1. Veronica's Story

    05:13

    from CCNC / Added

    Story of how Cabarrus Family Medicine's Virtual Care project for monitoring diabetes helps a patient cope and successfully manage her condition.

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    • Supporting Clinical Decisions with Computers - Part 2: Overview of CDSS types and examples

      18:55

      from CIOHTR / Added

      13 Plays / / 0 Comments

      Clinical decision making is a complex process that dentists spend years learning and improving. It can be supported—to a certain degree—by computerized decision support systems (DSS). Both passive and active DSSs can help improve decision making performance in specific contexts, and for specific tasks and levels of expertise. This module provides an overview of dental decision making and how it can be supported by computers. We first explore the basics of medical decision making, and highlight commonalities with and differences from dental decision making. Based on this discussion, we explore the different goals of computerized decision support systems (DSS), such as automating low-level, simple decisions; improving expert performance on difficult and/or rare decisions; and avoiding medical errors. DSSs are typically classified into passive and active systems. Passive DSSs simply provide information to the practitioner without any inferencing, i.e. processing or calculating. Active DSSs, on the other hand, perform operations on the information that result in specific recommendations or suggestions for the practitioner. The module will cover different inferencing methods, such as Bayesian Reasoning and production rules, as well as sample different systems.

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      • Supporting clinical decisions with computers: Part 1 - Applications and computational decision methods

        27:01

        from CIOHTR / Added

        8 Plays / / 0 Comments

        Clinical decision making is a complex process that dentists spend years learning and improving. It can be supported—to a certain degree—by computerized decision support systems (DSS). Both passive and active DSSs can help improve decision making performance in specific contexts, and for specific tasks and levels of expertise. This module provides an overview of dental decision making and how it can be supported by computers. We first explore the basics of medical decision making, and highlight commonalities with and differences from dental decision making. Based on this discussion, we explore the different goals of computerized decision support systems (DSS), such as automating low-level, simple decisions; improving expert performance on difficult and/or rare decisions; and avoiding medical errors. DSSs are typically classified into passive and active systems. Passive DSSs simply provide information to the practitioner without any inferencing, i.e. processing or calculating. Active DSSs, on the other hand, perform operations on the information that result in specific recommendations or suggestions for the practitioner. The module will cover different inferencing methods, such as Bayesian Reasoning and production rules, as well as sample different systems.

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        • Mosess Lake

          03:02

          from INHSPR / Added

          299 Plays / / 0 Comments

          Find out how INHS is working with rural hospitals to increase patient care.

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          • Building a bridge to the future with informatics

            49:56

            from Titus Schleyer / Added

            35 Plays / / 0 Comments

            This presentation reviews the status of electronic dental records, discusses the current movement towards quality in healthcare and suggests a few things that dentistry could do to take advantage of the rising computerization of dental practice. The electronic dental record (EDR) market is dominated by three large companies (Dentrix, Patterson Dental and Carestream) and a number of smaller ones. EDR adoption has risen rapidly over the last few years – it is currently at about 70%, with about 15% of all dentists being paperless. Despite their rapid development, problems of usability and information coverage in EDRs persist. At the same time, there is a national movement in the United States towards developing a "learning Healthcare System," in which data gathered during daily clinical practice become a cornerstone for outcomes assessment and quality improvement. We are currently developing a method for extracting and analyzing clinical dental data that is based on ontologies, and has the potential for supporting a "Learning Dental Care System." To move forward with improving dental care at a national scale, we need to begin reusing EDR data and leverage them for disease surveillance, comparative effectiveness research and disease registries. At the same time, we need to develop a workforce that can help us implement these advances into daily clinical practice.

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            • Controlled vocabularies, terminologies and ontologies - Part 2: Controlled vocabularies and terminologies

              21:28

              from CIOHTR / Added

              22 Plays / / 0 Comments

              This video is part of the online course "Introduction to Health Information Technology in Dentistry," a course in the University of Pittsburgh's Online Certificate Program in Biomedical Informatics (see http://www.dbmi.pitt.edu/content/online-certificate-program). Controlled vocabularies, terminologies and ontologies are instances of the models used to represent concepts in computers, either alone or in combination. The boundaries between them are not clearly defined and we will leave the more philosophical distinctions among them aside. Instead, we will take a practical look at existing and emerging vocabularies, terminologies and ontologies, such as the International Classification of Diseases (ICD), the Leake Codes, the EZcodes and the Systematized Nomenclature of Dentistry (SNODENT).

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              • Controlled vocabularies, terminologies and ontologies - Part 1: Representing real world concepts on computers

                18:17

                from CIOHTR / Added

                38 Plays / / 0 Comments

                This video is part of the online course "Introduction to Health Information Technology in Dentistry," a course in the University of Pittsburgh's Online Certificate Program in Biomedical Informatics (see http://www.dbmi.pitt.edu/content/online-certificate-program). This module will build on the concepts discussed in “Dental data and their representation” to explore further how computers represent the external world. A discussion of three kinds of models, i.e. information, terminology, and inference models, will be complemented by a review of existing controlled vocabularies, terminologies and ontologies.

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                • Dental data and their representation - Part 1: Representing the real world through bits

                  15:27

                  from CIOHTR / Added

                  18 Plays / / 0 Comments

                  This video is part of the online course "Introduction to Health Information Technology in Dentistry," a course in the University of Pittsburgh's Online Certificate Program in Biomedical Informatics (see http://www.dbmi.pitt.edu/content/online-certificate-program). Computers represent data differently from the way we do. While humans think in terms of numbers, text, pictures, colors and sounds, computers can think in only one unit: bits. This module will take you on a fascinating journey into how computers represent everyday data and information internally in the form of bits, data types and databases. This video, Part 1 of a two-part series, discusses how dental information is stored by computers as data and bits.

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                  • Dental data and their representation - Part 2: data types and information representation

                    17:01

                    from CIOHTR / Added

                    20 Plays / / 0 Comments

                    This video is part of the online course "Introduction to Health Information Technology in Dentistry," a course in the University of Pittsburgh's Online Certificate Program in Biomedical Informatics (see http://www.dbmi.pitt.edu/content/online-certificate-program). Computers represent data differently from the way we do. While humans think in terms of numbers, text, pictures, colors and sounds, computers can think in only one unit: bits. This module will take you on a fascinating journey into how computers represent everyday data and information internally in the form of bits, data types and databases. This video, Part 2 of a two-part series, discusses different data types and information representation in dental software.

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                    • NeHC stakeholder survey reveals focus on patient engagement, HIE benefits

                      03:05

                      from TriMed Media Group / Added

                      HIMSS 2013: Kate Berry, CEO of National eHealth Collaborative (NeHC), came to the Health Information and Management Systems Society annual conference in New Orleans to present the results of the 2013 NeHC Stakeholder Survey. Here are some of the headline findings.

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