Intelligent Automation in healthcare: top use cases for 2024

The healthcare industry is evolving at an unprecedented pace. One of the 2024 healthcare tech trends driving its rapid growth is intelligent automation (IA). This merger of artificial intelligence (AI), robotic process automation (RPA), and data analytics, allows digital health organizations to find innovative ways to streamline operations, enhance patient care, and make more informed decisions. In this article, we will explore the top use cases of intelligent automation in healthcare. We will also highlight how these cutting-edge digital health solutions can revolutionize healthcare delivery and the patient experience in 2024 and beyond.

What is Intelligent Automation?

Intelligent automation is a combination of AI and RPA technologies. AI uses machine learning and other techniques to mimic human cognitive abilities, such as reasoning, decision-making, and learning. RPA uses software bots to automate repetitive tasks that are typically performed by humans.

When combined, AI and RPA can create powerful intelligent automation solutions that can transform the way healthcare is delivered. This has the potential to speed up the already rapid evolution of healthcare services in 2024 and further down the line. For example, intelligent automation can be used to:

• Automate administrative tasks such as patient scheduling, billing, and claims processing
• Assist with clinical tasks such as diagnosis, treatment planning, and medication management
• Support research and development by automating data analysis and other complex tasks

What are the benefits of Intelligent Automation in healthcare?

Intelligent automation offers a number of benefits for healthcare organizations, including:

• Improved efficiency and productivity: With IA, healthcare providers can automate many of the time-consuming and repetitive tasks that currently take up a significant amount of their personnel’s time. This can free up medical personnel to focus on more complex and value-added activities, such as patient care and research.
• Reduced costs: The automation of time-consuming and repetitive tasks mentioned above can also help reduce healthcare costs. This can lead to significant savings over time.
• Improved quality of care: IA can help to improve the quality of care by reducing the risk of human error and improving the efficiency of clinical processes.
• Increased patient satisfaction: It can also help to increase patient satisfaction by improving the efficiency and responsiveness of healthcare services.

Intelligent Automation in healthcare: top use cases in 2024

Now that we understand the benefits of IA in healthcare, let’s take a look at specific examples and use cases:

Intelligent Automation of administrative tasks

Administrative tasks are essential for the smooth operation of healthcare organizations, but they can also be time-consuming and repetitive. Intelligent automation can be used to automate many of these tasks, freeing up staff to focus on more important things. We predict that the trend of streamlining administrative tasks with IA will accelerate in 2024.

• Appointment Scheduling: Intelligent automation can be used to streamline the patient scheduling process, from booking appointments to sending reminders. This can reduce the number of missed appointments and enhance scheduling efficiency.
• Claims Processing: This complex task usually consumes a lot of time. Healthcare providers can use IA to handle various steps in claims processing, including verifying patient eligibility, submitting claims to insurance companies, and following up on claims. This can speed up the way claims are handled and make them more accurate.
• Revenue Cycle Management: Revenue cycle management (RCM) involves collecting payments from patients and insurance companies for healthcare services. Intelligent automation can automate several RCM tasks, such as patient registration, coding and billing, and payment processing. This can improve RCM efficiency and reduce payment processing time.
• Electronic health record (EHR) management: EHR management is the process of maintaining and managing electronic health records. Intelligent automation can be used to automate many of the tasks involved in EHR management, such as data entry, patient charting, and report generation. This can help to reduce the workload on healthcare staff and improve the accuracy and efficiency of EHR management.
• Clinical document digitalization: Clinical document digitalization involves converting paper clinical documents into a digital format. Healthcare providers can use IA to automate many of the tasks involved in clinical document digitalization, such as scanning, indexing, and tagging documents. This can help to improve the accessibility and organization of clinical documents and make it easier for healthcare staff to access the information they need.
• Patient care monitoring: Patient care monitoring entails tracking and monitoring a patient’s health condition. Intelligent automation can be used to automate many of the tasks involved in patient care monitoring, such as collecting patient data, analyzing data, and generating alerts. This can help to identify potential health problems early and improve the quality of patient care. Solutions that help monitor patients’ health are remote patient monitoring and ambient health monitoring.

Intelligent Automation of clinical tasks

The utility of intelligent automation extends beyond administrative tasks; it can also enhance the efficiency and precision of clinical care. 2024 is shaping up to be a pivotal year in the automation of clinical tasks.

• Diagnosis and Treatment Planning: Intelligent automation can assist healthcare workers in diagnosing and planning treatments by providing access to relevant medical literature, clinical guidelines, and patient data. This can help healthcare workers make more informed decisions about diagnoses and treatment options.
• Medication management: IA can help healthcare workers manage patient medications by automating tasks such as dispensing medications, refilling prescriptions, and tracking patient compliance. This can help to improve the safety and effectiveness of medication therapy.
• Medical imaging analysis: Intelligent automation can be utilized to analyze medical images such as X-rays, CT scans, and MRIs to identify abnormalities and diseases. This can help healthcare workers to diagnose diseases more accurately and quickly.
• Virtual Care: IA can support the delivery of virtual care by automating tasks such as patient intake, triage, and follow-up. This improves access to healthcare for patients living in remote or underserved areas or facing difficulties in traveling to a doctor’s office.
• Patient education and support: Intelligent automation can be used to provide patients with personalized educational materials and resources, answer their questions, offer support, and assist them in managing their health and medications. This can simplify access to information and resources, aiding patients in their health management.

The role of AI agents in healthcare automation

In the evolving landscape of healthcare automation, AI agents stand at the forefront of innovation.

These intelligent systems not only automate routine administrative tasks but also revolutionize patient care by providing personalized health insights.

For instance, AI-powered virtual assistants can monitor patients’ health data in real-time, alerting clinicians to potential issues before they escalate. Moreover, AI agents enhance diagnostic accuracy by rapidly analyzing complex medical images and datasets, thereby supporting doctors in crafting precise treatment plans. As we look toward 2025 and beyond, the integration of AI agents in healthcare is poised to enhance efficiency, reduce costs, and most importantly, improve patient outcomes on a global scale.

Conclusions

Intelligent automation is a powerful tool capable of transforming healthcare. By automating repetitive and time-consuming tasks, it can free up healthcare workers to focus on more complex and value-added activities, such as patient care and research. Furthermore, it can enhance the efficiency, productivity, quality, and cost-effectiveness of healthcare delivery.