Regardless of industry, businesses today are faced with constant change in a competitive landscape and dynamic forces like threats of new competitors and products. In order to remain competitive, a firm must manage their bottom line, constantly re-evaluate their business plan and increase efficiency.
Although all business face similar pressures, the health care industry is faced with particularly difficult challenges involving higher patient volume, labor shortages, and maintaining security of highly sensitive data. Management teams must make tough decisions in day-to-day operations that will balance their organization’s profitability and earnings as well as ensuring their patient’s trust and security.
While managers face age-old difficulties, success lies in not just having a strategy, but an innovative one. The use of Artificial Intelligence (AI) is emerging as an essential component to innovative solutions for management in healthcare related to administrative workflow, fraud protection, and patient safety.
Administrative workflow assistance
According to Accenture, administrative workflow assistance is an $18 billion industry and is ranked as one of the top three AI applications that represent the “greatest near-term value”. Workflow assistance helps in the collection of tasks, personnel, information, and documentation of an organization. Depending on the size of a business, an entity may have a single or a group workflow processes.
Regardless of the size, workflow assistance helps solve clinicians’ and management’s administrative burden, freeing staff to perform more complex work. Clinical documentation by AI has been touted as increasing time efficiency up to 45% as well as improve quality of documentation by 36%. For example, by using AI workflow assistance, clinicians can more accurately capture patient information in electronic health records (EHRs), reduce error, and increase interaction with patients. Moreover, there are a number of firms such as Nuance that work with organizations to tailor administrative workflow assistance to suit the organization’s need.
As a $17 billion industry, fraud protection is becoming one of the most critical keys to success for business in healthcare. Whether for hospital and healthcare organizations that need to protect sensitive patient’s information, or insurance companies that must detect fraudulent claims, leverage AI and machine learning to identify patterns associated with user’s habits has been a major advancement in fraud protection.
As huge amounts of data are accumulated over time, AI also improves its accuracy and is able to identify trends and links on a scale that is impossible to match with human cognitive resources5. However, it is important to recognized that AI can only process information provided, which means that results are limited to the quality of the input. Therefore, there should still be a human element integrated to ensure accurate results. There are a number of firms that specialize in fraud protection such as Shift, a start-up company.
Dosage Error Reduction
As a $16 billion industry, dosage error reduction system is a safety feature that helps prevent medication error. Although frontline staff in the healthcare industry receive intensive training and rigorous examinations, they are still prone to human error when prescribing medication levels for patients. Thus, dosage error reduction approaches can not only save lives, especially for chronic patients, it can lead to reduction of potential lawsuits and reputational damage that may occur as a result of mistreatment.
Currently, there are a number of automatic systems such as Dose Error Reduction System (DERS) that helps warn users of incorrect medication orders for infusion pumps. Instead of using basic pumps system, DERS decrease level of risk for patients that are in severe condition and ensure appropriate dosage levels. Although implementing the system may require initial upfront cost, its benefit is expected to outweigh the initial cost and yield higher returns of investment in the long run.
Implementing AI applications may seem like an interruption of existing system in place. However, even at a profitable and efficient healthcare organization, it is fair to state that there’s always room for improvement in efficiency and risk reduction. By eliminating issues such as documentation – management and clinicians can focus on solving real-time issues at hand and thus, improve productivity which translate into better quality treatment for end-receivers such as patients.