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Medical practices need the equivalent of a point-of-sale system — AI might be the key

January 14, 2022
Artificial Intelligence Business Affairs
Lohith Reddy
By Lohith Reddy

Larger medical groups and hospital systems have proven attractive to many newly minted physicians, while a large proportion of smaller medical groups have been acquired and merged. That means doctors choosing to remain in solo or small practices must operate them in the most efficient manner possible to remain competitive.

While that sounds straightforward, it never is. Patients still must be seen, treated and referred in large numbers before a physician even has a chance to even glance at back office operations, which can only operate smoothly if competent staff can be recruited and retained. And while many doctors have obtained their MBAs, that number remains relatively small. In other words, doctors are clinicians first and businesspeople only when they have the time.

The COVID-19 pandemic has also scrambled priorities for patients. That means those who are coming through the doors on any given day may represent a drastically different mix compared to before the pandemic, and with different needs.

However, the shrewdest way for a physician to envision their practice from a purely business perspective may be not to focus strictly on what occurs during a patient encounter, but what occurs afterward.

While comparing the post-encounter process to the checkout line in a retail business sounds crude, it is not inaccurate. Those checkout lines carefully record all the transactions, adjust inventory and generate a bill of goods to collect payment. And the data being collected by a retailer’s point-of-sale system can be analyzed to try to better meet consumer demand while increasing revenue.

While retailers rely on what are known stock keeping units (SKUs) to monitor and manage inventory and sales, medical practices rely on current procedural terminology (CPT) codes in order to quantify the care that has been rendered and to collect payment for those services. And while it again seems distasteful to compare the collecting of codes from a patient encounter to gathering retail items in a basket for the checkout line, it is also not inaccurate.

The retail sector has numerous, if not a staggering amount of point-of-sale (POS) hardware and software products to quantify, analyze and boost revenue. While some suites are available to medical practices for inventory control, the equivalent of a full-fledged POS does not exist.

Artificial intelligence (AI) may be a way to address that issue. AI is already being used in many facets of healthcare delivery, such as analyzing eye scans for diabetic retinopathy and other serious medical conditions. It is also being placed into newer version of electronic medical records systems to assist in diagnosing patients. But its use in medical coding is relatively rare.
Using AI to analyze coding practices can help medical practices answer critical questions.

Among them:

• Can optimal coding be performed without a dedicated staff of coders?
• Can revenue be optimized and potentially even increased without a concurrent risk of audits or clawbacks from commercial insurers or the Medicare program?

Because there really isn’t a point-of-sale equivalent for physicians, suboptimal coding is omnipresent, leading to untold millions of dollars unwittingly left on the table by physicians throughout the U.S. Again, the clinician over businessperson role doctors must play is a critical factor. Providers must often see numerous patients in a short period of time, leading them to forgo charting notes. When notes are taken, they’re often written in a way that will omit critical codes. For example, a physician or a nurse practitioner may not be aware that a single procedure that is commonplace in a primary care or urgent care practice – such as placing a splint on a patient’s arm – can include multiple codes. More crucially, they may also miss modifiers that over time will exacerbate revenue shortfalls.

This is because most physicians are entering their patient encounter with a paper chart and a pen to keep track. Conversely, walk into any retailer – even many mom-and-pop businesses – and pen and paper can be awfully hard to find. Most business is being executed with scanners, styli, the Cloud and other high-tech equipment designed to keep an eye on the bottom line and make recommendations when asked.

An AI-based platform for a medical practice can perform similar tasks. By simply providing such platforms with granular but fairly basic encounter data, it can provide recommendations about how to change coding approaches and how physicians, nurses and other medical staff can go about documenting patient encounters with maximum efficiency.

The results are eye-opening: One urgent care practice in the Southeast U.S. was able to increase monthly revenue by 25% within a few months of deploying an AI-based platform to analyze its coding approach. The platform found that nearly every patient encounter was not properly coded, and in many instances perfectly appropriate modifiers that properly compensate for the labor and expertise provided were not being used. The practice had been in danger of shutting down due to COVID-19 cutting patient volumes by 75%. AI is keeping it in business.

With the number of retail clinics growing throughout the U.S. and drawing patients for their convenience and ease-of-use, a more bottom-line approach to primary care medicine is inevitable. However, smaller practices don’t need to completely transform themselves into something their principals don’t recognize or appreciate in order to remain afloat. A little AI can not only go a long way toward closing the gap with larger medical practices, but also keeping their doors open.

About the author: Lohith Reddy is senior vice president with ExdionRCM, a division of Exdion Solutions, which is a global health-tech firm helping medical practices prepare for the digital tomorrow. Its technology solutions transform revenue cycles through AI, data science and automation. As a medical coding powerhouse, the company services numerous medical practices through its flagship platform ExdionACE.

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