How Can Business Leverage Hyperautomation to Improve Efficiency in RCM?

In the ever-growing and changing era of Digital Transformation, businesses face a tsunami of valuable data. Collecting, storing, and processing this data for analysis is an overwhelming task. The Healthcare industry is no exception. Healthcare organizations constantly face the challenge of maintaining a profitable business while delivering improved care solutions. Not to forget, they must also ensure transparency in treatment, cost, and care.

Revenue Cycle Management (RCM) in healthcare prioritizes efficient alignment and management of all the administrative and clinical paperwork associated with individual patients. While AI-powered automation has simplified the manual management of the multitude of paperwork, revenue management is the newest application for automation.

RCM in the healthcare industry encompasses almost every detail, from patient registration to billing, insurance, payment, and related fields concerning revenue generation. Apart from efficiently monitoring and planning the financial roadmap, RCM automation has the potential to deliver numerous benefits, including streamlining several manual administrative tasks.

Hyperautomation emerges as the most practical solution for HCPs. It helps businesses focus on increasing profit margins while executing the right strategies and policies to boost efficiency. Furthermore, Hyperautomation aids in reducing costs and makes the revenue cycle more transparent and optimized.

What Is Hyperautomation, and How Is It Different from Intelligent Automation?

Hyperautomation is an amalgamation of multiple disruptive technologies like artificial intelligence, data analytics, big data, deep learning, RPA, etc., to amplify automation across different areas and augment human abilities.

A crucial aspect of Hyperautomation is allowing businesses to maximize operational efficiency by automating long-tail heavyweight tasks. Hyperautomation infuses machine intelligence into traditional processes to create self-learning models that can function with minimal human intervention. This is how it creates a resilient infrastructure.

While different from automation like Robotic Process Automation (RPA) and Intelligent Automation (IA) already democrats the automation requirement of a business, hyperautomation is still a distinct term and action. Hyperautomation harnesses the best efficiencies of RPA and Intelligent automation like artificial Intelligence, machine learning, and data analytics to streamline complex and vital business techniques for relevant business solutions. Hyperautomation initiatives emerge across numerous industries, including retail, banking & insurance, manufacturing, and healthcare.

CVS Health successfully implemented a new system using a combination of AI, RPA, machine learning, data analytics, and natural language processes (NLP) to automate their cross-functional, time-consuming manual tasks. VP analyst Frances Karamouzi quotes, “The initiative achieved classic automation goals, such as cutting administration time and costs as well as errors and risks, but also delivered a competitive differentiator.”

Medicine and perfumery distributing company GAM Pharmaceuticals faced a predicament about several data errors due to manual entry and delayed customer quotes. However, after implementing a custom automated solution to automate 22 rule-based processes across various business platforms, GAM Pharma saved 120,000 BR$ annually on manual tasks while increasing the speed of responding to customer requests.

Another instance reflects, that AMN healthcare made significant errors while processing timecards pertaining to the recruitment process outsourcing solutions to American HCPs by placing freelance medical staff for open healthcare positions. The cards tracked the hours of medical staff and listed their due payments accordingly while also billing the hospital for the same.

Due to inefficient data tracking solution, AMN lost almost 200 cards per year, formulating potential legal risks for the company. They sought solutions through intelligent or cognitive automation through a mobile application that allowed staff to upload photographs of their time cards on the company servers. They needed an automation tool to process those photos and route them to the appropriate team for further processing. Taking this approach, the company reduced the time spent on processing said timecards by up to 68% while reducing the number of hours seeking human intervention while processing from 8000 to 2600.

Hyperautomation assimilates various automation elements for a real digital transformation for businesses to scale up and transcend various organizational barriers.

Hyperautomation Vs Intelligence Automation (IA)

Intelligence Automation (IA) infuses several AI technologies like Natural Language Processing (NLP), Machine Learning, Optical Character Recognition (OCR), Intelligent Document Processing ( IDP), and Robotic Process Automation (RPA) to create a highly advanced form of human intelligence for performing complex tasks.

While hyperautomation and intelligent automation are often considered the same, they have a fair share of subtle differences:

How Can Hyperautomation Boost RCM Efficiency?

Hyperautomation through AI is mostly integrated with other pre-designed methods of maintaining RCM efficiency. Since the early 90s, hospital management bodies have implemented EDIS systems to keep logs of emergency patient data. Organizations design management systems to escalate RCM efficiency through AI. They incorporate advanced AI tools in predefined hospital information systems and EHR interfaces aided by RCM-IT vendors, aligning various workflows and boosting interoperability.

