Literature DB >> 29112003

Measuring Processes of Care in Palliative Surgery: A Novel Approach Using Natural Language Processing.

Elizabeth J Lilley1,2, Charlotta Lindvall3,4,5, Keith D Lillemoe4,6, James A Tulsky3,4,5, Daniel C Wiener4,7, Zara Cooper1,4,7.   

Abstract

: Palliative surgical procedures are often performed for patients with limited survival. Quality measures for processes of care at the end of life are appropriate in palliative surgery, but have not been applied in this patient population. In this paper, the authors propose 4 quality measures for end-of-life care in a palliative surgery, and then demonstrate the utility of natural language processing for implementing these measures.

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Mesh：

Year:  2018        PMID： 29112003     DOI： 10.1097/SLA.0000000000002579

Source DB:  PubMed          Journal:  Ann Surg        ISSN： 0003-4932            Impact factor:   12.969


  10 in total

1.  Sensitivity and Specificity of a Machine Learning Algorithm to Identify Goals-of-care Documentation for Adults With Congenital Heart Disease at the End of Life.

Authors:  Jill M Steiner; Christina Morse; Robert Y Lee; J Randall Curtis; Ruth A Engelberg
Journal:  J Pain Symptom Manage       Date:  2020-06-26       Impact factor: 3.612

Review 2.  Machine Learning to Predict, Detect, and Intervene Older Adults Vulnerable for Adverse Drug Events in the Emergency Department.

Authors:  Kei Ouchi; Charlotta Lindvall; Peter R Chai; Edward W Boyer
Journal:  J Med Toxicol       Date:  2018-06-01

3.  Randomized Trial of a Palliative Care Intervention to Improve End-of-Life Care Discussions in Patients With Metastatic Breast Cancer.

Authors:  Joseph A Greer; Beverly Moy; Areej El-Jawahri; Vicki A Jackson; Mihir Kamdar; Juliet Jacobsen; Charlotta Lindvall; Jennifer A Shin; Simone Rinaldi; Heather A Carlson; Angela Sousa; Emily R Gallagher; Zhigang Li; Samantha Moran; Magaret Ruddy; Maya V Anand; Julia E Carp; Jennifer S Temel
Journal:  J Natl Compr Canc Netw       Date:  2022-02       Impact factor: 11.908

4.  Using Natural Language Processing to Classify Serious Illness Communication with Oncology Patients.

Authors:  Anahita Davoudi; Hegler Tissot; Abigail Doucette; Peter E Gabriel; Ravi Parikh; Danielle L Mowery; Stephen P Miranda
Journal:  AMIA Annu Symp Proc       Date:  2022-05-23

5.  Implications of Physical Access Barriers for Breast Cancer Diagnosis and Treatment in Women with Mobility Disability.

Authors:  Nicole Agaronnik; Areej El-Jawahri; Lisa Iezzoni
Journal:  J Disabil Policy Stud       Date:  2021-05-10

6.  Charting a path to high-quality end-of-life care for children with cancer.

Authors:  Prasanna Ananth; Joanne Wolfe; Emily E Johnston
Journal:  Cancer       Date:  2022-08-25       Impact factor: 6.921

7.  Exploring the Use of Wearable Sensors and Natural Language Processing Technology to Improve Patient-Clinician Communication: Protocol for a Feasibility Study.

Authors:  Virginia LeBaron; Mehdi Boukhechba; James Edwards; Tabor Flickinger; David Ling; Laura E Barnes
Journal:  JMIR Res Protoc       Date:  2022-05-20

8.  Needle in a Haystack: Natural Language Processing to Identify Serious Illness.

Authors:  Brooks Udelsman; Isabel Chien; Kei Ouchi; Kate Brizzi; James A Tulsky; Charlotta Lindvall
Journal:  J Palliat Med       Date:  2018-09-22       Impact factor: 2.947

9.  Variation in Serious Illness Communication among Surgical Patients Receiving Palliative Care.

Authors:  Brooks V Udelsman; Katherine C Lee; Elizabeth J Lilley; David C Chang; Charlotta Lindvall; Zara Cooper
Journal:  J Palliat Med       Date:  2019-10-02       Impact factor: 2.947

10.  Impact of Different Approaches to Preparing Notes for Analysis With Natural Language Processing on the Performance of Prediction Models in Intensive Care.

Authors:  Malini Mahendra; Yanting Luo; Hunter Mills; Gundolf Schenk; Atul J Butte; R Adams Dudley
Journal:  Crit Care Explor       Date:  2021-06-11
  10 in total

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