EHR Reimagined: OmniMD adds artificial intelligence and machine learning to its EHR and RCM solutions

OmniMD, a leading provider of integrated Health IT platforms and services for medical practices incorporates AI and machine learning into its EHR and RCM solutions for medical practices. When thinking of EHRs, we usually think solely about the clinicians or the clinical elements; we are not always considering the revenue cycle management process being integrated and working harmoniously in tandem through a mutual exchange of data.
“OmniMD’s Advanced Data Science group has been working on AI and machine learning solutions for the past 3 years, “said Divan Da've, founder and CEO of OmniMD. “Our initial focus is specifically on machine learning-based clinical decision support systems, population management, predictive analytics, and financial.”
In this perpetually evolving healthcare landscape, single and/or integrated platforms across ambulatory settings will be a necessity for clinical, financial, and operational data flows. In the value-based care model, payments will be now considered based on the accuracy and completeness of medical documentation of services rendered and managed by the providers.
When considering the clinical components for appropriate use of an EHR, a practice will benefit from this data exchange:

Say Hello to ALICEA


ALICEA (Artificial & Learned Intelligence Clinical Evidence Assistant) is OmniMD’s new AI clinical decision support tool. To treat diseases in today’s care ecosystem, providers need to collaborate their care delivery with people, processes, and technology; hence Clinical Decision Support System (CDSS). ALICEA ensures that clinical staff have all the information they need when they need it to manage patients while helping them document and achieve their quality enhancement goals.

OmniMD AI Delivers Value and Efficiency

A typical provider has an average patient load of 2,500 and spends time doing a variety of daily tasks that can be assisted with machine learning such as following clinical care guidelines, writing prescriptions, reviewing labs,examining imaging results, addressing patient phone calls .. all while handling their day-to-day operations! It is estimated that a provider would need 21.7 hours a day to accomplish these tasks.
ALICEA can save 60-180 minutes of physician, nurse, medical assistant time per day.

One way ALICEA does this is through more efficient AI-assisted quick charting:

•  Initial visits can be charted in 180 seconds. (Suggested History & Physical, Differential Diagnosis & Treatment Order set for disease/sign or symptoms)
• Follow-up visits can be charted in 90 seconds. (Review previous visit note and document by exception) 

OmniMD AI Revenue Cycle Management

Healthcare providers are unnecessarily experiencing deteriorating revenues due to a variety of preventable and correctable reasons. Claim processing errors is an issue that immediately comes to mind. It is estimated that roughly one in every 5 claims being submitted are processed incorrectly.  Besides claim processing errors, discrepancies between submitted claims and the payments received can also impact revenue and your bottom line.