Using machine learning to minimize delays caused by prior authorization: A brief report-Reference-Cited by-同舟云学术

Using machine learning to minimize delays caused by prior authorization: A brief report

Published:2021-01-01 Issue:1 Volume:8 Page:
ISSN:2331-1916
Container-title:Cogent Engineering
language:en
Short-container-title:Cogent Engineering

Author:

Choudhury Avishek¹^ORCID,Perumalla Sunanda²

Affiliation:

1. Applied Data Science, Syracuse University, Syracuse, USA

2. Senior Data Scientist, Integris Health, Oklahoma

Funder

no funding from any agency in public, commercial, or not-for-profit sectors

Publisher

Informa UK Limited

Subject

General Engineering,General Chemical Engineering,General Computer Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/23311916.2021.1944961

Reference50 articles.

1. Abrams, K., O’Rourke, O. & Gerhardt, W. Viewing post-acute care in a new light: Strategies to drive value: Deloitte; 2017 [cited 2019 January 10]. Deloitte. Available from: https://www2.deloitte.com/content/dam/Deloitte/us/Documents/life-sciences-health-care/us-lshc-post-acute-care-innovation-report.pdf.

2. Survey: Patient clinical outcomes shortchanged by prior authorization [Internet]. American medical association 2018; March 19. Available from: https://www.ama-assn.org/survey-patient-clinical-outcomes-shortchanged-prior-authorization

3. Healthy People 2020

4. High-Risk Breast Lesions: A Machine Learning Model to Predict Pathologic Upgrade and Reduce Unnecessary Surgical Excision

5. Weakly supervised natural language processing for assessing patient-centered outcome following prostate cancer treatment

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