In theory, the widespread adoption of health information technology (HIT) and integrated applications can improve patients’ access to their health information and facilitate patient-centered care. In reality, this increased reliance on patient-facing technologies and data derived from connected devices, machine learning, and artificial intelligence can widen gaps in access, create new barriers to health equity, and generate biases that influence research and clinical decision-making that negatively impact the patient experience for those who have access and those who don’t.
According to a 2021 McKinsey & Company survey, telehealth was utilized for 13 percent to 17 percent of U.S. patient visits across all specialties, and according to research from Kaiser Permanente, there’s a low rate of in-person follow-up needed after a telehealth appointment, suggesting a long-term role for virtual care. Mass adoption of these technologies – ranging from appointment management, text messaging care providers, and yes, using your mobile phone to see your doctor face to face is expected to have a long-term role that supplements or replaces physical services altogether.
Equitable decision-making to reduce the risk of poor implementation and miscommunication can lead to new practices that increase access for patients willing to adopt these technologies and boost the quality and safety of these systems and data derived from them for all. Data and experience show significant challenges in patient engagement and research that can limit the effectiveness of programs that demonstrate an over-reliance on technological solutions.
Clinical and technical teams must be thoughtful in addressing the growing digital divide. With the adoption of these technologies, there will be a widening of gaps in access between those with limited or no access to high-speed internet, compatible devices, addressing mistrust, or simply sufficient digital literacy to benefit from these services compared to those that do. The technical teams designing software have a significant role in the patient experience in how these services are adopted. Ultimately more research is needed in how the user experience with technology can influence outcomes downstream.
There is a dire need for technical teams, including surveyors, researchers, and data scientists, to champion representation in the data. Designing processes to collect better data representative and faithful to the challenges and opportunities of different identities is more important than ever as technologists use this data to design software and guide the user experience. If those design decisions are made by flawed or biased data, then the tools developed may ultimately not be as effective, or worse, mask harm. Again, the technical teams – not patient care teams – have an outsized role here in designing equitable data collection and reporting practices.
Both technical and clinical teams must continue to invest in processes, not just stand-alone applications. Following the patient lifecycle – traditionally evaluated once the patient is at a physical location, should extend virtually. Understanding the patient’s journey from adopting a technology, their experience with the software, and ultimately interacting with the care team directly should be considered a continuous workflow, not siloed systems. The interaction between the technical designers, the front office staff, and physicians should encompass the entire experience across teams. And just as important, understanding why certain patients, or groups of patients, do not adopt a technology can lead to important advancements for health equity.
The health care industry is not historically known for being deep in technical innovation. But that is changing. Many organizations are exploring incorporating data analytics and related disciplines, such as machine learning and artificial intelligence, into clinical decision-making. Care teams are becoming increasingly technical, but the extent to which these roles influence patient outcomes remains unknown. By focusing on the gaps, both the clinical and technical teams can leverage their diverse skills to ensure equitable practices with the technology and extend those benefits to healthier patient populations and communities.
Juan Carlos Gonzalez, Jr. is a health equity researcher and advocate.
