This year, artificial intelligence – the ability for machines to do what we normally only associate with human capabilities – monopolized many discussions. Al. Machine learning. ChatGPT. Dall-E2. All of these became household terms. And in healthcare, as in banking, education, logistics and many other pursuits, AI has been a hot topic – and widely employed – for a long time. What is the enabler underneath all of these pursuits? Data. Lots of it.
Electronic health records, real-time alerting, supply chain management and improved prescription management are all examples of how healthcare is using data to make decisions. Back in 2015, President Barack Obama announced the Precision Medicine Initiative during a State of the Union address. Precision health also fits within the broader concept of data-driven decision science. Obama’s 2016 budget included money to launch All of Us, a federal research effort to collect bio data from a million people in order to build one of the most diverse databases in history to facilitate precision medicine. UCI is the biggest enroller of All of Us participants in Southern California. In February 2022, UCI launched the Institute for Precision Health (IPH), an endeavor that has as much to do with data as it does health.
Why now? Progress in many areas – everything from biostatisticians pioneering extremely complex decision- science methodology to improvements in cloud storage and computing power – means the time has come. Furthermore, the newest form of AI, called deep-learning neural networks, has revolutionized the way machine-learning algorithms learn and think. Researchers believe new forms of AI oftentimes represent major improvements to human thinking.
Getting people’s biological blueprints – genetic sequencing, heritable modifications of DNA (epigenetics) and omics, which include sequence RNA and cellular building blocks determined by DNA and RNA (transcriptomics), proteins (proteomics), and profile metabolites (metabolomics) – into health records will be a huge precision health achievement. But the time has also come for an embrace of new kinds of data.
Patient-centered health services research has sometimes revealed a divide between what patients value and what clinicians value. And research has also concluded that personal experiences – sometimes having to do with systemic barriers like bias and discrimination – can alter, for example, a treatment’s impact or a patient’s perception of the value of care. This info is also data and the machinations and methodologies behind precision health aim to embrace all of it.
So now when data is being crunched by precision medicine processes, it might include clinical information (biomarkers, mortality, etc.), patient- reported impacts (e.g., function, mood, symptoms), treatment-related attributes (mode of administration, dose frequency, adverse events, etc.), use of resources (e.g., hospitalizations) and/or societal effects (ability to work, caregiver burden, productivity, etc.). Data, data everywhere – and yet we will likely also discover that we sometimes haven’t collected the right data and we need more or different data.
UCI’s IPH aims to be at the center of these discussions as the hub for data, cheerleader for precision health research and the advocate for patient-centered and -controlled use of information. Researchers believe that data may hold the key to some of healthcare’s most perplexing diseases, including Alzheimer’s, incurable cancers, rare genetic diseases and much more.
IPH comprises eight programs focused on three goals: redesigning health practice to improve care and decrease costs, deploying solutions to achieve health equity, and empowering effective health policy. While IPH represents a new data-centric era in healthcare, it’s reassuring to know that its success will be measured by traditional values: improved patient outcomes, cost- effectiveness and equity.
UCI is conducting a national search for a director for the Institute for Precision Health.
