodes16 Core set of DICOM nodes provide flexibility in building solutions– Requires a mixture of DICOM commands including MOVE, FIND and STORE– IBM Integration Bus can act as both a client (SCU) and server (SCP)– DICOM images are propagated through IBM Integration Bus as XML messages
  • 17. © 2012 IBM Corporation17DICOM Data Analysis The DICOM Data Analysis profile understands DICOM messages– Data Analysis Profile includes a glossary with 2K+ standard DICOM tags– Vendor specific DICOM tags are common and are handled by the profile– Search for DICOM attributes and understand what modalities are actually sendingSearch for particular pieces ofinformation across all DICOMmessages using the displaynamesThe Navigator shows youthe meaning of theDICOM attributes – theData Filter allows you tosearch using these displaynamesThis is an example DICOM messagewhich flows through IBM IntegrationBus - the message contains codesthat specify the meaning of eachelement
  • 18. © 2012 IBM Corporation18Target Model Creating the target model is the same sequence of steps as before!– Simply drag-and-drop your DICOM attributes onto the target model– By default all attributes and elements are assumed to be required– Refine the target model by removing unnecessary data and renaming elements– Generate the IBM Integration Bus artefacts including map, subflow and libraryThe tooling generates an IBMIntegration Bus subflow which extractsthe information from DICOMmessages into the target model – theextraction is implemented as agraphical mapXPATH predicates are automaticallyadded to the map to locate therequired data from the DICOMmessages
  • 19. © 2012 IBM CorporationHealthcare AnalyticsHL7 v2
  • 20. © 2012 IBM CorporationHL7 v2 Introduction Messaging standard for the exchange of healthcare information– Health Level-7 refers to the application (top) layer in the ISO OSI Reference Model– Version 2.2 of the standard was ANSI accredited in 1996– HL7 is the key connectivity standard in the provider space Deployment specific message segments are supported (Z-segments) n– Supports variety of character encodings (ASCII, ISO-8859 and Unicode) Latest version (v2.7) was approved by ANSI in December 2012– Compliance as always lags behind the standardisation process– HL7 in IBM Integration Bus is up to date for everything up to and including v2.7 There are quite a few things that the HL7 v.2x standard does not cover! The standard is not a complete systems integration solution– Lack of process conformity within healthcare delivery environments– This effectively leads to a unique use of the standard at each site– Standard is really a common framework for integrating systems– Standard builds on other coding systems such as LOINC and SNOMED20
  • 21. © 2012 IBM CorporationHL7 MLLP Nodes21 Nodes encapsulate the MLLP protocol and HL7 message parsing– Nodes handle de-duplication, validation, acknowledgments and timeout handling– Fully up to date including HL7 v2.7 and all the specific chapter messages– Easy to use nodes enable new HL7 message processing scenarios– Examples include HL7 to data warehouse and HL7 device aggregator integration Models defined in industry standard Data Format Description Language– Outstanding tooling makes changing the HL7 models quick and easy to do!
  • 22. © 2012 IBM Corporation22HL7 v2 Data Analysis IBM Integration Bus is configured with an HL7 Data Analysis Profile– Makes it quick and easy to locate information and extract it from HL7 v2.7 messages– Backwards compatible with HL7 v2.x messages (for example, 2.3 and 2.5.1)– The Data Analysis Profile works closely with the HL7 DFDL schemas– DFDL schemas have very descriptive names so search and filtering is easy– The HL7 patterns all provide a journal to publish HL7 DFDL messages as XMLDFDL makes it simple to convert theHL7 ER format into XML ready forprocessing by your Data Analysisprojects – the HL7 patterns have thiscapability built in!
  • 23. © 2012 IBM Corporation23Target Model Creating the target model is the same sequence of steps as before!– Simply drag-and-drop your HL7 elements onto the target model– By default all attributes and elements are assumed to be required– Refine the target model by removing unnecessary data and renaming elements– Generate the IBM Integration Bus artefacts including map, subflow and libraryRedundant components in the HL7message can be removed – elementnames can be changed to make thedocument easy to consume bydownstream applications
  • 24. © 2012 IBM CorporationHealthcare Connectivity Pack24
  • 25. © 2012 IBM Corporation
  • 26. © 2012 IBM CorporationClinical Terminology - Introduction26 Most scientific fields of endeavour have a well defined terminology– Healthcare covers a huge breadth of scientific levels – radiologists work with subatomicparticles, haematologists study blood cells, physicians are concerned with abnormalbody functions, and public health doctors study the spread of disease in populations
  • 27. © 2012 IBM CorporationCoding vs Classification Classification collects things into groups or classes– It is the basis for the majority of statistical analysis, accountancy and much more– By its very nature, the process of classifying things loses accuracy Coding is the allocation of identifiers to things – an alternative name– No more interest to end users than a bar code on a cereal packet! Here is a skiing accident described by the trauma surgeon as a closedspiral fracture of the shaft of the right tibia with fractured fibula:In ICD-10 this injury is described by the following classification:Chapter XIX: Injury, poisoning, and certain other consequences of external cause (S00-T98)S82: Fracture of lower leg, including ankleS82.2: Fracture of shaft of tibia (with or without mention of fracture of fibula)S82.2.1: Closed fracture of shaft of tibia Note that ICD-10 does not specify whether the leg or left or right, whetherthe fracture is simple, spiral or compound or if the fibula is also fractured27
