The urgency to transform the healthcare experience skyrocketed with the onset of the COVID-19 pandemic. Providers, insurance companies, and millions of health-sector employees across the country have compounded the need to manage resources, prevent burnout, uphold privacy laws, and thwart medical errors. Patients, meanwhile, have insisted upon an upgraded experience that meets modern expectations...an experience that treats them like customers, not patients.
Fulfilling these needs requires data. An organization’s ability to capture, access, master, integrate, and analyze data is fundamental to their ability to improve processes, make better decisions, and create memorable and delightful experiences for everyone.
Once healthcare data has been harnessed, new capabilities emerge — specfically, capabilities in automation. Automation streamlines and enhances processes ranging from executive-level operational planning to a rich, safe customer journey. With business process automation (BPA), robotic process automation (RPA), machine learning (ML), and artificial intelligence (AI), the opportunity to fully transform the healthcare experience for providers and patients alike is fledging more by the day.
Here are five ways automation leads to more intelligent, inclusive, and personalized experiences for everyone involved with the healthcare sector (read: everyone), no matter which side of the claim they’re on.
Missed appointments cost the U.S. economy over $150 billion annually. They happen chiefly for two reasons, according to SCI Solutions:
1. Patients expect convenience but find barriers instead
2. Manual, error-prone processes leave slots open
This figure doesn’t include the additional potential cost of people who, lacking timely preventative care, receive diagnoses at more critical and costly stages that require more acute (and expensive) treatment.
So how does automation fill the gaps, get people through the clinic’s doors, and reduce costs? In a word: digitization. Remediating the tedious experience of scheduling a healthcare appointment could save millions of dollars a year and give providers and insurers invaluable data about how their customers seek out care.
Automatable scheduling and service capabilities include:
- Online/in-app scheduling
- Automated text reminders (and automatic follow-ups after an appointment)
- After-hours communication with bots powered by natural language processing (NLP)
- Virtual cancellations
- Language translation
- If available, the use of telehealth options that prevent in-office visits for prescription refills, etc.
Going digital-first can minimize the frustration of patients not showing up for appointments and act as a game-changer for patients’ experience with thehealthcare system, especially people with additional barriers to seeking care(such as a disability or lack of transportation).
Humans make mistakes, and there are few industries where accuracy is more important than in healthcare. Global medication errors alone cost healthcare providers $42 billion USD every year.
One way patient data is used to curb this alarming and costly statistic is by implementing automated processes such as electronic medication administration records (eMAR),which works in conjunction with electronic health records (EHR) to ensure the five rights of medication administration are fulfilled:
1. Correct patient
2. Correct medication
3. Correct dose
4. Correct time
5. Correct route for administration
Automation is also useful for diagnostic purposes, as it was when the University of California San Francisco Center for Digital Health Innovation worked with GE to create the Critical Care X-ray suite, which fundamentally changed the way people use portable chest x-ray machines. Before, technicians would take x-rays and place them in a huge pile for the radiologist to go through, flagging any huge, obvious findings for priority. The rest might not be read for hours.
That was a problem because some x-rays had subtle but important findings that, if not identified early, could rapidly turn into life-threatening emergencies (think a small collapsed lung, or a small misplacement of a breathing tube). The CDHI team developed models that looked for these small, early problems and notified technicians right there on the portable equipment so they could prioritize those patients.
These algorithms didn’t replace the radiologists. They didn’t eliminate anyone's job. What they did was improve the workflow to prevent potential crises before they happened and eliminate emergencies in real time.
Though employees must remain involved in process oversight and administration, AI and ML can handle complete patient data pipelines from multiple sources, connecting and verifying sources of truth for the most accurate, interoperable, and secure use. For repeatable tasks, robotic process automation (RPA) and intelligent process automation (IPA)are excellent additions to mitigate human error and reduce mental fatigue.
Furthermore, residents and attending physicians benefit from the power of augmented reality (AR) and3D modeling to support training, diagnostics, and surgery. The use of these virtual tools for educational purposes also aids in error prevention for healthcare providers, leading to more confident procedures and better patient outcomes.
One common pain point in the healthcare system is the lack of automatic data sharing. This stems from real and valid concerns about data privacy, but results in repetition, frustration, and an incomplete view of any given patient or condition. An ideal healthcare experience involves going to the doctor’s office and not filling out that three-page medical history again, because the doctor can quickly and securely see the entire path of an individual care plan in one place.
Interoperability of health records, particularly patient health records, has been a focus area for government organizations administering healthcare policy in America for more than a decade. Many in the healthcare industry understand the potential benefits as well as the risks that come with interoperability of personal health records.
The position in which the industry finds itself—wanting the ability to share highly sensitive personal health data at the click of a button, but into a largely unregulated third-party ecosystem—showcases our competing desires for privacy and ease of access to information.
