beth israel deaconess medical center a harvard medical school teaching hospital

To find a doctor, call 800-667-5356 or click below:

Find a Doctor

Request an Appointment

left banner
right banner
Smaller Larger

Hospital Medicine Research

Hospital Medicine Research encompasses a wide range of work aimed at improving the inpatient hospital care continuum. From the moment that a patient is admitted, up until the time of discharge, opportunities exist to improve patient healthoutcomes. Investigators within the Division are conducting studies with the goal of giving hospital clinicians tools for the proactive prevention of common medical complications within the hospital environment. The result will be safer, smarter, and more efficient, patient-centric care. Below is a sampling of the Division's ongoing work in this area.

Inpatient Medication Utilization

Research into inpatient medication utilization focuses on discerning connections between patterns of medication usage and patient outcomes. Dr. Shoshana Herzig has investigated the risks and benefits of acid-suppressive medication in medical inpatients, providing an evidence base for decisions surrounding this commonly used class of medications. Dr. Herzig's current research aims to determine whether sedative medications also represent potentially modifiable risk factors for hospital-acquired complications, with the ultimate goal of developing targeted, generalizable interventions to improve prescribing and reduce patient risk.

Clinical Predictive Guidelines

Clinical predictive guidelines enable clinicians to quickly identify, diagnose, and prevent patient health complications in the hospital setting. Dr. Ed Marcantonio, Chief of the Division's Section of Research, has conducted extensive work into clinical prediction rules for the onset of delirium during hospitalization and post-acute care. His current work focuses on the discovery of biomarkers that may serve as risk factors for delirium, along with developing a clinical diagnostic interview for delirium that will enable more efficient and accurate prediction of this complication.