Cargando…

Assessment of Machine Learning vs Standard Prediction Rules for Predicting Hospital Readmissions

IMPORTANCE: Hospital readmissions are associated with patient harm and expense. Ways to prevent hospital readmissions have focused on identifying patients at greatest risk using prediction scores. OBJECTIVE: To identify the type of score that best predicts hospital readmissions. DESIGN, SETTING, AND...

Descripción completa

Detalles Bibliográficos
Autores principales:	Morgan, Daniel J., Bame, Bill, Zimand, Paul, Dooley, Patrick, Thom, Kerri A., Harris, Anthony D., Bentzen, Soren, Ettinger, Walt, Garrett-Ray, Stacy D., Tracy, J. Kathleen, Liang, Yuanyuan
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	American Medical Association 2019
Materias:	Original Investigation
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6484642/ https://www.ncbi.nlm.nih.gov/pubmed/30848808 http://dx.doi.org/10.1001/jamanetworkopen.2019.0348

Ejemplares similares

Predictive Clinical Rule for Readmissions in OPAT. Improving in Security
por: Bengoetxea, Itsaso, et al.
Publicado: (2017)

Prospective Evaluation of a Machine-Learning Prediction Model for Missed Radiology Appointments
por: Rothenberg, Steven, et al.
Publicado: (2022)

Machine learning vs. conventional statistical models for predicting heart failure readmission and mortality
por: Shin, Sheojung, et al.
Publicado: (2020)

Does comorbidity index predict OPAT readmission?
por: Stubbs, Ryan D, et al.
Publicado: (2023)

Predictive Model for Heart Failure Readmission Using Nationwide Readmissions Database
por: Zheng, Lillian, et al.
Publicado: (2022)

Selecting the Best Prediction Model for Readmission
por: Lee, Eun Whan
Publicado: (2012)

Identifying Children at Readmission Risk: At-Admission versus Traditional At-Discharge Readmission Prediction Model
por: Symum, Hasan, et al.
Publicado: (2021)

Predicting and preventing hospital readmission for exacerbations of COPD
por: Kong, Chia Wei, et al.
Publicado: (2020)

Factors predicting readmission in patients with COVID-19
por: Nematshahi, Mohammad, et al.
Publicado: (2021)

Current Trends in Readmission Prediction: An Overview of Approaches
por: Teo, Kareen, et al.
Publicado: (2021)

Knowledge Graph Embeddings for ICU readmission prediction
por: Carvalho, Ricardo M. S., et al.
Publicado: (2023)

Readmission Risk Assessment Tool (RRAT) for Decreasing 30-Day Readmission Rates in Total Joint Arthroplasty (TJA) and Predicting Readmission
por: Dundon, John, et al.
Publicado: (2023)

Starvation vs. the “Ruling Passion”
Publicado: (1875)

Predicting Readmission at Early Hospitalization Using Electronic Clinical Data: An Early Readmission Risk Score
por: Tabak, Ying P., et al.
Publicado: (2017)

Sociocultural and Demographic Factors Predict Readmissions for General Surgery Patients
por: Kovoor, Joshua G., et al.
Publicado: (2023)

Readmission rates in not-for-profit vs. proprietary hospitals before and after the hospital readmission reduction program implementation
por: Birmingham, Lauren E., et al.
Publicado: (2018)

Can we predict early 7-day readmissions using a standard 30-day hospital readmission risk prediction model?
por: Saleh, Sameh N., et al.
Publicado: (2020)

Hospital Readmission in General Medicine Patients: A Prediction Model
por: Hasan, Omar, et al.
Publicado: (2009)

Rates of Complications and Readmissions: In-Patient vs Outpatient ORIF of Calcaneus Fractures
por: Patch, David A., et al.
Publicado: (2022)

Readmission After Elective Ileostomy in Colorectal Surgery Is Predictable
por: Iqbal, Atif, et al.
Publicado: (2018)

Integration of patient experience factors improves readmission prediction
por: Burke, Harry M., et al.
Publicado: (2023)

Predicting mortality and readmission based on chief complaint in emergency department patients: a cohort study
por: Sørensen, Søren Flink, et al.
Publicado: (2021)

B‐Type Natriuretic Peptide Predicts 30‐Day Readmission for Heart Failure but not Readmission for Other Causes
por: Flint, Kelsey M., et al.
Publicado: (2014)

All-Cause Readmission or Potentially Avoidable Readmission: Which Is More Predictable Using Frailty, Comorbidities, and ADL?
por: Mitsutake, Seigo, et al.
Publicado: (2023)

“Rule Out” vs “Do Without”
por: Levsky, Jeffrey M., et al.
Publicado: (2021)

Patient vs provider perspectives of 30-day hospital readmissions
por: Smeraglio, Andrea, et al.
Publicado: (2019)

Preventability of early vs. late readmissions in an academic medical center
por: Graham, Kelly L., et al.
Publicado: (2017)

Using the LACE index to predict hospital readmissions in congestive heart failure patients
por: Wang, Hao, et al.
Publicado: (2014)

Readmission prediction after colorectal cancer surgery: A derivation and validation study
por: D’Souza, Joel, et al.
Publicado: (2023)

Computational complexity: a quantitative perspective
por: Zimand, Marius
Publicado: (2004)

Blood eosinophil count predicts treatment failure and hospital readmission for COPD
por: Kerkhof, Marjan, et al.
Publicado: (2020)

A Machine Learning Model for Predicting the Risk of Readmission in Community-Acquired Pneumonia
por: Aldhoayan, Mohammed D, et al.
Publicado: (2022)

Unplanned readmissions after hospital discharge among patients identified as being at high risk for readmission using a validated predictive algorithm
por: Gruneir, Andrea, et al.
Publicado: (2011)

Prediction Rules for Ruling Out Endocarditis in Patients With Staphylococcus aureus Bacteremia
por: van der Vaart, Thomas W, et al.
Publicado: (2021)

Length of stay and readmission in older adults hospitalized for heart failure
por: Arundel, Cherinne, et al.
Publicado: (2020)

Machine learning for predicting readmission risk among the frail: Explainable AI for healthcare
por: Mohanty, Somya D., et al.
Publicado: (2021)

Trustworthy or flawed clinical prediction rule?
por: Granholm, Anders, et al.
Publicado: (2018)

The Limited Predictive Power of the Pauling Rules
por: George, Janine, et al.
Publicado: (2020)

Simple prediction of mortality in case of readmission to the intensive care unit
por: Klimasauskas, A, et al.
Publicado: (2007)

Readmission to Medical Intensive Care Units: Risk Factors and Prediction
por: Jo, Yong Suk, et al.
Publicado: (2015)

Cannot write session to /tmp/vufind_sessions/sess_upia7dgmbjf8re6q9p1n347mn2