Voice AI is the new frontier in healthcare. With its constantly evolving landscape, the healthcare sector is famous for its extensive patient and employee challenges. When outdated manual processes and systems fail the average clinician and begin to affect patient outcomes, it is key advancements in voice-powered artificial intelligence and automation that helps them get their eyes off screens and back to what they do best — face-to-face comprehensive patient care.
Current challenges facing healthcare systems
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Healthcare is faced with a diverse set of challenges, leading to widespread labor shortage and a quality-of-care crisis, not only affecting the clinicians, but also the quality of patient care and positive healing outcomes.
Of all healthcare challenges, the most significant has been the Covid-19 pandemic, which has affected hospital and home health systems worldwide. With the surge of Covid-19 patients entering the healthcare infrastructure, clinical labor has been unable to keep up. As clinicians began to experience severe burnout, medical errors grew to become the third leading cause of death in the US, while overall healthcare attrition rates have increased exponentially. In 2021 and 2022, nursing attrition rates increased to a staggering 7 percent. With new nursing positions decreasing, these attrition rates may not stabilize back to an estimated 4 percent until late 2023 or 2024. Labor force studies estimate that between February 2020 and November 2021, around 460,000 healthcare workers left their jobs to pursue other career paths.
Much of this turnover comes from increasing mental health burden on frontline clinicians. In a recent survey on World Mental Health Day, around 74% of healthcare professionals stated that due to Covid-19, they have felt an unusually high mental burden and overall decline of their mental health. The pandemic highlighted the severe need for mental health resources, and around 41% of healthcare professionals stated that they had to seek out a therapist or psychiatrist due to Covid-19 mental health burdens.
Additionally, with increased demand for new pharmaceutical drugs and remedies, input healthcare costs have risen in a similar trend to attrition, leaving patients unable to afford life saving treatments. McKinsey estimates that between 2019 and 2022, at the height of the pandemic, clinical labor costs increased 25 percent, prescription costs by 21 percent, with overall services between 16 and 18 percent. These challenges are compounded by the burdens of clinical paperwork, overlapping-yet-incompatible legacy systems, and overarching compliance requirements.
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However, clinical burnout is not attributed just to increasing patient acuity. Another common healthcare challenge is the administrative burdens of the clinical documentation process. As EHRs, or electronic health records, swept the healthcare infrastructure, many clinicians felt a mild sense of relief, as EHR systems could provide additional support that paper charting could not. The challenge with this shift is that the manual process has simply been digitized and relegated to screen time, shifting the eyes and hands of the clinician away from the patient.
Companies across the health spectrum are analyzing ways to unburden the clinical worker in hopes to ease the long-term challenges the clinicians face. However, many hospital and home health executives are struggling to find the best way to do this.
Voice is at the center of healthcare— from triaging a patient, to communicating test results and treatment plans, as well as inter-employee communication. With adaptable voice capabilities and workflow automations, voice can transform the experience for both the overworked clinician and the patient’s outcome.
How AI and process automation is transforming healthcare
Innovators and thought leaders have been steadily working to transform the healthcare industry, allowing clinicians to become more effective, utilizing artificial intelligence (AI) and process automation. However, without the feedback of cross-sectored teams including frontline clinicians, healthcare policymakers cannot deploy these changes alone. AI and process automation seek to bridge these gaps by creating workflows that transition seamlessly in-between sectors. Many healthcare companies are bridging this gap by hiring Chief Experience Officers, meant to act as a policymaking lead, while also getting direct input from the clinicians that experience these daily challenges.
General technology solutions like EHRs do not provide a quick fix on their own. Instead, sustainable, and adaptable solutions like AI are needed to address the cognitive overload, user burnout, and human-generated errors that challenge the healthcare field. The World Economic Forum’s research states, “the majority of AI decisions impact business processes, customer experience, and cost— key concerns for chief executives”.
