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As health systems increasingly rely on digital tools, a new challenge emerges: ensuring these technologies are not only engaging but also tolerable for patients, especially those with complex conditions.
In the rush to digitize healthcare, we’ve been asking the wrong questions. For years, health systems have focused on whether patients will engage with digital care-will they activate the portal, respond to reminders, or join virtual visits? These are important queries, but they no longer suffice. The next critical issue in digital health is tolerability: Can patients actually use these tools without overwhelming cognitive strain, sensory overload, or practical fatigue?
Tolerability goes beyond a subjective experience; it’s a measurable clinical parameter that reflects a patient’s ability to sustain an intervention without prohibitive burden. This burden can be quantified using validated psychometric instruments like the NASA Task Load Index (NASA-TLX) for mental demand and the User Burden Scale (UBS) for multidimensional costs of digital participation.
The importance of tolerability becomes especially evident in recovery and survivorship care, where patients are often expected to manage complex information at a time when their cognitive abilities may be at their weakest. For instance, the National Cancer Institute notes that cancer survivors frequently report symptoms of cognitive impairment, including memory problems, reduced concentration, slower information processing, and diminished executive function. These issues can significantly impact daily life and work performance.
The American Cancer Society estimates that 18.6 million people in the United States were living with a history of cancer as of January 1, 2025, and projects this number to exceed 22 million by 2035. If health systems continue to layer portals, symptom trackers, remote monitoring tools, AI navigation, and digital follow-ups onto these patients, they need to ask more than whether the tool was offered. They must consider whether patients can actually use these tools effectively while coping with fatigue, stress, disrupted sleep, and reduced mental stamina.

A recent patient-driven scoping review in JMIR Cancer underscores this issue. The study found that digital health portals for people living with cancer often fail to account for the cognitive and emotional challenges these individuals face. This oversight can lead to tools that are technically advanced but practically overwhelming, ultimately undermining their intended benefits.
To address the tolerability gap, healthcare providers and technology developers must adopt a more patient-centered approach. Danny Lee, MD, from a leading health system, emphasizes the importance of engaging patients through tools that support their care journey while improving care delivery. This means designing digital health solutions with a deep understanding of the patient’s context, needs, and limitations.
A care-centered approach for responsible design and use of AI is crucial. As health systems face rising demand for palliative care and an increasing emphasis on digital health innovation, technologies must be developed to enhance, not complicate, patient care. This involves integrating user feedback into the development process, conducting thorough usability testing, and continuously monitoring the impact of these tools on patients’ well-being.
Ultimately, the success of digital health initiatives hinges on their ability to balance engagement with tolerability. By focusing on both, we can ensure that these technologies not only reach but also truly serve those who need them most.
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Original Sources
Digital Health Keeps Measuring Engagement While Ignoring Tolerability - MedCity News
↗ https://medcitynews.com/2026/05/digital-health-keeps-measuring-engagement-while-ignoring-tolerability
About the author
Amara's entry point into AI was an epidemiology role at a London research hospital, where she spent five years studying how digital health tools reached — or conspicuously failed to reach — underserved communities. Watching early algorithmic systems in healthcare quietly entrench existing inequalities, she redirected her career toward the systemic consequences of AI at scale. She covers AI through an unflinching lens: who benefits, who bears the cost, and what evidence actually says versus what the press release claims. Her writing is calm and precise, but she doesn't mistake balance for neutrality.
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3 June 2026
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