We introduce you to a roadmap for successful adoption of this innovative approach.
Administrators and Providers
Administrators
Administrators bear the unique responsibility of controlling costs impacting the bottom line from many perspectives, the more challenging of which can be the unintended results from clinical decision making.
EPhysicians Office reduces cost, and in some cases, liability, by improving allocation of resources & supporting physicians in making better clinical decisions. Click the link Key To The Solution for an overview. Then explore the 3 application videos below to learn how our unique service accomplishes both.
Applications
Non-attendance “no shows”
Here is an innovative automated approach to solving a problem that is commonplace in any outpatient clinic, representing the first step in achieving improvement in service, outcomes and cost. I introduce the reader to the following slide presentation, followed by a link to our published study in IEEE, the engineering journal.
Covid
Identified during the pandemic created the need to have a data-driven contingency plan ready to deploy BEFORE a facility is overwhelmed. See the following slide. For further details regarding the innovative approach to Covid developed by E Physician’s Office, please click on the above link.
Chest pain in an ED.
Medical facilities across the U.S. face challenges in managing acute chest pain efficiently while controlling costs. E Physician’s Office offers a streamlined, automated analysis to enhance care, optimize outcomes, and reduce hospital expenses within existing workflows.
Providers
Introduction
ED/Cardiac
Evaluation of patients with chest pain presenting to an emergency department has been a perennial problem for clinicians and hospital systems. We present an IT tool with machine-learning capability that assists the provider in the triage of patients with indeterminate chest pain, thereby impacting service, outcomes and costs.
GI/Oncology: Barrett’s Esophagus Progression
A novel approach, based on unique machine-learning technology, to address a clinical scenario that continues to concern gastroenterologists and their patients. This was presented at a DDW annual conference.
Nonattendance/ No shows
Click on Nonattendance/No shows section under Applications and the IEEE publication for a detailed discussion of the methodology in building and testing our analytic tools.
Behavioral Health
GI/ID
An example of the benefit of machine-learning technology in uncovering factors in a clinical scenario that may be adversely affecting outcomes, not detected previously, and addressing them, thereby leading to improvement in service, outcome and cost in healthcare.
IEEE Publication
A robust web-based predictive tool, based on thousands of data sets aggregated from multiple hospitals within an IDN, followed by reiterative modeling and tested for validity. Published in IEEE, the premier on-line engineering forum, and presented at the annual CEWIT Stony Brook conference in New York. View Article.