Make no mistake, Robotic Process Automation (RPA) isn’t anything like the robots you generally see in science documentaries or Sci-fi movies. RPA is all software and it’s remarkably practical and economical enough to be adopted into real-time business applications. However, it also isn’t as complex and ridiculously expensive like the ‘aware’ computer systems that can make decisions for humans. Unlike the AI stacks of Google and Facebook that understand your choice of music with every minute you spent in cyberspace, RPA is simple.
Simple enough to become a powerful healthcare automation solutions package that offers immediate benefits in terms of time consumption, efforts needed and operational expenditure. In this blog, we look at its primary use cases for 2022 in Healthcare IT.
The Bot Remedy
The healthcare industry is undergoing a tectonic shift in the way healthcare IT solutions are being infused with the ecosystem. However, there are many big bad wolves hampering the progress of care management. They manifest in the form of inaccurate data capture, patient scheduling conundrums, denied claims, cumbersome EHR workflows and many more. Among these inaccurate data entry negatively impacts patient onboarding, billing, prescription management, and diagnosis. While the nature of the errors is simple, the consequences they bear are monumental.
Unfortunately, there are no silver bullets and a golden gun on offer to vanquish these problematic wolves. But, the relief is there is RPA.
Software Robots are capable of taking on thousands of detailed repetitive tasks and processes. Their diligence and accuracy make everyone in the healthcare system – patients, partners, caregivers, administrators, and communities-feel empowered.
The Crux of the Matter – Powerful Use Cases
RPA bots can process transactions, edit or change data, store and calibrate systems. The following are the top five use cases in RPA for healthcare providers to consider in 2022.
Scheduling: Currently, patients book appointments online and providers manage this process manually, despite using a software application to manage schedules. All of this is excluding the work needed in case the patient or care provider decides to reschedule. As a consequence, no-shows have become common. Care providers often accept no-shows as a part and parcel of the business and move on with their life.
After RPA: Through RPA, care providers can hope to significantly improve their scheduling processes. An RPA bot can be deployed to collect data from the patient by offering them a ‘self-service’ approach for booking appointments. It then uses the accumulated data to schedule an appointment with a relevant doctor. Upon completing the booking, it marks the date on the calendar of the appointment management application. In case of changes in the schedule, it updates the other party through e-mails once the input for the schedule changes are completed by either the doctor or the patient.
Insurance Verification: Health insurance processes are replete with high-volume and repetitive back office processes. But, most of these tasks such as insurance verification bear profound importance. One wrong step in the process can lead to unpleasant consequences for the provider and patient, in other words, denied claims. Insurance verification currently involves manual data extraction, integration of claim relevant data from diverse provider systems such as PMS and EHR.
After RPA: The exhaustive nature of error tracking workflows to prevent errors add another layer of complexity to the verification process. RPA remedies the cumbersome nature of insurance verification by automating eligibility information and benefit amount collection from payer sites. They can then compile information and update the patient profile on the PMS system as required by care providers.
Claims Management: Patient data input, data evaluation and submission are the three main components of the claims management process. The entire process is currently a manual task that require trained teams to enter, evaluate, correct and maintain claims data. All of the possible errors with manual processes can lead to denied claims. As the number of days a denied claim sits as a receivable increases, so does its dramatic impact on the healthcare facility’s cash flow.
After RPA: RPA gives healthcare providers a fast, reliable, accurate, and economical alternative to manual labor. Its sheer speed of operation and accuracy reduces the frequency and propensity of denied claims and it contributes to improved data quality and adherence to regulatory requirements such as the CMS Medicare Claims Processing Manual.
Discharge Instructions: Patients are usually prescribed medications and rehabilitative regiments after discharge. However, some patients usually do not follow their post-hospitalization responsibilities well. There is also usually no way for healthcare providers to ensure patients adhere to medication schedules. But encouraging patients to follow post medication guidelines through periodic reminders and updates can induce the behavioral change that most doctors desire in a patient after discharge.
After RPA: RPA bots can be configured to deliver post medical guidelines and follow-up notifications urging the patient to get in touch with doctors regularly. The bots can also send notifications for scheduled tests and follow-up appointments that help care providers track their progress after discharge.
Remote Care: Remote Patient Monitoring (RPM) involves routing physiological data such as heart rate, blood glucose level to an EHR system through the medical device attached to the the patient. RPM services primarily involve manual data entry and are an asynchronous process (non-real time). Even with a synchronous process in place that updates clinical teams with prompts for intervention, they are still required to reach out to a patient through phone calls or app notifications.
After RPA: RPA can integrate with the medical devices of the patient to monitor spikes in patient vital signs to dispatch reminders to the patient to measure blood pressure or blood glucose levels. It can also draw conclusions based on pre-determined workflows that require input from a patient or their dependent. For example, an RPA bot can notice a spike in blood pressure and alert the patient to update the medication schedule for the day. This automated action eliminates the need of manual intervention from a clinician.
The five use cases we have listed above only make up the tip of the iceberg. There are many such use cases to be depending on the specializations and the scale of operations of care providers. If simply eliminating manual intervention can revitalize healthcare operations, healthcare providers stand to gain significantly by exploring the potential of RPA in healthcare.
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