Key Takeaways

Healthcare has a burnout problem. In fact, nearly half of the American healthcare workforce is burned out. And, as a result, health systems across the country are experiencing significant levels of employee churn.

A variety of factors contribute to burnout. Career development opportunities are increasingly difficult to attain. Mounting patient volumes are placing more pressure on medical professionals to do more with less. But one stand-out factor is the unprecedented stress resulting from administrative burden — a symptom of fragmented, outdated workflows.

As leaders seek out and adopt innovative AI platforms to help alleviate care teams from overwhelming admin tasks, we’ve put together our five most important AI platform characteristics to look out for when aiming to boost employee retention in healthcare.

1. Reduce operational friction

The healthcare workforce doesn’t burn out overnight. It’s a gradual process that results from a consistent drip of stressors on the job that accumulate into overwhelming pressure, exhaustion, and a lack of motivation. 

One key contributor adding fuel to this fire is operational friction — gaps between technology and the tangible experiences of people using it.  A common example of this concept is when care team members juggle various usernames, passwords, and point solutions throughout the day. The added effort it takes to remember login details and switch between apps — the extra “toggles and clicks” — piles another layer to a jam-packed workday. 

Specifically, Memora Health’s intelligent care enablement platform deeply integrates into foundational tools like EHRs and CRMs. Memora’s platform can be easily launched within existing systems of record so clinicians never need to leave their workflows. Underlying this integrated approach, it pulls data directly from the EHR to personalize patient outreach — and writes back patient-reported data, like survey results, directly into the patient record.

The bottom line: Opt for healthcare AI technologies that are purpose-built to integrate fragmented workflows and foster more seamless care team experiences.

2. Support top-of-license care

At the end of the day, healthcare professionals are fulfilled when they’re doing what they love most on the job: helping patients. But with the sheer increase of tasks completely unrelated to top-of-license care in recent years, care teams are experiencing less time with those they treat and more time working in the EHR. 

A Medscape study found physicians spend an average of 15.5 hours on paperwork and administration every week. Furthermore, EHR documentation assumes nine of those hours. A troubling JAMIA report revealed ambulatory physicians spend five hours in the EHR for every eight hours spent with patients.

And let’s not forget about the increased influx of message alerts that have emerged with an increasingly open digital front door. Healthcare AI that integrates with existing infrastructure and that actively assists care teams has the potential to significantly diminish operational friction in these contexts. That’s why forward-thinking healthcare AI platforms don’t just streamline existing tasks to make them quicker and more efficient. They holistically address the administrative burden clinicians experience throughout the workday. 

For example, Memora’s platform leverages conversational AI to answer routine patient questions as they’re asked — retrieving client-assured answers from a clinician-curated database to flexibly and responsibly engage individuals on care journeys. This helps mitigate the influx of patient messages and calls that so often divert attention away from performing top-of-license care. 

The bottom line: Choose healthcare AI options that reduce the time care teams spend on administrative tasks and routine to-dos.

3. Intelligently triage patients

Many digital health tools have enabled specific aspects of patient engagement outside of the four walls of the hospital. For instance, wearable devices have enabled doctors to collect patient data once individuals return home. 

But a lot of these technologies have also increased the amount of data hospital staff must analyze and act upon. And beyond sorting through this information, care teams must decipher concerning signs, then prioritize in which order they will act up on them. 

What happens when prioritizing patient information itself becomes a burdensome task? Care teams must again divert attention away from delivering top-of-license care. Luckily, healthcare AI has the potential to sort through vast datasets and rapidly organize it and efficiently display it for actionable use by providers.

Memora Health’s platform intelligently triages concerns reported through its communication channels. This takes some of the tedious work of combing through data to prioritize patients off of care teams’ plates. Simultaneously, it streamlines effective interventions when they’re needed, enhancing the care experience for individuals who need urgent assistance directly from a clinician.  We know that some concerns just require human expertise, so when Memora's AI needs to escalate a patient concern, our platform not only surfaces alerts within clinicians existing workflows, but those alerts are contextualized with actionable information, and easy reference longitudinal data via a full patient profile.

Clinicians spend less time sifting and digging and focus their time on providing clinical guidance to resolve the patient's needs.

The bottom line: Actively seek out platforms that not only collect and organize data, but make it easy for care teams to focus on those who need their help the most.

4. Assist with care self-management

Much of healthcare is moving to the home setting. In fact, McKinsey predicts that up to $265 billion of Medicare-related care services could shift to at-home care by 2025. 

There are a multitude of benefits to this evolution — patients enjoy the comfort of their own homes, require fewer trips to the hospital, etc. However, ensuring high-quality care is maintained outside of the closely monitored environment of health systems is challenging.

Experts from across the industry have suggested reinforcing care self-management as an effective approach to ensuring positive outcomes at home. And there’s evidence to back up this strategy. One analysis points to various studies that have proven self-management improves “health distress, self-efficacy, and well-being,” and can “further lead to a reduction in healthcare resource utilization.”

The right healthcare AI platforms are well-positioned to embolden patients to understand their care journeys and more easily navigate managing conditions. But only if they’re developed to support patients with clinically relevant information. Memora's AI-enabled Care Programs are designed to proactively nudge patients toward behavior change and care self-management. Informed by deep UX research, Memora sends the right SMS at the right time to not only build patients’ confidence levels, but also monitor comprehension of and adherence to care plans. 

The bottom line: Consider healthcare AI platforms with a clinical focus, that are developed in part by medical professionals with deep expertise, and that proactively educate and guide patients.

5. Keep the human in healthcare

If you’ve worked in healthcare for the past couple of years, you’ve probably seen AI go from a suspicious prospect to a promising technology. In truth, there’s a lot of potential for intelligent programs to advance care delivery, promote better outcomes, and significantly streamline and integrate cumbersome workflows. 

However, many AI products — specifically those based on generative models — have shown distinct flaws in responsibly surfacing accurate and appropriate answers in the healthcare context. For instance, one solution infamously started issuing individuals facing eating disorders advice on dieting — which is obviously problematic and could actually cause unintended harm.

To prevent these dangerous situations, AI developers must incorporate a rigorous governance program as part of their creation process — one that prioritizes humanity. Memora Health boasts an established internal responsibility framework, overseen by a committee of stakeholders with diverse backgrounds — from clinical experts to legal specialists to clients. And, at a fundamental level, Memora’s platform runs on a retrieval-based AI model when surfacing patient-facing responses — one that requires upstream verification and approval by human stakeholders.

And what if care team members must get in contact with their patients to address concerns Memora’s AI escalates? Without leaving their workflows, clinicians can correspond directly with patients via SMS. This means fewer phone calls (that will likely go to voicemail), faster resolution time, and stronger patient-provider relationships. 

The bottom line: Don’t rush into generative AI. Embrace healthcare AI built with a well-defined responsibility framework that keeps the human in healthcare.

The age of AI is one of the most exciting eras for healthcare. By embracing intelligent technology, we can potentially witness unprecedented quality, establish new levels of clinical efficiency, and realize better experiences across the board. However, it’s up to healthcare leaders to select the right platforms that will get us there. Selecting technologies that reduce operational friction, support top-of-license care, intelligent triage patients’ needs, help individuals self-manage their care, and that are built with responsibility as a central tenet, we’ll get closer to a better future that much quicker.

Book a demo with our experts today to find out the ins and outs of our healthcare AI platform.