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    <title>Slideshows for Tag: informatics</title>
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    <pubDate>Fri, 25 Dec 2009 06:08:51 GMT</pubDate>
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      <title>InSTEDD Mesh4x Platform</title>
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      <pubDate>Fri, 25 Dec 2009 06:08:51 GMT</pubDate>
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        <media:description type="plain">InSTEDD&#8217;s Mesh4x (http://code.google.com/p/mesh4x) allows for data synchronization among different data sources regardless of technology platform or network connectivity. Users can make their data available to all users in their distributed project team or across different jurisdictions. We describe the utility and architecture of Mesh4x to share data over the Internet cloud where users determine which subset of their data are exchanged.  This technology raises the potential to share data (e.g., during outbreak investigation, disaster recovery or humanitarian relief efforts) where multiple people are then allowed access to see each other&#8217;s data, update the information as the event unfolds, and securely exchange data with one another.</media:description>
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      <title>Cultivating an informatics culture within nursing education</title>
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      <pubDate>Sat, 05 Dec 2009 23:34:58 GMT</pubDate>
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      <title>Nursing Informatics Competencies: Self Assessment for Nurses</title>
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        <![CDATA[<img src="http://cdn.slidesharecdn.com/niselfassessment-091205140243-phpapp01-thumbnail-2?1260043420" alt ="" style="border:1px solid #C3E6D8;float:right;" /><br> Presented at 2nd National Nursing Informatics Conference, CNIA, Toronto October 1, 2007]]>
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      <pubDate>Sat, 05 Dec 2009 19:59:00 GMT</pubDate>
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        <media:description type="plain">Presented at 2nd National Nursing Informatics Conference, CNIA, Toronto October 1, 2007</media:description>
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      <title>Nursing Informatics 101 Workshop</title>
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        <![CDATA[<img src="http://cdn.slidesharecdn.com/ni101-091205134707-phpapp02-thumbnail-2?1260042500" alt ="" style="border:1px solid #C3E6D8;float:right;" /><br> Presented at Atlantic Nursing Informatics Conference as PreConference Workshop

October 2008, Halifax, Nova Scotia]]>
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October 2008, Halifax, Nova Scotia]]>
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      <pubDate>Sat, 05 Dec 2009 19:44:48 GMT</pubDate>
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        <media:description type="plain">Presented at Atlantic Nursing Informatics Conference as PreConference Workshop

October 2008, Halifax, Nova Scotia</media:description>
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October 2008, Halifax, Nova Scotia</media:text>
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      <title>Nurses and Informatics: Think You Know Nursing? Take Another Look!</title>
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•	InSTEDD Mesh4X is a light-weight synchroniza-tion platform based on cloud computing and peer-to-peer architectures. This integration platform al-lows teams to share critical information reliably, selectively, timely and securely, with anyone, using any device, regardless of network connection, sys-tems or services.  Network connectivity is not a constant requirement, as Mesh4x can collect and distribute updates among users over SMS, Internet, or through other available means. 
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•	InSTEDD GeoChat is a communications system that lets teams coordinate around events as they unfold, linking field, headquarters, and the local community in a unified effective response.
Presently, these tools are being piloted in the Mekong Basin region of Southeast Asia (Cambodia, Thailand, Laos, and Cambodia), Ushahidi in Kenya, HIV clinics in rural Tanzania, Mongolia, Ghana, and Bangladesh.
Use of mobile telephones for public health events detection and intervention in developing countries has tremendous potential due to low start-up cost and low bandwidth (e.g., SMS gateway). In 2002, mobile subscribers overtook fixed line subscribers worldwide and this occurred across geographic re-gions, socio-demographic criteria (gender, income, age) or economic criteria such as GDP per capita1. In much of sub-Saharan Africa, there are more mobile phones than fixed-line phones2 and the use of mobile phones in many Asian countries is on the rise. Addi-tionally, mobile telephone subscriptions have been growing rapidly since the 1980s in both developing and developed countries. Furthermore, the demand for mobile phones exists beyond reducing the waiting list for traditional wire-line phones 3.
