Big data continues to have a monumental impact in the healthcare industry. However, the challenge remains to identify how this information can be analyzed and used to improve patient outcomes, boost efficiency and cut costs.
The influence of emerging technologies, such as machine learning and artificial intelligence (AI), are seen daily. Just think about the online shopping experience for instance. When purchasing one item, suggested items or add-on items appear almost automatically. These recommendations are provided based on an analysis of user data as well as factors that influence purchasing behavior, such as demographics, age, gender, and location.
Soon, this principle will be applicable to healthcare as well. Data in the healthcare industry can come from wearables, which carry immense promise for the future of the care. While the Fitbit is used mostly by individuals to keep track of their own health information, like heart rate and number of daily steps, the connection to the industry will come when that data can be shared with healthcare providers.
Take, for example, a patient who just received a hip replacement. With access to that patient’s Fitbit, physicians could monitor the user’s average daily movement and step count. If this movement drops significantly, the physician would be alerted that the patient may need assistance. Moreover, the doctor could access the patient’s medical history, including previous health care details, medical records, and even costs. This is all possible by making data interoperable. The data can then further be analyzed to derive specific insights that can influence future decisions through the power of AI.
While there are still steps needed to get to this point, there are more practical, immediate ways that AI can support the operational aspects of healthcare. Efficiencies can be created by leveraging AI in several ways, including:
• Task assistant: AI performs best when paired with humans. This technology is used in tandem with humans to create efficiencies that help hospital staff in their daily roles and give physicians more time to focus on value added activities, not mundane tasks. Where appropriate, AI can automate these tasks and functions – giving caregivers more time to dedicate to patient care.
• Enhanced employee self-service: AI can empower cross-functional self-service for healthcare employees who do not have immediate access to computers. By asking questions in employee self-service programs about paid time off (PTO) and/or vacation balances to company holidays, AI can provide quickly and accurately provide employees with the answers.
• Supply chain optimization: AI can trigger automatic re-orders of supply, answer employee queries about supply, and track inventory to minimize unnecessary spending. Another benefit of using AI to optimize the supply chain is that it can help to decrease how much time nurses and clinical staff spend looking for supplies. This is done by simply providing an answer for where supplies are located at that exact moment in time, so they can more quickly get back to their patients.
• The payment process can be augmented by AI by noticing payment, vendor and invoice patterns, and suggesting payment automation for invoices that get approval the majority of the time. This gives the finance department more time to focus on ways to strategically cut costs while improving patient care.
• Maintain a peaceful atmosphere: By using AI to oversee hospital equipment, staff can quickly access the insights needed to better care for their patients. These insights can then be used for something as simple as adjusting bright hallway lights during patient sleeping hours, or something as complicated as scheduling preventative maintenance when an important piece of equipment shows signs of possible failure. This helps maintain a peaceful environment and could potentially boost patient satisfaction scores, helping the hospital’s reimbursement levels.
AI enables healthcare organizations the opportunity to optimize and automate supply and demand, augment financial payments and processes, and improve employee self-service – giving providers more time with their patients and allowing organizations to improve cost and care efficiency.
We have yet to see the full potential of AI in healthcare, nor have we seen its ability to make healthcare data interoperable. That said, while we are not fully ready to use machine learning to adapt treatment and care routines in real-time, computing power, analytics and AI are set to disrupt the healthcare industry of the future.
Mark Weber is the SVP of Healthcare Development at Infor.