Lessons Learned in the Development of a Computable Phenotype for Response in Myeloproliferative Neoplasms.
| Autor: | Sholle E; Information Technologies & Services, Weill Cornell Medicine, New York, NY., Krichevsky S; Department of Medicine, Weill Cornell Medicine, New York, NY., Scandura J; Department of Medicine, Weill Cornell Medicine, New York, NY., Sosner C; Department of Medicine, Weill Cornell Medicine, New York, USA., Campion TR Jr; Department of Healthcare Policy and Research, Weill Cornell Medicine, New York, USA. |
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| Jazyk: | angličtina |
| Zdroj: | IEEE International Conference on Healthcare Informatics. IEEE International Conference on Healthcare Informatics [IEEE Int Conf Healthc Inform] 2018 Jun; Vol. 2018, pp. 328-331. Date of Electronic Publication: 2018 Jul 26. |
| DOI: | 10.1109/ICHI.2018.00045 |
| Abstrakt: | Determining response status in patients with myeloproliferative neoplasms is a complex problem requiring the integration of both structured and unstructured data elements from disparate information systems. By applying multiple techniques, a collaborative team of informatics professionals and research personnel were able to determine which elements were amenable to automated extraction and which required expert adjudication. With this knowledge in mind, we were able to build a system that joins together programmatically-derived and manually-abstracted data elements to facilitate response assessment - an important end point in clinical and translational research in this disease area. |
| Databáze: | MEDLINE |
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