However, technical, financial and regulatory barriers remain great challenges to fully adopting mobile technology as a platform in developing countries. Using mobile phones for health data exchange in developing countries has not been demonstrated giv-en the costs of data transmitted over mobile phone are greater than voice costs 2, 4, language and illitera-cy barriers2, and privacy and security issues since SMS messages can leave a trail. Other challenges include the physical components of a telephone (headset or network) are not isolated but are part of an entire business model that includes pricing plans and other incentives which can provide leverage em-ployed by public health agencies and policymakers.
References
1.	Feldmann V: Mobile overtakes Internet: Implica-tions for Policy and Regulation. International Tele-commjunications Union 2003:1-39 [http://www.itu.int/osg/spu/ni/mobileovertakes/Resources/Mobileovertakes_Paper.pdf]. last accessed 13 March 2009.
2.	Vodafone Policy Paper: Africa: The Impact of Mobile Phones. Vodafone Policy Paper Series Number 2 2005 [http://www.vodafone.com/assets/files/en/AIMP_09032005.pdf]. last accessed 13 March 2009. 
3.	Kundu A, Sarangi N: ICT and Human Develop-ment: Towards Building a Composite Index for Asia. Realizing the Millennium Development Goals. United Nations Development Program (UNDP) Technical Paper:1–35 2004 [http://www.apdip.net/elibrary#rhdr]. last accessed 13 March 2009.
4.	Waldick L: The Best Policy: Telecom Research from an African Perspective. International Devel-opment Research Center Report 2003 [http://www.idrc.ca/en/ev-46209-201-1-DO_TOPIC.html]. last accessed 13 March 2009.]]>
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•	InSTEDD GeoChat is a communications system that lets teams coordinate around events as they unfold, linking field, headquarters, and the local community in a unified effective response.
Presently, these tools are being piloted in the Mekong Basin region of Southeast Asia (Cambodia, Thailand, Laos, and Cambodia), Ushahidi in Kenya, HIV clinics in rural Tanzania, Mongolia, Ghana, and Bangladesh.
Use of mobile telephones for public health events detection and intervention in developing countries has tremendous potential due to low start-up cost and low bandwidth (e.g., SMS gateway). In 2002, mobile subscribers overtook fixed line subscribers worldwide and this occurred across geographic re-gions, socio-demographic criteria (gender, income, age) or economic criteria such as GDP per capita1. In much of sub-Saharan Africa, there are more mobile phones than fixed-line phones2 and the use of mobile phones in many Asian countries is on the rise. Addi-tionally, mobile telephone subscriptions have been growing rapidly since the 1980s in both developing and developed countries. Furthermore, the demand for mobile phones exists beyond reducing the waiting list for traditional wire-line phones 3.
However, technical, financial and regulatory barriers remain great challenges to fully adopting mobile technology as a platform in developing countries. Using mobile phones for health data exchange in developing countries has not been demonstrated giv-en the costs of data transmitted over mobile phone are greater than voice costs 2, 4, language and illitera-cy barriers2, and privacy and security issues since SMS messages can leave a trail. Other challenges include the physical components of a telephone (headset or network) are not isolated but are part of an entire business model that includes pricing plans and other incentives which can provide leverage em-ployed by public health agencies and policymakers.
References
1.	Feldmann V: Mobile overtakes Internet: Implica-tions for Policy and Regulation. International Tele-commjunications Union 2003:1-39 [http://www.itu.int/osg/spu/ni/mobileovertakes/Resources/Mobileovertakes_Paper.pdf]. last accessed 13 March 2009.
2.	Vodafone Policy Paper: Africa: The Impact of Mobile Phones. Vodafone Policy Paper Series Number 2 2005 [http://www.vodafone.com/assets/files/en/AIMP_09032005.pdf]. last accessed 13 March 2009. 
