Electronic Health Records(EHRs) have revolutionized the healthcare process and emerged as a preferred solution to improve patient care. Moreover, the ubiquitous adoption of EHR over the last few years has become an integral part of the healthcare delivery system. This is the reason, nearly all healthcare enterprises big and small have implemented EHRs to collect and report data. As per the research report, EHR and EMR market size is projected to reach USD 47.6% billion by 2030.

However, despite the adoption of Electronic health records, not all physicians are content with utilizing EHR. Because in the healthcare system integration of one solution to another is a constant challenge that might deter patient care experience. And data interoperability can erase all these challenges and can help healthcare providers achieve better healthcare workflow. Although achieving and maintaining interoperability in EHR presents enormous challenges and too often it stops healthcare providers from completely utilizing EHR and getting the benefit in the long run.

Challenges with Patient Data Interoperability in EHR

• Unique Patient Identifier
  On any given day, a healthcare provider often receives multiple patient appointments scheduled for checkups. And in the beginning days of EHR in healthcare, space had minimum or no standardization for identifying patients, storing data, and building care plans. Not having a patient record poses challenges in EHR data interoperability, as the absence of data leaves nothing to store. Also, healthcare providers store these data in multiple systems and databases, which makes it tough to collect, track, and analyze the data which further creates challenges in data interoperability.
• Validation and Standardization of Patient Data
  Every healthcare organization follows different EHR Standard formats, hence the information that is shared by them also varies. Maintaining the EHR standards as per the rules and regulations and validating the patient data all across the system, is indeed a task for the healthcare provider. Additionally, maintaining the privacy and security of patient data during data interoperability is a must. And manually validating and taking approval for high-volume patient data pose some key difficulties in front of healthcare providers.
• Financial Concerns and Investment Costs
  Healthcare providers often invest thousands of millions of dollars in EHR systems. And achieving EHR interoperability comes at a cost. In most healthcare organizations, hardly any healthcare professional has the time and skills to perform these tasks. Because when manually performed, this process requires extra manual effort and that will lead to higher costs and longer turnaround times. Apart from the skill and administrative challenges, there are various data trust barriers, IT issues and reporting barriers that limit successful EHR integration.

[Also Read:What is Robotic Process Automation (RPA) in Healthcare? Use Cases, Benefits, and Challenges in 2023]

How RPA and AI is the solution to Data Interoperability?

However, automated data sharing and processing is still underway in healthcare processes but the requirement for real-time information has brought a change in healthcare organizations. With changing competition and offering value care to patients, the need to access real-time information has also increased. But without easy data interoperability, the goal of sharing real-time information is far away.

However, all thanks to RPA and AI that can make the process of sharing information all across the organization and system a cakewalk. Let’s learn how-

• RPA and AI-built tools can help organizations achieve interoperability in healthcare like never before. By leveraging AI technologies like Machine Learning, and OCR, healthcare providers can create an ecosystem of intelligent document processing that can easily collect information from any system, in any format without any manual effort.
• Moreover, this intelligent document processing tool can be trained to encrypt the data it shares with anyone. Having secure data sharing not only helps in building patient trust but also helps healthcare physicians to get detailed insights from past medical records, and x-ray images to offer better diagnosis and patient care.
• Additionally, Intelligent document processing reduces the need for assisting healthcare staff in data extraction and processing. AI-built document processing solutions autonomously offer real-time insights to err out the confusion and offer accurate information.
• Another way through which healthcare data interoperability can be accelerated in the organization is API integration. APIs make it easier for healthcare providers to ensure software interoperability within and across organizations. Their fast deployment time and obstacles-free access to lab results, treatment records, and so on make them a great choice for hospitals. Additionally, they facilitate third-party integration by providing a consistent standard for all systems.

There is no preset path to data interoperability in the healthcare organization but the underlying challenges that organizations often face to meet regulatory compliance and standards can be met by adding the technical capacity of RPA in healthcare. And nothing is more important than making the lives of healthcare staff easier who are working day and night to add more value while offering patient care. Hence, if you are ready to harness the power of RPA and Intelligent Document Processing to ease the data interoperability challenges, then do contact us here.

