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Recent technological developments have sparked endless discussion on the implications of Artificial Intelligence in the modern world. Using addy.ai, we firmly believe that AI holds the potential to revolutionize the back office workflows of the healthcare industry. In particular Large Language Models (LLMs) can effectively automate the tedious manual tasks that burden healthcare clinicians today. By embracing these emerging technologies and modernizing their infrastructure, clinicians can eliminate laborious documentation and data-entry efforts, allowing them to focus on more rewarding activities and improving patient care. 

To provide compelling solutions, it is essential to identify and address specific use cases that require deep domain expertise in healthcare workflows and a profound understanding of emerging technologies such as LLMs. The rapid advancement of AI makes it the opportune time for healthcare clinicians to consider how this technology can make their operations more efficient, patient-centric, and ultimately profitable. 

Impact of EMRs

One significant transformation in the healthcare industry has been the adoption of Electronic Medical Record systems (EMRs). These systems have improved access to patient information, enhanced patient safety, streamlined workflows, facilitated communication, enabled data-driven insights, and advanced clinical research. However, they have also increased the burden of data entry for healthcare teams. According to a 2022 Mayo Clinic survey, 63% of physicians in the US are experiencing burnout, with one major contributing factor being the increased documentation demands from EMRs. Physicians spend an average of two additional hours after office hours doing documentation¹, with approximately 16 minutes per patient encounter dedicated to EMR usage, according to Cerner (a leading EMR software company). This increase in data-entry work is not limited to physicians; it affects everyone working in a hospital or clinic. What the healthcare providers need are simple solutions that integrate with EMR systems and automate the manual tasks. 

AI + Automation 

LLMs excel at identifying, extracting, and summarizing key information from large volumes of data in a human-like manner, but at machine speed and accuracy. For instance, AI can classify, review, and summarize documents (patient referrals, lab results, imaging results, etc.)  while engaging in electronic communications, significantly reducing mundane data-entry tasks. Integrating this technology into various EMR systems alleviates the burden of data entry while allowing users to continue working in their familiar EMR environment. Robotic process automation (RPA) tools are used to transfer insights into an EMR without any human involvement.

It is crucial for any back office solution to be very flexible, considering the wide range of healthcare providers from small and mid-sized practices (SMBs) to large health care systems. The SMBs, in particular, have unique requirements and smaller budgets for technology implementations. Flexible AI solutions like addy.ai can greatly benefit such providers, offering customization options that maximize cost efficiency. Addy.ai solutions are built on an AI platform that simplifies targeted text extractions for each individual use case. 

Why Back Office?

While most recent healthcare innovations focus on improving diagnosis and treatment of specific diseases (such as medical imaging and early diagnostics, and robotics in surgery), little investment has been made leveraging AI for the back office functions, which serve as the backbone of any clinical practice. Inefficiencies within these functions exacerbate the current shortage of healthcare workers. Solving these problems can have a significant impact on healthcare practices and improving the well-being of the team. 

Data Security

While LLMs have proven to be highly effective in extracting specific healthcare data, such as demographic information, it’s important to note that companies like OpenAI, which owns ChatGPT, do not yet offer HIPAA-compliant versions. Therefore, healthcare professionals must exercise caution regarding data security whenever using LLMs. They must ensure that transmissions are encrypted and secure to protect sensitive information. 

Some LLMs, such as Microsoft Azure OpenAI services, provide BAAs for HIPAA readiness, and there are emerging specialized LLMs that focus on verticals such as healthcare. Although data security issues will eventually be addressed by LLMs, healthcare providers need to be diligent when evaluating current AI-powered apps to ensure that they adequately address data security requirements. 

No Stopping AI

There is no stopping the impact of AI on the healthcare industry, including its back office functions. It’s only a matter of time before this welcomed advancement allows clinicians to be more patient-facing and less burdened with performing tedious, administrative tasks. AI will provide increasingly better insights that will increase efficiencies, improve patient care, and help overcome labor shortages within the industry. Addy.ai, for its part, already is helping SMB providers to leverage AI for their back office functions so that they can effectively compete in today’s market with efficient, patient-centric, and profitable businesses. 

1. American Medical Association ↩︎