The global healthcare industry faces a long list of challenges as it moves toward 2024. Some, such as widespread staffing shortages and fallout from inflation, are being driven by external forces. Others, such as evolving patient needs, are coming from within.
While a variety of factors may be driving these challenges, one solution promises to help healthcare companies move the needle in a positive direction: automation, driven by artificial intelligence and machine learning.
How AI is reshaping automation
Artificial intelligence has ushered in a new age of automation. Innovations such as natural language processing have allowed AI-driven automations to be deployed in a much broader way, with a much higher level of public acceptance. AI also allows automation to handle more complex tasks that previously required human interaction.
AI makes automation more flexible and resilient by allowing for dynamic adaptation. As AI learns from the data it gathers, it can adjust its behaviors and optimize its performance. AI’s ability to drive predictive analysis also supports resilience, empowering it to be proactive in adapting to future needs.
How AI automation is reshaping the patient experience
Consumer expectations have evolved dramatically in the healthcare sector in recent years. In the aftermath of the COVID-19 pandemic, patients expect convenient access to providers through online portals and telehealth platforms. Many patients have also come to expect self-service tools that provide self-scheduling, self-monitoring, and self-diagnosis.
Consumers also expect to have a digital experience when engaging with healthcare providers. They expect mobile apps to provide scheduling, onboarding, and reminders about appointments and follow-up steps. They have also come to expect digital services and the interactions they facilitate to be personalized.
By leveraging AI to empower automations, healthcare companies can meet many of those expectations. AI-driven chatbots, for example, provide convenient, 24/7 self-service access to patient services, with the level of service greatly improved by natural language processing.
AI automations can also be used to serve patients during office visits. Mobile apps and kiosks can streamline onboarding, check-in and check-out, and billing. They can verify insurance eligibility, keep patients updated on wait times, and even gather basic vital signs like temperature, heart rate, weight, and blood pressure.
How AI automation is reshaping healthcare operations
Leveraging AI to enhance the automation of administrative tasks offers healthcare companies a solution to staff shortages. AI automations can lighten the load on clerical staff by handling appointment scheduling, insurance coding, billing, and data entry. It can also assist with the management of patient records, streamlining the process by allowing staff to use voice commands and automated workflows to navigate systems and maintain records.
AI automations can also assist with claims processing. Recent reports show the average medical office spends nearly three hours each day on paperwork related to prior authorization insurance requirements. AI automations can streamline the process by verifying information, flagging errors, and handling approvals.
Data management is a pressing need in the healthcare industry, where the average hospital collects 50 petabytes of data each year — the equivalent of 25 trillion pages of standard printed text. AI automations can optimize data management in a number of ways, increasing data mobility and allowing enhanced data analytics.
By automating patient record reviews, AI can help deliver optimal preventive care. Automated processes can alert doctors when patients are at a high risk of readmission, prompting proactive care interventions. It can also analyze electronic medical records to automatically provide doctors with risk ratings for patients, allowing them to better advise patients.
How AI automation is reshaping healthcare revenue cycles
The healthcare industry is facing a number of challenges in the area of revenue cycles. Complex processes, intensive data needs, and a lack of standardization all contribute to slower cycles, which strains cash flow and ultimately leads to higher operating costs.
AI automations can contribute to improved revenue cycles in a number of ways. On the front end, AI can automate the data capture process, using natural language processing to extract billing codes from clinical notes. AI can also automate the data review process, identifying errors and incomplete information that can lead to denied claims.
AI can provide automated reports on problematic patterns in the revenue cycle. By identifying revenue leakage, coding gaps, and denial patterns, AI can help providers improve systems in ways that improve revenue performance.
Digital transformation has created unprecedented opportunities in the healthcare space, empowering better care outcomes, as well as more efficient and profitable business operations. AI automations provide healthcare providers with the tools they need to take advantage of those opportunities. The future of healthcare is being shaped today by AI and machine learning innovations that solve healthcare's most pressing needs.
— Sean Shahkarami is the CEO of Opilio, a leading AI company aimed at changing the way businesses mobilize their data. Opilio is at the forefront of automating data management, delivering innovative solutions that streamline workflows, eliminate manual tasks, and allow organizations to allocate resources more strategically. Opilio's use of machine learning and AI empowers businesses to unlock their data's full potential, facilitating accurate predictions and data-driven decision-making across all areas of their operations.