POLITEHNICA University of Bucharest Faculty of Control and

POLITEHNICA University of Bucharest Faculty of Control and Computers Impact of Information Technology on the Quality of Health Services RADU DOBRESCU

POLITEHNICA University of Bucharest Faculty of Control and Computers A draft vision for e. Health Overall goal to improve health and quality of health-related information 1 2 3 Integrated e. Health systems for everyone, everywhere to improve access to quality health services, and allow for better health and well being of all citizens and better health systems management. We believe e. Health should support: – Personal, family, community, public health services and preventative interventions, particularly in resource-poor environments – The most relevant health research, information and education, for health providers, researchers, policy makers and citizens – Appropriate, complete, consistent and interoperable health information systems, that integrate public health and clinical requirements for overall health systems management and stewardship.

POLITEHNICA University of Bucharest Faculty of Control and Computers “e. Health” a broad and diverse realm of efforts Different types of e. Health initiatives include, but not limited to: e. Health: the use of information and communication technologies (ICT) to improve health Health information systems • Public health informatics: • Support for disease prevention • Disease and intervention surveillance (e. g. PDAs to community health workers for disease surveillance) • National health info systems to detect/track global threats to public health • Health and clinical informatics: • Electronic health records (EHR), electronic medical records (EMR), patient health records (PHR) • Decision support for healthcare professionals • Health system administration and operations • Pharmacy and supply chain management systems • Laboratory systems (e. g. electronic ordering, transmission processing) • Clinical administration software (e. g. billing) Healthcare and expertise • Telemedicine / telehealth Health research, advisories and education • e. Learning for physician, nurse, healthcare personnel training • Access to research for healthcare personnel • Patient support and information (SMS reminders for drug compliance, online health information, etc. ) • Decision support for healthcare professionals

POLITEHNICA University of Bucharest Faculty of Control and Computers Variety of challenges to reaching vision Barriers and impediments to e. Health advancement Optimal e. Health development path unclear Little capacity for developing and managing health information technology Prohibitive policy environment System is fragmented – donors and other stakeholders push for narrow, specific solutions without interoperability considerations • Leads to inefficient use of funds • Creates program stovepipes Lack of private sector providers due to low market incentives threatens sustainability, independence Immaturity and Lack of awareness about value of e. Health and breadth of possible solutions youth of e. Health effort Lack global forums with all relevant stakeholders in which to discuss in developing progress, issues and learnings countries

STOVEPIPING Stovepiping is a metaphorical term which recalls a stovepipe's function as an isolated vertical conduit, has been used, in the context of intelligence, to describe several ways in which raw intelligence information may be presented without proper context. The lack of context may be due to the specialized nature, or security requirements, of a particular intelligence collection technology. The most common types of intelligence collection, and to some extent processing, which are commonly found in "stovepipes", include signal intelligence (SIGINT), imagery intelligence (IMINT), and human intelligence (HUMINT)

POLITEHNICA University of Bucharest Faculty of Control and Computers Solution areas grounded in domains of e. Health applications “Path to Interoperability” Enablers Capacit Policies y building EHR m. Health Optimal development path Interop. PHI e. Health applications Markets A 2 K finding optimal development path to maximize e. Health potential • “e. Health Policies” and “Capacity Building” address the enabling environment to lower the barriers and impediments to e. Health diffusion and advancement • “Electronic Health Records”, “m. Health”, “Public Health Informatics” and “Access to Information” provide grounding in applications that strengthen health systems

POLITEHNICA University of Bucharest Faculty of Control and Computers Connected health information network will require interoperability across several dimensions Metcalfe’s Law Examples of dimensions to be addressed The value of a network (e. g. Telecomm) is proportional to the square of the number of users of the system (n²) Across programs Census Across geographies Malaria TB Across points of care HIV/ AIDS Across technologies Hospital Health clinic Community health worker Early stage of e. Health in much of developing countries is an advantage – possible to take action now