The Covid-19 outbreak has magnified some of the patient scheduling challenges in healthcare delivery systems such as Electronic Health Records(EHR), long wait times, delayed patient appointments, overworked frontline staff, and lack of skilled labor. And patient scheduling is one of the key challenges that is still prevailing in the healthcare industry. Also, after Covid 19 outbreak patients have become accustomed to virtual care, and dealing with digital records, that’s making it compulsory for the healthcare provider to churn out the patient scheduling challenges and offer value patient care.

In our previous blog, we discussed the growing adoption of RPA in Healthcare and how it can help healthcare providers in offering patient care on time. Now let’s gear up to explore more about patient scheduling challenges and how automation can help remove the hurdles and create a seamless patient experience.

What is Patient Scheduling Process in Healthcare?

Patient scheduling is the first process for healthcare providers where they can generate more revenue but with so many roadblocks in the patient scheduling process, growing higher is out of the question. Additionally, healthcare service desk staff also face challenges like-

1. Extracting data from past medical records of a patients
2. Managing many different appointment types
3. Handling referrals and associated authorizations
4. Verifying insurance eligibility before scheduling an appointment
5. Adjusting appointment schedules as per patient preference and doctors availability
6. Issuing appointment status to patients and doctors on time

Considering the amount of work involved in the patient scheduling process, it is no surprise that healthcare providers are moving to automation solutions and AI technologies both out of necessity and in response to customer preference.

As per Gartner, around 85% of healthcare providers are going to increase or sustain hyperautomation investment strategies in the coming years. Using the hyperautomation approach and automation in healthcare work as a helping hand for healthcare staff in scheduling appointments and a lot more.

How Automation Helps Healthcare Staff in Patient Scheduling?

Automated patient scheduling and registration processes can be performed by both attended and unattended bots as per the healthcare provider’s preferences. Unlike the traditional methods, automated patient scheduling uses bots to perform all the processes without any extra manual effort. These bots can be integrated into the healthcare system and when invoked these bots can perform several actions.

• Bots can get patient details autonomously from the patient ID, and their medical records, check their earlier visits
  Further, these bots can search the patient ID in the healthcare database
• If patient ID is not available in the healthcare database, it easily schedules a patient appointment as per the patient preference and doctor availability and notifies the patient and doctor
• And if the patient ID is already found in the hospital healthcare database, it checks the insurance eligibility, verifies the details, updates the appointment details in the patient ID, and notifies the user and doctors

See how automated patient scheduling looks simple and fast with RPA. Leveraging AI bots kick the manual effort out of the patient scheduling process and give healthcare staff the focus to work on a patient-centric process.

[Also Read:What is Robotic Process Automation (RPA) in Healthcare? Use Cases, Benefits, and Challenges in 2023]

Benefits of Automated Patient Scheduling

1. Interoperability and Data Processing
   Unlike the traditional method of patient data collection, AI bots are capable of navigating between multiple departments across the healthcare organization. Healthcare providers can program these bots in a way that they can navigate between your appointment scheduling software, EHR system, EMR, and payer portals to verify the document and share data in the respective application or to other application software. Healthcare providers can also use unattended bots for registration and scheduling for 24/7 days which means AI bots will perform tasks even when there are no front-office tasks available.
2. Accurate Patient Scheduling Management
   Do you know missed appointments can also contribute to attrition and poor healthcare outcomes? What if we say it costs millions to healthcare providers? Many clinicians and healthcare providers still use manual efforts to book an appointment and make appointment changes in case a patient doesn’t show up. Also, some other common tasks like administrative details, patient insurance, medical history, diagnosis, treatment, and other reports need to be added to the database. AI bot can perform all these processes without any manual intervention using an electronic health record system that can easily be accessed by patients and clinicians. This whole automated process not only saves the patient time but also allows the healthcare provider to collect data, analyze it and offer outstanding patient care.
3. Self-Scheduling Experience
   Being a healthcare provider, every organization strives to create a difference in the patient care experience. And automation is the opportunity to make that difference by leveraging RPA and AI bots with EHR management. It’s a poor use of everyone’s time for a patient to fill out a form in the office and wait for the treatment. Instead of this time-consuming method, healthcare providers can create self-scheduling options for patients with bots where a patient can autonomously book their appointment through bots and connect with healthcare professionals for early diagnosis and treatment. To make it more effective, healthcare providers can use these bots for sharing healthcare records and data directly to patient IDs for easy knowledge sharing.
4. Regulatory & Compliance
   While booking an appointment, patients often share their personal and some other confidential details. With a large amount of data sharing, it is a must to keep the data secure to safeguard sensitive information. Healthcare providers can program these bots by state and federal healthcare compliance and regulatory laws and also maintain the log of users accessing the data and providing reports if any breaches occurred.

