CorporateMeasures
Patient information in healthcare organizations is distributed across several systems and data silos. Clinicians make decisions based on data in patient health records. Improving the efficiency of decision-support requires collective knowledge of all patient information. The classical approach of li...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , |
| التنسيق: | conferenceObject |
| منشور في: |
2018
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| الوصول للمادة أونلاين: | http://hdl.handle.net/10725/7835 http://dx.doi.org/10.1109/HealthCom.2016.7749451 http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://ieeexplore.ieee.org/abstract/document/7749451/ |
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| _version_ | 1864513467066613760 |
|---|---|
| author | Mansour, Nashat |
| author2 | Danas, Konstantinos Nammour, Fadi |
| author2_role | author author |
| author_facet | Mansour, Nashat Danas, Konstantinos Nammour, Fadi |
| author_role | author |
| dc.creator.none.fl_str_mv | Mansour, Nashat Danas, Konstantinos Nammour, Fadi |
| dc.date.none.fl_str_mv | 2018-05-17T06:26:29Z 2018-05-17T06:26:29Z 2018-05-17 |
| dc.identifier.none.fl_str_mv | 978-1-5090-3370-6 http://hdl.handle.net/10725/7835 http://dx.doi.org/10.1109/HealthCom.2016.7749451 Nammour, F., Danas, K., & Mansour, N. (2016, September). CorporateMeasures: A clinical analytics framework leading to clinical intelligence. In e-Health Networking, Applications and Services (Healthcom), 2016 IEEE 18th International Conference on (pp. 1-6). IEEE. http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://ieeexplore.ieee.org/abstract/document/7749451/ |
| dc.language.none.fl_str_mv | en |
| dc.publisher.none.fl_str_mv | IEEE |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.title.none.fl_str_mv | CorporateMeasures a clinical analytics framework leading to clinical intelligence |
| dc.type.none.fl_str_mv | Conference Paper / Proceeding info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/conferenceObject |
| description | Patient information in healthcare organizations is distributed across several systems and data silos. Clinicians make decisions based on data in patient health records. Improving the efficiency of decision-support requires collective knowledge of all patient information. The classical approach of linking patient data from many databases into one data warehouse poses various problems when it comes to building clinical analytics. An implementation of the Performance Measurement and Management approach used in Engineering and Business is adapted to healthcare scenarios, and a new system is developed that allows clinicians that are not technical professionals to develop, test and apply custom analytics to patient health data. Part I of this paper is an introduction to the problems and current situation in healthcare data analytics. Part II states the aim and objectives. Part III explains the system design and its modular components. Part IV presents the results of three performance indicators evaluated through the system, and evaluates the system through technical and clinical usability methods. Part V concludes and discusses future work. |
| eu_rights_str_mv | openAccess |
| format | conferenceObject |
| id | LAURepo_c3a4de406a6fbdd90f2446357fd65892 |
| identifier_str_mv | 978-1-5090-3370-6 Nammour, F., Danas, K., & Mansour, N. (2016, September). CorporateMeasures: A clinical analytics framework leading to clinical intelligence. In e-Health Networking, Applications and Services (Healthcom), 2016 IEEE 18th International Conference on (pp. 1-6). IEEE. |
| language_invalid_str_mv | en |
| network_acronym_str | LAURepo |
| network_name_str | Lebanese American University repository |
| oai_identifier_str | oai:laur.lau.edu.lb:10725/7835 |
| publishDate | 2018 |
| publisher.none.fl_str_mv | IEEE |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | CorporateMeasuresa clinical analytics framework leading to clinical intelligenceMansour, NashatDanas, KonstantinosNammour, FadiPatient information in healthcare organizations is distributed across several systems and data silos. Clinicians make decisions based on data in patient health records. Improving the efficiency of decision-support requires collective knowledge of all patient information. The classical approach of linking patient data from many databases into one data warehouse poses various problems when it comes to building clinical analytics. An implementation of the Performance Measurement and Management approach used in Engineering and Business is adapted to healthcare scenarios, and a new system is developed that allows clinicians that are not technical professionals to develop, test and apply custom analytics to patient health data. Part I of this paper is an introduction to the problems and current situation in healthcare data analytics. Part II states the aim and objectives. Part III explains the system design and its modular components. Part IV presents the results of three performance indicators evaluated through the system, and evaluates the system through technical and clinical usability methods. Part V concludes and discusses future work.N/AIEEE2018-05-17T06:26:29Z2018-05-17T06:26:29Z2018-05-17Conference Paper / Proceedinginfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject978-1-5090-3370-6http://hdl.handle.net/10725/7835http://dx.doi.org/10.1109/HealthCom.2016.7749451Nammour, F., Danas, K., & Mansour, N. (2016, September). CorporateMeasures: A clinical analytics framework leading to clinical intelligence. In e-Health Networking, Applications and Services (Healthcom), 2016 IEEE 18th International Conference on (pp. 1-6). IEEE.http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.phphttps://ieeexplore.ieee.org/abstract/document/7749451/eninfo:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/78352021-03-19T10:03:30Z |
| spellingShingle | CorporateMeasures Mansour, Nashat |
| status_str | publishedVersion |
| title | CorporateMeasures |
| title_full | CorporateMeasures |
| title_fullStr | CorporateMeasures |
| title_full_unstemmed | CorporateMeasures |
| title_short | CorporateMeasures |
| title_sort | CorporateMeasures |
| url | http://hdl.handle.net/10725/7835 http://dx.doi.org/10.1109/HealthCom.2016.7749451 http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://ieeexplore.ieee.org/abstract/document/7749451/ |