3.	Kundu A, Sarangi N: ICT and Human Develop-ment: Towards Building a Composite Index for Asia. Realizing the Millennium Development Goals. United Nations Development Program (UNDP) Technical Paper:1–35 2004 [http://www.apdip.net/elibrary#rhdr]. last accessed 13 March 2009.
4.	Waldick L: The Best Policy: Telecom Research from an African Perspective. International Devel-opment Research Center Report 2003 [http://www.idrc.ca/en/ev-46209-201-1-DO_TOPIC.html]. last accessed 13 March 2009.]]>
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        <media:description type="plain">Combining the power of the Web with the ubiquity and accuracy of mobile computing, InSTEDD helps teams and organizations communicate, share and analyze information more seamlessly, make better decisions, and take more effective action in the face of a public health threat or natural disaster. The In-STEDD Collaboration Suite consists of three open-source software tools that help public health users detect anomalies, visualize clusters of potential events, predict the rate and spread of a disease out-break and provide decision makers with tools, me-thodologies and processes to investigate the event. These software tools are: 
&#8226;	InSTEDD Mesh4X is a light-weight synchroniza-tion platform based on cloud computing and peer-to-peer architectures. This integration platform al-lows teams to share critical information reliably, selectively, timely and securely, with anyone, using any device, regardless of network connection, sys-tems or services.  Network connectivity is not a constant requirement, as Mesh4x can collect and distribute updates among users over SMS, Internet, or through other available means. 
&#8226;	InSTEDD Evolve is a set of integrated services (analytic, collaborative and visualization) that helps to build and sustain a community of domain experts from the local to the international level.  Evolve is equipped with a machine learning algo-rithm that augment users input and accurately classifies 7 syndromes, 10 transmission modes, over 100 infectious diseases, over 180 micro-organisms, over 140 symptoms, and over 50 chemicals. 
&#8226;	InSTEDD GeoChat is a communications system that lets teams coordinate around events as they unfold, linking field, headquarters, and the local community in a unified effective response.
Presently, these tools are being piloted in the Mekong Basin region of Southeast Asia (Cambodia, Thailand, Laos, and Cambodia), Ushahidi in Kenya, HIV clinics in rural Tanzania, Mongolia, Ghana, and Bangladesh.
Use of mobile telephones for public health events detection and intervention in developing countries has tremendous potential due to low start-up cost and low bandwidth (e.g., SMS gateway). In 2002, mobile subscribers overtook fixed line subscribers worldwide and this occurred across geographic re-gions, socio-demographic criteria (gender, income, age) or economic criteria such as GDP per capita1. In much of sub-Saharan Africa, there are more mobile phones than fixed-line phones2 and the use of mobile phones in many Asian countries is on the rise. Addi-tionally, mobile telephone subscriptions have been growing rapidly since the 1980s in both developing and developed countries. Furthermore, the demand for mobile phones exists beyond reducing the waiting list for traditional wire-line phones 3.
However, technical, financial and regulatory barriers remain great challenges to fully adopting mobile technology as a platform in developing countries. Using mobile phones for health data exchange in developing countries has not been demonstrated giv-en the costs of data transmitted over mobile phone are greater than voice costs 2, 4, language and illitera-cy barriers2, and privacy and security issues since SMS messages can leave a trail. Other challenges include the physical components of a telephone (headset or network) are not isolated but are part of an entire business model that includes pricing plans and other incentives which can provide leverage em-ployed by public health agencies and policymakers.
References
1.	Feldmann V: Mobile overtakes Internet: Implica-tions for Policy and Regulation. International Tele-commjunications Union 2003:1-39 [http://www.itu.int/osg/spu/ni/mobileovertakes/Resources/Mobileovertakes_Paper.pdf]. last accessed 13 March 2009.
2.	Vodafone Policy Paper: Africa: The Impact of Mobile Phones. Vodafone Policy Paper Series Number 2 2005 [http://www.vodafone.com/assets/files/en/AIMP_09032005.pdf]. last accessed 13 March 2009. 