The digital era is here for healthcare and being a healthcare provider if you are looking forward to reducing cost, enhancing the patient experience, and giving employee relief from manual work then automation is the staircase to drive the optimum healthcare experience. So let automation take over the repetitive process and healthcare staff enhance the patient care experience with automated patient scheduling.

We all have heard about the brighter side of RPA and its consumption to help healthcare organizations achieve better operational efficiency, provide 100% ROI and improve employee percept and also assist in scaling up business operations in a short span of time.

Typically organizations implement any new process/technology either by using the ‘Top-Down approach’ or ‘Bottom-Up Approach. ’However, RPA automation might create a fright of losing jobs and unclear responsibilities after automated chatbots or Robots are deployed.

Robotic process automation (RPA) projects are a demanding endeavor. However, if organizations take on their automation projects prepared and are aware of the possible roadblocks, they can reap great rewards. Many are already making the most out of it as workflow automation services as the global RPA market increases in value and volume. The Grand View Research forecasts this market to hit $13.74 billion by 2028, growing at a CAGR of 32.8% from 2020

Inaccurately identified Use cases for automation in healthcare will only produce a low ROI, cluttered operational model, and would not improve the process efficiency as expected by the business or even the metrics proposed to the Business. The entanglement of processes identified for automation plays a pivotal role in producing the expected ROI. A few of them are:

Not following best practices

• If the team misses out on the best practices, it would be difficult for other team members to understand and re-use the flow.
• In case of transitions, the time taken for the new members would be longer than expected.
• When there is a need to automate the process, it will be an intimidating task to decode the logic.

In almost all the RPA projects, we will come across situations where there would not be an elementary solution. In this case, if the team members are unable to automate a particular step, it will be important to ensure there is enough support from the RPA platform vendors as they have the expertise in using the tool features in multiple ways by different customers. Customization and ease of use are the Keys here.

Post-Implementation Adoption

Businesses often pertain to all the measures required before the adoption of RPA. However, they fail to take care of the aftermath, which might come after the automation is deployed into production.

So, we can culminate by saying that the challenges faced by different projects provide a checklist for being prepared to not fall into any one of the categories mentioned above. It also helps in creating a knowledge graph of possible constancies for each challenge identified, different propositions to solving them, and how to ad-lib on each solution once they are implemented.

The Future of Robotics in the healthcare genre

As AI, ML, data analytics, computer vision, and other technologies accelerate, RPA will evolve to complete tasks autonomously and more efficiently, and accurately.

Technology providers and researchers need to explore the next generation of robotics solutions by providing learning & development support, to drive the discovery of new applications for AI and IoT technologies within the field of medical robotics. These will support the ongoing innovations that increase automation, drive efficiencies, and solve some of the greatest healthcare challenges.

But the fear of losing employment still will persist within the workforce. Organizations need to tackle this situation with the desired KT and need to create an environment where technology and manpower can be clubbed together to create a healthy Caregiving sphere.

From rapid diagnosis to robot-assisted surgeries, the transformation of automation and AI in healthcare is fast-tracking patient care by minimizing human interventions.

Artificial intelligence eases the lives of patients, doctors, Payers, and hospital administrators by executing tasks that were typically done by humans manually but in less time and at a lesser cost. Also, trends like Homecare, telehealth, and chat therapy are also growing at a pace all across the healthcare industry. As per statistics, Homecare/Healthcare market is expected to grow at the compounded annual growth rate of 4.67% during the forecast period 2022-2027.

Truly, AI is reinventing and revivifying modern healthcare through ML that can predict, comprehend, learn and act smarter. The prime objective of this entire automation or AI game is to free healthcare professionals from being ‘overburdened’ to ‘ever happy.’

