Lean principles first appeared in healthcare in the 1990s, when healthcare costs began to soar. At the time, lean healthcare was primarily focused on lowered costs. This focus brought pushback from providers who felt their focus should be on the work, regardless of the cost. At the core, providers were concerned that lean principles would interfere with their day-to-day responsibilities. They worried that lean processes would force them to rush through appointments or keep patients from being seen in person when they truly needed the in-person care.
Yet, as more healthcare organizations began to implement lean principles, they noticed that not only did their costs decrease, but there were also improvements in patient care. And these trends have largely continued into the present state of lean healthcare. Across several studies, lean in healthcare has demonstrated the following results:
- Reduced wait times: Healthcare providers have reduced patient wait times by standardizing processes, such as requiring patients to fill out forms electronically before an appointment.
- Improved patient safety: A natural side effect of lean practices is the ability to identify errors in systems. As such, lean principles have helped healthcare organizations identify potential hazards in their processes and procedures and reduce the number of mistakes overall.
- Enhanced efficiency: Healthcare organizations have improved productivity and maximized their current resources through streamlined processes and intentional problem-solving.
- Increased quality of care: Working with patients is critical to implementing lean strategies in healthcare. By acknowledging and actively planning for patient needs, healthcare organizations demonstrate a dedication to the patient experience.
The future of lean in healthcare is bright. As the country turns toward preventative care and patient-centered practices, lean practices in healthcare will continue to evolve.
Artificial Intelligence in Lean Healthcare
We are currently seeing this through the acceptance of advanced technology. For example, several research studies suggest that artificial intelligence can perform just as well as or better than humans at tasks such as diagnosing diseases. In one study, an AI team taught their computer to examine a lung as a 3D object rather than viewing a 2D slice from a typical CT scan. After applying this AI technology to over 45,000 CT screenings, the AI was able to detect 5 percent more cancer cases and reduce false positives by 11 percent. This data was compared to the findings of unassisted radiologists looking at the same screenings.
Machine Learning for Process Improvement
Artificial intelligence isn’t the only technology helping to streamline healthcare policies and procedures. Machine learning will eventually allow healthcare organizations to automate their processes. Informed by data analytics, machine learning will be able to collect patient data and feedback and adjust accordingly. For example, some healthcare organizations are using machine learning to predict the treatment protocols most likely to succeed on a patient based on various data entered into the system.
Robotics for Surgical Precision & Administrative Tasks
While some healthcare organizations are using actual mini robots to help in a variety of surgical procedures, including prostate and neck surgery, other healthcare organizations are using robotic process automation (RPA). RPA allows healthcare providers to automate administrative processes, such as prior authorization or billing. RPA can also collect data to feed to other AI programs within a healthcare system.
The application of Artificial Intelligence in healthcare is limitless. As lean principles continue to grow across the healthcare industry, advanced technology will lead the way in waste elimination and patient satisfaction.