Publications by authors named "Mohammed A Mahyoub"
Article Synopsis
- Discharge date prediction is essential for efficient healthcare management, helping with resource allocation and improving patient care by providing accurate estimates for when patients will leave the hospital.
- The study developed a prediction model using machine learning (XGBoost) and collaborated with clinical experts to gather relevant data, which was integrated into an Electronic Medical Record system for practical use.
- The model improved prediction accuracy significantly, reducing excess hospital days by nearly 19%, highlighting its effectiveness for enhancing healthcare resource management and patient outcomes, with recommendations for future research on its long-term applicability.
Background: Sepsis is a life-threatening condition caused by a dysregulated response to infection, affecting millions of people worldwide. Early diagnosis and treatment are critical for managing sepsis and reducing morbidity and mortality rates.
Materials And Methods: A systematic design approach was employed to build a model that predicts sepsis, incorporating clinical feedback to identify relevant data elements.
The Impact of a Hybrid Hospital at Home Program in Reducing Subacute Rehabilitation.
Risk Manag Healthc Policy
October 2023
Purpose: The purpose of this study was to compare health outcomes for patients receiving acute care in their homes through a Hospital at Home (HaH) program to outcomes for inpatients in the traditional hospital setting.
Patients And Methods: We compared outcomes for patients in a HaH program at Virtua Health in 2022 (N = 271) to traditional inpatients during the same year (N = 13,776) with the same diagnoses. We defined outcomes as recommendations for subacute rehabilitation (SAR) upon discharge as this recommendation indicates the need for additional therapy based on a physician's assessment of the patient.