The WEF believes that utilizing AI can transform population health management, decrease medical loss ratios, and reduce overheads for customer care employee costs. Operationally, AI can house extensive learning tools for medical testing, diagnosis, and treatment, which can lead to faster and more accurate diagnoses and treatment outcomes for patients, while simultaneously customizing patient care.
At its core, voice AI effectively unburdens the clinician, while improving patient care. According to McKinsey research, over one trillion dollars of accessible revenue still remains untouched due to errors created by outdated software and inadequate treatments. Capturing clinical data in real time and automating workflows are highly effective at migrating screen time to face time with patients on a day to day basis. More face-to-face time with patients, has the potential to generate faster patient recovery times. This is a radical productivity shift.
The rise of the “superclinician” in hospitals and home care
80% of global employees do not work in front of a screen, and this is especially true in a clinical setting where patient focus creates constant clinician mobility. This often leaves paperwork and compliance as a component of work that clinicians have to make time for, leading to errors, lost revenue and potential gaps in patient care. These errors occur most often in EMR note-taking and form data inputs, dissection of up to date patient data and clinical lab results, and navigating through multiple work systems to achieve process requirements.
Voice, more specifically enterprise voice capabilities, reduces human-generated errors often caused by handwritten or manually-input data or process requirements. An enterprise voice capability can impact frontline workers across the healthcare spectrum, from doctors and nurses to home health aids and even locum tenens workers.
Implementing voice AI technology has an added bonus to administrative automation, where clinicians begin to feel more effective, valued, heard and satisfied. This transforms the employee experience into a positive, while generating better day-to-day efficiency, creating “superclinicians” in the process.
The use of voice AI can be combined with the ability to interact with multiple back-office systems, including Epic or Cerner, to not only send and receive information, but actually execute a transaction with voice, all while in the company of the patient. Additionally, voice-specific workflows can be built and monitored with the safety standards in mind to keep data secure and within current healthcare compliance standards.
Voice workflows can be customized depending on the specific setting, whether it be large hospital networks or home healthcare, to give the clinician the exact tools they need to increase their own efficiency, and transform successful patient outcomes. The superclinician can utilize voice workflow capabilities to retrieve accurate information quickly, allowing them to get back to their primary objective, providing high quality patient care.
Voice AI Applications
- Voice AI can generate up to 30% higher clinician productivity, by automating these healthcare use cases
- Updating records
- Provider duress
- Platform orchestration
- Shift management
- Client data handoff
- Home healthcare
- Maintenance
- Equipment ordering
- Meal preferences
- Case data queries
- Patient schedules
- Symptom logging
- Treatment room setup
- Patient condition education
- Patient support recommendations
- Medication advice
- Incident management
- … and many more
- Benefits of adopting a Voice AI solution in healthcare
- Burden Reduction
- Employee Retention
- Compliance
- Data Integrity
- Patient Outcomes
- Face to Face Output
Conclusion
While the relationship between Tony Stark and his AI assistant Jarvis may seem unrealistic in the short term, Voice AI and automation is today’s best practice, and can simplify the complex reality of the clinical setting while maintaining and improving quality and accuracy.
Voice-powered automation can be used to improve employee experience and patient outcomes simultaneously.
The key drivers to adoption of a new voice channel is the positive value created in the employee experience. Workflows can be designed specifically to improve the employee experience by taking away the need to enter and retrieve data from difficult to use legacy systems on small screens. Even something as simple as a voice-enabled ability to request shift changes signals to the employee that their employer is on their side in looking to make their work experience better.
Large health care providers should have their own enterprise voice capabilities in order to make use of diagnostic information, because these institutions often have multiple EHRs via acquisition.
Photo: berya113, Getty Images
Tomer Garzberg is the CEO of ybot.com, a multilingual voice AI that uses simple commands to automate comprehensive work tasks for frontline employees. Tomer is a TED speaker on AI, and co-founded ybot with Dima Galat, a technical leader in applied machine learning and computer science. Prior to ybot, they led an automations skunkworks, delivering innovative artificial intelligence and robotic process automation solutions for enterprise and government organizations.
