Browsing by Subject "CDSS"

Now showing 1 - 3 of 3
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    A Coherent Healthcare System with RDBMS, NoSQL and GIS Databases
    (2017) Wu, Huanmei; Ambavane, Ashish; Mukherjee, Sunanda; Mao, Songan; BioHealth Informatics, School of Informatics and Computing
    With new database system development and new data types emerging, many applications are no longer using a monolithic, simple client/server structure, but using more than one types of database systems to store heterogeneous data. In this project, we exploit the benefits of combing Relational Database Management System (RDBMS) and NoSQL systems in the development of better Electronic Health Records (EHRs) and Clinical Decision Support Systems (CDSS). Specifically, MySQL, MongoDB, and GIS databases are integrated to improve EHR systems and to provide better clinical decision supports. The ACID (atomicity, consistency, isolation, durability) properties of the RDBMS ensure data integrity, database security, efficient SQL queries, easy data access, and effective transaction processing. MongoDB provides the system with clear internal data structure, easy scaling-out, fine-Tuning, and convenient mapping of application objects to the database objects. The GIS database allows vivid visualization of the geographic locations of patients, physician offices, and medical facilities. The integrations of these database systems in healthcare help application systems to comply with the EHR HIPAA requirements without compromising on scalability and performance.
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    Leveraging electronic tablets for general pediatric care: a pilot study
    (Schattauer, 2015) Anand, V.; McKee, S.; Dugan, T. M.; Downs, S. M.; Department of Pediatrics, IU School of Medicine
    BACKGROUND: We have previously shown that a scan-able paper based interface linked to a computerized clinical decision support system (CDSS) can effectively screen patients in pediatric waiting rooms and support the physician using evidence based care guidelines at the time of clinical encounter. However, the use of scan-able paper based interface has many inherent limitations including lacking real time communication with the CDSS and being prone to human and system errors. An electronic tablet based user interface can not only overcome these limitations, but may also support advanced functionality for clinical and research use. However, use of such devices for pediatric care is not well studied in clinical settings. OBJECTIVE: In this pilot study, we enhance our pediatric CDSS with an electronic tablet based user interface and evaluate it for usability as well as for changes in patient questionnaire completion rates. METHODS: Child Health Improvement through Computers Leveraging Electronic Tablets or CHICLET is an electronic tablet based user interface. It is developed to augment the existing scan-able paper interface to our CDSS. For the purposes of this study, we deployed CHICLET in one outpatient pediatric clinic. Usability factors for CHICLET were evaluated via caregiver and staff surveys. RESULTS: When compared to the scan-able paper based interface, we observed an 18% increase or 30% relative increase in question completion rates using CHICLET. This difference was statistically significant. Caregivers and staff survey results were positive for using CHICLET in clinical environment. CONCLUSIONS: Electronic tablets are a viable interface for capturing patient self-report in pediatric waiting rooms. We further hypothesize that the use of electronic tablet based interfaces will drive advances in computerized clinical decision support and create opportunities for patient engagement.
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    A patient-oriented clinical decision support system for CRC risk assessment and preventative care
    (BioMed Central, 2018-12-07) Liu, Jiannan; Li, Chenyang; Xu, Jing; Wu, Huanmei; Biohealth Informatics, School of Informatics and Computing
    Colorectal Cancer (CRC) is the third leading cause of cancer death among men and women in the United States. Research has shown that the risk of CRC associates with genetic and lifestyle factors. It is possible to prevent or minimize certain CRC risks by adopting a healthy lifestyle. Existing Clinical Decision Support Systems (CDSS) mainly targeted physicians as the CDSS users. As a result, the availability of patient-oriented CDSS is limited. Our project is to develop patient-oriented CDSS for active CRC management.