Impact of Information Technology on the Quality of Health Services

1. Impact of Information Technologyon the Quality of Health Services RADU DOBRESCU

2. A draft vision for eHealthOverall goal to improve health and quality of health-related information Integrated eHealth 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 eHealth 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. 1 2 3

3. “eHealth” a broad and diverse realm of efforts Different types of eHealth initiatives include, but not limited to: • 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 • eLearning 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 eHealth: the use of information and communication technologies (ICT) to improve health

4. Variety of challenges to reaching vision Barriers and impediments to eHealth advancement Little capacity for developing and managing health information technology Prohibitive policy environment Optimal eHealth development path unclear • 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 youth of eHealth effort in developing countries Lack of awareness about value of eHealth and breadth of possible solutions Lack global forums with all relevant stakeholders in which to discuss progress, issues and learnings

5. 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)

6. Solution areas grounded in domains of eHealth applications “Path to Interoperability” -findingoptimal development path to maximize eHealth potential “eHealth Policies” and “Capacity Building” address the enabling environment to lower the barriers and impediments to eHealth diffusion and advancement “Electronic Health Records”, “mHealth”, “Public Health Informatics” and“Access to Information” provide grounding in applications that strengthen health systems Enablers Optimal development path Capacity building Policies Interop. Markets EHR mHealth PHI A2K eHealth applications

7. Connected health information network will require interoperability across several dimensions Census Malaria TB HIV/ AIDS Hospital Health clinic 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 Across geographies Across points of care Across technologies Community health worker Early stage of eHealth in much of developing countries is an advantage – possible to take action now

8. Hypothesis: Collaborative action necessary for success • Fostering spread of eHealth requires multiple, interconnected efforts • HCIT capacity building required to support many eHealth 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 1 • Collaboration can achieve synergy through united action • Branding: uniting all eHealth-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 2 • 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? 3

9. Goal : engage stakeholders on collaborative action to address challenges facing eHealth efforts Key collaborative actions Enablers Cap. build. Policy Optimal development path Interop Market

10. SNOMED HL7 v2.51 XML HTTP TCP IP Example: hierarchy of eHealth standards supported by communication standards Standard Term Description First use Systematized Nomenclature of Medicine Health Level Seven eXtensible Markup Language Hypertext Transfer Protocol Transmission Control Protocol Internet Protocol Systematically organized collection of medical terminology covering most areas of clinical information Enables the exchange, management and integration of healthcare information Facilitates sharing of structured data across different information systems Used to transfer or convey information on the World Wide Web Provides reliable, in-order delivery of a stream of bytes Data-oriented protocol used for communicating data across the internet 1987 2003 1997 1996 1974 1977 Informationstandards Communication standards

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

12. eHealth - The Future of Healthcare The banking metaphor Most transactions carried out by the customer Centralisation of specialist services Decentralisation of non-specialist services 12(#total)

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

14. eHealth “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)

15. “Healthcare which is supported by electronic processes” eHealth 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)

16. 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)

17. 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)

18. 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)

19. 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)

20. 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)

21. 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)

22. 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)

23. eHealth / eScience : 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 cancer-related problems • Data-mining of patient record databases • Improved clinical decision making. • Currently clinicians travel large distances • Grid technology can provide access to appropriate clinical information and images across the network. 23(#total)

24. Benefits of eHealth 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 context-relevant information to the physician 24(#total)

25. Benefits of eHealth (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)

26. Why is eHealth 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)

27. Presentation HL7 MITA, HL7, CMS, DHHS, ONC, FEA -> alignment of healthcare architecture MITA Business Architecture -> Information Architecture MITA Enroll Provider (HL7 MITA WG Example) MITA Inquire Member Eligibility (Gateway 5010 Project) Information Architecture Business Architecture Technical Architecture

28. HL7 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. (HL7 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.

29. HL7 Today Version 3 Reference Information Model (RIM v3) 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 HL7 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 HL7 messages.

30. 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

31. HL7 Diversified HL7 started with and is traditionally thought of as “messaging”. For most of its life, however, HL7 has also produced more than messaging standards. Electronic Data Exchange in Healthcare Environments (i.e. “messaging”) (v2 and v3) Visual/Context Integration (CCOW) Version 2.x XML (XML encoding of HL7 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

32. Cooperation with Other Standards Developing Organizations HL7 cooperates closely with other standards developers, such as: Accredited Standards Committee X12N (AXC X12N) Systemized Nomenclature of Medicine Clinical Terms (SNOMED CT) Digital Imaging and Communications in Medicine (DICOM) eHealth Initiative (eHI) 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

33. Work Group; Teams HL7 MITA Work Group (HL7 MITA WG) The HL7 MITA Project Work Group is focused on creating the initial MITA Business Process Models and Information Model which will become the MITA Information Architecture. HL7 MITA Project Work Group Business Process Team Use Cases, Storyboards, additional requirements for v2.01 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

34. MITA Architecture Governance Structure MITA Architecture Review Board • MITA Standards • Framework updates MITA Business Architecture Review Board MITA Information Architecture Review Board MITA Technical Architecture Review Board • Service definitions • Infrastructure definitions • Technical processes • Technical capabilities • Mapping to Standards • Business Process • Business Capability • S-SA process • Data Models • Vocabulary • Mapping to Standards • Data Management Strategy

35. 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

36. Multi-Architecture Impact MITA Review Boards ARB BARB TARB IARB MITA Users NMEH TAC HL7-MITA Project

37. The Big Picture MITA Review Boards ARB BARB TARB IARB MITA Users STAG Technical Implementer New Bus Proc NMEH TAC Other DSMOs State Business SMEs HL7-MITA Project Independent Information Spec. HL7 HL7Healtth Data Community

38. Federal Enterprise Architecture (FEA)

39. Healthcare Standards Environment FEA Participates in

40. HL7 MITA Work Group Process Flow (Draft)

41. Framework is Essential HL7 Development Framework Healthcare Development Framework (HDF) Version 1.2 Published on: April 23rd, 2008

42. 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

43. HL7 V3 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

44. 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. 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.

45. Medicaid Mission and Goals MITA Principles, Goals, and Objectives Technical Area Business Area Conceptual Data Model Business Process Technical Function LogicalData Model Business Capability Technical Capability Physical Data Model

46. Provider Enrollment – Credentialing Step 5 YEARS 10+ YEARS NOW LEVEL 5 LEVEL 3 LEVEL 1 5 YEARS NOW 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

47. Evolving Enroll Provider Business Capability Level 5 Level 4 Level 4 Level 3 Level 3 Level 2 Level 1 NOW 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…

48. 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.

49. UML v2.0 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.

50. HL7 Modeling Hierarchy