3.	Kundu A, Sarangi N: ICT and Human Develop-ment: Towards Building a Composite Index for Asia. Realizing the Millennium Development Goals. United Nations Development Program (UNDP) Technical Paper:1&#8211;35 2004 [http://www.apdip.net/elibrary#rhdr]. last accessed 13 March 2009.
4.	Waldick L: The Best Policy: Telecom Research from an African Perspective. International Devel-opment Research Center Report 2003 [http://www.idrc.ca/en/ev-46209-201-1-DO_TOPIC.html]. last accessed 13 March 2009.</media:description>
        <media:text type="html">&lt;img src=&quot;http://cdn.slidesharecdn.com/insteddintegratedglobalearlywarningandresponsetahakass-houtamia2009-091113025414-phpapp02-thumbnail-2?1258102534&quot; alt =&quot;&quot; style=&quot;border:1px solid #C3E6D8;float:right;&quot; /&gt;&lt;br&gt; Combining the power of the Web with the ubiquity and accuracy of mobile computing, InSTEDD helps teams and organizations communicate, share and analyze information more seamlessly, make better decisions, and take more effective action in the face of a public health threat or natural disaster. The In-STEDD Collaboration Suite consists of three open-source software tools that help public health users detect anomalies, visualize clusters of potential events, predict the rate and spread of a disease out-break and provide decision makers with tools, me-thodologies and processes to investigate the event. These software tools are: 
&#8226;	InSTEDD Mesh4X is a light-weight synchroniza-tion platform based on cloud computing and peer-to-peer architectures. This integration platform al-lows teams to share critical information reliably, selectively, timely and securely, with anyone, using any device, regardless of network connection, sys-tems or services.  Network connectivity is not a constant requirement, as Mesh4x can collect and distribute updates among users over SMS, Internet, or through other available means. 
&#8226;	InSTEDD Evolve is a set of integrated services (analytic, collaborative and visualization) that helps to build and sustain a community of domain experts from the local to the international level.  Evolve is equipped with a machine learning algo-rithm that augment users input and accurately classifies 7 syndromes, 10 transmission modes, over 100 infectious diseases, over 180 micro-organisms, over 140 symptoms, and over 50 chemicals. 
&#8226;	InSTEDD GeoChat is a communications system that lets teams coordinate around events as they unfold, linking field, headquarters, and the local community in a unified effective response.
Presently, these tools are being piloted in the Mekong Basin region of Southeast Asia (Cambodia, Thailand, Laos, and Cambodia), Ushahidi in Kenya, HIV clinics in rural Tanzania, Mongolia, Ghana, and Bangladesh.
Use of mobile telephones for public health events detection and intervention in developing countries has tremendous potential due to low start-up cost and low bandwidth (e.g., SMS gateway). In 2002, mobile subscribers overtook fixed line subscribers worldwide and this occurred across geographic re-gions, socio-demographic criteria (gender, income, age) or economic criteria such as GDP per capita1. In much of sub-Saharan Africa, there are more mobile phones than fixed-line phones2 and the use of mobile phones in many Asian countries is on the rise. Addi-tionally, mobile telephone subscriptions have been growing rapidly since the 1980s in both developing and developed countries. Furthermore, the demand for mobile phones exists beyond reducing the waiting list for traditional wire-line phones 3.
However, technical, financial and regulatory barriers remain great challenges to fully adopting mobile technology as a platform in developing countries. Using mobile phones for health data exchange in developing countries has not been demonstrated giv-en the costs of data transmitted over mobile phone are greater than voice costs 2, 4, language and illitera-cy barriers2, and privacy and security issues since SMS messages can leave a trail. Other challenges include the physical components of a telephone (headset or network) are not isolated but are part of an entire business model that includes pricing plans and other incentives which can provide leverage em-ployed by public health agencies and policymakers.
References
1.	Feldmann V: Mobile overtakes Internet: Implica-tions for Policy and Regulation. International Tele-commjunications Union 2003:1-39 [http://www.itu.int/osg/spu/ni/mobileovertakes/Resources/Mobileovertakes_Paper.pdf]. last accessed 13 March 2009.
