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A novel decision algorithm for reducing medication errors in CPOE systems

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TitleInfo
Title
A novel decision algorithm for reducing medication errors in CPOE systems
Name (type = personal)
NamePart (type = family)
Imbo
NamePart (type = given)
Samuel
DisplayForm
Samuel Imbo
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
NamePart (type = family)
Srinivasan
NamePart (type = given)
Shankar
DisplayForm
Shankar Srinivasan
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
chair
Name (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
School of Health Professions
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school
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Text
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theses
OriginInfo
DateCreated (qualifier = exact)
2019
DateOther (qualifier = exact); (type = degree)
2019-01
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2019
Place
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xx
Language
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eng
Abstract (type = abstract)
The projection of the U.S. national healthcare expenditure in year 2019 is $4.7 trillion. Medical errors are part of this increasing healthcare costs because they cause tens of thousands of deaths in the U.S. hospitals each year, more than major diseases such as AIDS, breast cancer combined to highway accidents (Chiang S. Jao, Daniel B. Hirer) [10]. Based on a research published in the British Medical Journal (BMJ) in 2016 and conducted by (Michael Daniel & Martin A Makary) [98], Medical error is ranked the third cause of death in the US.
With the advancement in technology, we have seen during the last years, important improvements in the design as well as the use of electronic health records (EHRs), Computerized Physician Order Entry (CPOE), and Clinical Decision-Support Systems (CDSS), and Diagnosis Decision-Support Systems (DDSS) to improve the quality of health care delivery; progress have been made but challenges remain. Medication errors can be:
•Wrong drug,
•Wrong dose,
•Wrong route,
•Wrong patient,
•Bad combination,
•Bad reaction
to list a few, and are found at every stage from prescription and administration of drugs to monitoring. They hurt about 1.5 million people, and cost billions of dollars each year according to the Institute of Medicine of the National Academies. Medication errors can happen anywhere, from Doctors offices to hospitals, and pharmacies and your home. Sound-Alike / Look-Alike also known as drug name errors, are the most common causes of medication errors, they originate from poor communication between health care providers, poor communication between patients and their providers. To reduce the likelihood of ham related to medications and Adverse Drug Events (ADEs), many interventions have been attempted including notably: The US Food and Drug Administration (FDA), government legislation, policy makers, drug utilization reviews, health professionals, and patients education, all of this with limited success.
The aim of this dissertation is to evaluate medication errors related to Sound-Alike drug names, and to propose a new approach of preventing them by "Embedding the Novel Decision Algorithm" coupled with "Confused Drug Names, Generic and Brand drug names" and "Doses" within a computerized provider order entry (CPOE) during the drug prescribing process.
Subject (authority = RUETD)
Topic
Biomedical Informatics
Subject (authority = ETD-LCSH)
Topic
Medication errors
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Rutgers University Electronic Theses and Dissertations
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ETD_9401
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electronic resource
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application/pdf
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Extent
1 online resource (279 pages : illustrations)
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Note (type = statement of responsibility)
by Samuel Imbo
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School of Health Professions ETD Collection
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rucore10007400001
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Identifier (type = doi)
doi:10.7282/t3-j80z-c775
Genre (authority = ExL-Esploro)
ETD doctoral
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Rights

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The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Imbo
GivenName
Samuel
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2018-12-05 19:51:46
AssociatedEntity
Name
Samuel Imbo
Role
Copyright holder
Affiliation
Rutgers University. School of Health Professions
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Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
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Type
Embargo
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2019-01-31
DateTime (encoding = w3cdtf); (qualifier = exact); (point = end)
2019-08-02
Detail
Access to this PDF has been restricted at the author's request. It will be publicly available after August 2nd, 2019.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical

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2018-12-05T05:01:57
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