atient wellbeing has an often overlooked connection to data—the accuracy of which depends on how the data is collected, analyzed, and aggregated for use. As digital innovations become increasingly important to today’s world of biotechnology, medical research, and development, we need to accelerate equitable design and implementation of digital innovations in patient care to improve health and wellness. Primary care providers are well placed to gather health data—for use both by providers and medical researchers—from patients during patient–provider interactions, using equitable and inclusive practices. In order to support wellbeing, clinical decision-making, and research and development, the quality and accuracy of health data collection cannot be overlooked.
This is important because digital innovation often lacks the patient’s perspective—the viewpoint of the individual striving for better health and wellbeing. If a digital health wearable device is not developed using inclusive and equitable design approaches, data bias may result. For example, wearable devices like pulse oximeters have displayed inaccurate readings on individuals with darker skin tones. Digital innovations have potential to enhance data–driven approaches to generate evidence for better understanding of genetic, chronic, and acute health conditions—making it paramount we ensure these innovations eliminate unintended biases. Challenges arise when technological advancement exacerbates discrepancies or introduces biases that hinder the collection of representative health data.
Digital health data management platforms are emerging innovations developed through public–private partnerships between health systems and industry. Such unconventional collaborations have shown promise in facilitating novel data collection methods for AI algorithms. According to Mayo Clinic and Google Cloud, investing in these partnerships improves health data analysis and aggregation when implemented across healthcare systems.
Building trust in the use of health data requires the active engagement of patient communities to ensure they benefit from access and improve decision-making and wellbeing. Stakeholder engagement—applied across diverse groups—can be effective in achieving these goals. As a learned society of experts, we must catalyze a future that enhances overall health and well-being for generations to come.
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Primary–care providers key to inclusive wellbeing in the digital age
Photo by Eben Kassaye on Unsplash
June 17, 2025
Digital innovation in the wellbeing space often lacks the patient’s perspective, which can lead to data bias. Primary–care providers should be on the front line of gathering good information during patient–provider interactions for an inclusive future of digital health, writes Yasmeen Long.
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atient wellbeing has an often overlooked connection to data—the accuracy of which depends on how the data is collected, analyzed, and aggregated for use. As digital innovations become increasingly important to today’s world of biotechnology, medical research, and development, we need to accelerate equitable design and implementation of digital innovations in patient care to improve health and wellness. Primary care providers are well placed to gather health data—for use both by providers and medical researchers—from patients during patient–provider interactions, using equitable and inclusive practices. In order to support wellbeing, clinical decision-making, and research and development, the quality and accuracy of health data collection cannot be overlooked.
This is important because digital innovation often lacks the patient’s perspective—the viewpoint of the individual striving for better health and wellbeing. If a digital health wearable device is not developed using inclusive and equitable design approaches, data bias may result. For example, wearable devices like pulse oximeters have displayed inaccurate readings on individuals with darker skin tones. Digital innovations have potential to enhance data–driven approaches to generate evidence for better understanding of genetic, chronic, and acute health conditions—making it paramount we ensure these innovations eliminate unintended biases. Challenges arise when technological advancement exacerbates discrepancies or introduces biases that hinder the collection of representative health data.
Digital health data management platforms are emerging innovations developed through public–private partnerships between health systems and industry. Such unconventional collaborations have shown promise in facilitating novel data collection methods for AI algorithms. According to Mayo Clinic and Google Cloud, investing in these partnerships improves health data analysis and aggregation when implemented across healthcare systems.
Building trust in the use of health data requires the active engagement of patient communities to ensure they benefit from access and improve decision-making and wellbeing. Stakeholder engagement—applied across diverse groups—can be effective in achieving these goals. As a learned society of experts, we must catalyze a future that enhances overall health and well-being for generations to come.