2.	Vodafone Policy Paper: Africa: The Impact of Mobile Phones. Vodafone Policy Paper Series Number 2 2005 [http://www.vodafone.com/assets/files/en/AIMP_09032005.pdf]. last accessed 13 March 2009. 
3.	Kundu A, Sarangi N: ICT and Human Develop-ment: Towards Building a Composite Index for Asia. Realizing the Millennium Development Goals. United Nations Development Program (UNDP) Technical Paper:1&#8211;35 2004 [http://www.apdip.net/elibrary#rhdr]. last accessed 13 March 2009.
4.	Waldick L: The Best Policy: Telecom Research from an African Perspective. International Devel-opment Research Center Report 2003 [http://www.idrc.ca/en/ev-46209-201-1-DO_TOPIC.html]. last accessed 13 March 2009.</media:text>
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        <![CDATA[<div style="width:425px;text-align:left" id="__ss_2490639"><a style="font:14px Helvetica,Arial,Sans-serif;display:block;margin:12px 0 3px 0;text-decoration:underline;" href="http://www.slideshare.net/kasshout/integrated-global-early-warning-and-response" title="Integrated Global Early Warning And Response">Integrated Global Early Warning And Response</a><object style="margin:0px" width="425" height="355"><param name="movie" value="http://static.slidesharecdn.com/swf/ssplayer2.swf?doc=insteddintegratedglobalearlywarningandresponsetahakass-houtamia2009-091113025414-phpapp02&stripped_title=integrated-global-early-warning-and-response" /><param name="allowFullScreen" value="true"/><param name="allowScriptAccess" value="always"/><embed src="http://static.slidesharecdn.com/swf/ssplayer2.swf?doc=insteddintegratedglobalearlywarningandresponsetahakass-houtamia2009-091113025414-phpapp02&stripped_title=integrated-global-early-warning-and-response" type="application/x-shockwave-flash" allowscriptaccess="always" allowfullscreen="true" width="425" height="355"></embed></object><div style="font-size:11px;font-family:tahoma,arial;height:26px;padding-top:2px;">View more <a style="text-decoration:underline;" href="http://www.slideshare.net/">presentations</a> from <a style="text-decoration:underline;" href="http://www.slideshare.net/kasshout">Taha Kass-Hout, MD, MS</a>.</div></div>]]>
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      <title>Chi Telehealth Team 3 Info648</title>
      <link>http://www.slideshare.net/andreakyer/chi-telehealth-team-3-info648</link>
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        <![CDATA[<img src="http://cdn.slidesharecdn.com/chitelehealthteam3info648-091102113343-phpapp02-thumbnail-2?1257278784" alt ="" style="border:1px solid #C3E6D8;float:right;" /><br> Week 7 presentation on Consumer Healthcare Informatics and Telehealth for INFO648 - Biomedical Informatics, iSchool Drexel University, Professor Michelle Rogers, PhD, Fall 2009]]>
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        <![CDATA[<img src="http://cdn.slidesharecdn.com/chitelehealthteam3info648-091102113343-phpapp02-thumbnail-2?1257278784" alt ="" style="border:1px solid #C3E6D8;float:right;" /><br> Week 7 presentation on Consumer Healthcare Informatics and Telehealth for INFO648 - Biomedical Informatics, iSchool Drexel University, Professor Michelle Rogers, PhD, Fall 2009]]>
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      <pubDate>Mon, 02 Nov 2009 17:33:35 GMT</pubDate>
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        <media:title>Chi Telehealth Team 3 Info648</media:title>
        <media:credit>andreakyer</media:credit>
        <media:description type="plain">Week 7 presentation on Consumer Healthcare Informatics and Telehealth for INFO648 - Biomedical Informatics, iSchool Drexel University, Professor Michelle Rogers, PhD, Fall 2009</media:description>
        <media:text type="html">&lt;img src=&quot;http://cdn.slidesharecdn.com/chitelehealthteam3info648-091102113343-phpapp02-thumbnail-2?1257278784&quot; alt =&quot;&quot; style=&quot;border:1px solid #C3E6D8;float:right;&quot; /&gt;&lt;br&gt; Week 7 presentation on Consumer Healthcare Informatics and Telehealth for INFO648 - Biomedical Informatics, iSchool Drexel University, Professor Michelle Rogers, PhD, Fall 2009</media:text>
        <media:keywords></media:keywords>
