A leading hospital chain in India saw a 50% reduction in turnaround time and cost savings, amounting to nearly Rs 1 crore over a period of 12 months, when it upgraded its digital infrastructure and implemented process automation to manage the overwhelming number of patient transactions. It enabled them to reduce errors and recover pending payments in a consistent and timely manner.
This is one of the many real-world examples of how healthcare – a highly complex and legacy-driven industry – is impacted by emerging technologies, such as robotic process automation (RPA), artificial intelligence (AI) and machine learning (ML). The IBEF has pegged the Indian healthcare industry to reach a valuation of Rs 19.57 lakh crore ($ 280 billion) this year. However, for the sector to achieve this scale of growth, it needs to rise above certain endemic inefficiencies. These include lack of resources, low access to quality care and high cost of upgrading legacy infrastructure.
Healthcare organisations also need to be able to manage huge loads of data and information collected and processed by them, including patient information, lab result, claims and insurance-related data, appointment schedules, prescriptions etc. This is where RPA can play a crucial role by automating these tedious, repetitive and rule-based tasks, thereby helping healthcare organisation in managing costs, reducing errors and improving efficiency.
How can the business of health care get done better?
Studies have shown that nearly 36% of the processes in a healthcare organisation can be automated. Many leading healthcare providers have used RPA technologies to automate their entire revenue cycle, including patient scheduling and appointment processes, billing processes, claims submissions etc. RPA software are also helping extract and optimize patient data from multiple systems and provide clinical staff with insights for crafting customized care pathways, thereby elevating patient experience. Automated report generation for audits and streamlining workflows involved in case and utilization management and remote monitoring are few other areas where provider organizations have reaped the benefits of RPA technologies.
Constantly facing the dilemma of enhancing patient experience while managing cost pressure, even payer organizations have adopted RPA technologies for highly repeatable and costly (when handled manually) activities within their claim adjudication and call center operations. Whether collating data from disparate systems for handling claims or processing large amounts of paperwork for member enrollments or managing provider networks in terms of contracts, data integrity etc. RPA has helped bring in process efficiency and deliver tangible cost benefits. Also, by integrating smart workflows, many payer organisations have managed to streamline their appeals & grievances process and reduce rework efforts through intelligent queue automations.
Before you go for an RPA deployment …
While RPA is proving to be valuable in streamlining operations, there are some key considerations that businesses should review before adopting it:
- Process identification: It is critical to identify what to automate, how to automate, and how patients will continue to get best-quality care. RPA is not likely to be effective on tasks/processes undergoing frequent changes or upgrades. The key is to first establish clearly defined processes and then work out the automation opportunities. There could be some processes that are not fully transactional but are human-driven and require decision-making strategies to complete the process.
- Evaluation of the best-fit solution: Enterprises need to appraise the best RPA operating solution that suits their existing organizational processes and plan the implementation and execution strategies accordingly. These technological solutions must also be scalable, depending on the business cycle and applicable across organizational processes.
- Governance and security considerations: A robust governance infrastructure is essential to prevent and mitigate issues and address any leakages with appropriate controls. A report by Ernst and Young states that around 30-50% of RPA implementation cycles fail owing to poor planning and execution. From a security perspective while there are no specific automation-related regulations, it is necessary to ensure organizations’ compliance with the existing IT policies and healthcare regulations in relation to RPA. It is especially critical in the healthcare sector to ensure that sensitive patient information is not breached.
Skill up to scale up
Adopting radical technology alone is not enough; it needs to be backed by an efficient and competent digital operations workforce. While many organizations hold short-term classroom training programs to upskill their workforce to automate simpler tasks, long-term success in RPA implementation needs enterprises to adopt a structured approach to designing, developing, managing and retiring RPA bot solutions. In order to continuously realize business value from these solutions, it is important to upskill technology and business teams to optimally design RPA solutions and monitor ongoing performance of these solutions in production environments. The training modules should span across the entire software life cycle, including the stages of analysis, bot development, testing, deployment and finally production.
Moving from robotics process automation to intelligent process automation
Organisations are now increasingly looking at converging the benefits of RPA technologies with AI/ML based solutions to develop intelligent automation across a whole host of business processes. These solutions can help improve productivity by automating not just high-volume repetitive tasks but also ‘thinking’ tasks. Case in point, using RPA and AI in Cognitive Document Automation (CDA) can help in tracking invoices, identifying the supplier it was received from and the purchase order associated with it, and prompt the billing system for payment. The same concept can be extended to managing medical records. Other examples include integrating technologies like computer vision and machine learning to build disease prediction solutions.
While developed nations like the US and Europe are looking at RPA to simplify healthcare and provide better quality of care at lower costs through scalability and remote care services, developing countries like India and Africa, are still focused on access to quality care. This is where RPA can help us step up and can support medical personnel to focus on what matters most – helping people live healthier lives and helping make the health system work better for everyone.
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