With the advent of the data sharing standard Fast Healthcare Interoperability Records, or FHIR, interoperability through application programming interfaces, and the heightened support around expanding access to patient health records, has dramatically increased the ease, speed, and extent to which sensitive health data can be shared automatically with third parties.
This is important because the ability to securely search, access, and review patient medical history in situ offers increased visibility and accuracy for future recommendations. Automation can help by verifying information, parsing it to avoid duplication and errors, and even proactively suggesting health data that, based on generalized historical data, the machine believes is relevant to the care question at hand.
As healthcare evolves and becomes more precise, interoperability is key to delivering better experiences for all. The application of AI is making it a safe option to continually improve outcomes and experiences for customers and providers alike.
Speaking of using AI to improve outcomes and experiences, we would be remiss not to address one of the most exciting automation-based technologies being built today: zero trust and confidential computing.
Collecting information about our health has never been easier thanks to IoT devices. Using that data securely and ethically, however, is another story. As lawmakers, insurance companies, and providers look to the future, there’s a clear need for generalized health data—immense amounts of data from people across all backgrounds and locations that can be used to create predictions and, consequently, proactively prevent or treat the biggest health concerns of our time.
The balance between data and security is vital for both patient safety and adherence to federal laws and regulations such as HIPAA. While employees in the healthcare sector are trained in safe recordkeeping, and laws are in place to safeguard patient data, the risk of a data breach is always present. Firewalls, privacy controls, and encryption are just a few ways providers can leverage intelligent security solutions in the healthcare industry.
But companies like BeeKeeperAI attest that AI can answer healthcare’s biggest unknowns while maintaining complete patient privacy. The idea? If data stewards like research hospitals could securely provide data to algorithm owners like startups, academic researchers, and medical device manufacturers, then model validation and training on more diverse datasets could accelerate—without ever having to move the data.
Since data is most vulnerable to attack when in motion, this solution will solve the security issues of using this valuable, regulated, well-guarded data. Additionally, with machines performing the tedious, repetitive work of model validation, doctors are free to focus on seeing patients.
For healthcare organizations that have a strong desire to use their data for something innovative, but for which the risks have outweighed the potential benefits, confidential computing is the key to creating an environment where their ideas can thrive.
Transformation happens when people are empowered. Despite the frustrations of the healthcare system, people have never been more plugged into and knowledgeable about their personal health. This is a massive opportunity for the healthcare industry to engage everyone in creating a healthier future.
At the same time, the healthcare system has been pushed to the limits over the last few years. Especially after the Great Resignation, attracting and retaining staff is imperative for organizations in the health sector—and that requires engagement and empowerment, as well.
Data helps with staff engagement in two ways. First, it can help leaders get face time with employees through automations like Viva Insights, which tracks interactions and auto-schedules important and sometimes overlooked touchpoints like annual reviews. These personal interactions not only help create a positive atmosphere for everyone, they also garner feedback and data that, paired with the operational insights being gathered and mastered elsewhere in the company, give leaders the information they need to make strategic business decisions going forward.
The second way automation alleviates the stress associated with the job is by optimizing what manual tasks are part of the job. By funneling tedious and low-value tasks to machines and using intelligent solutions to take over some of responsibilities associated with day-to-day operations, employees have time in their day to focus on creative, critical-thinking, high-value work.
When people are challenged by and engaged with the work they do, it fosters an environment of innovation. The results of implementing automation like RPA and IPA: increased productivity, fewer errors, and improved overall efficiency.
Automation also allows patients to get involved with their wellness. Wearables like Fitbit and Apple Watch track data that ranges from number of steps to length of REM sleep, and apps track everything from meditation times to calories consumed. People who are privy to their own health records can take proactive steps to manage their health, creating a better healthcare ecosystem.
In response to the surge in personalized health insights, insurers have started to provide wearable or whole-self health programs to members. Much like with health sector employees, when individuals are educated, invested, and accountable, the whole system benefits.
When people hear “human experience,” they often assume that experience refers only to the customer. In fact, these data-enabled automation technologies are built for the business. They make the job easier—fewer mundane and repeatable tasks, easier billing and verification, more proactive appointments with fewer claims, better predictability, less turnover, and, in some cases, the weight of life-altering medical decisions lifted. Data-driven tech enriches the services a health-sector organization provides.
In essence: Automated healthcare experiences give people not only what they need, such as preventative care and diagnostic monitoring, but also what they want: Better, more convenient, and digitally enabled experiences.
As the Healthcare Sector embraces a digital-first culture, automation is vital to staying both relevant and competitive in the healthcare field. For more on the intersection of data, AI, and the pinnacle of experiences in healthcare, read the Future of Healthcare edition of Navigator Magazine.