Healthcare systems are under increasing pressure to process data from an expanding array of internal and external sources faster and more accurately. At the same time, Covid-19 has exacerbated an already severe shortage of trained medical professionals.
By automating routine tasks, streamlining operations, and enhancing patient care, technologies including artificial intelligence (AI) and automation are helping to optimize resources and improve healthcare efficiency. These benefits, in turn, help offset the impact of the talent shortage.
Why healthcare needs automation
A recent study showed that many healthcare workers are experiencing burnout, and administrative work is a big contributor: survey respondents reported that they spend 34% of their time on administrative work.
In addition, a study on "reducing and preventing medical errors" found that medical errors have become the leading cause of death in the United States, causing about 100,000 deaths each year. These statistics highlight serious issues in the healthcare industry that require urgent attention. They also show that healthcare organizations and policymakers need to prioritize investments in automation and other innovative technologies to improve the delivery of care.
For example, by automating data entry and appointment scheduling with AI, healthcare organizations can reduce the administrative burden on staff and allow them to focus on more complex tasks that require human interaction or intervention. Similarly, by using predictive analytics to optimize staffing levels, healthcare organizations can ensure they have the right number of employees at the right time, which can help improve patient outcomes and reduce burnout.
The benefits of hyperautomation
Hyperautomation has the potential to solve many of these challenges by increasing efficiency, reducing costs, and improving patient outcomes.
Hyperautomation requires the automation of human workflows while directing a range of related tasks. With hyperautomation, multiple technologies work together to overcome the barriers posed by a single technology.
For example, robotic process automation (RPA) and other forms of automation offer great promise for increasing business agility and operational efficiency in healthcare environments. Despite its huge potential, RPA cannot be used alone to adapt to the changing healthcare environment. Artificial intelligence, machine learning (ML), natural language processing (NLP), and intelligent document processing are all examples of technologies that provide a cognitive layer for RPA.
Unlike RPA, which has limited capabilities to automate the processing of unstructured data, intelligent automation (IA) leverages AI to incorporate analysis, logic, judgment, and decision-making into the automation of higher-order tasks. By all of these technologies working together, management and other tasks can be automated, freeing up caregivers to focus on higher-level tasks, especially better patient care.
4 healthcare use cases
In the healthcare industry, there is a strong emphasis on patient-centered care. As a result, healthcare providers are turning to digital platforms that have the potential to introduce exciting new ways to deliver care. This allows for a specialized approach to enhance patient care. Below, I've highlighted four use cases of hyperautomation, two of which are specifically related to patient care.
1.AI medical diagnosis
By combining hyperautomation with other technologies such as computer vision, ML, and intelligent processes, healthcare companies can generate reliable reports in record time. For example, to identify medical conditions, computer vision and ML-based solutions analyze radiology scans. The automated workflow can then assign cases based on specialization, department, reading ability, etc. It can then prioritize them accordingly.
After the test is complete, the doctor can electronically send the diagnosis back to the patient and include it in an electronic medical record (EMR). AI can then analyze patient data from EMRs, including medical history and lab results, to help doctors make more accurate diagnoses and treatment recommendations. Some AI-driven diagnostic tools, such as Merative (formerly IBM Watson Health), can do this easily.
2. Remote patient monitoring
In recent years, we have experienced physical access to medical facilities limited by barriers and lockdowns. In these types of scenarios, remote patient monitoring (RPM) enables healthcare providers to track a patient's health outside of a traditional clinical setting. RPM typically involves the use of wearables, sensors, or mobile apps to collect patient data and transmit it to healthcare providers for analysis.
The goal of RPM is to allow healthcare providers to monitor patients in real time and detect any relevant trends or anomalies that may require intervention. This can help improve patient outcomes by detecting the occurrence of health problems earlier and providing more personalized care, reducing readmissions and reducing healthcare costs.
High-risk patients, such as those with chronic conditions or undergoing post-acute care, can benefit from wearables to track vital signs, such as blood pressure and blood sugar levels. Because data analytics is able to sound alerts and provide recommendations for patient engagement programs, digital health assistants can drive adherence to treatment recommendations to handle personalized care.
3. Administrative tasks
Through AI, RPA, process mining, and data analytics, you can improve the patient experience and operational efficiency. In my experience, AI and RPA help automate repetitive and time-consuming tasks such as data entry and appointment scheduling, so healthcare professionals can spend more time on patient care.
Process mining and data analytics can help identify inefficiencies in workflows and processes, support data-driven decision-making, and improve operational efficiency. For example, appointment scheduling can be implemented using virtual health bots, such as Microsoft's Azure Healthcare Bot.
Microsoft's virtual health bot provides AI capabilities and is very easy to set up. It can be used to detect missing eligibility data. In addition, it connects with external applications to collect information lost during appointment and patient registration.
Based on my experience with this Microsoft healthcare bot, here are five steps to help you implement it correctly so you get the most out of it:
- Define use cases: This may include tasks such as appointment scheduling, symptom checks, medication administration, and more.
- Develop bots: Build and train bots using Microsoft's Bot Framework. This involves defining the bot's conversational flow, developing natural language processing capabilities, and integrating the bot with related back-end systems, such as EMR systems.
- Deploy your bot: Deploy your bot to the desired platform, such as your organization's website, mobile app, or messaging.
- Testing and improvement: Test your bot in a controlled environment to ensure it performs as expected. Optimize bot responses and workflows based on user feedback and data analysis.
- Scale and maintain: Scale your robots to meet demand as your usage increases. Monitor the robot's performance and regularly update it with new features and capabilities.
4. Supply chain
In a supply chain, coordinating the flow of goods and services from suppliers to customers can be a complex and time-consuming process. In the healthcare industry, the supply chain is responsible for the timely delivery of various materials.
AI algorithms are used to analyze demand patterns and predict future demand, enabling organizations to optimize inventory levels and reduce waste. Automation is also used to streamline the procurement process, reducing the time and effort required to order and receive goods.
Final thoughts
In many industries, hyperautomation is quickly becoming a necessity rather than a novelty. In healthcare, hyperautomation has not only increased the efficiency of the industry's rapid transformation in response to the pandemic, but has also had a beneficial impact on patient treatment and health outcomes.
In healthcare, hyperautomation can provide businesses with new ways to deliver measurable business value through significant operational improvements and ROI. When it comes to day-to-day operations in the healthcare sector, such as patient registration, notification, and advice, this technology can help many departments within healthcare organizations. As the use of AI and automation increases, more organizations will experience better outcomes, including reduced reliance on human labor and improved accuracy.