Healthcare Challenges and Opportunities

The healthcare industry of today is overburdened by high costs, incredibly high volume, and stringent regulations. These pressures can challenge the quality and urgency of patient care. The drive to reduce costs is countered by the need to continuously improve the patient experience and meet regulations that often require onerous paperwork and reporting. In healthcare organizations, many repetitive processes and decisions rely on the availability of accurate data. Automating these process with RPA and AI can not only reduce reliance on manual efforts but also helps in ac

1. Patient onboarding and follow-ups

   Patient onboarding includes a series of tasks that must be completed by scheduling staff and the intake coordinator before a patient visits the doctor. These steps include insurance eligibility verification, doctor availability, EHR record management and updating information in the healthcare database. Manually performing these steps might lead to errors and delays in offering quality patient care. But, RPA bots make the patient onboarding process efficient by autonomously accessing patient IDs and searching in the database for insurance eligibility verification and scheduling patients as per doctors’ availability. Also, if in any situation, a doctor is unavailable, RPA bots update the patient with details and follow the further course of action. RPA benefits don’t stop here; after a patient visit, RPA bots keep tracking the patient’s health and follow up with them and generate a notification for a doctor visit, medical tests, and other purposes.

2. Medical billing and claims processing

   Medical billing processes are not performed or reliant on a single entity. It involves every step of association between patients and healthcare organizations. From the pre-registration process to the completion of the patient visit, medical billing is a comprehensive assessment. This process involves the patient’s insurance plan, copay options, insurance eligibility and coverage options, generation of medical code and payment reimbursement. Automation solutions like RPA bots can keep track record of all the data required for the medical billing process. Bots can extract data from multiple touchpoints, identify and resolve areas that require attention, and merge all caregiver activities for higher reimbursement and greater patient experience.

3. Generating reports for physicians

   Medical report generation for physicians or healthcare professionals is a tedious process due to the involvement of a huge volume of data. Collecting data from multiple sources and aggregating them together is a lot on the healthcare staff’s part. This health re[prt must be in sync considering the latest and past healthcare reports. RPA can keep track of all the data shared by patients during doctor visits, and bots can extract these data together. Once data extraction is done, RPA bots collectively add the data to the particular patient records and share them effortlessly when required by physicians.

4. Prescription management

   Managing prescriptions include monitoring, reconciling medications and ensuring patients get their desired outcomes. With the high volume of patient visits and multiple patient requirements, fulfilling all requirements manually is a mammoth task for healthcare professionals. Automating the prescription management process helps healthcare staff on keeping track of whether medications prescribed to patients are taken properly for desired healthcare outcomes. Using RPA, healthcare staff make sure the necessary medicines that are prescribed to patients are in enough amounts, so there is no chance of poor quality care.

Also, in this league, the home-based care sector with therapists, social workers, and healthcare professionals are now able to serve safely, happily, and scientifically, eliminating the pile of Paperwork and manual database maintenance tasks. Gone are those days when a standard Doctor’s chamber would have data entry operators with a mountain of patient charts, registration notebooks, and unmapped patient history files.

Healthcare Automation Benefits

1. With the advancing technology, Care at home has been made quite popular and user friendly, with Robots or smart Phone applications doing the job of “Custom to Commission” on behalf of the administration staff. From searching for local physicians, booking and tracking appointments – making payments – scheduling visits for consultation, and most importantly, Data security at ease at home – all is done and Sorted 24/7.
2. Healthcare Providers are using Robotic Process Automation to reduce costs, increase process efficiency, and improve the patient care experience, and some of the challenges in healthcare can also be mitigated with Robotic Process Automation like Administrative data entry: The document digitization process: Managing and scheduling patient appointments: Billing and processing: Records management: Customer service and remote care.
3. Software “chat Bots” are another extension of the automation sphere, which can be “triggered” to perform tasks based on various parameters. In some larger platforms, Bots are even used in prospective care – which means scheduling physician’s appointments and maintaining post-visit records along with billing and payment model integrations. It’s just a couple of clicks and Bots instruction-based model which simplifies patient care even more. These “Bots” can be programmed using various commercially viable tools so that they can take over thousands of detailed, repetitive tasks and processes, making everyone in the healthcare system—patients, partners, caregivers, administrators, and communities—feel a whole lot at ease.
4. Innumerable factors go into running a successful medical practice. One of those is revenue cycle management RCM Although the main aim of RCM is to accelerate provider revenue, it delivers other benefits as well. These serve not only the providers but also the patients, giving revenue management even greater value. By implementing RCM, healthcare providers can efficiently identify the gaps.
   This decreases the likelihood of misaims, denials, and overclaims at times since about 90% of these errors are due to easily preventable technical issues, like missing information in the patient’s chart or improper coding. This directly impacts patients’ insurance claims, too, as healthcare payers are in the same league of data inaccuracy often. When these errors are mitigated, and claims are approved after their first submission, providers smoothly receive their reimbursements. Also, they don’t have to incur extra money for Sherlock and appeal denied claims.

