March 25, 2024

How AI solves healthcare’s antiquated admin problem

In the late 1990s and early 2000s, the adoption of electronic medical records (EMRs) changed the healthcare landscape forever. EMRs enabled clinicians to digitize and store medical records, taking them from paper to the computer and launching healthcare communications into the 21st century. The way these new digital records were produced was novel at the time, but the boom in technology since and has left EMRs in the proverbial dust. Hospitals are left with a communication system that might resemble your old family desktop computer and the old Yahoo web browser that came with it. In order to bring hospital administrative communications up to speed with the rest of the modern world, especially considering the importance of the data they’re dealing with, health systems need to deal with the technological roadblock that is the archaic system behind the old EMR. 

The problem with old school EMRs 

Most hospitals fill out their EMRs manually with a system that requires clinicians to essentially “fill in the blank” with a series of drop-down checklists that broadly target what a clinician is trying to record. In an old school EMR system, all diagnostic and treatment information is organized into rigid blocks that clinicians need to “find” by navigating through all the right checklists. Understandably, filling out one medical record with all the necessary nuance and specificity can take a long time because of how each piece of information is retrieved. 

The cost of using such an antiquated communication system is literal and figurative. Clinicians report frequent inaccuracies in EMR medical records because arriving at diagnostic specificity can be so difficult and time-consuming. The Journal of American Medical Informatics Association reported a 24.4% rate of inaccurate documentation in one hospital system alone, concluding that changes needed to be made.  Some health systems even report going back to paper records to ensure accuracy and to avoid figuring out EMRs in the middle of a busy work day. Other EMR databases aren’t sophisticated enough to detect patterns and link other risk factors, leaving patients with an incomplete understanding of their overall health. 

With such a faulty record-keeping system, patients are at risk of receiving inadequate care because of their inadequate medical records. Health systems lose money on health problems that never get solved with frequent hospital readmittance, and patient satisfaction and trust plummets. With a never-ending pile of frustrating EMRs to file, clinicians get burned out and too busy to spend any extra time with their patients. In the healthcare equation, a bad administrative system is bad for everyone. 

How AI transforms the old EMR problem

Early adopters of AI-driven clinical platforms are singing AI’s praises with such enthusiasm because it’s like trading that old 90s family desktop computer for a brand new model with a modern search engine. AI admin systems revolutionize the ability to locate specific information and record it instantaneously. Instead of searching through a series of checklists to “find” the right information, AI platforms eliminate the checklist manifesto altogether by retrieving all relevant information based on any searched term. Instead of sifting through figurative mountains of rigidly organized blocks of information to arrive at that one term, AI platforms locate exactly what is needed, the moment it is needed.  

  • AI-ensured accuracy

Having an AI-managed database changes the foundation of how healthcare communicates. A National Library of Medicine report concluded that AI-enabled decision support systems can increase patient safety by flagging potential errors and even managing patient drugs. By utilizing a powerfully intelligent database, health systems can monitor trends and patterns in patient health like never before. Because AI-driven clinical platforms are so specific, patient records reflect the warranted nuance needed in order to arrive at optimal health outcomes for each individual. 

  • AI-transformed time

Not only do AI-driven clinical platforms save time by finding the right information quickly, but also by recording it for the clinician instantly. By utilizing ambient listening technology which records a clinician’s instructions while talking to their patients, AI-driven clinical platforms like Playback Health save clinicians up to 3 hours a day by automating notes for them. Not only is the note recorded hands-free, but the right information is found and filled-in instantly by the intelligent database. Health systems using AI-driven clinical platforms increase in productivity with all that time saved. 

  • AI-controlled cost

When the monotony of paperwork is overhauled by an intelligent operating-system that does the busy rote work for clinicians, clinicians work-lives change. Clinicians spend less time behind a desk doing secretarial work, and more time seeing more patients per day. The National Institute of Health did a study on the economics of AI in healthcare, finding that the speed and accuracy of AI tools play a big part in how they save health systems money. By flagging medical errors and inaccuracies in paperwork, AI-driven clinical platforms help health systems do the job right the first time, saving money on materials, hospital beds, clinician appointments. 

As more health systems integrate these powerful new AI platforms into their daily operations, the potential for healthcare to evolve as a whole is imminent. With better tools, better work gets done. In healthcare, better work means more lives and health journeys transformed. 

Playback Health’s unified clinical platform updates healthcare communications to the same modernity of medicine it supports. Get started today.