A Model-Integrated, Guideline-Driven, Clinical Decision-Support System

1. ealth Infrastructures A Model-Integrated,Guideline-Driven,Clinical Decision-Support System Janos L. Mathe, Andras Nadas, Janos Sztipanovits November 11, 2010 Institute for Software Integrated Systems

2. Outline • STEEP: Project Overview • Integration Challenge • Systems architecture • Approach • Reusability Challenge • Knowledge architecture • Approach • Summary

3. Sepsis Treatment Enhanced through Electronic Protocolization (STEEP) • TRUST testbed for a new generation of privacy-aware health information systems • A fully model-integrated clinical decision support and patient management system • Developed jointly by TRUST and VUMC research teams • Funded by NSF-TRUST, NIH and VUMC • Currently under clinical trial in the Medical ICU (MICU) and Surgical ICU (SICU) of VUMC

4. Goals of STEEP Support for managing septic patients using formally modeled evidence-based guidelines Improve adherence to evidence-based guidelines in disease management Establish a real-life experimental platform for privacy-aware HIS Model-integrated approach for synergizing utility under privacy constraints

5. Concept of Operation for STEEP Computerized Provider Order Entry (CPOE) Patient Management Dashboard Surveillance Tool STEEP GUI Physician Patient Execution Engine EMR DB Service • 1. Identify patients based on modified SIRS criteria and prompt clinical teams • 2. Provide treatment recommendations real-time based on live patient data • 3. Monitor and track treatment trajectory and manage information flows • 4. Integrate with HIS services of the hospital

6. Meaning of “Model Integrated” STEEP GUI • Formally defined (structural and behavioral semantics • Analyzable and translatable Physician Execution Engine Model-based Runtime Configuration XML Protocol Models GME T Configure, Integrate and Execute system using the Protocol Models Build Protocol Models

7. Meaning of “Model Integrated” STEEP GUI • Formally defined (structural and behavioral semantics • Analyzable and translatable Physician Execution Engine Model-based Runtime Configuration XML Protocol Models GME T Configure, Integrate and Execute system using the Protocol Models Build Protocol Models

8. Meaning of “Model Integrated” STEEP GUI • Formally defined (structural and behavioral semantics • Analyzable and translatable Physician Execution Engine Derived Protocol Representation XML Protocol Models GME T Configure, Integrate and Execute system using the Protocol Models Build Protocol Models

9. Architecture of the Software Suite Treatment Status Patient Status STEEP GUI Client Protocol Visualization GUI Chart Visualization AJAX HTTP Execution Engine Chart Data Formatter Protocol and Orders Mediator JNDI / EJB3 JNDI / EJB3 JNDI / EJB3 Persistency DB Server CPOE Interface Decision Support (individualized protocol execution) JDBC Hibernate EMR Interface JNDI / EJB3 JDBC Hibernate Protocol Execution Engine File IO • Code is fully reusable • Model is changingand complex • Environment is very heterogeneous Model-based Runtime Configuration Orders to HEO HL7 Patient Data

10. Clinical Trial • Started in October, 2010 • 6 months late and ongoing • Performed by Attendants and Fellows in the MICU and SICU • Long period of hands-on tests, GUI debugging, qualityreviews and evaluations Lessons learnt (so far) • Integrationis a significant challenge (seemingly mundane, but this is the source of most systems challenges and tightly linked to privacy/security requirements • Reusability is a crucial – solution requires compositionality on the level of models

11. Outline • STEEP: Project Overview • Integration Challenge • Systems architecture • Approach • Reusability Challenge • Knowledge architecture • Approach • Ongoing work

12. Conditions for Clinical Integration The process required: • passing of the institutional HIPAA (privacy), security and quality review process • the integration of STEEP into Vanderbilt's clinical information systems, including • the EMR, Order Management (CPOE), Medical Administration and Surveillance & Alert Management systems

13. Integration Architecture Lab System Patient Management System Nursing System Medication Tracking System CPOE Patient Website User-specific Settings Role-specific Settings Patient Management System Surveillance Tool (Sepsis Alert) EMR DB Service (Data Integration) CPOE (Order Management) DB Rule Execution Centralized Data Cache UI Dashboard DB Historic Data Warehouse DB STEEP GUI STEEP (Sepsis Management) STEEP GUI Execution DB

14. Security/Privacy Related Questions • STEEP is integrated into a live clinical environment: • Interact with personnel (providers) with different roles • Exchanges information with external systems • How to control access to data and functionality? • What are the consequences of access violations? • Privacy • Safety

15. Integration Architecture Closed Environment Lab System Patient Management System Nursing System Medication Tracking System CPOE Patient Website • Authentication • Does information leave the closed environment (on a new path)? • Clinical trial evaluation: Conforms with HIPAA? • Non-discrimination • Opt-out option • Tracking of patient information used for the purpose of research User-specific Settings Role-specific Settings Patient Management System Surveillance Tool (Sepsis Alert) EMR DB Service (Data Integration) CPOE (Order Management) DB Rule Execution Centralized Data Cache UI Dashboard DB Historic Data Warehouse DB STEEP GUI STEEP (Sepsis Management) STEEP GUI Execution DB

16. Initial Analysis

17. Outline • STEEP: Project Overview • Integration Challenge • Systems architecture • Approach • Reusability Challenge • Knowledge architecture • Approach • Ongoing work

18. Lessons Learnt • Development of the Clinical Process Modeling Language (CPML) has been a significant effort • CPML integrates many different kinds of knowledge (medical guidelines, execution semantics, privacy policies, interface abstractions of connected systems, etc.) • Our conclusion is that for future problem domains we need to decompose the knowledge CPML into sub-languages that capture separate knowledge components and obtain Protocol Models via model composition • Reusable model libraries built for these separate aspects will then be used to generate the integrated domain specific models

19. Status of the Modeling Language • Medical guideline modeling using ontology language • general medical ontology, condition specific ontology, HCO specific ontology • Execution platform modeling • processes, triggering events, actions temporal relations • Interface modeling • messages, information content, agents • Policy modeling • roles, messages, information content,constraints

20. Composition of Modelsusing Model-based Techniques Sepsis Medical Ontology Modeling of STEEP Execution Semantics Execution Platform Models Medical Ontology Models T Protocol Models HCO-specific Data Concepts HCO-specific Action Concepts HCO-specific Security & Privacy Policies UI Configuration Patient-based CIG Specialization + + HCO-specific, Integrated, Executable Protocol Models + + + + + + + +

21. Summary • Model-integrated TRUST testbed • Clinical process modeling with privacy rules • Being introduced in ICUs at VUMC • Lessons Learnt • Separation on concerns is important • Use of models can help • Supports reuse • Provides analyzability