Khalid Al-Maskari

Artificial Intelligence (AI) is opening up new possibilities for Electronic Health Records (EHRs). Physicians have largely regarded EHRs as a time-wasting hindrance, but fortunately advancements in automation have increased the technology’s utility value. While EHRs are not created equally, an interoperable EHR that can accurately handle administration, data management and patient relations can serve as an asset to clinics. The forecast for EHRs is finally starting to change, and AI is leading the way.

AI-enabled EHR technology has become especially beneficial during COVID-19, as physicians are now tasked with engaging a growing patient population virtually. This is partly because virtual solutions have yet to find a way to replicate the triage process which can introduce data concerns without proper technology. During triage, patients speak with the administrator, nurse, and doctor—all of whom collect data independently. But rather than speaking with admins and nurses, telehealth patients are immediately connected to the provider.

Although having a direct connection to the health care provider can be ideal for patient efficiency, it can also make it more difficult to properly obtain and manage data. Providers relying on standard meeting services or legacy technology are forced to manually enter the data into their EHR, then hope their existing tools and remote administrators can handle billing appropriately. Conversely, an EHR equipped with AI can handle the back-end data entry automatically. This not only helps physicians provide better short-term care, it also allows them to see more patients in a reduced timeframe. Time not spent on data entry can be used to promote better care outcomes.

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Telemedicine was initially created for low acuity care, but it didn’t receive widespread adoption until the onset of the COVID-19 pandemic. Even though the technology was stagnant for decades, telemedicine has now become a critical component for managing cough, cold, flu and more. To address a growing patient population with dwindling provider availability, AI is helping to bridge the gap between patient need and provider time.

By including AI in EHRs, lower acuity patient can be treated at home, these patients no longer risk contracting COVID-19 while seeking treatment, and they receive more convenient care at a time that works for them. Because telehealth can be made available during off hours, low acuity patients don’t need to plan their day around visiting their doctor. They can schedule a virtual appointment at a time that works for them. With AI managing the back-end of low acuity care, providers can also hop on a meeting, treat their patients and immediately see another patient without hesitation.

Although these patients are being deterred from visiting in-person clinics due to the dangers of catching the COVID-19 virus, AI enhanced EHRs makes it possible for them to receive quality treatment nonetheless. This also comes at a benefit to providers. Before the pandemic, providers were less likely to generate low acuity revenue because people were treating themselves. Now, telehealth options make patients more likely to engage with their primary providers to help diagnose and resolve symptoms.

While telehealth is providing patients with at-home, socially-distanced access to a physician, AI is also sending automatic reminders to help them stay on top of their treatment. The platform lets them know when to take their medication, when to rest and when to contact a live physician.

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AI integration in EHRs can improve the clinical workflow for both patients and physicians, but it needs to be implemented properly for best results. A successful AI integration provides clinical teams with the correct decision-making data based on their current patient populations. This data explains where patients are in their care lifecycles and lets providers know if they’d benefit more from telemedicine or from in-person treatment.

It’s also key to remember that AI is meant to reduce the number of non-essential tasks required by staff. If clinics find their teams spending even more time on data entry or administration, it’s best to reevaluate. AI is meant to be a benefit, not a roadblock to patient care. However, the most important component of successful AI integration is interoperability.

A great example of AI interoperability can be found at COPE Community Services in Tucson, Arizona. Because this behavioral health care clinic already had an interoperable network of IT solutions, it was able to instantly implement a robust telehealth offering when COVID-19 struck. The pandemic made it necessary for clinics nationwide to integrate telehealth quickly—which is no easy task in an industry known for slow adoption of technology, but COPE’s strong interoperability put them ahead of the curve. Cohesive and AI-driven technology enabled COPE to become one of the few clinics that didn’t lose revenue during the onset of COVID-19.

“During the first months of the COVID pandemic, clinics were reporting 65-70% loss in billable hours, but COPE’s billing actually increased,” said Rod Cook, CEO of COPE. “COPE is one of the few organizations that can say that, and our EHR’s interoperability is one of the main reasons.”

Society was ill-equipped for the AI revolution before COVID-19, but the adoption of AI in health care is advancing little by little, day by day. Practices that are learning and adjusting are poised for more favorable long-term outcomes than clinics that aren’t positioned to manage the ongoing crisis. AI is a key driver of societal change, and the health care industry is one worth watching.

With more than 20 years of experience in health care, 

 is considered a thought leader by peers in the integrated health care field. As CEO of 

Health Information Management Systems (HiMS)

, Khalid rapidly grew the company from a single, Tucson-based customer to achieve a multi-state presence. HiMS is headquartered in Phoenix, Arizona and designs Electronic Health Records (EHR) software that transforms the integrated health care experience. HiMS creates innovative solutions that lead to better outcomes, lower costs and higher-quality care. The company sets itself apart from its competitors by harnessing the power of artificial intelligence to improve data discovery and extraction and personalize treatment recommendations. Khalid can be contacted at 

Articles

While EHRs are not created equally, an interoperable EHR that can accurately handle administration, data management and patient relations can serve as an asset to clinics.

