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020 ▼a 9781687904775
035 ▼a (MiAaPQ)AAI22620666
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 247004
0820 ▼a 362.1
1001 ▼a Beauchemin, Melissa Parsons.
24510 ▼a Supporting Clinical Decision Making in Cancer Care Delivery.
260 ▼a [S.l.]: ▼b Columbia University., ▼c 2019.
260 1 ▼a Ann Arbor: ▼b ProQuest Dissertations & Theses, ▼c 2019.
300 ▼a 141 p.
500 ▼a Source: Dissertations Abstracts International, Volume: 81-04, Section: B.
500 ▼a Advisor: Schnall, Rebecca.
5021 ▼a Thesis (Ph.D.)--Columbia University, 2019.
506 ▼a This item must not be sold to any third party vendors.
520 ▼a Background: Cancer treatment and management require complicated clinical decision making to provide the highest quality of care for an individual patient. This is facilitated in part with ever-increasing availability of medications and treatments but hindered due to barriers such as access to care, cost of medications, clinician knowledge, and patient preferences or clinical factors. Although guidelines for cancer treatment and many symptoms have been developed to inform clinical practice, implementation of these guidelines into practice is often delayed or does not occur. Informatics-based approaches, such as clinical decision support, may be an effective tool to improve guideline implementation by delivering patient-specific and evidence-based knowledge to the clinician at the point of care to allow shared decision making with a patient and their family. The large amount of data in the electronic health record can be utilized to develop, evaluate, and implement automated approaches
590 ▼a School code: 0054.
650 4 ▼a Oncology.
650 4 ▼a Health care management.
690 ▼a 0992
690 ▼a 0769
71020 ▼a Columbia University. ▼b Nursing.
7730 ▼t Dissertations Abstracts International ▼g 81-04B.
773 ▼t Dissertation Abstract International
790 ▼a 0054
791 ▼a Ph.D.
792 ▼a 2019
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T15493746 ▼n KERIS ▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다.
980 ▼a 202002 ▼f 2020
990 ▼a ***1008102
991 ▼a E-BOOK