Human-Centered AI For Better Health Outcomes
Health care has come a long way and with the integration of technologies including artificial intelligence, machine learning¹ and natural language processing, clinicians derive insights from data with better outcomes. At the same time, the adoption of technology in healthcare has faced challenges with health care providers unable to harness the power of technology to address patient problems.
Human-centered design is one framework gaining traction in the health care world, with physicians using frameworks to understand patient problems and address them. The human-centered model has the interest of patients and enables collaboration and communication. Simply put, human-centered design² brings together all stakeholders including patients, clinicians and technology to offer seamless experiences across the board.
Problem-solving is the biggest hurdle facing health care today and this is where human-centered design steps in. From a human-centered design perspective, we go from purpose to means with electronic health records³ a good example. EHR systems are sometimes poorly designed from the user perspective where they unintentionally serve as a data repository for clinical information.
Healthcare organizations are often customers of health IT and have a different set of duties, goals, and stakeholders they must satisfy. Understanding your stakeholders is important if you want to improve the quality of care. Problems and pain points exist in all organizations, and the best place to start is by understanding the problems faced by clinicians and patients.
If we are to make strides with AI in healthcare⁴, these are the questions we should be focusing more on as an industry. Technology can save lives but it is an enabler, not a solution by itself. True innovation is born in the interplay between people and technology. This requires a thoroughly human-centric approach to AI.
The following are some approaches health organizations can use to adopt human-centered design in their organizations:
Burdened by clerical work and inefficient systems, clinicians now spend more time with machines and with reporting than directly with their patients. People with health trackers often do not know what to do with the numbers they are given. These examples serve as a reminder that as an industry, we should design solutions around people’s needs, not around what’s technologically possible.
Nurses want to focus their time and energy on patients. Patients with chronic diseases and healthy people alike want to be empowered in taking control of their own health. Only if we design for those needs, will people fully embrace AI-enabled solutions in their daily work and lives. This is a very fundamental notion, which is also deeply ingrained in competitive health organizations.
Any AI-enabled solution should be designed as a natural and helpful extension for people, like a car navigation system that supports you in finding the best route to your destination. AI will augment healthcare⁶ providers, patients, and healthy people alike.
