An Overview of RPA & Intelligent Automation in the Healthcare Sector
The recent surveys estimate that the healthcare industry processes 30 billion transactions annually at a cost of more than $250 billion.
This high costs can be attributed to one reason. In other words, these transactions are usually processed manually. As a result, operating margins have been squeezed, and the quality of patient care may also have been negatively affected. Additionally, there is still room for improvement since the healthcare industry is constantly evolving in response to global changes.
In recent years companies in the healthcare sector are increasingly turning to intelligent automation. Furthermore, automation of complex processes can be achieved by combining Robotic Process Automation (RPA) with Artificial Intelligence (AI), and many decision points can also be automated if clear rules are applied to them.
Companies in the healthcare industry can expect substantial benefits as a result of these initiative. In a vendor-agnostic industry survey conducted by ETR, it was found that the average return on investment was +250% for customers across industries.
Among the many benefits of automation in healthcare, the following are among the most notable:
01. Reduce the amount of manual labor.
With intelligent automation, clinical and administrative staff are able to focus on higher-value tasks by automating everything that can be automated.
02. Make cost reductions.
When clinical, compliance, and administrative workloads continue to grow, the need to hire additional staff can be reduced, and an organization will have the ability to scale more easily.
03. Enhance quality.
When used in simple and complex workflow processes, it eliminates the possibility for human error.
Further, the use of intelligent automation, also called cognitive automation or hyperautomation, is the combination of automation technologies with artificial intelligence methods such as the following:
Through intelligent bots that have decision-making capabilities, we can easily able to automate end-to-end processes even if it is having a complex process.
Let's explore a few notable intelligent automation use cases in the healthcare industry in this article, since you can easily identify a RPA vendor to complete the process study and enable the bots for the upcoming P&L impact. :)
Use Case 01: Streamline the patient journey
Patients' overall experience depends on moving smoothly through the different phases of their care. As a result, they get the services they need when they need them. To reduce delays, lab results, examination notes, and the rest of their records must be instantly accessible.
Healthcare organizations usually have highly siloed systems, one of which is the electronic health record. It's challenging to get the right data to the right place. In contrast, intelligent automation allows patient data to be extracted, moved, integrated, and accessed seamlessly.
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Use Case 02: Process insurance claims
Precision is required when processing health insurance claims. There is usually a 10% to 25% error rate, resulting in rework.
It takes several minutes for a health plan employee to verify claim status. It might not seem like much, but consider how many patients or healthcare providers want to check the status of their claims.
Annually, healthcare providers and patients pay billions in billing and insurance-related (BIR) costs. The use of intelligent automation can save healthcare companies hundreds of thousands-if not millions-in employee labor costs. According to McKinsey, intelligent automation will cut costs from claims processing by + 40%.
Use Case 03: Streamline clinical workflows
Automating clinical processes gives doctors, nurses, and other clinicians a respite from repetitive tasks that take them away from treating patients. Using RPA, software robots ("bots") can perform rote tasks that are necessary for positive patient outcomes, but distract clinicians from patient-facing work.
In order to achieve this, how does intelligent automation accomplish it? Bots can integrate data from multiple disparate systems and make it accessible and available from one application to another.
Use Case 04: Payment processing
There is no doubt that billing payment automation goes hand in hand with claims processing automation. As a result of intelligent automation, healthcare providers can get reimbursed from insurance companies much faster and with less hassle than ever before.
The traditional reimbursement process required providers to provide medical histories, diagnostic codes, and other data from disparate systems to be reimbursed. The extraction and aggregation of data can be automated with intelligent automation and get it into the correct format for claim submission.
Use Case 05: Customer Service & Book an appointment
Thousands of dollars are lost each year due to missed appointments. With AI-powered chatbots and RPA bots, repetitive customer service tasks can be handled and patient scheduling can be self-served:
Use case 06: Manage compliance
Healthcare companies always focus on compliance. Legal, regulatory, reputational, and financial reasons dictate compliance with all regulatory requirements.
Role-based access controls can be implemented in intelligent automation to prevent unauthorized access. Further, the detailed, granular data collected by intelligent bots makes it easy to comply with audits and requests for specific data.
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It is also likely that there will be many more opportunities within all health care industries to explore.
As we all know, increasing patient satisfaction while reducing costs is the responsibility of healthcare organization today. As much as possible, they should be efficient, accurate, and minimize errors to benefit employees, payers, and others involved in the healthcare value chain. By eliminating manual work and waste, intelligent automation helps meet their responsibilities.
An intelligent bot can do the job faster, cheaper, and more accurately. This improves operating margins and frees up clinicians and administrators to focus on what matters: improving patient outcomes and experiences.