Generating Big Data Sets from Knowledge-based Decision Support Systems to Pursue Value-based Healthcare
Talking about Big Data in healthcare we usually refer to how to use data collected from current electronic medical records, either structured or unstructured, to answer clinically relevant questions. This operation is typically carried out by means of analytics tools (e.g. machine learning) or by ex...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Universidad Internacional de La Rioja (UNIR)
2018-03-01
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| Series: | International Journal of Interactive Multimedia and Artificial Intelligence |
| Subjects: | |
| Online Access: | http://www.ijimai.org/journal/node/1626 |
| _version_ | 1818356143187034112 |
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| author | Arturo González-Ferrer Germán Seara Joan Cháfer Julio Mayol |
| author_facet | Arturo González-Ferrer Germán Seara Joan Cháfer Julio Mayol |
| author_sort | Arturo González-Ferrer |
| collection | DOAJ |
| description | Talking about Big Data in healthcare we usually refer to how to use data collected from current electronic medical records, either structured or unstructured, to answer clinically relevant questions. This operation is typically carried out by means of analytics tools (e.g. machine learning) or by extracting relevant data from patient summaries through natural language processing techniques. From other perspective of research in medical informatics, powerful initiatives have emerged to help physicians taking decisions, in both diagnostics and therapeutics, built from the existing medical evidence (i.e. knowledge-based decision support systems). Much of the problems these tools have shown, when used in real clinical settings, are related to their implementation and deployment, more than failing in its support, but, technology is slowly overcoming interoperability and integration issues. Beyond the point-of-care decision support these tools can provide, the data generated when using them, even in controlled trials, could be used to further analyze facts that are traditionally ignored in the current clinical practice. In this paper, we reflect on the technologies available to make the leap and how they could help driving healthcare organizations shifting to a value-based healthcare philosophy. |
| first_indexed | 2024-12-13T19:52:31Z |
| format | Article |
| id | doaj.art-6b2829766c284d68bc639eab64b488cd |
| institution | Directory Open Access Journal |
| issn | 1989-1660 1989-1660 |
| language | English |
| last_indexed | 2024-12-13T19:52:31Z |
| publishDate | 2018-03-01 |
| publisher | Universidad Internacional de La Rioja (UNIR) |
| record_format | Article |
| series | International Journal of Interactive Multimedia and Artificial Intelligence |
| spelling | doaj.art-6b2829766c284d68bc639eab64b488cd2022-12-21T23:33:23ZengUniversidad Internacional de La Rioja (UNIR)International Journal of Interactive Multimedia and Artificial Intelligence1989-16601989-16602018-03-0147424610.9781/ijimai.2018.477ijimai.2018.477Generating Big Data Sets from Knowledge-based Decision Support Systems to Pursue Value-based HealthcareArturo González-FerrerGermán SearaJoan CháferJulio MayolTalking about Big Data in healthcare we usually refer to how to use data collected from current electronic medical records, either structured or unstructured, to answer clinically relevant questions. This operation is typically carried out by means of analytics tools (e.g. machine learning) or by extracting relevant data from patient summaries through natural language processing techniques. From other perspective of research in medical informatics, powerful initiatives have emerged to help physicians taking decisions, in both diagnostics and therapeutics, built from the existing medical evidence (i.e. knowledge-based decision support systems). Much of the problems these tools have shown, when used in real clinical settings, are related to their implementation and deployment, more than failing in its support, but, technology is slowly overcoming interoperability and integration issues. Beyond the point-of-care decision support these tools can provide, the data generated when using them, even in controlled trials, could be used to further analyze facts that are traditionally ignored in the current clinical practice. In this paper, we reflect on the technologies available to make the leap and how they could help driving healthcare organizations shifting to a value-based healthcare philosophy.http://www.ijimai.org/journal/node/1626Big DataDSSe-healthKnowledge ManagementManagemet Systems |
| spellingShingle | Arturo González-Ferrer Germán Seara Joan Cháfer Julio Mayol Generating Big Data Sets from Knowledge-based Decision Support Systems to Pursue Value-based Healthcare International Journal of Interactive Multimedia and Artificial Intelligence Big Data DSS e-health Knowledge Management Managemet Systems |
| title | Generating Big Data Sets from Knowledge-based Decision Support Systems to Pursue Value-based Healthcare |
| title_full | Generating Big Data Sets from Knowledge-based Decision Support Systems to Pursue Value-based Healthcare |
| title_fullStr | Generating Big Data Sets from Knowledge-based Decision Support Systems to Pursue Value-based Healthcare |
| title_full_unstemmed | Generating Big Data Sets from Knowledge-based Decision Support Systems to Pursue Value-based Healthcare |
| title_short | Generating Big Data Sets from Knowledge-based Decision Support Systems to Pursue Value-based Healthcare |
| title_sort | generating big data sets from knowledge based decision support systems to pursue value based healthcare |
| topic | Big Data DSS e-health Knowledge Management Managemet Systems |
| url | http://www.ijimai.org/journal/node/1626 |
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