Tonya Hongsermeier

Publications of Tonya Hongsermeier

• A legal framework to enable sharing of Clinical Decision Support knowledge and services across institutional boundaries.

  Authors: Tonya Hongsermeier, Saverio Maviglia, Lana Tsurikova, Dan Bogaty, Roberto A Rocha, Howard Goldberg, Seth Meltzer, Blackford Middleton

  AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium. 01/2011; 2011:925-33.

  The goal of the CDS Consortium (CDSC) is to assess, define, demonstrate, and evaluate best practices for knowledge management and clinical decision support in healthcare information technology atThe goal of the CDS Consortium (CDSC) is to assess, define, demonstrate, and evaluate best practices for knowledge management and clinical decision support in healthcare information technology at scale - across multiple ambulatory care settings and Electronic Health Record technology platforms. In the course of the CDSC research effort, it became evident that a sound legal foundation was required for knowledge sharing and clinical decision support services in order to address data sharing, intellectual property, accountability, and liability concerns. This paper outlines the framework utilized for developing agreements in support of sharing, accessing, and publishing content via the CDSC Knowledge Management Portal as well as an agreement in support of deployment and consumption of CDSC developed web services in the context of a research project under IRB oversight.

• Creating shareable decision support services: an interdisciplinary challenge.

  Authors: Marilyn D Paterno, Saverio M Maviglia, Harley Z Ramelson, Molly Schaeffer, Beatriz H Rocha, Tonya Hongsermeier, Adam Wright, Blackford Middleton, Howard S Goldberg

  AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium. 01/2010; 2010:602-6.

  Creating shareable decision support services is a complex task requiring effort from multiple interdisciplinary role players with a wide variety of experience and expertise. The CDS ConsortiumCreating shareable decision support services is a complex task requiring effort from multiple interdisciplinary role players with a wide variety of experience and expertise. The CDS Consortium research project has developed such a service, defining a multi-layer representation of knowledge and building upon an architectural service design created at Partners Health Care, and is demonstrating its use in both a local and an external institutional setting. The process was iterative, and we encountered unexpected requirements based on decisions made at various points. We report in this paper on challenges we faced while pursuing this research: knowledge representation and modeling, data interchange and standards adoption, the process of getting agreement on content, logistics of integrating into a system that already has multiple CDS interventions, legal issues around privacy and access, inter-team communication and organization.

• The morningside initiative: collaborative development of a knowledge repository to accelerate adoption of clinical decision support.

  Authors: Robert Greenes, Meryl Bloomrosen, Nancy E Brown-Connolly, Clayton Curtis, Don E Detmer, Robert Enberg, Douglas Fridsma, Emory Fry, Mary K Goldstein, Peter Haug, Nathan Hulse, Tonya Hongsermeier, Saverio Maviglia, Craig W Robbins, Hemant Shah

  The open medical informatics journal. 01/2010; 4:278-90.

  The Morningside Initiative is a public-private activity that has evolved from an August, 2007, meeting at the Morningside Inn, in Frederick, MD, sponsored by the Telemedicine and Advanced TechnologyThe Morningside Initiative is a public-private activity that has evolved from an August, 2007, meeting at the Morningside Inn, in Frederick, MD, sponsored by the Telemedicine and Advanced Technology Research Center (TATRC) of the US Army Medical Research Materiel Command. Participants were subject matter experts in clinical decision support (CDS) and included representatives from the Department of Defense, Veterans Health Administration, Kaiser Permanente, Partners Healthcare System, Henry Ford Health System, Arizona State University, and the American Medical Informatics Association (AMIA). The Morningside Initiative was convened in response to the AMIA Roadmap for National Action on Clinical Decision Support and on the basis of other considerations and experiences of the participants. Its formation was the unanimous recommendation of participants at the 2007 meeting which called for creating a shared repository of executable knowledge for diverse health care organizations and practices, as well as health care system vendors. The rationale is based on the recognition that sharing of clinical knowledge needed for CDS across organizations is currently virtually non-existent, and that, given the considerable investment needed for creating, maintaining and updating authoritative knowledge, which only larger organizations have been able to undertake, this is an impediment to widespread adoption and use of CDS. The Morningside Initiative intends to develop and refine (1) an organizational framework, (2) a technical approach, and (3) CDS content acquisition and management processes for sharing CDS knowledge content, tools, and experience that will scale with growing numbers of participants and can be expanded in scope of content and capabilities. Intermountain Healthcare joined the initial set of participants shortly after its formation. The efforts of the Morningside Initiative are intended to serve as the basis for a series of next steps in a national agenda for CDS. It is based on the belief that sharing of knowledge can be highly effective as is the case in other competitive domains such as genomics. Participants in the Morningside Initiative believe that a coordinated effort between the private and public sectors is needed to accomplish this goal and that a small number of highly visible and respected health care organizations in the public and private sector can lead by example. Ultimately, a future collaborative knowledge sharing organization must have a sustainable long-term business model for financial support.