1 2 3 • Hypothesis: Collaborative action necessary for success Fostering spread of e. Health requires multiple, interconnected efforts • HCIT capacity building required to support many e. Health efforts • National policies needed to support all types of programs • Emerging platform technologies, e. g. mobile health, span multiple areas of focus public health, clinical and patient-centered informatics Multi-player, multi-sectoral initiative needed • Ministries of health and other representatives of target countries • Private donors/foundations • Non-governmental organizations • Multilateral donor/aid organizations • • • Technology companies Biopharmaceutical companies Entrepreneurs Research and academia Others? Collaboration can achieve synergy through united action – Branding: uniting all e. Health-related efforts to increase awareness – Funding coordination: drives alignment on key issues, reduces redundant activities – Mitigate HR constraint: limited group of experts in this field

Goal : engage stakeholders on collaborative action to address challenges facing e. Health efforts Key collaborative actions Enablers Cap. build. Policy Optimal development path Interop Capacity building Policy advocacy Standards support Funding coordination Market-making • help countries build and sustain HR capacity to manage, maintain and develop e. Health solutions • develop enabling policy guidelines • advocate to and/or advise countries on policy development • identify/advocate/implement critical data standards to ensure data quality and interoperability • raise funds for e. Health, reduce redundant activities and increase pool of funding • align funders on key issues (e. g. interop. standards), channel funding as needed • connect “buyers” and “sellers” of e. Health solutions – educate consumers on portfolio of available applications – aggregate demand for e. Health solutions – potentially provide base level of freeware / starter kits

Example: hierarchy of e. Health standards supported by communication standards Informa tion standar ds Standard SNOME D Term Description Systematized Nomenclature of Medicine Systematically organized collection of medical terminology covering most areas of clinical information 1987 Health Level Seven Enables the exchange, management and integration of healthcare information 2003 e. Xtensible Markup Language Facilitates sharing of structured data across different information systems 1997 Hypertext Transfer Protocol Used to transfer or convey information on the World Wide Web 1996 Transmission Control Protocol Provides reliable, in-order delivery of a stream of bytes 1974 Internet Protocol Data-oriented protocol used for communicating data across the internet 1977 HL 7 v 2. 51 Communication standards XML HTTP TCP IP First use

POLITEHNICA University of Bucharest Faculty of Control and Computers • • • • The Future of Healthcare - The banking metaphor Existing Health on the Web e. Health - terminology Transmural Care Electronic Medical Records (EMR) Medical Records - Access Clinical Decision Support Systems Telemedicine - Case Studies e. Health Standards e. Health / e. Science : Cancer Diagnosis Benefits of e. Health Medical Errors Why is e. Health Adopted Slowly? New sources of "health" 11(#total)

POLITEHNICA University of Bucharest Faculty of Control and Computers e. Health - The Future of Healthcare The banking metaphor • Most transactions carried out by the customer • Centralisation of specialist services • Decentralisation of nonspecialist services 12(#total)

POLITEHNICA University of Bucharest Faculty of Control and Computers Existing Health on the Web Access to accurate information can lead to Ø more knowledgable, empowered, less anxious patients Ø more participatory health decisions Ø better care as patient and doctor become partners Mis-information can lead to Ø confused angry patients Ø bad decisions, mis-placed hope, worse care, harm Privacy violations can cause emotional and economic damage 13(#total)

POLITEHNICA University of Bucharest Faculty of Control and Computers e. Health “Healthcare which is supported by electronic processes” Other terms: – Healthcare informatics or Health Information Technology (HIT) – Medical Information Systems (MIS) – Biomedical informatics (also includes Bioinformatics: gene sequencing etc. ) 14(#total)

POLITEHNICA University of Bucharest Faculty of Control and Computers “Healthcare which is supported by electronic processes” e. Health includes: – Electronic Medical Records: easy communication of patient data between different healthcare professionals (GPs, specialists, care team, pharmacy) – Telemedicine: do not require a patient and specialist in same physical location. – Decision support systems in healthcare • Data can be analysed to provide alerts, reminders and real-time decision aids – Evidence Based Medicine: • • • The application of the scientific method to medical practice Check if diagnosis is in line with scientific research. Data can be kept up-to-date. – Citizen-oriented Information Provision: for both healthy individuals and patients – Specialist-oriented Information Provision: best practice guidelines from latest medical journals. – Virtual healthcare teams: collaborate and share information on patients through digital equipment (for transmural care). 15(#total)

