The award recognized the AI solution that IQVIA has built to identify patient-level social determinants of health from unstructured medical records.
IQVIA is delighted to announce that we have been awarded the "Best AI Solution for Healthcare” at the 2023 AI Breakthrough Awards. This award acknowledges companies that have demonstrated exceptional innovation, leadership and—importantly—impactful solutions. With so much buzz around AI and is practical application in health care at the minute–we are delighted that our solution has been recognized for the impact it is making to patients.
The award recognized the AI solution that IQVIA has built to identify patient-level social determinants of health from unstructured medical records.
The challenge
It is well established that health outcomes are impacted significantly by factors outside of the four walls of a health system, and beyond the genetic predispositions to disease that we all have. A growing body of evidence points toward various factors such as our living environment, work conditions, and level of education, playing a crucial role in shaping health outcomes. These social risk factors are better known as social determinants of health (SDoH). Despite the known importance of these features in predicting outcomes, they are very poorly represented in structured clinical data, limiting the ability of health care organizations to action them.
The solution
IQVIA's innovative AI solution unlocks a groundbreaking way to tackle SDoH challenges in health care organizations by prioritizing review of at-risk patients by their social risk factors. In a recent partnership at NorthShore–Edward-Elmhurst Health led to the deployment of IQVIA’s NLP solution with the health system’s emergency department, where it is being used to identify patients with SDoH documented in their medical records (such as transportation issues, social isolation, or history of abuse). The technology then enables social care workers to more accurately triage and manage these patients based on the NLP findings. Since deploying this new AI-enabled workflow, clinicians at Northshore are now screening 56 percent more at-risk patients based on SDoH factors than previous best practice, allowing social workers to proactively intervene and helping EDs to focus their efforts more effectively.
In a recently presented case study, the clinicians from Northshore described a real-life example of the impact of this workflow. A patient presented to the ED with a headache, and the AI solution was able to “read” the clinical notes from past health care interactions and flag that this patient had previously spoken about being a victim of abuse. Immediately, this AI output was sent to a care provider who was able to explore the topic further with the patient and refer her to counseling and legal assistance.
Given the vital importance of transparency and trust in health care AI solutions, IQVIA's approach involved a two-phase validation process. In the first phase, research coordinators reviewed patient data to assess the tool's accuracy and potential biases. The second phase involved prospective validation, with ED social workers collaborating with the AI model to verify its insights through patient interactions. This is a perfect example of how responsible AI is not intended to replace clinicians, but to support them.
The use of this technology can have a profound impact in not only patient care, but also quality reporting. With new mandates coming in to force around SDoH screening and reporting, NLP provides a way for organizations to demonstrate where proper social screening is taking place, but just has not been structured, and through the NLP–enable this data to be captured and fed back into the EMR.
The partnership with NorthShore–Edward-Elmhurst Health exemplifies how data-driven innovation can lead to tangible improvements in patient outcomes and experiences. As AI continues to shape the health care landscape, collaborations like this will pave the way for a more efficient, patient-centered approach to addressing complex health care challenges where solutions have eluded us to date.