Conclusion

A survey conducted to understand the healthcare payer market size, shares, trends, and analysis stated that the global payer healthcare market is forecast to reach $111.9 billion by 2030, and the Healthcare players are redefining their role to deliver higher value-based care while they adapt to adopt the new age technology driven automated non-human-driven solutions. Let’s get Automated; it’s high time!

In healthcare, the ‘fee-for-service’ model had been dominant over the years. In this model, humans were responsible for many activities like customer support, back-office operations, financial transaction, and patient data management, along with schedules and reporting for doctors. With the slow but steady transition to value-based care along with the digital transformation, processes around these activities were abdicated and software tools were set in motion to reduce the trammel on humans and the occurrence of error.

For a healthier tomorrow, as the “Patient First” centricity is pivotal in today’s world, healthcare automation continues to evolve to empower physicians to perform better. The patient-first approach with the latest automation tools has become a basic necessity rather than a need. The necessity is not just to flaunt a great technology-driven infrastructure or tech-savvy medical staff but to facilitate physicians and healthcare players with a time-saving, more scientific, and error-free CARE GIVING MODEL.

With the changing time, hospitals and clinics are more connected and operating in an automated vogue, equipped with smart devices and cognitive decision-making platforms with a fast shift to EMRs EHRs and RCMs, but still, few questions are unanswered:

• Why do 40% of healthcare professionals believe that automation and AI/NLP/ML will be crucial for caregiving?
• How does Machine Learning save about 80% of time and overheads on document processing?
• What steps can you take to implement intelligent automation in your organization? And how would it be effective?

But above all, it’s critical to figure out error-prone unstructured medical data, time-consuming physical notes at the physician’s chamber, and manual processes – wrong risk score derivation from the Insurance companies submitted to the CMS leading to penalties…. Who’s at more risk? Payers, providers, or overall the healthcare landscape?

Incomplete medical histories and large patient charts, when handled manually can trigger human errors. However, AI can predict and diagnose disease and its occurrence at a faster rate. Since healthcare handles real-time operations, delays/errors can be life-threatening. With AI-powered healthcare solutions, professionals can detect issues and notify care teams quickly, enabling providers to discuss options, and provide faster decisions, thus saving lives.

Since the emergence of the pandemic and Covid-19 implications, technologies have immensely transformed the way businesses operate and offered their services. Among all the strategic and technological approaches, “Hyperautomation” is one of the approaches that has gained a lot of traction from technology leaders.

As per Research and Market reports, the global hyperautomation market is expected to grow by USD 26.0 billion in 2027. These statistics clearly show the hyperautomation growth and its impact on business leaders. But is it that simple? Automation is simple to understand and easy to justify, but when it comes to execution, it’s complex and tough, especially if you don’t have the right strategy. Quite often, the biggest challenge in the embracing automation journey is the right set of use cases and aligning them with the right solutions.

However, many leaders believed that they found their tool for digital transformation in RPA. But, RPA is not hyperautomation and also hyperautomation is not a technology and strategic approach that is a combination of RPA and some AI technologies like Machine Learning, NLP, and others. So what is Hyperautomation?

What is Hyperautomation?

As it’s clear that Hyperautomation is not a technology, Hyperautomation is a business-driven approach that involves the orchestrated use of multiple tools, technologies and platforms.

Hyperautomation delivers a state that delivers an end-to-end, event-driven, intelligent and very well-integrated form of automation. That’s a lot of things, and you can deliver all of these with a single technology. For this reason, hyperautomation requires multiple orchestrations of technology tools and platforms. And to make this, you need to build a technology portfolio for the hyperautomation platform. These technologies could be RPA, AI/ML, Intelligent Document Processing, Business Process Automation, task mining, process discovery, Conversational AI and many others.

And to gain the most out of these technologies with minimal effort and gaining higher ROI, your organization requires an orchestration of these technologies. As per the Gartner survey, around 2 technologies, low code/no code and Business Process Automation, are used by IT leaders to enhance their business processes. So how do you choose the right portfolio for your organization? Here are three key steps to follow and build a technology portfolio for hyperautomation.