POLITEHNICA University of Bucharest Faculty of Control and Computers Transmural Care Transmural: Care should not stop at the walls of the hospital – Both intra- and extra-mural, thus ‘transmural care’. – Care before, during and after the hospital stay. – Cooperation and coordination among local practitioner, hospital, home care and rehabilitation centres – Patient part of an agreed programme - protocols and standards. 16(#total)

POLITEHNICA University of Bucharest Faculty of Control and Computers Electronic Medical Records (EMR) (also called Electronic Health Record (EHR)) – Access of patient data by clinical staff at any given location – Accurate and complete claims processing by insurance companies – Building automated checks for drug and allergy interactions – Clinical notes – Prescriptions – Scheduling – Sending and viewing labs Two types of record: – “Born digital" record : information originally entered in electronic format – “Digital format” record : originally produced in a hardcopy form (x-ray film, photographs, etc. ), scanned or imaged and converted to a digital form. Also: Personal Health Record (PHR) - stored and maintained by the patient. – Issue: Home computer vulnerable to attack 17(#total)

POLITEHNICA University of Bucharest Faculty of Control and Computers Electronic Medical Records (EMR) Maintaining Records – May be required many years after a patient’s death • Insurance claims or murder investigation • Investigate illnesses within a community – industrial or environmental disease – doctors committing murders – need for periodic conversion and migration to ensure the formats they were captured in remain accessible – Media degrades – Media becomes obsolete – protection of privacy is a major concern - need privacy and security policies 18(#total)

POLITEHNICA University of Bucharest Faculty of Control and Computers Clinical Decision Support Systems • Software to aid clinical decision-making: characteristics of patient are matched to knowledge base, recommendations are presented to the clinician/patient • Objectives: – – – Diagnostic support Drug dosing Preventive care reminders Disease management (diabetes, hypertension, AIDS, asthma) Test ordering, drug prescription 19(#total)

POLITEHNICA University of Bucharest Faculty of Control and Computers Clinical Decision Support Systems • Methods: – rule-based, bayesian network, neural network, fuzzy logic, genetic algorithms, case-based reasoning, etc. • Forward reasoning (data-driven) use if sparse data – start with data, execute applicable rules, see if new conclusions trigger other rules: • if high WBC AND cough AND fever AND etc. => pneumonia • if pneumonia => give antibiotics, etc. • Backward reasoning (goal-driven) use if lots of data – start with “goal rule, ” determine whether goal rule is true by evaluating the truth of each necessary premise • patient with lots of findings and symptoms • is this lupus? => are 4 or more relevant criteria satisfied? 20(#total)

POLITEHNICA University of Bucharest Faculty of Control and Computers Telemedicine “The delivery of medicine at a distance. ” Two basic forms: – Live telemedicine - videoconference link – Store-and-forward telemedicine - transmit for assessment offline Typical Telemedicine interaction: store and forward followed by live interaction. Data types – text (e. g. patient's notes) – image (e. g. x-ray) Telemedicine often relies on images (still or moving) Equipment – general purpose (e. g. PCs) – specialist (e. g. electronic stethoscope) 21(#total)

POLITEHNICA University of Bucharest Faculty of Control and Computers Telemedicine (contd. ) Telemedicine most useful when – Specialist services are in very high demand or – Patients are extremely isolated Home care is often delivered by telemedicine – Automatic monitoring and pill dispensing etc. Telesurgery may also be considered as a subset of telemedicine. – Patient operated on by remotely controlled robotic arms etc. 22(#total)

POLITEHNICA University of Bucharest Faculty of Control and Computers e. Health / e. Science : Cancer Diagnosis Telemedicine on the Grid – Multi-site videoconferencing – Real-time delivery of microscope imagery – Communication and archiving of radiological images • Supports multi-disciplinary meetings for the review of cancer diagnoses and treatment. Remote access to computational medical simulations of tumours and other cancerrelated problems Data-mining of patient record databases Improved clinical decision making. Ø Currently clinicians travel large distances § Grid technology can provide access to appropriate clinical information and images across the network. 23(#total)

POLITEHNICA University of Bucharest Faculty of Control and Computers Benefits of e. Health – Reduced record keeping expenses – More accurate data • No poor handwriting problems – Automated sharing among patients and provider • Empower the patient to manage their own health - via Internet information and decision support tools – Reduced office visits to get results – Avoidance of duplicating tests – Automatic summarisation/graphical displays of contextrelevant information to the physician 24(#total)

