GPSS: Health Information System for Genetic Prognosis Support

1. Integrative Computational BioScience Center GPSS: Health Information System for Genetic Prognosis Support Adison Wichiencharoen, BoonsitYimwadsana, CharnyotePluempitiwiriyawej, and ApirakHoonlor 28 Nov 2013 The National Conference on Medical Informatics (NCMedInfo 2013)

2. Agenda • Introduction • Background • Motivation and GPSS • GPSS as a Clinical Service • Development and Evaluation of GPSS

3. Introduction • Medical informatics is a discipline that integrates information science, computer science and health care together. • Medical informatics is also known as health informatics or health information systems • Thanks to the advance in medical technology and information technology, physicians in hospital today can use large amount of data recorded electronically or produced by medical equipment to provide better care. • A majority of work in the field of medical and health informatics, especially in Thailand, focus on hospital information systems. However, little work address the clinical research system.

4. Background • Electronic Health/Medical Record (EHR/EMR) • Used to be called “computerized provider order entry (CPOE)” existed for more than 30 years. • Used mainly in order to reduce physical storage space and reduce data-reading error. • Electronic data is also easier to manage and secure than physical paper-based data. • According to Center for Disease Control (CDC), United States, in 2012, integrated EHR/EMR adoption rate was 72 %. • EHR/EMR is often used to keep patients’ information for information retrieval purpose, billing, and insurance. Information is organized and structured. • Most physicians find the data gathering phase of EHR/EMR time-consuming and overly complex when the EHR/EMR is used to manage large amount of data inefficiently.

5. Example of EHR/EMR Systems

6. EHR/EMR Data Collection • EHR/EMR data today collect information for the purpose of • Epidemiology • Clinical studies • Track care (e.g. prescriptions and treatments) • Track patients’ progress and outcomes • Trigger warnings and reminders • Send and receive orders, reports, and results for communication purpose (Customer Relationship Management, Government and Legal Compliance, etc) • Handwriting recognition has been used successfully in some settings, in particular English language.

7. Motivation and GPSS • Most EHR/EMR systems are designed to fit the general need of hospital and physician office. • The EHR/EMR systems are not suitable for individual need of physicians who conduct cutting-edge research for better treatment. For example, effective treatments for westerners may be inefficient for Thai people especially for genetic disease. Thai physicians using western EHR/EMR system would like to modify the system to accommodate their need. This will not be simple to do. • Most genetic diseases cannot be treated and cured quickly. Technical genetic information is not designed to be recorded in general EHR/EMR systems.

8. GPSS Data Collection • Genetic Prognosis Support System is designed to support mainly the need of physicians for clinical studies which include, but not limited to, the collection of data such as • Disease specific information (e.g. trigger age, hypothesized cause, and organ specific information.) • For example, data such as “when the patient did begin to unable to walk regularly” and “state of the patient’s walk pattern” may not be captured by general EHR/EMR systems. • Genetic information (e.g. family disease information and gene-specific information about the disease) • In general, EHR/EMR systems do not link patients together to form a well defined pedigree chart which can be used to track genetic heredity of diseases. • General EHR/EMR systems cannot support specific collection of gene data. There are too many genes to record for diseases. Effective genetic database has to be designed.

9. GPSS System Architecture • GPSS system architecture is based on MVC (Model-View-Controller) model View Controller Model

10. GPSS Interfaces • Follow best practices in software engineering’s “business requirement engineering” and “human computer interaction” to create the best view for system users. • Key issues: • Rapid and accurate data input method • reduce time-consuming electronic data input method such as mouse-click and unguided data fields or free text input • Increase time-reduction electronic data input method such as keyboard tab sequence, drop-down list, default values, and autocomplete. • Intuitive and organized data input form layout. • Understand human eye movement. • Streamline, sequential and meaningful data input fields • Semantics of data must be taken into account in developing flow of form fields.

11. GPSS Database • GPSS database is integral to the success of GPSS system as the system’s model. The GPSS database must be designed carefully to support the collection of data in the database so that the data is stored in organized, structured, and efficient manner or the purpose of information retrieval. • The data stored in the database must be pertinent to the physicians’ need. Unnecessary data take up data storage area and incomplete data results in inaccurate research and deficient or ineffective treatments.

12. Clinical Record Management System • CRMS is a controller component for the data transaction used for collecting patients’ clinical information specific for each diseases. • CRMS is essentially a database application providing efficient CRUD (create, retrieve, update, delete) transaction of data. • CRMS accepts data and query from GPSS interface, execute the query on the GPSS database, and return the data output back to the GPSS interface (which may transform raw data into tables, charts, and reports) for users.

13. CRMS Implementation • We develop three web-based systems to demonstrate the concept of CRMS for the following diseases • Duchenne Muscular Dystrophy (DMD) • Hereditary Colorectal Cancer (HCC) • Von Hippel-Lindau Syndrome (VHL) • We learn that different diseases require different system model (MVC) due to the nature of the diseases. • Some data such as patients’ profile can be shared but not disease specific information • Physicians may order different lab to patients for different diseases (in some cases, even for the same disease depending on patients’ health situation)

14. CRMS Implementation

15. Software Development Lifecycle • Based on software engineering concept, there are mainly two models. Agile Model Waterfall Model

16. Clinical Pedigree Management System • Family pedigree is needed in order to study genetic trail of Thai families. • From interviews with physicians, family disease history is not kept accurately and extensively. • Many Thai people do not know the actual death or disease of their ancestors due to poor medical recording systems. • A large number of medical records were destroyed due to major floods and fire. • Human has long lifespan. In order to use pedigree to study a genetic disease, information of at least 30 – 50 years is needed. • Patients’ records from different repositories must be integrated and linked to discover genetic relationship.

17. Implementation • Pediew is a first version of the pedigree drawing program used to solve the problem of paper-based drawing. • Some drawing cannot be modified easily in paper. • Some drawing is too large to be drawn on paper. • Pediew links directly to Clinical Record Management System using web information exchange standard (e.g. XML). • Patient profiles can be linked together based on family relationship stored in Pediew.

18. Pediew Implementation

19. Genetic-Disease Data Analysis System • In essence, GDAS is used to provide easy-to-read reports to physicians. • The report engine are more than just information retrieval. Information is analyzed and structurally reported in tabular or visualized format using business intelligence, and data mining/machine learning methods so that physicians can acquire knowledge not provided by general EHR/EMR systems.

20. Genetic-Disease Data Analysis System • Questions such as the followings can be answered: • What are the number of patients and families in the database? • How many families have more than one person who have this illness and who are they? • How many members in a family have been tested for carrier possibility? • What are the most common symptoms for a disease? • How many patients have a specific symptom? • Since last year, what is the lab test progress of a specific patient? • In the last 3 months, what are the treatments given to a specific patient? • What is the doctor’s first diagnosis on a specific patient?

21. CRMS Implementation

22. GPSS as a Service • GPSS could be designed as a web service under the three tier model under the Service-Oriented Architecture (SOA) consisting of • End-user computer systems • Web service • Database service

23. GPSS as a Service

24. Initial Testing and Evaluation Results • Unit tests were conducted on the subsystems of pedigree chart drawing program, and the clinical information systems of DMD, HCC, and VHL. The data used for these tests were based on the physicians’ requirements, and the synthetic medical data provided by the physicians in order to avoid the use of real sensitive patient data. • System integration test is performed to verify the linkage between the Clinical Pedigree Management System and Clinical Record Management System together.

25. Issues and Future works • Different data requirements of each different disease • Data standard compliance • Information security • Personalized data collection and reporting system

26. Thank You