• Creating and sharing clinical decision support content with Web 2.0: Issues and examples.

  Authors: Adam Wright, David W Bates, Blackford Middleton, Tonya Hongsermeier, Vipul Kashyap, Sean M Thomas, Dean F Sittig

  Journal of biomedical informatics. 11/2008;

  Clinical decision support is a powerful tool for improving healthcare quality and patient safety. However, developing a comprehensive package of decision support interventions is costly andClinical decision support is a powerful tool for improving healthcare quality and patient safety. However, developing a comprehensive package of decision support interventions is costly and difficult. If used well, Web 2.0 methods may make it easier and less costly to develop decision support. Web 2.0 is characterized by online communities, open sharing, interactivity and collaboration. Although most previous attempts at sharing clinical decision support content have worked outside of the Web 2.0 framework, several initiatives are beginning to use Web 2.0 to share and collaborate on decision support content. We present case studies of three efforts: the Clinfowiki, a world-accessible wiki for developing decision support content; Partners Healthcare eRooms, web-based tools for developing decision support within a single organization; and Epic Systems Corporation's Community Library, a repository for sharing decision support content for customers of a single clinical system vendor. We evaluate the potential of Web 2.0 technologies to enable collaborative development and sharing of clinical decision support systems through the lens of three case studies; analyzing technical, legal and organizational issues for developers, consumers and organizers of clinical decision support content in Web 2.0. We believe the case for Web 2.0 as a tool for collaborating on clinical decision support content appears strong, particularly for collaborative content development within an organization.

• A study on Design and Development of Enterprise-wide Concepts for Clinical Documentation Templates.

  Authors: Li Zhou, Rupali Gurjar, Rachel Regier, Stephen J Morgan, Theresa Meyer, Teal P Aroy, Debora Scavone Goldman, Tonya Hongsermeier, Blackford Middleton

  AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium. 02/2008;

  Structured clinical documents are associated with many potential benefits. Underlying terminologies and structure of information are keys to their successful implementation and use. This paperStructured clinical documents are associated with many potential benefits. Underlying terminologies and structure of information are keys to their successful implementation and use. This paper presents a methodology for design and development of enterprise-wide concepts for clinical documentation templates for an ambulatory Electronic Medical Record (EMR) system.

• The Semantic Web in action.

  Authors: Lee Feigenbaum, Ivan Herman, Tonya Hongsermeier, Eric Neumann, Susie Stephens

  Scientific American. 01/2008; 297(6):64-71.

• Advancing translational research with the Semantic Web.

  Authors: Alan Ruttenberg, Tim Clark, William Bug, Matthias Samwald, Olivier Bodenreider, Helen Chen, Donald Doherty, Kerstin Forsberg, Yong Gao, Vipul Kashyap [......] Chimezie Ogbuji, Jonathan Rees, Susie Stephens, Gwendolyn T Wong, Elizabeth Wu, Davide Zaccagnini, Tonya Hongsermeier, Eric Neumann, Ivan Herman, Kei-Hoi Cheung

  BMC bioinformatics. 02/2007; 8 Suppl 3:S2.

  BACKGROUND: A fundamental goal of the U.S. National Institute of Health (NIH) "Roadmap" is to strengthen Translational Research, defined as the movement of discoveries in basic research toBACKGROUND: A fundamental goal of the U.S. National Institute of Health (NIH) "Roadmap" is to strengthen Translational Research, defined as the movement of discoveries in basic research to application at the clinical level. A significant barrier to translational research is the lack of uniformly structured data across related biomedical domains. The Semantic Web is an extension of the current Web that enables navigation and meaningful use of digital resources by automatic processes. It is based on common formats that support aggregation and integration of data drawn from diverse sources. A variety of technologies have been built on this foundation that, together, support identifying, representing, and reasoning across a wide range of biomedical data. The Semantic Web Health Care and Life Sciences Interest Group (HCLSIG), set up within the framework of the World Wide Web Consortium, was launched to explore the application of these technologies in a variety of areas. Subgroups focus on making biomedical data available in RDF, working with biomedical ontologies, prototyping clinical decision support systems, working on drug safety and efficacy communication, and supporting disease researchers navigating and annotating the large amount of potentially relevant literature. RESULTS: We present a scenario that shows the value of the information environment the Semantic Web can support for aiding neuroscience researchers. We then report on several projects by members of the HCLSIG, in the process illustrating the range of Semantic Web technologies that have applications in areas of biomedicine. CONCLUSION: Semantic Web technologies present both promise and challenges. Current tools and standards are already adequate to implement components of the bench-to-bedside vision. On the other hand, these technologies are young. Gaps in standards and implementations still exist and adoption is limited by typical problems with early technology, such as the need for a critical mass of practitioners and installed base, and growing pains as the technology is scaled up. Still, the potential of interoperable knowledge sources for biomedicine, at the scale of the World Wide Web, merits continued work.

• Research Paper: A Description and Functional Taxonomy of Rule-based Decision Support Content at a Large Integrated Delivery Network.