POLITEHNICA University of Bucharest Faculty of Control and Computers Benefits of e. Health (contd. ) – – – Decision Support Tools -> Improved decisions Remote access to data - e. g. ill while travelling Improved workflows Decreased risk of malpractice suits Ability to mine large record databases • • Research causes of disease Assess effectiveness of treatment programmes/drugs Monitor outbreaks of diseases Easier to conduct clinical trials and rapidly incorporate research results in decision support tools 25(#total)

POLITEHNICA University of Bucharest Faculty of Control and Computers Why is e. Health adopted slowly? – Lags behind other industries by 10 -15 years – Complex regulations - e. g. • Patient records • Privacy laws – Lack of interoperability/standards – Doctors reject IT systems Risks – Potential for errors due to software bugs – Highly coupled systems - greater risk of catastrophe – Decision support systems could lead to mass produced mistakes – Privacy - data vulnerable to attack 26(#total)

POLITEHNICA University of Bucharest Faculty of Control and Computers Presentation • HL 7 • MITA, HL 7, CMS, DHHS, ONC, FEA -> alignment of healthcare architecture • MITA Business Architecture -> Information Architecture – MITA Enroll Provider (HL 7 MITA WG Example) – MITA Inquire Member Eligibility (Gateway 5010 Project) Business Architecture Information Architecture Technical Architecture

POLITEHNICA University of Bucharest Faculty of Control and Computers HL 7 • An international standard development organization established more than 20 years ago. • Enables interoperability of healthcare information. • Creates standards for the exchange, management, and integration of electronic healthcare information. • Develops specifications, e. g. , a messaging standard that enables disparate healthcare applications to exchange key sets of clinical and administrative data. (HL 7 does not develop software). • Why Health “Level Seven”? – this refers to the highest level of the International Organization for Standardization (ISO) communications model for Open Systems Interconnection (OSI) – the application level. – The seventh level supports such functions as security checks, participant identification, availability checks, exchange mechanism negotiations and, most importantly, data exchange structuring.

POLITEHNICA University of Bucharest Faculty of Control and Computers HL 7 Today Version 3 Reference Information Model (RIM v 3) • Messages evolved over several years using a "bottom-up" approach that has addressed individual needs through an evolving ad-hoc methodology. • Many optional data elements and data segments, making it adaptable to almost any site. • The optionality forces implementers to spend more time analyzing and planning their interfaces to ensure that both parties are using the same optional features. • Well-defined methodology based on a reference information (i. e. , data) model. It will be the most definitive standard to date. • Rigorous analytic and message building techniques and incorporating more trigger events and message formats, resulting in a standard that is definite and testable, and provide the ability to certify vendors' conformance. • Uses an object-oriented development (OOD) methodology and a Reference Information Model (RIM) to create messages. The RIM is an essential part of the HL 7 Version 3 development methodology, as it provides an explicit representation of the semantic and lexical connections that exist between the information carried in the fields of HL 7 messages.

POLITEHNICA University of Bucharest Faculty of Control and Computers Steering Divisions: Foundations & Technologies Provides fundamental tools and building blocks – – – – – Conformance Infrastructure & Messaging Implementable Technology Specifications (ITS) Java Modeling & Methodology Security Services Oriented Architecture (SOA) Templates Vocabulary

POLITEHNICA University of Bucharest Faculty of Control and Computers HL 7 Diversified HL 7 started with and is traditionally thought of as “messaging”. For most of its life, however, HL 7 has also produced more than messaging standards. – Electronic Data Exchange in Healthcare Environments (i. e. “messaging”) (v 2 and v 3) – Visual/Context Integration (CCOW) – Version 2. x XML (XML encoding of HL 7 messages) • Clinical Context Documentation Implementation Guide (CCD) – Electronic Health Record System (EHRS) Functional Model – Personal Health Record System (PHRS) Functional Model – Services (i. e. , Services as related to a Services Oriented Architecture

