Cognitive Automation in Healthcare
Using machine learning algorithms in conjunction with experienced human eyes, this new wave of emerging technologies is transforming the healthcare systems we know.
While Robotic Process Automation is here to unburden human resources of repetitive tasks, Cognitive Automation is adding the human element to these tasks, blurring the boundaries between AI and human behavior.
Robotic Process Automation (RPA) enables task automation on the macro level, standardizing workflow, and speeding up some menial tasks that require human labor. On the other hand, Cognitive Process Automation (CPA) is a bit different but is very much compatible with RPA. Cognitive Automation is based on machine learning, utilizing technologies like natural language processing, and speech recognition.
CPA, RPA, and AI healthcare are improving data management and compliance at astonishing rates. They go hand in hand, igniting this digital transformation across industry branches.
A growing need for Cognitive Healthcare Solutions
The most important reason why these technologies are a necessity: there is very little room for error in the medical field. This is as true in the examination room as it is in the billing department. One missed document or incorrectly entered code can cost a patient drastically both financially and in terms of their own health.
To increase accuracy and reduce human error, Cognitive Automation tools are starting to make their presence felt in major hospitals all over the world. With the implementation of these tools, hospitals can free up one of the most important resources they have, human capital. With the reduction of menial tasks, healthcare professionals can focus more on saving lives.
What is Healthcare Automation?
Healthcare automation encompasses a wide range of functions. Most often it refers to Robotic Process Automation (RPA). This is not to say that there have never been attempts to address use cases that result in virtual reality consultation — specifically for psychological therapy — most instances of automation in healthcare are found in administrative areas.
This is because the type of automation that is gaining in popularity in the healthcare industry is Cognitive Automation. That means that automation works in tandem with healthcare professionals to streamline and optimize processes that are often repetitive. The automation allows human workers to focus on interpreting and analyzing data instead of mindlessly entering that data.
The world population is projected to reach almost 10 billion people by 2050, and with the advances in the medical field, the aged population will be larger than ever. This of course raises the question, “Who will care for these people”, and the answer is unfolding before our eyes right now. With Robotic Process Automation, healthcare workers can manage to keep up with the growing world population.
Most common challenges for Cognitive Automation, RPA, and AI in healthcare
Implementing automation software to reap the benefits of RPA in healthcare, isn’t without its pitfalls. If you don’t pay attention to the most common challenges involving the implementation of medical RPA software, you could end up with a convoluted system that benefits no one.
There are several main areas of concern regarding the application of RPA in healthcare, including:
Identifying processes to automate
Correctly choosing the process to automate should be obvious. Often these processes are the ones that have insignificant business impacts, processes that change too frequently to have noticeable benefits, or a process where errors are disproportionately costly. Failing to pick the right process to automate can lead to a negative ratio of cost-effectiveness.
Through the media, we are constantly being bombarded with stories of an automated future, where man is replaced with a machine. It is no wonder that the average worker is often intimidated by any push for automation. The reality is far tamer — the human worker is the one that benefits from the machine, and the machine cannot replace them. Do not disregard employee education as a key step towards RPA automation.
Failure to use the appropriate software solution
Choosing an outdated solution to cut initial expenses is a sure way to limit your results from the very start. RPA and CPA are novel technologies that are being improved upon almost daily. Leveraging the full capacity of your chosen solution should be of utmost importance.
Consider consulting an experienced automation software solution company to properly identify, and avoid these problems. Strickland Solutions has been helping businesses achieve their goals since 2001. We take pride in our ability to correctly overcome all the potential challenges faced by our clients, and our ability to meet their expectations and add value to their business.
AI Healthcare Solutions: How is artificial intelligence used in healthcare?
But what does automation actually look like in healthcare? It is all well and good to mention artificial intelligence and machine learning, but it is important to highlight RPA healthcare use cases to show the variety of functions that can be improved with Cognitive IT.
AI allows for large stores of information to be processed at lightning speed and with pinpoint accuracy. Incorporating machine-learning allows for optical character recognition and even natural language processing — meaning less time is needed to interpret information that comes directly from doctors and patients on forms and charts.
These abilities improve healthcare outcomes in ways that may surprise you. Some examples of RPA in healthcare include:
RPA data analytics can automatically scan insurance claims for keywords and important information to automatically route claims to the relevant queues. Also, RPA enables monitoring of network devices and can improve service desk operations. This separates the scalability issue from human resources and allows companies to handle a larger number of claims without extra recruiting or training.
Some studies have shown that automating and integrating lab processes such as coagulation and hematology blood tests with front-end processing and specimen storage reduces manual labor in a medical lab setting by as much as 82%.
One study pointed to a fully automated VR treatment study in which patients with phobias worked in a virtual environment with an automated avatar to safely confront situations that had triggered their phobic responses in the past.
Finding Diagnostic Patterns
With RPA analyzing diagnostic data, patients who match common factors for cancer diagnoses can be recognized and brought to a doctor’s attention faster and with less testing. It improves the care cycle tremendously and streamlines much of the time-consuming research work.
Machine-learning allows transcription programs to recognize natural language regardless of accent and to incorporate punctuation without the need for the speaker to highlight periods and commas. This frees up medical professionals to focus on patient care.
RPA healthcare use cases are varied and span the length and breadth of the medical industry. As more studies are conducted and more use cases are explored, the benefits of automation will only grow.
Benefits of Cognitive Automation and RPA in healthcare
RPA use cases in healthcare are numerous, providing not only cost-effective solutions for manual processes but also helps overall employee satisfaction. Having more time to focus on complex tasks rather than worrying about data collection, data entry, and other repetitive tasks allows the staff to focus more on providing better patient care — thus increasing its overall quality.
Organizations can also benefit from RPA’s and CPA’s ability to improve the revenue cycle and streamline administrative processes. The technology automates repetitive processes such as accounts payable and data digitization — increasing billing efficiency. This effectively helps organizations save their most valuable resources: time and money.
Keeping your patients’ records safe is also an important aspect of automation. RPA and AI in healthcare could prevent data breaches and leaks of sensitive information. Patient confidentiality and compliance with regulations are safer with smart automation because there is always a danger of human error. New technologies are constantly evolving, learning, discovering patterns, and learning from them.
While reducing overall costs with its cost-effective process streamlining, the true value of process automation lies in its ability to improve the patients’ well being and satisfaction. In the long run, this can also immensely improve the ROI of RPA implementation.
AI healthcare is a sector of the industry that is only going to grow. As studies that show the effectiveness of Cognitive Automation and the freedom it offers to health care professionals continue to come in, more hospitals and clinics will incorporate RPA.
It is important for doctors, nurses, and administrators to have accurate information as quickly as possible and RPA gives them exactly that. From the lab to the exam room to the billing department, Cognitive Automation allows humans to do their jobs with less risk of costly human error. The right time to invest in RPA is now.
Since it has proven effects on saving time and effort, all while cutting down costs, it is expected that healthcare RPA will become a staple in the healthcare industry. Implementation of RPA, CPA, and AI in healthcare will allow medical professionals to focus on patients themselves. Addressing these challenges on time will help secure the future of the industry, with the wellbeing of patients in mind.