Browsing by Author "Simonaitis, Linas"

Now showing 1 - 5 of 5
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    Building a Production-Ready Infrastructure to Enhance Medication Management: Early Lessons from the Nationwide Health Information Network
    (2009-11) Simonaitis, Linas; Dixon, Brian E.; Belsito, Anne; Miller, Theda; Overhage, J. Marc
    Poor medication management practices can lead to serious erosion of health care quality and safety. The DHHS Medication Management Use Case outlines methods for the exchange of electronic health information to improve medication management practices. In this case report, the authors describe initial development of Nationwide Health Information Network (NHIN) services to support the Medication Management Use Case. The technical approach and core elements of medication management transactions involved in the NHIN are presented. Early lessons suggest the pathway to improvements in quality and safety are achievable, yet there are challenges for the medical informatics community to address through future research and development activities.
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    Lessons Learned from Implementing Service-Oriented Clinical Decision Support at Four Sites: A Qualitative Study
    (Elsevier, 2015-11) Wright, Adam; Sittig, Dean F.; Ash, Joan S.; Erickson, Jessica L.; Hickman, Trang T.; Paterno, Marilyn; Gebhardt, Eric; McMullen, Carmit; Tsurikova, Ruslana; Dixon, Brian E.; Fraser, Greg; Simonaitis, Linas; Sonnenberg, Frank A.; Middleton, Blackford; Department of Epidemiology, Richard M. Fairbanks School of Public Health
    Objective To identify challenges, lessons learned and best practices for service-oriented clinical decision support, based on the results of the Clinical Decision Support Consortium, a multi-site study which developed, implemented and evaluated clinical decision support services in a diverse range of electronic health records. Methods Ethnographic investigation using the rapid assessment process, a procedure for agile qualitative data collection and analysis, including clinical observation, system demonstrations and analysis and 91 interviews. Results We identified challenges and lessons learned in eight dimensions: (1) hardware and software computing infrastructure, (2) clinical content, (3) human-computer interface, (4) people, (5) workflow and communication, (6) internal organizational policies, procedures, environment and culture, (7) external rules, regulations, and pressures and (8) system measurement and monitoring. Key challenges included performance issues (particularly related to data retrieval), differences in terminologies used across sites, workflow variability and the need for a legal framework. Discussion Based on the challenges and lessons learned, we identified eight best practices for developers and implementers of service-oriented clinical decision support: (1) optimize performance, or make asynchronous calls, (2) be liberal in what you accept (particularly for terminology), (3) foster clinical transparency, (4) develop a legal framework, (5) support a flexible front-end, (6) dedicate human resources, (7) support peer-to-peer communication, (8) improve standards. Conclusion The Clinical Decision Support Consortium successfully developed a clinical decision support service and implemented it in four different electronic health records and four diverse clinical sites; however, the process was arduous. The lessons identified by the Consortium may be useful for other developers and implementers of clinical decision support services.
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    Measuring agreement between decision support reminders: the cloud vs. the local expert
    (Springer Nature, 2014-04-10) Dixon, Brian Edward; Simonaitis, Linas; Perkins, Susan M.; Wright, Adam; Middleton, Blackford; Biomedical Engineering and Informatics, Luddy School of Informatics, Computing, and Engineering
    Background: A cloud-based clinical decision support system (CDSS) was implemented to remotely provide evidence-based guideline reminders in support of preventative health. Following implementation, we measured the agreement between preventive care reminders generated by an existing, local CDSS and the new, cloud-based CDSS operating on the same patient visit data. Methods: Electronic health record data for the same set of patients seen in primary care were sent to both the cloud-based web service and local CDSS. The clinical reminders returned by both services were captured for analysis. Cohen's Kappa coefficient was calculated to compare the two sets of reminders. Kappa statistics were further adjusted for prevalence and bias due to the potential effects of bias in the CDS logic and prevalence in the relative small sample of patients. Results: The cloud-based CDSS generated 965 clinical reminders for 405 patient visits over 3 months. The local CDSS returned 889 reminders for the same patient visit data. When adjusted for prevalence and bias, observed agreement varied by reminder from 0.33 (95% CI 0.24 - 0.42) to 0.99 (95% CI 0.97 - 1.00) and demonstrated almost perfect agreement for 7 of the 11 reminders. Conclusions: Preventive care reminders delivered by two disparate CDS systems show substantial agreement. Subtle differences in rule logic and terminology mapping appear to account for much of the discordance. Cloud-based CDSS therefore show promise, opening the door for future development and implementation in support of health care providers with limited resources for knowledge management of complex logic and rules.
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    The state of the art in clinical knowledge management: An inventory of tools and techniques
    (2010-01) Sittig, Dean F.; Wright, Adam; Simonaitis, Linas; Carpenter, James D.; Allen, George O.; Doebbeling, Bradley N.; Sirajuddin, Anwar Mohammad; Ash, Joan S.; Middleton, Blackford
    Purpose To explore the need for, and use of, high-quality, collaborative, clinical knowledge management (CKM) tools and techniques to manage clinical decision support (CDS) content. Methods In order to better understand the current state of the art in CKM, we developed a survey of potential CKM tools and techniques. We conducted an exploratory study by querying a convenience sample of respondents about their use of specific practices in CKM. Results The following tools and techniques should be priorities in organizations interested in developing successful computer-based provider order entry (CPOE) and CDS implementations: (1) a multidisciplinary team responsible for creating and maintaining the clinical content; (2) an external organizational repository of clinical content with web-based viewer that allows anyone in the organization to review it; (3) an online, collaborative, interactive, Internet-based tool to facilitate content development; (4) an enterprise-wide tool to maintain the controlled clinical terminology concepts. Even organizations that have been successfully using computer-based provider order entry with advanced clinical decision support features for well over 15 years are not using all of the CKM tools or practices that we identified. Conclusions If we are to further stimulate progress in the area of clinical decision support, we must continue to develop and refine our understanding and use of advanced CKM capabilities.
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    Using a Service Oriented Architecture Approach to Clinical Decision Support: Performance Results from Two CDS Consortium Demonstrations
    (2012-11) Paterno, Marilyn D.; Goldberg, Howard S.; Simonaitis, Linas; Dixon, Brian E.; Wright, Adam; Rocha, Beatriz H.; Ramelson, Harley Z.; Middleton, Blackford
    The Clinical Decision Support Consortium has completed two demonstration trials involving a web service for the execution of clinical decision support (CDS) rules in one or more electronic health record (EHR) systems. The initial trial ran in a local EHR at Partners HealthCare. A second EHR site, associated with Wishard Memorial Hospital, Indianapolis, IN, was added in the second trial. Data were gathered during each 6 month period and analyzed to assess performance, reliability, and response time in the form of means and standard deviations for all technical components of the service, including assembling and preparation of input data. The mean service call time for each period was just over 2 seconds. In this paper we report on the findings and analysis to date while describing the areas for further analysis and optimization as we continue to expand our use of a Services Oriented Architecture approach for CDS across multiple institutions.