POLITEHNICA University of Bucharest Faculty of Control and Computers Cooperation with Other Standards Developing Organizations HL 7 cooperates closely with other standards developers, such as: – Accredited Standards Committee X 12 N (AXC X 12 N) – Systemized Nomenclature of Medicine Clinical Terms (SNOMED CT) – Digital Imaging and Communications in Medicine (DICOM) – e. Health Initiative (e. HI) – Logical Observation Identifiers Names and Codes (LOINC) – National Council for Prescription Drug Programs (NCPDP) – Object Management Group (OMG) – Health Information Technology Standards Panel (HITSP) – Continuity of Care Document (CCD) – XML standard for medical information summarization

POLITEHNICA University of Bucharest Faculty of Control and Computers Work Group; Teams HL 7 MITA Work Group (HL 7 MITA WG) The HL 7 MITA Project Work Group is focused on creating the initial MITA Business Process Models and Information Model which will become the MITA Information Architecture. – HL 7 MITA Project Work Group • Business Process Team – Use Cases, Storyboards, additional requirements for v 2. 01 business process templates • Data Analytics Team – Information Model Data analysis and database • Modelers Team – Diagrams and models for business processes • Vocabulary Team – Medicaid specific vocabulary • Education and Training Team – Documentation and assistance for newcomers; lessons learned; best practices

POLITEHNICA University of Bucharest Faculty of Control and Computers MITA Architecture Governance Structure MITA Architecture Review Board MITA Business Architecture Review Board MITA Information Architecture Review Board • Business Process • Data Models • Business Capability • Vocabulary • S-SA process • Mapping to Standards • Data Management Strategy • MITA Standards • Framework updates MITA Technical Architecture Review Board • Service definitions • Infrastructure definitions • Technical processes • Technical capabilities • Mapping to Standards

POLITEHNICA University of Bucharest Faculty of Control and Computers Supporting Review Organization Activities • Supporting Organization – TAC • Activities – – Technical function recommendations – Technical Function capability level recommendations – Technical Function Information Model recommendations – Technical Service WSDL recommendations – Harmonization recommendation between MITA and Technical – Interface between MITA and technical industry

POLITEHNICA University of Bucharest Faculty of Control and Computers Multi-Architecture Impact MITA Users ARB BARB TARB IARB NMEH TAC HL 7 -MITA Project

POLITEHNICA University of Bucharest Faculty of Control and Computers The Big Picture MITA Users STAG ARB BARB New Bus Proc Technical Implementer TARB IARB NMEH TAC Other DSMOs State Business SMEs Independent Information Spec. HL 7 -MITA Project HL 7 Healtth Data Community

POLITEHNICA University of Bucharest Faculty of Control and Computers Federal Enterprise Architecture (FEA)

POLITEHNICA University of Bucharest Faculty of Control and Computers Healthcare Standards Environment Participates in FEA

POLITEHNICA University of Bucharest Faculty of Control and Computers HL 7 MITA Work Group Process Flow (Draft)

POLITEHNICA University of Bucharest Faculty of Control and Computers Framework is Essential HL 7 Development Framework Healthcare Development Framework (HDF) Version 1. 2 Published on: April 23 rd, 2008

POLITEHNICA University of Bucharest Faculty of Control and Computers MITA Information Models • The Business Process Model is derived by analyzing the Medicaid Business Requirements in terms of the Concept of Operations. • The Business Process Model is neutral with respect to any organization, location, staff, outsourcing, and automation. • Applying the Medicaid Maturity Model (MMM) to the Business Process Model yields the Business Capabilities. • Business Capabilities show the evolution of Business Processes over time. – – – UML Use Case models Activity models Message schemas (HMD, CMET) Information models (DMIM, RMIM) Abstract WSDL

POLITEHNICA University of Bucharest Faculty of Control and Computers HL 7 V 3 Message Development Methodology: How • • Use Case Modeling – Produce a storyboard example – Generalize the storyboard example into a storyboard Information Modeling – Define classes, attributes, datatypes, and relationships – Define vocabulary domains, code systems, and value sets – Define states, trigger events, and transitions Interaction Modeling – Define application roles – Define interactions Message Design – Define D-MIM, CMETs, and R-MIMs – Define HMD and Message Types

POLITEHNICA University of Bucharest Faculty of Control and Computers MITA Information Architecture Models • • The Business process/ Business capability combinations are the cornerstone of the Business Architecture and the driver for the Technical Architecture. Business Capabilities map to the Conceptual Data Model. The Conceptual Model is the basis for the Logical Data Model. New functional requirements may change the Business Capabilities may update the Conceptual Data Model, and thereby evolve the Logical Data Model. The Logical Data Model can be expressed as a WSDL. The Logical Model will be implemented via a Physical Model via a information technology specification such as Java or XML. – Business Model – Conceptual Model – Logical Model – Physical Model Note: CMS will provide Medicaids with specifications for making their systems interoperable, and reusable. CMS does not mandate types of software.