Hyperautomation, as an optimization-oriented process, improves overall efficiency. Healthcare organizations that integrate AI-based Hyperautomation processes are programmed to collect and analyze big data to understand patient needs better. ML algorithm-based calculative predictive models augment human actions and improve decision-making processes, enhancing the RCM cycle significantly.

AI/ML solutions help fast-track claim adjudication and reduce claim abandonment rates. RCM professionals use precisely coded tracking processes to track every step and claim in the revenue cycle process, reducing the number of claims per se. AI solutions transcript identified data during entry and recheck them to correct any possible mistakes while improving medical billing accuracy.

Most healthcare organizations, pre-hyperautomation, faced significant challenges in implementing RCM solutions. Statistics stated the US healthcare sector faced a monthly revenue loss of over $50 billion amidst the pandemic between March to July 2020 and over $206.6 billion in total.

Besides providing an efficient service, it is equally crucial for the HCPs to maintain a financially stable platform for their business to be kept afloat.

Some of the critical RCM pain points are –

• Inefficient RCM processes that slow down cash flows and reduce ROIs. The US lost 15% of gross healthcare expenses to poor RCM operations, straining an organization’s resources and causing an imbalance between delivering treatment plans and ensuring adequate profits.
• Coding errors and billing inefficiencies that can potentially affect million-dollar healthcare-based deals.
• The growing demands for staffing in different tiers of RCM manual operation. Primitive manual RCM management and static staffing structures fail to deliver patient needs.
• Creation and execution of employee-oriented training programs to support a healthcare company’s overall performance and revenue generation.

Hyperautomation offers uptakes for various segments of the healthcare industry. Different processes in the healthcare industry solicit solutions from AI-providing bodies to simplify internal operations and make administration management more convenient for HCPs. Consequently, HCPs can focus on innovating and implementing better healthcare solutions for patients.

For example, AI-based error detection systems and RPA data management software to input, sort, and manage customer/patient data. Again, advanced ML algorithms can analyze patient data and detect symptoms to diagnose or predict potential diseases in the early stages. Thus, doctors can start the treatment promptly to increase the life expectancy of patients.

Hyperautomation streamlines RCM in various ways, like –

• Automating Routine Tasks – Hyperautomation incorporates AI solutions into routine processes. Robotic process automation can automate communications such as app/website queries, first-line customer service calls, and administrator questions. HCPs must adhere to strict data management policies and regulatory compliance protocols because they deal with sensitive records. Hyperautomation can provide a robust and secure model for data storage and transfer.
• Convenient Patient Assistance – Hyperautomation can streamline and manage registration tasks with high accuracy and speed. They can match patients with the right providers at their nearest location and schedule medical appointments. AI-powered automation software excels at data capture, making it easier for patients to access the necessary healthcare services instantly.
• Digital Assistance – Hyperautomation boosts internal healthcare processes, freeing human employees’ valuable time. Remote healthcare apps allow medical professionals to monitor patients’ vitals and prescribe appropriate measures. They make it easier for HCPs to prioritize the needs of different patients and assign medical staff accordingly.
• Managing Financial Documents – Medical billers and coders can shift to processes requiring critical thinking and domain knowledge of medical procedures. Automated medical billing software can monitor patient prescriptions, send reminders to purchase medicines, book appointments, and process bills faster. Using Hyperautomation tools allows HCPs to design personalized treatment plans for patients.

Hyper-automation in various tiers of RCM operations strengthens the overall performance of a healthcare organization and aligns different vectors in a healthcare management system to fulfill crucial needs. Statistics show that 78% of healthcare conglomerates implement Hyperautomation in RCM and automate numerous aspects of a revenue cycle to fulfill care demands.

Hyperautomation-driven RCM for Better Care Delivery and Increased ROI

Hyperautomation in RCM management is the need of the hour. As much as the common mass needs affordable front-end medical services, HCPs must maintain administrative processes smoothly to ensure that. After all, healthcare organizations must churn adequate profits to continue servicing patients in need.

Thus, HCPs must adopt intelligent solutions to fulfill the dynamic healthcare needs of an expanding market and streamline management workflows for increased profits. An automated RCM model promises both sustenance and growth for HCPs.

JKTech provides Hyperautomation powered RCM solutions to help healthcare companies overcome pressing challenges. Focusing on patient-centricity, we strive to deliver personalized and convenient solutions to help you attain new heights of digital health transformation. We help you reap functional and operational value by streamlining all aspects of healthcare operations management.