Discharge timing: Does targeting an ideal length of stay for patients undergoing colectomy impact readmissions and costs of care?

Cousin-Peterson, Evelena; Janjua, Haroon; Barry, Tara M.; Baker, Marshall S.; Kuo, Paul C.

doi:10.1016/j.amjsurg.2020.11.009

The American Journal of Surgery

2021

DOI: 10.1016/j.amjsurg.2020.11.009

|View full text |Cite

Discharge timing: Does targeting an ideal length of stay for patients undergoing colectomy impact readmissions and costs of care?

Evelena Cousin-Peterson

Haroon Janjua

Tara M. Barry

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2021

2024

Publication Types

Select...

Article4

Relationship

Self Cite1

Independent3

Authors

Journals

Cited by 4 publications

(1 citation statement)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Various strategies have been explored to abate unforeseen hospital readmission. Models determining optimal discharge timing, ideal hospital lengths of stay, location of patient discharge, and the temporal influence of index hospitalization have all been investigated to further reduce this burden (6,7,(9)(10)(11). While the complete cadre of factors comprising the healthcare macroenvironment and their influence on readmission has yet to be elucidated, several authors have made significant strides in identifying modifiable predictors for individualized disease processes.…”

mentioning

confidence: 99%

Identifying and mitigating factors contributing to 30-day hospital readmission in high risk patient populations

Rogers¹,

Kuo²

2021

Ann Transl Med

Self Cite

View full text Add to dashboard Cite

mentioning

confidence: 99%

Identifying and mitigating factors contributing to 30-day hospital readmission in high risk patient populations

Rogers¹,

Kuo²

2021

Ann Transl Med

Self Cite

View full text Add to dashboard Cite

Wearable technology and the association of perioperative activity level with 30-day readmission among patients undergoing major colorectal surgery

et al. 2021

View full text Add to dashboard Cite

A systematic literature review of predicting patient discharges using statistical methods and machine learning

Pahlevani,

Taghavi,

Vanberkel

2024

Health Care Manag Sci

View full text Add to dashboard Cite

Discharge planning is integral to patient flow as delays can lead to hospital-wide congestion. Because a structured discharge plan can reduce hospital length of stay while enhancing patient satisfaction, this topic has caught the interest of many healthcare professionals and researchers. Predicting discharge outcomes, such as destination and time, is crucial in discharge planning by helping healthcare providers anticipate patient needs and resource requirements. This article examines the literature on the prediction of various discharge outcomes. Our review discovered papers that explore the use of prediction models to forecast the time, volume, and destination of discharged patients. Of the 101 reviewed papers, 49.5% looked at the prediction with machine learning tools, and 50.5% focused on prediction with statistical methods. The fact that knowing discharge outcomes in advance affects operational, tactical, medical, and administrative aspects is a frequent theme in the papers studied. Furthermore, conducting system-wide optimization, predicting the time and destination of patients after discharge, and addressing the primary causes of discharge delay in the process are among the recommendations for further research in this field.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Discharge timing: Does targeting an ideal length of stay for patients undergoing colectomy impact readmissions and costs of care?

Cited by 4 publications

References 7 publications

Identifying and mitigating factors contributing to 30-day hospital readmission in high risk patient populations

Identifying and mitigating factors contributing to 30-day hospital readmission in high risk patient populations

Wearable technology and the association of perioperative activity level with 30-day readmission among patients undergoing major colorectal surgery

A systematic literature review of predicting patient discharges using statistical methods and machine learning

Contact Info

Product

Resources

About