POLITEHNICA University of Bucharest Faculty of Control and Computers Medicaid Mission and Goals Business Area MITA Principles, Goals, and Objectives Conceptual Data Model Business Process Technical Area Technical Function Logical Data Model Business Capability Technical Capability Physical Data Model

POLITEHNICA University of Bucharest Faculty of Control and Computers Provider Enrollment – Credentialing Step 5 YEARS NOW 10+ YEARS LEVEL 1 LEVEL 3 LEVEL 5 The enrollment process is automated by an interface with the RHIO Provider Directory which invokes a credential verification service Provider enrollment staff use automated, web-based, online credentialing and sharing of primary source verification with other state health programs and other Medicaid agencies Provider enrollment staff spend hours verifying provider credentials or fail to do primary credentialing verification because of difficulty and liability risk Business Capability Matrix

POLITEHNICA University of Bucharest Faculty of Control and Computers Evolving Enroll Provider Business Capability NOW Level 5 Level 4 Level 3 Level 2 Level 1 5 YEARS 10+ Outcomes based enrollment; continuous verification against national databases Enrollment/verification via RHIOs; access clinical record Real time rules driven enrollment /verification; one-stop collaboration Use proprietary EDI for enrollment /verification; legacy MMIS hard coded rules Receive paper enrollment application; verify via phone; manual processing Example of Maturing Business Capabilities…

POLITEHNICA University of Bucharest Faculty of Control and Computers Challenges with the Art/Science of Modeling • Evolution to Unified Modeling Language (UML) – Object-Oriented Analysis (OOA) – Object-Oriented Design (OOD) – Object-Oriented Analysis and Design (OOAD) – Object-Oriented Software Engineering (OOSE) – UML » General purpose modeling language that tries to achieve compatibility with every possible implementation language.

POLITEHNICA University of Bucharest Faculty of Control and Computers UML v 2. 0 UML Modeling Structure Diagrams: what things must be in the system being modeled. Behavior Diagrams: what must happen in the system being modeled. Interaction Diagrams: subset of behavior diagrams that emphasize flow of control and data among the things in the system being modeled.

POLITEHNICA University of Bucharest Faculty of Control and Computers HL 7 Modeling Hierarchy

POLITEHNICA University of Bucharest Faculty of Control and Computers HL 7 V 3 Message Design Models RIM • Select RIM classes to be included in D-MIM Reference Information Model • Clone subset classes of the RIM (1) Define a D-MIM • Select a subset of class relationships • Select a subset of class attributes • Select a subset of attribute data types and domains D-MIM • Create clones of D-MIM classes and attributes Domain Message Information Model (2) Define a R-MIM • Assign alias class and relationship role names • Eliminate unnecessary class hierarchies • Finalize class relationships and cardinality R-MIM Refined Message Information Model • Finalize attribute data types and domains • Select a root class for the message (3) Create an HMD • Arrange classes and attributes hierarchically • Declare inclusion and repetition constraints • Declare data type and domain value constraints HMD Hierarchical Message Definition HMD • Assign message element names

POLITEHNICA University of Bucharest Faculty of Control and Computers Reference Models Reference Information Model Datatype Specification Vocabulary Specification Design Models Interaction Model Design Information Model Common Message Type Model Message Specifications Hierarchical Message Definition Message Type Definition Implementation Technology Specification Conformance Profiles Message Profile Specification Localized Message Specification Message Conformance Statements

POLITEHNICA University of Bucharest Faculty of Control and Computers Reference Models Reference Information Model The HL 7 Reference Information Model is the information model from which all other information models and message specifications are derived. Datatype Specification The HL 7 Datatype Specification defines the structural format of the data carried in an attribute and influences the set of allowable values an attribute may assume. Vocabulary Specification The HL 7 Vocabulary Specification defines the set of all concepts that can be taken as valid values in an instance of a coded attribute or message element.