  Authors: Adam Wright, Howard Goldberg, Tonya Hongsermeier, Blackford Middleton

  JAMIA. 01/2007; 14:489-496.

• Creation of structured documentation templates using Natural Language Processing techniques.

  Authors: Vipul Kashyap, Alexander Turchin, Laura Morin, Frank Chang, Qi Li, Tonya Hongsermeier

  AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium. 02/2006;

  Structured Clinical Documentation is a fundamental component of the healthcare enterprise, linking both clinical (e.g., electronic health record, clinical decision support) and administrativeStructured Clinical Documentation is a fundamental component of the healthcare enterprise, linking both clinical (e.g., electronic health record, clinical decision support) and administrative functions (e.g., evaluation and management coding, billing). One of the challenges in creating good quality documentation templates has been the inability to address specialized clinical disciplines and adapt to local clinical practices. A one-size-fits-all approach leads to poor adoption and inefficiencies in the documentation process. On the other hand, the cost associated with manual generation of documentation templates is significant. Consequently there is a need for at least partial automation of the template generation process. We propose an approach and methodology for the creation of structured documentation templates for diabetes using Natural Language Processing (NLP).

• On implementing clinical decision support: achieving scalability and maintainability by combining business rules and ontologies.

  Authors: Vipul Kashyap, Alfredo Morales, Tonya Hongsermeier

  AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium. 02/2006;

  We present an approach and architecture for implementing scalable and maintainable clinical decision support at the Partners HealthCare System. The architecture integrates a business rules engineWe present an approach and architecture for implementing scalable and maintainable clinical decision support at the Partners HealthCare System. The architecture integrates a business rules engine that executes declarative if-then rules stored in a rule-base referencing objects and methods in a business object model. The rules engine executes object methods by invoking services implemented on the clinical data repository. Specialized inferences that support classification of data and instances into classes are identified and an approach to implement these inferences using an OWL based ontology engine is presented. Alternative representations of these specialized inferences as if-then rules or OWL axioms are explored and their impact on the scalability and maintenance of the system is presented. Architectural alternatives for integration of clinical decision support functionality with the invoking application and the underlying clinical data repository; and their associated trade-offs are discussed and presented.

• Design and implementation of a clinical rule editor for chronic disease reminders in an electronic medical record.

  Authors: Rupali Gurjar, Qi Li, Donald Bugbee, Judith Colecchi, Michael Sperling, Andrew Karson, Thomas Sequist, Tonya Hongsermeier, Eric G Poon

  AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium. 02/2006;

  Clinical reminders have well-documented benefits in improving quality of care. Once clinicians approve evidence-based rules, they should be quickly implemented. However, most of the reminders in ourClinical reminders have well-documented benefits in improving quality of care. Once clinicians approve evidence-based rules, they should be quickly implemented. However, most of the reminders in our home-grown EMR historically were hard-coded, making it difficult to maintain old rules and implement new ones. We designed a web-based editor to make rule logic readable and editable by non-programmers. We hope to decrease the turnaround time of reminder authoring and maintenance, thereby improving quality of care.

• A Knowledge Management platform for Translational Medicine.

  Authors: Tonya Hongsermeier, Vipul Kashyap

  AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium. 02/2005;

• Definitions Management: A Semantics-Based Approach for Clinical Documentation in Healthcare Delivery.

  Authors: Vipul Kashyap, Alfredo Morales, Tonya Hongsermeier, Qi Li

  The Semantic Web - ISWC 2005, 4th International Semantic Web Conference, ISWC 2005, Galway, Ireland, November 6-10, 2005, Proceedings; 01/2005

• A description and functional taxonomy of rule-based decision support content at a large integrated delivery network.

  Authors: Adam Wright, Howard Goldberg, Tonya Hongsermeier, Blackford Middleton

  Journal of the American Medical Informatics Association : JAMIA. 14(4):489-96.

  OBJECTIVE: This study sought to develop a functional taxonomy of rule-based clinical decision support. DESIGN: The rule-based clinical decision support content of a large integrated delivery networkOBJECTIVE: This study sought to develop a functional taxonomy of rule-based clinical decision support. DESIGN: The rule-based clinical decision support content of a large integrated delivery network with a long history of computer-based point-of-care decision support was reviewed and analyzed along four functional dimensions: trigger, input data elements, interventions, and offered choices. RESULTS: A total of 181 rule types were reviewed, comprising 7,120 different instances of rule usage. A total of 42 taxa were identified across the four categories. Many rules fell into multiple taxa in a given category. Entered order and stored laboratory result were the most common triggers; laboratory result, drug list, and hospital unit were the most frequent data elements used. Notify and log were the most common interventions, and write order, defer warning, and override rule were the most common offered choices. CONCLUSION: A relatively small number of taxa successfully described a large body of clinical knowledge. These taxa can be directly mapped to functions of clinical systems and decision support systems, providing feature guidance for developers, implementers, and certifiers of clinical information systems.