Administrative AI and automation technologies have been overlooked in the massive boom of recent healthcare innovations. While they may not be as exciting as surgical robots and other clinical AI solutions, AI and automation are crucial to improving practice administration and office management. The newest AI in oncology can help streamline administrative processes, reduce costs, and improve patient care with minimal effort.
According to the National Cancer Institute, there were over 1.8 million new cancer cases in the US in 2020. With such a large patient population and the additional pandemic-related issues such as staff shortages, burnout, and increased demand for remote care, it’s no surprise that oncology practices are looking to AI for solutions.
Practices collect, compile, and share vast amounts of complex data daily. Despite the best efforts to analyze this enormous amount of data without the assistance of AI technologies, over 12 million “serious diagnostic errors” are recorded each year. AI and automation processes can help reduce strain on practices with limited staff and resources and improve overall patient care by quickly and accurately analyzing data to provide new, meaningful insights.
What Is AI?
AI is any technology or machine that can complete a task typically associated with human intelligence, including detecting diseases, managing records, overseeing scheduling, and resourcing allocation. Before AI technology can be used, it must be approved by the FDA. The types of AI technologies used in healthcare are:
- Machine learning
- Robotic process automation
- Natural language processing
- Rule-based expert systems
- Treatment and diagnosis applications
- Patient adherence applications
- Medical Software Programs
Machine learning and robotic process automation are the most common AI technologies implemented in practice management. According to a 2019 report in the Future Healthcare Journal, 63% of companies surveyed employed machine learning in their practices. Robotic process automation is an administrative technology that’s a simple way to boost efficiency in practice management.
How Is Machine Learning Used in Oncology Practices?
Most oncology AI uses machine learning, which drives most of these applications. The application uses algorithms to detect and report previously unrecorded parallels and patterns in the large amounts of data collected. The more data the application has, the more accurate the insights will be. More sophisticated machine learning, also known as deep learning, can understand different levels of abstraction and better diagnose disease, predict patient outcomes, and suggest personalized care plans.
An online virtual assistant is a real-life example of machine learning in oncology AI. Virtual nursing assistant programs help bridge the gap between healthcare workers and patients and have been projected to save the healthcare industry as much as $20 billion annually. With online patient portals, mobile applications, and virtual nursing assistants, patients can talk directly with a nurse to see if an office visit is necessary. This keeps appointments open for patients who need them and helps monitor patients remotely so they can heal in the comfort of their homes.
How Is Robotic Process Automation Used in Oncology Practices?
Significant time and effort goes into repetitive administrative tasks requiring no specialized knowledge base. Robotic process automation, also known as software robotics, performs these back-end tasks like pulling data, completing forms, managing files, and data transfer authorizations.
AI in oncology isn’t meant to replace workers but free up their time to focus on the growth of the practice and improving patient care. Robotic process automation can also be used on office tasks such as scheduling and billing. Medical software programs can complete prior authorizations without needing a manual check because they can recognize possible coding errors.
Considering the number of patients diagnosed yearly, oncologists are particularly interested in improving care using robotic process automation and machine learning.
How Can Oncology AI Improve Practice Management?
AI technology, such as machine learning and robotic process automation, are innovative solutions that can help increase patient satisfaction, improve staff morale, and reduce costs. According to MIT’s Sloan Review, when the Mayo Clinic utilized AI tools to manage their staff, resources, and space, they reduced doctor overtime by 10% and increased space utilization by 19%.
AI technologies can transform oncology practice management by decreasing inefficiencies in administrative processes and minimizing time spent on non-patient care activities like prescribing medications and ordering tests.
How Does an Oncology Practice Launch AI Technology Successfully?
It’s highly recommended that an oncology practice management expert is there to support the practice as it rolls out new AI technologies. Verdi Oncology provides clinical, technological, operational, and financial support to small practices to empower them to access innovative solutions.
Founded on the five core pillars of patient experience, patient growth, clinical pathways, practice efficiency, and value-based care, Verdi Oncology supports practices’ growth and helps them prioritize personalized patient care. Contact us to learn more about our personalized, innovative AI solutions.