POLITEHNICA University of Bucharest Faculty of Control and Computers Design Models Interaction Model An Interaction Model is a specification of information exchanges within a particular domain as described in storyboards and storyboard examples. Design Information Model A Domain Information Model is an information structure that represents the information content for a set of messages within a particular domain area. Common Message Type Model A Common Message Type Model is a definition of a set of common message components that can be referenced in various message specifications.

POLITEHNICA University of Bucharest Faculty of Control and Computers Message Specifications Hierarchical Message Definition Message Type Definition Implementation Technology Specification An Hierarchical Message Definition is a specification of message elements including a specification of their grouping, sequence, optionality, and cardinality. A Message Type Definition is a specification of a collection of message elements and a set of rules for constructing a message instance. An Implementation Technology Specification is a specification that describes how to construct HL 7 messages using a specific implementation technology.

POLITEHNICA University of Bucharest Faculty of Control and Computers Conformance Profiles Localized Message Specification A Localized Message Specification is a refinement of a HL 7 message specification standard that is specified and balloted by an HL 7 International Affiliate. Message Profile Specification A Message Profile Specification is a description of a particular or desired implementation of an HL 7 Message standard or Localized Message specification. Message Conformance Statement A Message Conformance Statement is a comparison of a particular messaging implementation and an HL 7 message standard, localization, or profile.

POLITEHNICA University of Bucharest Faculty of Control and Computers Application Role Trigger Event Information Modeling Storyboard Sender References Interaction HL 7 V 3 Methodology: What and Interaction Modeling Service Definition How Message Design Storyboard Example Content Use Case Modeling Derive D-MIM Receiver Triggers Example RIM Restrict R-MIM Serialize HMD Restrict Message Type

POLITEHNICA University of Bucharest Faculty of Control and Computers Domain Analysis Model (DAM)

POLITEHNICA University of Bucharest Faculty of Control and Computers Domain Analysis Model (DAM)

POLITEHNICA University of Bucharest Faculty of Control and Computers Design Dynamic Model

POLITEHNICA University of Bucharest Faculty of Control and Computers Medicaid Business Process Model

POLITEHNICA University of Bucharest Faculty of Control and Computers Use Triggers to Reference the Process Triggers New Enrollment

POLITEHNICA University of Bucharest Faculty of Control and Computers Static Model • • • Collect relevant "data in motion" for a business process. Example: For the Enroll Provider business process, collect relevant provider data from NPI, X 12 transaction, and MMIS data dictionaries. Develop Conceptual Data Model (CDM) - e. g. , provider is a role class (with attributes) played by an entity class with attribute and scoped by one or more entities (credentialing, supervision, enumeration etc. )

POLITEHNICA University of Bucharest Faculty of Control and Computers Dynamic Model – Use Case Start with MITA Business Process Templates • Consider Use Case Diagram • Consider Business Process Diagram • Actors = Application Roles • Inputs and Outputs = Messages • Events = Trigger Events prompting interchange

POLITEHNICA University of Bucharest Faculty of Control and Computers Dynamic Model NEXT: • Develop activity diagram for the business process steps and exceptions • Determine – Pre-condition – Post-condition • Add – Trigger Events – Receiver Responsibilities (Role of Receiving Application) – Update requirements

POLITEHNICA University of Bucharest Faculty of Control and Computers Messaging Finding the correct data element from HL 7 RIM Example of Enroll Provider Step 12: Request that the Manage Administrative and Health Services Contract business process negotiate contract and send enrollment determination notifications.

POLITEHNICA University of Bucharest Faculty of Control and Computers Example of HL 7 to MITA Messaging

POLITEHNICA University of Bucharest Faculty of Control and Computers HL 7 v 3 Static Models = MITA Logical Model

POLITEHNICA University of Bucharest Faculty of Control and Computers Serialize –> The Physical Model Transform Serialized Table Format XML Schema Serialize into Message Types from which XML Schema is generated.