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        <![CDATA[<div style="width:425px;text-align:left" id="__ss_2404504"><a style="font:14px Helvetica,Arial,Sans-serif;display:block;margin:12px 0 3px 0;text-decoration:underline;" href="http://www.slideshare.net/andreakyer/chi-telehealth-team-3-info648" title="Chi Telehealth Team 3 Info648">Chi Telehealth Team 3 Info648</a><object style="margin:0px" width="425" height="355"><param name="movie" value="http://static.slidesharecdn.com/swf/ssplayer2.swf?doc=chitelehealthteam3info648-091102113343-phpapp02&stripped_title=chi-telehealth-team-3-info648" /><param name="allowFullScreen" value="true"/><param name="allowScriptAccess" value="always"/><embed src="http://static.slidesharecdn.com/swf/ssplayer2.swf?doc=chitelehealthteam3info648-091102113343-phpapp02&stripped_title=chi-telehealth-team-3-info648" type="application/x-shockwave-flash" allowscriptaccess="always" allowfullscreen="true" width="425" height="355"></embed></object><div style="font-size:11px;font-family:tahoma,arial;height:26px;padding-top:2px;">View more <a style="text-decoration:underline;" href="http://www.slideshare.net/">presentations</a> from <a style="text-decoration:underline;" href="http://www.slideshare.net/andreakyer">andreakyer</a>.</div></div>]]>
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      <title>Real-Time Surveillance for Rapid Correction of Clinical Decision Support Failures</title>
      <link>http://www.slideshare.net/amccoyphd/realtime-surveillance-for-rapid-correction-of-clinical-decision-support-failures</link>
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        <![CDATA[<img src="http://cdn.slidesharecdn.com/mccoynlm2009-091102090905-phpapp02-thumbnail-2?1257174655" alt ="" style="border:1px solid #C3E6D8;float:right;" /><br> The utilization of clinical decision support (CDS) is increasing among healthcare facilities which have implemented computerized physician order entry or electronic medical records.  Formal prospective evaluation of CDS implementations occurs rarely, and misuse or flaws in system design are often unrecognized.  Retrospective review can identify failures but is too late to make critical corrections or initiate redesign efforts. Real-time surveillance of user responses and patient outcomes comprises one approach to give immediate feedback to CDS designers and help operate a safety net which intercepts CDS failures.  We outline four types of CDS (passive alerts, interruptive alerts, order sets, and complex ordering advisors) and describe common failures with surveillance applications for high-alert medications such as aminoglycosides, anticoagulants, and insulin.   We then present a computerized tool for high-alert medication prescriptions which serves developers, clinical pharmacists, and institutional physician leaders.  The tool has two views: the surveillance view allows users to scan all CDS failures and prioritize high-risk scenarios, and the patient detail view provides context for understanding CDS failures.  Entries on the surveillance tool populate automatically when CDS is used or ignored, allowing verification of prescription safety and accuracy.]]>
      </description>
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        <![CDATA[<img src="http://cdn.slidesharecdn.com/mccoynlm2009-091102090905-phpapp02-thumbnail-2?1257174655" alt ="" style="border:1px solid #C3E6D8;float:right;" /><br> The utilization of clinical decision support (CDS) is increasing among healthcare facilities which have implemented computerized physician order entry or electronic medical records.  Formal prospective evaluation of CDS implementations occurs rarely, and misuse or flaws in system design are often unrecognized.  Retrospective review can identify failures but is too late to make critical corrections or initiate redesign efforts. Real-time surveillance of user responses and patient outcomes comprises one approach to give immediate feedback to CDS designers and help operate a safety net which intercepts CDS failures.  We outline four types of CDS (passive alerts, interruptive alerts, order sets, and complex ordering advisors) and describe common failures with surveillance applications for high-alert medications such as aminoglycosides, anticoagulants, and insulin.   We then present a computerized tool for high-alert medication prescriptions which serves developers, clinical pharmacists, and institutional physician leaders.  The tool has two views: the surveillance view allows users to scan all CDS failures and prioritize high-risk scenarios, and the patient detail view provides context for understanding CDS failures.  Entries on the surveillance tool populate automatically when CDS is used or ignored, allowing verification of prescription safety and accuracy.]]>
