MARC details
| 000 -LEADER |
|---|
| fixed length control field |
03027nam a22004457a 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
220124s20212021 xxu||||| |||| 00| 0 eng d |
| 022 ## - INTERNATIONAL STANDARD SERIAL NUMBER |
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| International Standard Serial Number |
1549-8417 |
| 024 ## - OTHER STANDARD IDENTIFIER |
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| Standard number or code |
01209203-202112000-00028 [pii] |
| 024 ## - OTHER STANDARD IDENTIFIER |
|---|
| Standard number or code |
10.1097/PTS.0000000000000837 [doi] |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
Ovid MEDLINE(R) |
| 099 ## - LOCAL FREE-TEXT CALL NUMBER (OCLC) |
|---|
| PMID |
34852413 |
| 245 ## - TITLE STATEMENT |
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| Title |
Realizing the Power of Text Mining and Natural Language Processing for Analyzing Patient Safety Event Narratives: The Challenges and Path Forward. |
| 251 ## - Source |
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| Source |
Journal of patient safety. 17(8):e834-e836, 2021 12 01. |
| 252 ## - Abbreviated Source |
|---|
| Abbreviated source |
J Patient Saf. 17(8):e834-e836, 2021 12 01. |
| 252 ## - Abbreviated Source |
|---|
| Former abbreviated source |
J Patient Saf. 17(8):e834-e836, 2021 Dec 01. |
| 253 ## - Journal Name |
|---|
| Journal name |
Journal of patient safety |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
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| Year |
2021 |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Manufacturer |
FY2022 |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Publication date |
2021 Dec 01 |
| 265 ## - SOURCE FOR ACQUISITION/SUBSCRIPTION ADDRESS [OBSOLETE] |
|---|
| Publication status |
ppublish |
| 266 ## - Date added to catalog |
|---|
| Date added to catalog |
2022-01-25 |
| 268 ## - Previous citation |
|---|
| -- |
Journal of patient safety. 17(8):e834-e836, 2021 Dec 01. |
| 269 ## - Original dates |
|---|
| Original fiscal year |
FY2022 |
| 501 ## - WITH NOTE |
|---|
| Local holdings |
Available online through MWHC library: March 2005 - present |
| 520 ## - SUMMARY, ETC. |
|---|
| Abstract |
ABSTRACT: Patient safety event (PSE) reports are a useful lens to understand hazards and patient safety risks in healthcare systems. However, patient safety officers and analysts in healthcare systems and safety organizations are challenged to make sense of the ever-increasing volume of PSE reports, including the free-text narratives. As a result, there is a growing emphasis on applying text mining and natural language processing (NLP) approaches to assist in the processing and understanding of these narratives. Although text mining and NLP in healthcare have advanced significantly over the past decades, the utility of the resulting models, ontologies, and algorithms to analyze PSE narratives are limited given the unique difference and challenges in content and language between PSE narratives and clinical documentation. To promote the application of text mining and NLP for PSE narratives, these unique challenges must be addressed. Improving data access, developing NLP resources to practically use contributing factor taxonomies, and developing and adopting shared specifications for interoperability will help create an infrastructure and environment that unlocks the collaborative potential between patient safety, research, and machine learning communities, in the development of reproducible and generalizable methods and models to better understand and improve patient safety and patient care. Copyright (c) 2021 Wolters Kluwer Health, Inc. All rights reserved. |
| 546 ## - LANGUAGE NOTE |
|---|
| Language note |
English |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
*Natural Language Processing |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
*Patient Safety |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Algorithms |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Data Mining |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Humans |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Machine Learning |
| 651 ## - SUBJECT ADDED ENTRY--GEOGRAPHIC NAME |
|---|
| Institution |
MedStar Institute for Innovation |
| 656 ## - INDEX TERM--OCCUPATION |
|---|
| Department |
National Center for Human Factors in Healthcare |
| 657 ## - INDEX TERM--FUNCTION |
|---|
| Medline publication type |
Journal Article |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Local Authors |
Fong, Allan |
| 790 ## - Authors |
|---|
| All authors |
Fong A |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
|---|
| DOI |
<a href="https://dx.doi.org/10.1097/PTS.0000000000000837">https://dx.doi.org/10.1097/PTS.0000000000000837</a> |
| Public note |
https://dx.doi.org/10.1097/PTS.0000000000000837 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Koha item type |
Journal Article |
| Item type description |
Article |