  • 28. © 2012 IBM CorporationICD-10 International Statistical Classification of Diseases and Health Problems Enables the recording, analysis and interpretation for patient mortality– ICD-10 contains more than 140K codes (ICD-9 contains 17K codes) In practice, it has become the standard classification for all generalepidemiological and many health management purposes ICD-10 is not suitable for coding distinct clinical entities Format XXX.XXX X [category.etiology/site/severity extension]:K50.013 Crohn’s disease of small intestine with fistulaK71.51 Toxic liver disease with chronic active hepatitis with ascitesH02.835 Dermatochalasis of left lower eyelidT81.530 Perforation due to foreign body accidently left in body following surgical operation ICD-10 widely used for medical reimbursements in the US (HIPPA)28Epidemiology is the study of patterns of health and illness and associated factors at the populationlevel
  • 29. © 2012 IBM CorporationRead Codes Read Codes are widely used by GPs in the UK NHS and New Zealand– Used by clinicians to record patient findings and procedures– Read codes come in two versions – v2 and v3 (Clinical Terms v3)– Codes are organised into chapters identified by the first character Codes are five characters long with missing letters replaced by a dot– Letters are 0-9, A-Z and a-z (omitting O and I to reduce coding errors)– Results in a very large potential code space > 750M codes (605)H Respiratory disease (H33zz Asthma NOS)J Digestive system diseases (J20.. Acute appendicitis)G Circulatory system diseases (G3z.. Ischaemic heart disease NOS) Framework is broken down into subchapters to give more precise detailH.... Respiratory system diseaseH3... Chronic Obstructive Pulmonary DiseaseH33.. AsthmaH331. Intrinsic asthmaH3311 Intrinsic asthma with status asthmaticus Problems stem from the single hierachy provided by the codes– Consider the clinically accurate code 8H2P (emergency admission asthma)29
  • 30. © 2012 IBM CorporationSNOMED CT - Overview SNOMED has a long history dating back more than 40 years Comprehensive (multi-lingual) clinical terminology for recording the healthand care of individual patients– Codes can be indexed and retrieved for use at the clinical point-of-care– SNOMED codes can also be re-used for management and research Latest evolution of the standard (SNOMED CT) was formed in 1999– Merger of SNOMED with NHS Clinical Terms v3– Every Read Code and existing SNOMED code is represented In 2007 the International Health Terminology Standards DevelopmentOrganisation (IHTSDO) acquired the SNOMED IPR SNOMED CT is sufficiently complex to only be useful in an IT context– By January 2009, it contained over 350K active concepts, ~1M descriptions and 1.38Mrelationships – the sheer size of the standard is an on-going maintenance issue30
  • 31. © 2012 IBM CorporationSNOMED CT – Building Blocks31 Building blocks of SNOMED are concepts, descriptions and relationships– Each concept represents a single specific clinical meaning– Concepts have a fully specified name (FSN) which may not be the preferred term Every concept, relationship and description has an identifier (SCTID)– SCTID contains the unique identifier, partition identifier and a trailing check digit
  • 32. © 2012 IBM CorporationSNOMED CT – Expressions and Grammar Expressions are usually presented using a composition grammar87628006 | bacterial infectious disease | Concepts can be combined in post-coordinated expressions to create amore accurate clinical meaning87628006 | bacterial infectious disease |:246075003 | causative agent |= 9861002 | streptococcus pneumoniae | Nested expressions supported through the use of parenthesis:87628006 | bacterial infectious disease |:246075003 | causative agent |= 9861002 | streptococcus pneumoniae |,363698007 | finding site |= (45653009 | structure of upper lobe of lung |:272741003 | laterality |= 7771999 | left |) Concepts can be combined using the plus sign:87628006 | bacterial infectious disease | + 50043002 | disorder of respiratory system |32
  • 33. © 2012 IBM CorporationSNOMED CT and HL7 SNOMED CT and HL7 do not always sit easily together– Not surprising when message structure and terminology have evolved separately For example consider the transport of Taurine deficiency– No pre-coordinated term exists in SNOMED CT for this disorder Transmit the data as a post coordinated term in OBX.5:70241007 | Nutritional deficiency |: 47429007 | Associated with |= 10944007 | Taurine | Alternatively use observation sub IDs in HL7 messages:OBX|1|CE|29308-4|1|70241007^Nutritional deficiency^SCT|...OBX|2|CE|29308-4|1.1|47429007 ^Associated with^SCT|...OBX|3|CE|29308-4|1.1.1| 10944007^Taurine^SCT|... Impossible to draw a clean dividing line between the two!– Guidelines exist to provide some clarity – for example use HL7 message structure totransmit dates, times, people and places - use SNOMED CT for semantic relationshipssuch as laterality and other post coordinated information33
  • 34. © 2012 IBM CorporationLOINC Logical Observation Identifiers Names and Codes (LOINC)– Coding system for medical and laboratory observations– Relatively new standard (inception dates back to 1994)– Identified by HL7 as the preferred code set for laboratory test names Each test or observation has a unique six digit code containing:– Component - what is measured, evaluated, or observed (for example, urea)– Property - characteristics of what is measured, such as length, mass and volume– Time - interval of time over which the observation or measurement was made– System - specimen type within which the observation was made (for example, blood)– Scale - the scale of measure for the measurement or observation– Method - procedure used to make the measurement or observation Observation code and value transmitted in OBX-3 and OBX-5 (ORU)34

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