Projects
Since 2017, our team has deployed several projects throughout The Mount Sinai Hospital System.
CDI Alert System for Metastatic Disease
The Metastatic streaming engine was developed to identify inpatient encounters with high risk of metastatic disease (cancer that spreads from where it started to a distant part of the body) and optimize the capture rate. It was deployed at The Mount Sinai Hospital on...
Oncology Prognosis Tool
The Oncology Prognosis Tool is a classifier used to determine the eligibility of patients for serious illness conversation. It was deployed at the Mount Sinai Oncology Outpatient unit in March 2021 and Inpatient unit in August 2022. Challenges Majority of patients(~...
Patient Experience Project
The objective of the Patient Experience project is to predict patients who are most likely to report a sub-optimal inpatient experience in order to initiate service recovery, or other engagement strategies of the patient experience team, prior to discharge. The...
MUST-Plus: A Machine Learning Classifier That Improves Malnutrition Screening in Acute Care Facilities
The paper below was published in the Journal of the American College of Nutrition, 40:1,3-12. Prem Timsina, Himanshu N. Joshi, Fu-Yuan Cheng, Ilana Kersch, Sara Wilson, Claudia Colgan, Robert Freeman, David L. Reich, Jeffrey Mechanick, Madhu Mazumdar, Matthew A. Levin...
MEWS++: Enhancing the Prediction of Clinical Deterioration in Admitted Patients through a Machine Learning Model
The research paper below was published in Journal of Clinical Medicine. 2020; 9(2):343. Kia A, Timsina P, Joshi HN, Klang E, Gupta RR, Freeman RM, Reich DL, Tomlinson MS, Dudley JT, Kohli-Seth R, Mazumdar M, Levin MA. MEWS++: Enhancing the Prediction of Clinical...
48hr Discharge (Length of Stay) MSH
The 48Hr Discharge (aka Length of Stay) streaming engine was created to predict the probability of patient discharge (by 2pm and midnight daily) and therefore help automate the RTDC system and assist in the prioritization of remaining tasks at Mount Sinai Hospital....