Open Source Modular Units for Electronic Patient Records. Hari Kusnanto Faculty of Medicine, Gadjah Mada University

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1 Open Source Modular Units for Electronic Patient Records Hari Kusnanto Faculty of Medicine, Gadjah Mada University

2 Open Source Initiatives in Patient Information System electronic health records, scheduling software, insurance billing, accounting, and access controls user interface is generated from database configuration allowing us to redesign and rebuild the user interface as requirements evolve clinical artefacts that are used across EHR systems as these provide the basis for international interoperability and as the foundation for generic decision support systems and other added value

3 The use of open source in healthcare will break down many barriers to EHR adoption, from high cost and lack of interoperability, to inaccessibility and complexity. The open source movement in industries besides healthcare: reduce the cost of software development and deployment, speed the pace of innovation, reduce the number of errors or bugs in a system, and promote widespread adoption of reliable, stable and state-of-the-art applications.

4 Adaptation? Customization? Reconstruction? or.. create a new one? We need a generous repository of modular pieces (archetypes) as building blocks for electronic patient record

5 Patient Registration System Patient Master Index Order Entry and Reporting Appointment and Scheduling Outpatient Visit Picture Archieving and Communicating System Clinical Coding System Inpatient Record Clinical Decision Support System Admission, Discharge & Transfer Billing

6 The Myth: open source project will attract a lot of developers most software is still largely monolithic or made of modules that are too large and so most volunteer developers do not have the time or motivation to fully understand the code enough, and to want or be able to add significantly to it Goldman and Gabriel (2005): Innovation happens elsewhere: open-source as business strategy, San Fransisco:Elsevier

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20 PatientOS v0.89 Registration, Scheduling, Reminders, Patient Lists. Lab result viewing, flowsheet (observation) viewing. Clinical and Administrative Forms, Templates. Physician Order Entry, Prescription Writing. Clinical Documentation Inking, Multimedia. HL7 Interfaces ADT, Orders, Results, Observations, Charges. Patient Portal and integration. Custom reports, batch jobs, data mining.

21 Distributed System Windows Linux Mirth PostgreSQL RMI over TCP/IP Hibernate (JDBC) Solaris Mac JBoss Oracle (future) Fat Clients ApplicationServer(s) Database Server HTTP HL7, XML X-Win NxClient Terminal Services Thin Clients Patient Portal External Systems

22 Layered Architecture Data DB Hibernate JDBC PatientOS Data Access PatientOS Business Logic Reports Mirth PatientOS Domain Models.. PatientOS Service Layer Business Logic PatientOS Service Facade PatientOS Dynamic MVC Presentation

23 Service Oriented Business Logic S Y S T E M S E C U R I T Y S C H E D U L I N G R E P O R T I N G R E G I S T R A T I O N O R D E R S Presentation M E D I C A T I O N C L I N I C A L Data B I L L I N G

24 Inpatient Example Select Patient

25 Open Chart Quick Access to Form

26 Generic Admission Assessment

27 Arrival

28 Presenting Complaints

29 History Current Medications

30 History Vaccines

31 Legal

32 Social

33 Examination

34 New Medications

35

36 Abstract problems it addresses Semantic interoperability: how do different pieces of software know what the data mean? Patient centric view: how to build a patientcentric longitudinal EHR across enterprises? For decision support, Care pathways, Medical research Continual change and complexity: how to build systems that keep up with reality?

37 Information Level 1 & 2 The cognitive User interface: Different ways of Presenting & Capturing the Same information Logical data-sets: Achieved by templates That re-use and Organise underlying Standardised data Points according to use

38 Information Level 2 & 3 Logical data sets: Templates using only Selected items from a Number of archetypes Standardised models of The data: Achieved by archetypes Organised by topic, Independent of use

39 Information Level 3 & 4 Standardised clinical models of the data: Archetypes all based On same reference model RM SM virtual EHR terminology demographic EHR archetype service service service service { { EHR Extract domain EHR Demographic Integration Template OM } Composition openehr Archetype Profile patterns { Security Common Archetype OM Data Structures Data Types core{ Support (identifiers, terminology access) AM Standardised technical representation of the data: The reference model Enables interoperability

40 Language (ADL)

41

42 Where Do We Go From Here?

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