1. Align Your Business Goals

   While embracing the automation journey, the first question that comes to mind is what value it would bring to use cases on which it is applied and what will be its impact on business. Aligning business goals is often complete in these stages such as.
   

   • Setting the Objectives

     When it comes to aligning business goals for hyperautomation, three things that hold the utmost importance are- revenue, cost, and risk. Another important aspect is feasibility, which means what will be the complexity, scope and predictability of the outcome when new technology is introduced to the already deployed infrastructure. So to set the objectives right, determine the key outcomes and identify key metrics to measure those desired outcomes. Once you determine the outcomes, for example, if we say improved agility or higher ROI, prioritize your automation use cases accordingly that can help deliver these outcomes.

   • Discovering Automation Opportunities

     To effectively discover and analyze automation opportunities, first align your use cases against three categories of automation that are-

     1. Task Automation
     2. Process Automation
     3. Augmentation

     Ask questions like are the process is simple and repetitive and involves daily tasks, whether they are complex and require a better technological approach or whether the data value is structured and unstructured. This helps in shooting down the automation opportunity all across the organization.

   • Identifying Technology that Brings Desired Outcome

     Once an automation opportunity is discovered, the next step is to choose the technology that is the best fit for the business process. As each technology has a different role and characteristics hence, their capabilities are different as well. So select the technology that aligns with business goals and use cases.

   

2. Choosing the Right Set of Technology

   When it comes to selecting the right set of technologies, it is not as simple as comparing one tool to another one. In fact, the enterprise should focus on determining the best combination of complementary technologies. To build a hyperautomation technology portfolio, organizations must prioritize the capabilities required for each hyperautomation initiative and then evaluate the product and technology features that optimally align with those requirements.
   

3. Build Your Technology Portfolio

   Along with choosing technology that aligns with your business goals and objectives, it’s essential to keep these key considerations in mind while building the hyperautomation-
   

   • Time to Market Constraints

     A trade-off between tactical and strategic value to establish the optimal equilibrium.

   • Total Cost of Ownership

     Evaluate the TCO for a selected automation tool that justifies your overall budget. Evaluate your company’s ability to build, implement, and sustain automation using the chosen set of technologies.

   • Skill Requirements

     Check whether your organization has the talent or opportunity to build support and maintain automation using the right set of technology.

   • Vendor Maturity

     Evaluate the platform and capabilities offered by the vendor and check whether the solutions align with your enterprise architecture.

[Also Read: Top 10 Hyperautomation Use Cases and Examples in 2023 ]

Rising customer expectations and building a workplace experience require a strategic approach that goes beyond RPA. And hyperautomation is that disciplined approach that enables enterprises to go beyond RPA and offer customers what they expect. So are you ready to go on a hyper-drive with Hyperautomation? Reach out to us for a quick demo with our experts.

Collecting payments in the healthcare industry is not as simple as sending invoices and processing payments. Healthcare providers have to determine who owes the money, insurance eligibility, and document verification before any transaction is made.

And the most common billing problems in the healthcare industry occur due to manual errors in data entry and management. And if stuck with an ad-hoc manual approach, healthcare staff might get too bogged down to improve patient care. In order to increase revenue and focus on value-based patient care, healthcare providers must have effective healthcare revenue management.

Healthcare Revenue Cycle Management(RCM) Challenges

Healthcare revenue cycle management involves multiple back and front office activities and data sharing among three stakeholders: patients, providers, and payers. And when healthcare providers have to maintain the revenue cycle management activity manually, this whole process becomes resource-intensive and time-consuming. There are several stages in revenue cycle management that poses a range of challenges for effective revenue management. These challenges are-

• Interoperability

  With a large amount of data involved in the healthcare process, there is an urgent need to share that information all across the department efficiently. Inadequate implementation and integration of health records, medical images, billing and claims cycles, and other data exchanges can negatively impact patient care. In addition, keeping track of these records manually is extremely time-consuming and expensive for healthcare providers.

• Erroneous Medical Billing

  Healthcare providers need data related to claims, patient registration bills, medical bills, and others to manage their revenue cycle effectively. With the large number of documents involved in integrating data into healthcare systems, healthcare staff often find it tough to maintain data processing errorless. Hence with wrong medical billing and erroneous data, there is a chance of a long time resolution between billing and payment that impacts the healthcare revenue cycle.

