Emerging technologies are reshaping the expectations from modern healthcare and the ways it operates. Starting from how consumers access it, how and which providers deliver it, how consumers and government pay for it, to what health outcomes it achieves. More than ever, Healthcare Payers and Providers have been leveraging advanced technologies such as cloud, analytics, AI/ML, and Automation, and more to improve various functions such as patient engagement, claims adjudication, inventory management, risk adjustments, and billing management.
To date, automation has been used in the healthcare industry to gain operational efficiency. Now, a combination of automation technologies such as Robotic Process Automation (RPA), NLP, digital twins, and Artificial Intelligence (AI) can be used to analyze reams of data to draw inferences that can lead to automation of non-standard tasks. This fusion of automation technologies, called Intelligent Automation, is enabling healthcare to optimize processes, strengthen business resilience, reduce risk and generate useful business insights.
| Current Automation | Intelligent Automation |
|---|---|
| Considered as Process automation (Input-Output) e.g. RPA implementation | Automation for outcomes i.e. convergence of RPA with AI & ML |
| Focus on cost reduction & efficiency improvement | Focus on improving customer experience |
| Building a repository of data for further analysis | In addition of capturing data, providing insights for auto execution |
What is Intelligent Automation?
Intelligent Automation is the convergence of RPA with AI and ML. With intelligent automation, AI and ML automate the decision-making, and RPA automates the manual next steps within the process. For instance, by combining RPA with Intelligent Optical Character Recognition (iOCR), healthcare organizations can build the capability to eliminate repetitive and time-consuming admin tasks surrounding logging test results and processing health claims. This frees up human workers to take up higher-value tasks and provide better direct patient care, while digital workers (a.k.a. intelligent automation) process at machine speed and eliminate errors.
Enabling Intelligent Automation for Healthcare Providers
Many providers and staff spend more time within the EHR than on patient care. Additionally, due to minimal support for interoperability, providers struggle to surface EHR data into applications to make provider and patient workflows more efficient.
With Intelligent Automation, these challenges can be averted. For instance, providers looking to build a mobile check-in-and-visit experience can leverage intelligent automation to extract patient data that the patient has shared during previous visits and use it to fill out fields in the EHR automatically. Similarly, everything patients share in their mobile intake, and registration forms can automatically be populated back into the EHR. This would ensure up-to-date patient records for providers and free up staff time on data entry. This freed-up time can be used for patient care. This helps create a modern-day user experience for both patients and providers that mirrors their experiences from other aspects of their lives.
In order to achieve Intelligent Automation, a provider must map the administrative workflows with the clinical workflows. Any manual activity that requires inter-linking of data from these two streams, when extracted/injected, interpreted, analyzed, and executed, can build an Intelligent Automation workflow.
Enabling Intelligent Automation for Healthcare Payers
In addition to cost concerns, wherein consumers are bearing increasingly greater out-of-pocket costs, consumers are increasingly seeking highly customized and anticipatory service over value when they choose to stay with a given health plan. Hence Payers are experiencing pressure to adapt to stay competitive in a challenging healthcare landscape.
Payers who continuously automate their core operations and fuel investment in more strategic priorities will win the consumer in this new payer world e.g., implementing solutions that can track, measure, and forecast productivity for each function in real-time will enable management to allocate staff accordingly to meet the demand.
ACS Methodology for Implementing Intelligent Automation
ACS has a well-defined methodology to enable Intelligent Automation for Payers & Providers. The figure below provides details of this 5 step methodology.
Plan:
- Assess, target, and prioritize processes across the delivery life cycle to be optimized and automated using available techniques.
- Analyze use cases to determine business metrics.
- Make use of scripts, macros, batch programs, mini bots, and custom solutions to automate standard and repetitive tasks.
- Identify optimal workflows, and propose an automation path.
Analyze:
- Identify best automation tools based on workflows to be automated.
- Build POC and technical flows for the identified automation opportunities
- Develop scripts on the automation tool
- Perform testing on scripts and conduct live trials
- Collect feedback and map to the business KPI's
Optimize:
- Establish Center of Excellence
- Govern the transformation and support rapid deployment of IPA solutions
- Create blueprints for future structures and identify patterns with AI to embed new capabilities
Accelerate:
- Expanding the application of automation to various processes
- Accelerating efficiency-driven wide range automation
- Adopting design thinking for future
Attain Intelligent Automation:
- Through process re-engineering by the adoption of automation (RPA) and artificial intelligence
- Application of cognitive chatbots and intelligent bots for all possible processes and to focus on optimizing processes
- Applying AI to access unstructured information, including human chat conversation, audio, and video, is crucial to making end-to-end Automation possible
- Comprehending vast amounts of data, analyze, understand, and intelligently automate processes to bring in more operational and business efficiency
Additionally, it’s critical to have the right capability team designed for Intelligent Automation. It’s a mix of data scientists, automation, delivery, and change management people.
Conclusion and Next Steps
The next journey in the healthcare industry is Intelligent Automation. Healthcare Payers must adopt intelligent automation to define product strategies, develop and maintain provider networks, pricing and risk management, marketing and sales, and patient engagement. Healthcare providers must bring in intelligent automation in revenue cycle management, diagnostics, patient data management, procurement and inventory management, and medical billing. The outcome of implementing Intelligent Automation in healthcare will only be realized when the added advantage of cost savings & data availability is used in improving consumer engagement.
Intelligent Automation has immense potential and is being extensively implemented across the healthcare spectrum. To learn more about how we can help you in effectively implementing Intelligent Automation and stay ahead of the competition, contact us today!