POLITEHNICA University of Bucharest Faculty of Control and Computers Inquire Member Eligibility Input Messages (Class Diagram)

Inquire Member Eligibility Business Process (Activity Diagram) POLITEHNICA University of Bucharest Faculty of Control and Computers

POLITEHNICA University of Bucharest Faculty of Control and Computers Accomplishments • Defined the Technical Services needed to completely implement several MITA business services. • Demonstrated the ability to coordinate with at least one other major industry initiative. • Demonstrated a working proof of concept. • Collaborated with the MITA HL 7 Work Group. – Reviewing CAQH Provider Data. Source, which has over 600 K+ providers, and is free of charge to providers. Its mission is to reduce the administrative burdens of provider data collection processes like credentialing; HITSP. Others are considering uses for this database, e. g. emergency response, that providers could opt-into. • Define the process of adopting a MITA Technical Service

HL 7 and Service-oriented Architecture (SOA) © 2002 -2008 Health Level Seven ®, Inc. All Rights Reserved. HL 7 and Health Level Seven are registered trademarks of Health Level Seven, Inc. Reg. U. S. Pat & TM Off 73

Topics • HL 7 Vision and Mission • Understanding Service-oriented Architecture (SOA) • The case for Healthcare SOA Standards • Introducing HSSP • Status of Standards Work

First, A Few Terms… • • • DSTU = Draft Standard for Trial Use HL 7 = Health Level Seven HSSP = Healthcare Services Specification Project OMG = Object Management Group OHT = Open Health Tools SOA = Service-oriented Architecture

SOA ≠ Web Services SOA Web Services Is a technology platform? No Yes Is a transport protocol? No Yes Primary ownership is businessline owned? Yes No Affects workflow and business processes? Yes No Is an enabler for business and IT transformation? Yes Is an industry standard? No Yes

How is SOA different from messaging? • • A common practice in healthcare, just not yet in healthcare IT Many key products use them but do not expose interfaces Ensures functional consistency across applications Accepted industry best practice Furthers authoritative sources of data Minimizes duplication across applications, provides reuse Messages can be either payloads in or infrastructure beneath services • Service-oriented architecture provides the framework for automation of common services • Still, SOA has to be done well. It is cheaper and easier than ever to create badly designed applications So: Why SOA Healthcare Standards?

Why develop healthcare SOA standards? • Healthcare organizations are being driven to interoperate • “Messaging” is not the ideal approach for every interoperability challenge • SOA has demonstrated viability and benefits for many organizations and in many vertical-markets

High Interoperability Ability to Interoperate Understanding Low

SOA In Action… An Identity Management Example Scenarios 1. Query local domain: entity found locally 2. Query local domain: entity not found locally, retrieve from Local/Regional Domain 2 master domain 3. Query master domain: retrieve linked entities from master Regional Identity Service (EIS) domain 4. External System Query: Retrieve from master domain Implementation External organization’s system Interface National/Master Domain 4. 1 service client National Identity Service Local/Regional Domain 1 3. 4 Implementation “Local” Identity Service 2. 5 1. 4 2. 4 4. 2 2. 6 3. 3 Implementation 1. 3 Interface 2. 3 3. 2 Interface 1. 2 2. 2 service client 1. 1 2. 1 3. 1

The Healthcare Services Specification Project (HSSP) • An effort to create common “service interface specifications” tractable within Health IT • A joint standards development project involving Health Level 7 (HL 7) and the Object Management Group (OMG) • Its objectives are: – To create useful, usable healthcare standards that address functions, semantics and technologies – To complement existing work and leverage existing standards – To focus on practical needs and not perfection – To capitalize on industry talent through open community participation

The Benefits of HSSP Standards… • Define industry standard behaviors for healthcare-oriented service functions • Eliminate “different flavors” of web services from occurring in different organizations • Rapid-pace stds development: ~18 -24 months • Methodology embracing cross-group standards development

HSSP is part the bigger HIT landscape…

Cross-Organizational Standards Development Service Functional Model OMG ANSI Standard OMG Request for Proposal (RFP) RFP Responder s HL 7 Draft Stds for Trial Use OMG HDTF HL 7 SOA SIG HL 7 Technical Specification

Summary “How do you know that the [web-] services you’re building are not just the next generation of stovepipes? ” Stovepiping is a metaphorical term which has been used, in the context of intelligence, to describe several ways in which raw intelligence information may be presented without proper context.

POLITEHNICA University of Bucharest Faculty of Control and Computers Thank you