To be competitive, organizations need to realize the full potential of end-to-end automation. The term for unifying different technologies, platforms, and tools to deploy processes like artificial intelligence, machine learning, and Robot Process Automation (RPA) is hyperautomation.
This blog post will analyze hyperautomation in the context of the healthcare industry and discuss:
What automation is
Specific use cases in the healthcare industry
The Role of Hyperautomation
By 2024, Gartner predicts that over 70% of large global enterprises will have over 70 hyperautomation initiatives running simultaneously. Hyperautomation helps businesses:
Automate processes across their business
Increase agility and optimize workflows
Produce products more quickly by using intelligent insights, improving consistency, and reducing human error
Reduce costs by replacing manual tasks with automation
Hyperautomation will transform the healthcare industry, and the process has already begun in areas like:
Scheduling and rescheduling appointments
Identifying gaps in data and auto-populating patient forms
Working with insurance agencies to collect missing information
Using Voice Biometric technology to identify patients.
Leveraging chatbots to answer patient FAQs
Hyperautomation also makes a significant impact on analytics and actionable data usage. Healthcare organizations can use process mining and data analytics to improve patient registration and the insurance verification process. It also helps the pharmaceutical industry automate requirements for drug reconciliations for controlled substances. In a recent study, HIMSS found that 35 pharmacies were able to save ten hours a month using hyperautomation.
Patients and organizations alike will also increasingly rely on remote monitoring and connected devices. Remote monitoring is essential right now given the need for social distancing. Organizations will be deploying wearables, digital health assistants, and data analytics more. Patients can use devices for monitoring blood pressure and glucose levels. With support from analytics, digital health assistants will eventually be able to give patients treatment recommendations and plans.
Specific Use Cases for Hyperautomation in Healthcare
One way hospitals and clinics can use this newer healthcare innovation is documentation, instead of dictating notes during and after a patient’s visit. AI can assist in patient-physician conversations during the visit, and those tools can prompt the physician to add clarity and context to notes. Automated tools can also read patient data, documentation, and prioritize work for specialists.
“These AI tools are identifying cases and factors that they need to explore and investigate,” says Jared Sorensen, VP at 3M Healthcare Information Solutions to HIMSS. “Whether there’s a documentation gap or a quality issue that needs to be addressed, it can be done in real-time through prioritization findings rather than looked at retrospectively after the patient has left.”
AI can also significantly improve the backend processes for administrative functions like coding and billing. It can create automated coding for records in areas like radiology, ultrasound, and mammography. This helps contribute to creating a direct-to-bill revenue cycle within healthcare.
It takes a considerable amount of time and resources to generate a patient’s bill and send it to them. Automation can shave off costs and productivity, streamline compliance, and provide greater accuracy.
How to Get Started With Hyperautomation
Get stakeholder support and consult internal experts. Retrieve perspectives from the business sector and the technology sector.
Identify constraints, risks, or challenge areas you may need to mitigate.
As IBM notes, “Whenever a process is automated, particularly with hyperautomation, you should expect to encounter employee fears of replacement and concerns about the value and competency of technology.” Carve out time to assuage their fears, educate them, and answer questions.
Focus on areas where the highest value exists. Figure out what processes you need to help now with automation, and which ones can wait.
Get Support for Your Hyperautomation Goals
Hyperautomation can save healthcare organizations time and money, and help them provide more accurate information both internally and externally. However, introducing any new process in healthcare requires a methodical strategy.
The DMI team has ample experience in operationalizing AI and machine learning to meet customer goals. As a new breed of end-to-endless partner, we’ll work with you to deliver a comprehensive hyperautomation strategy for healthcare and multiple other industries. Contact DMI to start the process.