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      <pubDate>Mon, 02 Nov 2009 15:08:57 GMT</pubDate>
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      <author>amccoyphd@slideshare.net(amccoyphd)</author>
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        <media:title>Real-Time Surveillance for Rapid Correction of Clinical Decision Support Failures</media:title>
        <media:credit>amccoyphd</media:credit>
        <media:description type="plain">The utilization of clinical decision support (CDS) is increasing among healthcare facilities which have implemented computerized physician order entry or electronic medical records.  Formal prospective evaluation of CDS implementations occurs rarely, and misuse or flaws in system design are often unrecognized.  Retrospective review can identify failures but is too late to make critical corrections or initiate redesign efforts. Real-time surveillance of user responses and patient outcomes comprises one approach to give immediate feedback to CDS designers and help operate a safety net which intercepts CDS failures.  We outline four types of CDS (passive alerts, interruptive alerts, order sets, and complex ordering advisors) and describe common failures with surveillance applications for high-alert medications such as aminoglycosides, anticoagulants, and insulin.   We then present a computerized tool for high-alert medication prescriptions which serves developers, clinical pharmacists, and institutional physician leaders.  The tool has two views: the surveillance view allows users to scan all CDS failures and prioritize high-risk scenarios, and the patient detail view provides context for understanding CDS failures.  Entries on the surveillance tool populate automatically when CDS is used or ignored, allowing verification of prescription safety and accuracy.</media:description>
        <media:text type="html">&lt;img src=&quot;http://cdn.slidesharecdn.com/mccoynlm2009-091102090905-phpapp02-thumbnail-2?1257174655&quot; alt =&quot;&quot; style=&quot;border:1px solid #C3E6D8;float:right;&quot; /&gt;&lt;br&gt; The utilization of clinical decision support (CDS) is increasing among healthcare facilities which have implemented computerized physician order entry or electronic medical records.  Formal prospective evaluation of CDS implementations occurs rarely, and misuse or flaws in system design are often unrecognized.  Retrospective review can identify failures but is too late to make critical corrections or initiate redesign efforts. Real-time surveillance of user responses and patient outcomes comprises one approach to give immediate feedback to CDS designers and help operate a safety net which intercepts CDS failures.  We outline four types of CDS (passive alerts, interruptive alerts, order sets, and complex ordering advisors) and describe common failures with surveillance applications for high-alert medications such as aminoglycosides, anticoagulants, and insulin.   We then present a computerized tool for high-alert medication prescriptions which serves developers, clinical pharmacists, and institutional physician leaders.  The tool has two views: the surveillance view allows users to scan all CDS failures and prioritize high-risk scenarios, and the patient detail view provides context for understanding CDS failures.  Entries on the surveillance tool populate automatically when CDS is used or ignored, allowing verification of prescription safety and accuracy.</media:text>
