Application of machine learning in predicting hospital readmissions: a sco** review of the literature

Y Huang, A Talwar, S Chatterjee… - BMC medical research …, 2021‏ - Springer
Background Advances in machine learning (ML) provide great opportunities in the
prediction of hospital readmission. This review synthesizes the literature on ML methods and …

HealtheDataLab–a cloud computing solution for data science and advanced analytics in healthcare with application to predicting multi-center pediatric readmissions

L Ehwerhemuepha, G Gasperino, N Bischoff… - BMC medical informatics …, 2020‏ - Springer
Background There is a shortage of medical informatics and data science platforms using
cloud computing on electronic medical record (EMR) data, and with computing capacity for …

Realizing the potential of social determinants data: a sco** review of approaches for screening, linkage, extraction, analysis and interventions

C Li, DL Mowery, X Ma, R Yang, U Vurgun… - medRxiv, 2024‏ - pmc.ncbi.nlm.nih.gov
Background Social determinants of health (SDoH) like socioeconomics and neighborhoods
strongly influence outcomes, yet standardized SDoH data is lacking in electronic health …

[HTML][HTML] A super learner ensemble of 14 statistical learning models for predicting COVID-19 severity among patients with cardiovascular conditions

L Ehwerhemuepha, S Danioko, S Verma… - Intelligence-Based …, 2021‏ - Elsevier
Background Cardiovascular and other circulatory system diseases have been implicated in
the severity of COVID-19 in adults. This study provides a super learner ensemble of models …

Identifying children at readmission risk: at-admission versus traditional at-discharge readmission prediction model

H Symum, J Zayas-Castro - Healthcare, 2021‏ - mdpi.com
The timing of 30-day pediatric readmissions is skewed with approximately 40% of the
incidents occurring within the first week of hospital discharges. The skewed readmission …

Development and validation of an early warning tool for sepsis and decompensation in children during emergency department triage

L Ehwerhemuepha, T Heyming, R Marano… - Scientific Reports, 2021‏ - nature.com
This study was designed to develop and validate an early warning system for sepsis based
on a predictive model of critical decompensation. Data from the electronic medical records …

Multicenter study of risk factors of unplanned 30‐day readmissions in pediatric oncology

K Hoenk, L Torno, W Feaster, S Taraman… - Cancer …, 2021‏ - Wiley Online Library
Background Pediatric oncology patients have high rates of hospital readmission but there is
a dearth of research into risk factors for unplanned 30‐day readmissions among this high …

Prolonged hospital length of stay in pediatric trauma: a model for targeted interventions

D Gibbs, L Ehwerhemuepha, T Moreno, Y Guner… - Pediatric …, 2021‏ - nature.com
Background In this study, trauma-specific risk factors of prolonged length of stay (LOS) in
pediatric trauma were examined. Statistical and machine learning models were used to …

Race, ethnicity, and insurance: the association with opioid use in a pediatric hospital setting

L Ehwerhemuepha, CD Donaldson, ZN Kain… - Journal of racial and …, 2021‏ - Springer
Background This study examined the association between race/ethnicity and health
insurance payer type with pediatric opioid and non-opioid ordering in an inpatient hospital …

Realizing the potential of social determinants data in EHR systems: A sco** review of approaches for screening, linkage, extraction, analysis, and interventions

C Li, DL Mowery, X Ma, R Yang, U Vurgun… - Journal of Clinical and …, 2024‏ - cambridge.org
Background: Social determinants of health (SDoH), such as socioeconomics and
neighborhoods, strongly influence health outcomes. However, the current state of …