Pub Date : 2020-03-18DOI: 10.1163/9789004429086_004
J. Andriessen, M. Baker
{"title":"The Seven Samurai","authors":"J. Andriessen, M. Baker","doi":"10.1163/9789004429086_004","DOIUrl":"https://doi.org/10.1163/9789004429086_004","url":null,"abstract":"","PeriodicalId":92467,"journal":{"name":"... IEEE Conference on Collaboration and Internet Computing. IEEE Conference on Collaboration and Internet Computing","volume":"39 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80603855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-03-18DOI: 10.1163/9789004429086_006
J. Andriessen, Michael D. Baker
{"title":"Second Interlude","authors":"J. Andriessen, Michael D. Baker","doi":"10.1163/9789004429086_006","DOIUrl":"https://doi.org/10.1163/9789004429086_006","url":null,"abstract":"","PeriodicalId":92467,"journal":{"name":"... IEEE Conference on Collaboration and Internet Computing. IEEE Conference on Collaboration and Internet Computing","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88955559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-03-18DOI: 10.1163/9789004429086_012
Á. Gunnarsson, Michael Johnson
{"title":"Collaboration","authors":"Á. Gunnarsson, Michael Johnson","doi":"10.1163/9789004429086_012","DOIUrl":"https://doi.org/10.1163/9789004429086_012","url":null,"abstract":"","PeriodicalId":92467,"journal":{"name":"... IEEE Conference on Collaboration and Internet Computing. IEEE Conference on Collaboration and Internet Computing","volume":"38 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81399951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-01Epub Date: 2020-02-13DOI: 10.1109/CIC48465.2019.00024
Cindy Kim, Christoph U Lehmann, Dupree Hatch, Jonathan S Schildcrout, Daniel J France, You Chen
We strive to understand care coordination structures of multidisciplinary teams and to evaluate their effect on post-surgical length of stay (PSLOS) in the Neonatal Intensive Care Unit (NICU). Electronic health record (EHR) data were extracted for 18 neonates, who underwent gastrostomy tube placement surgery at the Vanderbilt University Medical Center NICU. Based on providers' interactions with the EHR (e.g. viewing, documenting, ordering), provider-provider relations were learned and used to build patient-specific provider networks representing the care coordination structure. We quantified the networks using standard network analysis metrics (e.g., in-degree, out-degree, betweenness centrality, and closeness centrality). Coordination structure effectiveness was measured as the association between the network metrics and PSLOS, as modeled by a proportional-odds, logistical regression model. The 18 provider networks exhibited various team compositions and various levels of structural complexity. Providers, whose patients had lower PSLOS, tended to disperse patient-related information to more colleagues within their network than those, who treated higher PSLOS patients (P = 0.0294). In the NICU, improved dissemination of information may be linked to reduced PSLOS. EHR data provides an efficient, accessible, and resource-friendly way to study care coordination using network analysis tools. This novel methodology offers an objective way to identify key performance and safety indicators of care coordination and to study dissemination of patient-related information within care provider networks and its effect on care. Findings should guide improvements in the EHR system design to facilitate effective clinical communications among providers.
{"title":"Provider Networks in the Neonatal Intensive Care Unit Associate with Length of Stay.","authors":"Cindy Kim, Christoph U Lehmann, Dupree Hatch, Jonathan S Schildcrout, Daniel J France, You Chen","doi":"10.1109/CIC48465.2019.00024","DOIUrl":"10.1109/CIC48465.2019.00024","url":null,"abstract":"<p><p>We strive to understand care coordination structures of multidisciplinary teams and to evaluate their effect on post-surgical length of stay (PSLOS) in the Neonatal Intensive Care Unit (NICU). Electronic health record (EHR) data were extracted for 18 neonates, who underwent gastrostomy tube placement surgery at the Vanderbilt University Medical Center NICU. Based on providers' interactions with the EHR (e.g. viewing, documenting, ordering), provider-provider relations were learned and used to build patient-specific provider networks representing the care coordination structure. We quantified the networks using standard network analysis metrics (e.g., in-degree, out-degree, betweenness centrality, and closeness centrality). Coordination structure effectiveness was measured as the association between the network metrics and PSLOS, as modeled by a proportional-odds, logistical regression model. The 18 provider networks exhibited various team compositions and various levels of structural complexity. Providers, whose patients had lower PSLOS, tended to disperse patient-related information to more colleagues within their network than those, who treated higher PSLOS patients (P = 0.0294). In the NICU, improved dissemination of information may be linked to reduced PSLOS. EHR data provides an efficient, accessible, and resource-friendly way to study care coordination using network analysis tools. This novel methodology offers an objective way to identify key performance and safety indicators of care coordination and to study dissemination of patient-related information within care provider networks and its effect on care. Findings should guide improvements in the EHR system design to facilitate effective clinical communications among providers.</p>","PeriodicalId":92467,"journal":{"name":"... IEEE Conference on Collaboration and Internet Computing. IEEE Conference on Collaboration and Internet Computing","volume":"2019 ","pages":"127-134"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7339831/pdf/nihms-1602882.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38136424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Attribute Based Access Control (ABAC) is fast replacing traditional access control models due to its dynamic nature, flexibility and scalability. ABAC is often used in collaborative environments. However, a major hurdle to deploying ABAC is to precisely configure the ABAC policy. In this paper, we present an ABAC mining approach that can automatically discover the appropriate ABAC policy rules. We first show that the ABAC mining problem is equivalent to identifying a set of functional dependencies in relational databases that cover all of the records in a table. We also propose a more efficient algorithm, called ABAC-SRM which discovers the most general policy rules from a set of candidate rules. We experimentally show that ABAC-SRM is accurate and significantly more efficient than the existing state of the art.
{"title":"Efficient bottom-up Mining of Attribute Based Access Control Policies.","authors":"Tanay Talukdar, Gunjan Batra, Jaideep Vaidya, Vijayalakshmi Atluri, Shamik Sural","doi":"10.1109/CIC.2017.00051","DOIUrl":"https://doi.org/10.1109/CIC.2017.00051","url":null,"abstract":"<p><p>Attribute Based Access Control (ABAC) is fast replacing traditional access control models due to its dynamic nature, flexibility and scalability. ABAC is often used in collaborative environments. However, a major hurdle to deploying ABAC is to precisely configure the ABAC policy. In this paper, we present an <i>ABAC mining</i> approach that can automatically discover the appropriate ABAC policy rules. We first show that the ABAC mining problem is equivalent to identifying a set of <i>functional dependencies</i> in relational databases that cover all of the records in a table. We also propose a more efficient algorithm, called ABAC-SRM which discovers the most general policy rules from a set of candidate rules. We experimentally show that ABAC-SRM is accurate and significantly more efficient than the existing state of the art.</p>","PeriodicalId":92467,"journal":{"name":"... IEEE Conference on Collaboration and Internet Computing. IEEE Conference on Collaboration and Internet Computing","volume":"2017 ","pages":"339-348"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CIC.2017.00051","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36729397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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