At Memora Health, our deep bench of medical and technology professionals embody our mission to make complex care journeys simple for patients and clinicians. Uniting real-world clinical experience with digital health experience, these experts in their field continuously strive to ensure our intelligent care enablement platform lives up to its promise to empower stakeholders across the care continuum.

Join the conversation as they dig into emerging topics in workforce challenges, healthcare AI, and more.

Understanding burnout as a systemic challenge

Physician burnout and I were once close friends. I deeply understand the desire to focus on supporting the wellbeing of others while working tirelessly within a system that puts more value on selflessness than self-care. Over time, the guilt of stopping to put yourself first shadows any relief you might get from decompressing. 

Alexandra DePorre, MD, and Gargi Banerjee, MD, at Henry Ford Health recently published an article discussing current responses to physician burnout, why it continues to grow despite improvements, and whether big changes need to occur to better support our medical community. 

Indeed, healthcare institutions everywhere focus on finding effective interventions to address burnout. But the answer isn’t that simple. According to Drs. DePorre and Banerjee, burnout is a multifaceted challenge, and most research and interventions aimed at addressing the issue have concentrated on personal behavior change — leaving out systemic gaps that might present barriers for adopting more resilient coping behaviors. The authors suggest mental health and peer support programs are critical to quelling burnout — as are environments that value them. 

At Memora Health, we understand why it’s so important for physicians to actually spend “pajama time” in their pajamas. By streamlining provider workflows, we reconnect clinicians to their patients and support them to focus on work-life balance without worrying that taking care of themselves means caring less for the individuals they treat.

Using digital health to get ahead of patient symptoms

Before joining Memora, I was an inpatient hematology and oncology nurse on a blood and marrow transplant floor. At that time, one thing I struggled with the most was seeing patients admitted to the hospital for a lengthy stay that could have been prevented by earlier symptom-related communication with care teams. Instead of addressing concerns at their onset, clinicians and patients often had to inevitably work against more complex issues that developed during delays in care.

One strategy that can help prevent such situations is using electronic patient-reported outcome measures (ePROMs) — indicators used to assess a patient’s symptoms, their severity, and their effect on quality of life on a regular basis. The goal of using ePROMs is to preempt concerning symptoms before the patient needs more emergent and extended care. Research shows that leveraging ePROMs results in improved communication, clinical efficiency, symptom control, and survival for patients, as well as reduced emergency department attendance and hospitalization.

Notably, Memora uses ePROMs in its Oncology Care Programs. They allow patients to communicate early and often with their care teams about what affects them most in regard to their cancer and treatment, and they help clinicians zero in on specific symptoms and tailor care to the individual. In this way, they fit in perfectly with our mission to make healthcare more accessible, actionable, and always-on.

Healthtech can help us reinforce preventive care

Healthcare is often reactive. Emergency departments and urgent care centers across the country are filled with patients expressing concerns about new or worsening symptoms — anxious to determine the cause. While some patients arrive with unexpected issues from falling off a bike or a cold that developed a few days ago, many present symptoms that indicate something much more chronic and preventable — conditions more effectively managed through primary care or preventive measures. Though research suggests that preventable risk factors contribute to as many as 50% of deaths in the U.S., few individuals receive all preventive services for middle-aged adults recommended by the U.S. Preventive Services Task Force.

A pilot randomized controlled trial tested a decision tool developed to tell patients about life expectancies they might achieve by adhering to established preventive care. The study found that this individualized approach led to an improved understanding of primary prevention, and participating patients utilized more preventive services than control groups. The outcome of this study might seem predictable (more time spent on individualized care = a better understanding of an individual’s health). 

So why is this result so hard to achieve in practice? Time. A more recent study found that a primary care physician (PCP) would need over 24 hours a day to provide preventive, chronic disease, and acute care for their patients. Between these two articles, the importance of administering individualized, preventive care is clear. But PCPs would need an infeasible amount of time to do this for every patient. That’s why many of us are frustrated with the current design of healthcare infrastructure. And it’s where technology — including AI — will need to step in to intelligently augment the efforts of providers, allowing them to take the individualized approach without stretching themselves unreasonably thin. 

One of my favorite quotes from Desmond Tutu is a good reminder of the future we need to seek in healthcare: “There comes a point where we need to stop just pulling people out of the river. We need to go upstream and find out why they’re falling in.” It’s time to prioritize preventive care and go upstream.

Generative AI is promising in healthcare — but it comes with risks

Generative AI has been in the news a lot since ChatGPT made a splash in November 2022. There are myriad intriguing use cases being developed to leverage this new technology, from documenting patient visits to drafting patient portal message responses. And they’re just the beginning.

But this intelligent innovation poses a concerning risk. The large language models that form the foundation of most generative text systems have a tendency to hallucinate — creating output text that sounds plausible and confident, but may be completely made up.

A chatbot provided by a national helpline for people confronting eating disorders presents a cautionary tale of using generative AI for patient communication. Reporters found that the developer of the virtual assistant for the helpline switched its model to a generative AI system without telling their client. As a result, users started getting answers from the chatbot suggesting dieting and focusing on limiting caloric intake — fraught topics that require a more guarded set of responses than what this AI technology delivered.

What gets lost in the hype and rush to use AI systems is the real danger they can pose. Without understanding how these models and systems work — and knowing how to deploy techniques to mitigate the risks — people’s health and wellbeing are on the line. That’s why Memora’s approach to AI development weighs these potential hazards against the solutions we create — delivering a conversational experience to patients, safeguarded through responses from our evidence-based, client-validated clinical content library.

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