In the past two decades, the healthcare industry has undergone tremendous disruptions in technology, science, and business models.
Intelligent Robotic Process Automation (RPA) is one of the most powerful tools you can use to address the toughest challenges in healthcare. This eBook provides an overview to some of the major trends and challenges reshaping healthcare today, along with the opportunities for automation.
Electronic health records (EHRs), wearable sensors, environmental monitoring, and online activities have generated big data that promise new insights and predictive capabilities through advanced analytics, such as computer vision (optical character and image recognition), natural language processing (NLP), and machine learning (ML). The resulting data tsunami has driven different and sometimes conflicting agendas, such as biopharma’s need for access to patient data repositories for research purposes vs. increasing regulatory requirements for tighter security around personal health information (PHI).
What has not kept up is the ability to scale the processing and analysis of massive data. The result is an inability to fully leverage data to understand internal operations, meet regulatory requirements, demonstrate positive outcomes to customers and payers, or inform business strategy. To deal with increasing data, most healthcare organizations have simply continued to add headcount—one of the most expensive ways to perform manual, repetitive, and rule-based work. The associated opportunity cost is that employees are not doing work that would be more valuable to the company and personally fulfilling.
Solution: Intelligent RPA can access, read, understand, collate, structure, and analyze multi-channel data from internal and external sources. Software robots (bots) deliver speed, accuracy, capacity, and monitoring, operating 24/7/365 if needed. This frees up employees to provide actual patient care. From a business perspective, it enables strategic end-to-end enterprise automation for efficiency and competitive advantage.
In addition, automation can be used to monitor the operational and business performance of an organization’s internal processes, which can be very useful when changes, such as new functions, are introduced. The near real-time reporting that a dashboard provides can enable an organization to be more flexible, adaptable, and profitable.
AI is one of the hottest trends in healthcare today. The spectrum of AI ranges from traditional rule- based deterministic decision support to newer machine learning techniques that have advanced dramatically in the last decade. Learning machines are computing models that learn more, faster, and better than humans can. Insights from neural networks now power predictive algorithms in many industries, giving humans the ability to explore beyond former analytic limits.
Even highly regulated, conservative, and complex industries like healthcare are now taking the first steps toward AI, using simple rule-based automation for low-risk, nonclinical back-office processes. However, the real power of AI in healthcare will only become evident when it is applied to healthcare- specific tasks and processes, such as those in the areas of care quality, safety, compliance, security, and patient care experience.
Next-generation capabilities like computer vision allow for more sophisticated handling of faxes, signatures, handwriting, and images. NLP handles unstructured text, which represents 80% of the electronic health record. Fuzzy logic allows matching of similar records for data cleansing. Machine learning builds domain expertise over time, delivering progressively better performance and new capabilities like predictive analytics. These expand the potential for current and future applications in healthcare.
Healthcare payers and providers are interested in AI. However, with few exceptions, the crowded AI market has generally failed to deliver on the potential of AI. Not enough value has been generated to justify cost and disruption.
Intelligent RPA is a different approach. It offers a well-reasoned, staged, low-risk approach to AI where every stage can have an acceptable level of risk, clear objectives, and measurable benefits. Initial stages focus on simple rule-based automation that increases efficiency immediately. As a side benefit, the company gains a better understanding of its own business processes. Later stages expand the scope of automation to include intelligent data extraction and analysis. Ultimately, new insights and expertise in AI can lead to an enterprise automation roadmap that delivers a sustainable competitive advantage.
Healthcare is being disrupted on many fronts, from big data, escalating costs, new reimbursement schemes, and a changing regulatory environment to staffing shortages and increasing consumer demands. On the IT front, security breaches continue to be worrisome while the lack of multi- system interoperability and integration reduces visibility into enterprise performance, making strategic planning challenging.
As healthcare organizations ride this tidal wave of change, they are finding that traditional operating models, structures, and processes are being stretched to their limits. To meet these unprecedented challenges, many forward-thinking enterprises are now going through a digital transformation. Creating a flexible, profitable, and sustainable healthcare enterprise in today’s environment will require strategic resource planning and business process reengineering.
A robust, intelligent RPA platform is a key enabler of digital transformation. Its broad spectrum of capabilities addresses diverse needs across the healthcare enterprise, delivering cost savings, increased productivity and quality, higher service levels, and greater employee job satisfaction. More fundamentally, it gives the strategic healthcare organization a way to reshape itself to compete and thrive in the 21st century.