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        <![CDATA[<div style="width:425px;text-align:left" id="__ss_2403126"><a style="font:14px Helvetica,Arial,Sans-serif;display:block;margin:12px 0 3px 0;text-decoration:underline;" href="http://www.slideshare.net/amccoyphd/realtime-surveillance-for-rapid-correction-of-clinical-decision-support-failures" title="Real-Time Surveillance for Rapid Correction of Clinical Decision Support Failures">Real-Time Surveillance for Rapid Correction of Clinical Decision Support Failures</a><object style="margin:0px" width="425" height="355"><param name="movie" value="http://static.slidesharecdn.com/swf/ssplayer2.swf?doc=mccoynlm2009-091102090905-phpapp02&stripped_title=realtime-surveillance-for-rapid-correction-of-clinical-decision-support-failures" /><param name="allowFullScreen" value="true"/><param name="allowScriptAccess" value="always"/><embed src="http://static.slidesharecdn.com/swf/ssplayer2.swf?doc=mccoynlm2009-091102090905-phpapp02&stripped_title=realtime-surveillance-for-rapid-correction-of-clinical-decision-support-failures" type="application/x-shockwave-flash" allowscriptaccess="always" allowfullscreen="true" width="425" height="355"></embed></object><div style="font-size:11px;font-family:tahoma,arial;height:26px;padding-top:2px;">View more <a style="text-decoration:underline;" href="http://www.slideshare.net/">presentations</a> from <a style="text-decoration:underline;" href="http://www.slideshare.net/amccoyphd">amccoyphd</a>.</div></div>]]>
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      <title>Oswego in the Cloud: Scenario Script</title>
      <link>http://www.slideshare.net/kasshout/oswego-in-the-cloud-scenario-script</link>
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        <![CDATA[<img src="http://cdn.slidesharecdn.com/oswegointhecloudscenarioscript-091101183348-phpapp01-thumbnail-2?1257125599" alt ="" style="border:1px solid #C3E6D8;float:right;" /><br> A near-real time data exchange between multiple instances of Epi Info™ was enabled by configuring Mesh4x (http://code.google.com/p/mesh4x/) for Internet cloud (e.g., Amazon’s EC2, Google cloud/App Engine) and for peer-to-peer (over SMS) synchronization. A client-based tool can easily be used by an epidemiologist to build and configure a mesh environment, without requiring prior technical knowledge.]]>
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        <![CDATA[<img src="http://cdn.slidesharecdn.com/oswegointhecloudscenarioscript-091101183348-phpapp01-thumbnail-2?1257125599" alt ="" style="border:1px solid #C3E6D8;float:right;" /><br> A near-real time data exchange between multiple instances of Epi Info™ was enabled by configuring Mesh4x (http://code.google.com/p/mesh4x/) for Internet cloud (e.g., Amazon’s EC2, Google cloud/App Engine) and for peer-to-peer (over SMS) synchronization. A client-based tool can easily be used by an epidemiologist to build and configure a mesh environment, without requiring prior technical knowledge.]]>
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      <pubDate>Mon, 02 Nov 2009 00:33:37 GMT</pubDate>
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        <media:description type="plain">A near-real time data exchange between multiple instances of Epi Info&#8482; was enabled by configuring Mesh4x (http://code.google.com/p/mesh4x/) for Internet cloud (e.g., Amazon&#8217;s EC2, Google cloud/App Engine) and for peer-to-peer (over SMS) synchronization. A client-based tool can easily be used by an epidemiologist to build and configure a mesh environment, without requiring prior technical knowledge.</media:description>
        <media:text type="html">&lt;img src=&quot;http://cdn.slidesharecdn.com/oswegointhecloudscenarioscript-091101183348-phpapp01-thumbnail-2?1257125599&quot; alt =&quot;&quot; style=&quot;border:1px solid #C3E6D8;float:right;&quot; /&gt;&lt;br&gt; A near-real time data exchange between multiple instances of Epi Info&#8482; was enabled by configuring Mesh4x (http://code.google.com/p/mesh4x/) for Internet cloud (e.g., Amazon&#8217;s EC2, Google cloud/App Engine) and for peer-to-peer (over SMS) synchronization. A client-based tool can easily be used by an epidemiologist to build and configure a mesh environment, without requiring prior technical knowledge.</media:text>
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