• Maintaining Regulatory Compliance

  New regulations and compliance standards are constant in healthcare, and maintaining them is vital for healthcare providers. Failing to be updated with the evolving compliance landscape can lead to claim denials, payment delays, and appointment and billing backlogs that directly impact the revenue cycle.

• Lack of Data-Driven Insights

  Multiple data points are available at various stages of healthcare revenue management. And gaining efficiencies in healthcare revenue cycle management requires a big picture behind these data points that showcase what is happening inside the enterprise. Lack of these data-driven insights is not always by default in the healthcare system, and in the absence of these insights, it is tough to check where the scope of improvement in the healthcare life cycle is.

• Security Management

  With a large amount of data shared all across the healthcare staff, physicians and IT service providers, the chances of data branches and identity thefts might delay the insurance claims process and payment initiation. And this friction hampers the healthcare revenue cycle management and creates more challenges.

  [Also Read:What is Robotic Process Automation (RPA) in Healthcare? Use Cases, Benefits, and Challenges in 2023]

Healthcare Revenue Cycle Management(RCM) Automation With RPA and AI

As per Grand View Research, the global market for revenue cycle management is projected to expand at a compound annual growth rate of 11.6% from 2022-2030. Considering the amount of increment in revenue cycle management, demand for a technology solution like AI and RPA in healthcare is also accelerating. Some reports stated that AI in healthcare is expected to expand at an annual growth rate of 38.4% from 2022-2020. As healthcare revenue management involves multiple steps, leveraging AI and automation solutions can help drive better revenue management.

In simple words, the RCM process begins with patient appointments and ends when full payment is initiated in the provider’s account. Between these two points occur five important steps that complete the whole revenue cycle. Automating these steps and processes with RPA and AI can help create better revenue management systems. These five steps are–

• Insurance Eligibility Verification

  Before seeing a patient, healthcare providers often check the insurance eligibility to verify whether the patient is able to fill the claims or not. Verifying the information provided by each patient and manually checking data can take minutes to an hour and a week which hinders the organization’s referral rate. Utilizing RPA bots can help healthcare organizations get rid of the tedious task of following the paper trail. AI-driven bots can access the data faster using OCR and machine learning capabilities and make the data extraction for verification an easy task.

• Medical Coding and Claims Preparation

  The medical codes are reports from physicians, which can include diagnostics, treatments, or surgery performed by the healthcare provider. In a field reliant on accurate data, medical coding is vital for insurance claims and other processes to maintain the revenue cycle. And collecting codes from multiple physicians and integrating them into the healthcare systems is an uphill task. But, RPA bots can help healthcare providers’ data integration all across the healthcare system be better and more efficient. Automation cuts down the time and effort used in integrating medical codes and preparing claims. With faster data access, claim preparation gets better with less manual effort and time.

• Claims Submission

  Healthcare providers share insurance claims with insurance providers through portals. With a large number of healthcare portals, the data integration for multiple systems is a tedious process. To wipe out these challenges, automation and AI are the solutions to drive process efficiency. RPA bots can easily operate through as many interfaces and help healthcare providers submit faster claims.

• Dispute Management

  Insurers don’t agree with every claim processed by healthcare providers. They may reject claims outright and delay the payment process, which directly affects patient care. Also, keeping an eye on every piece of data to recheck claims from insurers and effectively resolve the dispute requires a talent pool of employees for faster resolution and payment. Using RPA bots with a predefined set of rules can escalate these exceptions for human staff and enhance employee productivity for faster resolution and payment.

• Claims Reconciliation

  Once insurers receive the claims and verify the information and transfer the funds directly to healthcare providers’ accounts, it is the healthcare staff’s responsibility to reconcile the payment information in their financial system. Aggregating this large volume of information and reconciling it to the system is a challenging process for employees. AI chatbots can easily track the data shared by insurers and integrate this information directly into the system autonomously.

Conclusion

To make sure that patients are getting excellent patient care along with faster reimbursement for their services, healthcare providers must turn to AI and automation solutions for better revenue cycle management. AI and automation enable healthcare providers to offer excellent patient care beyond costs and facilitate healthcare experience for patients, healthcare providers and physicians. That’s the power of RPA and AI.

Looking for automation in your healthcare process, Reach out to us for a quick demo with our experts.