Artificial intelligence leading the way in EHR interoperability

Effective Revenue Cycle Management (RCM) is non-negotiable for all health care practices, but despite this, clinics across the board are reporting increasing levels of dissatisfaction with their current RCM tools.

According to a 2019 KLAS report, more than one-third of the 140 respondents to their RCM survey said they wouldn’t purchase their vendor’s services again, and even more respondents reported complete dissatisfaction with their vendor’s full RCM outsourcing software.

RCM includes everything surrounding claims processing, and the revenue cycle is the most important administrative function for health care practices. Without it, clinics and hospitals can’t financially support themselves in order to treat their patients. Effective RCM isn’t something clinics should take lightly—their revenue cycles need to be optimized at every stage to ensure cash flow.

 (AI) solutions can save clinics $7 billion each year, according to data from Accenture Analytics. RCM tasks such as coding, billing, collections, denials, and more can now be easily automated with AI.

To get a complete picture of what’s holding effective RCM back, it’s critical to have a basic understanding of the industry’s pain points and to understand how technology can address the mounting issues surrounding the revenue cycle. RCM is constantly changing, but it’s time that it finally changed for the better.

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One of the primary reasons for RCM dissatisfaction is the growth in denied health care claims. The American Academy of Family Physicians reported that practices experience a rejection rate between 5-10%, and each denial costs the clinic an additional $25 to re-process.

Not only does this process frustrate clinical staff, it also causes panic for the patients. Patient out-of-pocket costs have increased four times over the last 12 years, and the average inpatient bill totals nearly $5,000, according to research from TransUnion Healthcare. Although patient insurance plays a factor in high out-of-pocket costs, insurance is just one of five key contributing factors to claim denials.

Incomplete or incorrect or repeated information

While an uninsured medical service might be unavoidable at times, these additional reasons uncover issues with the clinic’s RCM. If an RCM solution is unable to correctly file claims on time, that’s a strong indicator that it could be time to look for a new one. Clinics should never forget that RCMs are supposed to work with them, not against them.

Scalability is a common pain point for clinics and hospitals with multiple locations, but especially for clinics looking to expand. Having one or two people at the front desk to handle the revenue cycle might work for small clinics with low patient volume, but this strategy becomes increasingly ineffective the more the clinic grows.

The key to scaling RCM is automation, and not having robust automation is costing billions. According to the CAQH index, the lack of automation for claims processing costs the health care industry more than $11 billion each year. By having an automatic operational flow, clinics with high patient volumes and multiple locations can effectively speed up their revenue cycles. Instead of employing dozens, or even hundreds of administrative employees, clinics can 

 with artificial intelligence to properly code thousands of claims without risking human error.

 is one of the most important reasons why clinics struggle to manage their revenue cycle. While some clinics operate with no RCM tools, it’s even more common for clinics to have three or more separate RCMs. These RCMs usually can’t communicate with one another, leaving room for patient billing information to get filed incorrectly or lost completely. This causes operational issues and introduces the problem of data silos, and having too many RCM providers spread out across an entire organization is arguably as inefficient as having no RCM at all.

It’s important for clinics and hospitals alike to choose 

 RCM that can be integrated with its existing technology and with the technology at other clinics. Black Book Research discovered that 86 percent of hospital networks with one EHR and RCM vendor stated they were confidently prepared to provide value-based care. And with health care budgets that are tighter than ever before, clinics need an interoperable solution that can address everything, from changing regulations, all the way to data size management.

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One of the best ways RCM can improve is by prioritizing patient pre-registration. By having as much information as possible about patient insurance eligibility, scheduling, and past payment information before the patient walks in the door, clinics can get a better understanding of the patient’s ability to pay. This can be done easily by using a patient portal. The portal makes it simple for patients to conveniently pay their bills online, and it makes it possible for the clinic to send reminders and notifications to help keep the revenue cycle on track.

It’s equally as important for clinics to automate the revenue cycle strategically. When systems are both automated and interoperable, it allows the revenue process to operate seamlessly with little room for error. Otherwise, providers that don’t take a strategic and detailed look at their RCM’s automation capabilities could just be adding an extra layer of complexity to the process. And as mentioned, the more that can be automated on the front-end of the patient lifecycle, the better. By having a strong front-end, staff members who handle the back-end have more accurate information to work with.

No matter where a patient’s claim is in the revenue cycle, clinics should have an RCM that’s able to process all claims quickly, correctly and seamlessly. By prioritizing the technology that powers the revenue cycle, clinics should see a boost in their bottom lines.

 (HiMS), a company that offers Axiom Electronic Health Record (EHR) software that harnesses the power of technology to create value for integrated health care providers.

Advanced, user-friendly artificial intelligence (AI) solutions can save clinics $7 billion each year