I used to shadow at Grady Memorial Hospital in downtown Atlanta. There was one patient in particular—who I’ll call Sam—I’ll never forget. Sam came into the ED with a gunshot wound and immediately went into surgery. As he was recovering and prepared for discharge, I saw his anxiety as the nurse walked him through a lengthy packet of instructions and medications he would need. He processed only a fraction of the information yet was seemingly hesitant to share that confusion.
Anyone who’s spent time delivering care has come across a patient like Sam—as you prepare them for discharge, you feel their hopelessness knowing they aren’t going to get the support they need. Our healthcare system isn’t equipped with the tools needed to support our sickest patients in their transition out of the hospital. And that exists for every clinician in every hospital in the United States.
These breakdowns in delivering care are illustrated by a widespread lack of collecting patient-reported outcomes (PROs)—information providers rely on to track and help patients after discharge. However, recent guidance from the Centers for Medicare and Medicaid Services (CMS) presents a critical opportunity for clinicians to accelerate PRO collection initiatives with the help of AI.
Starting in July 2024, mandatory reporting for inpatient total hip and knee arthroplasties begins, while voluntary reporting for outpatient procedures starts in 2025—potentially generating data collection on over 2 million procedures performed annually. This guidance could help create a blueprint for how longitudinal quality outcomes can be leveraged in the ongoing shift to value-based care.
Making this long-awaited change to data-driven, outcome-oriented and value-based care isn’t simple. It demands significant operational reforms that are known to strain care teams. It requires significantly better technology—and change management to ensure successful adoption. These challenges speak to a troubling truth in healthcare: the technology clinicians use to deliver care hasn’t kept up with the aggressive transformation of how it’s experienced and reimbursed. And we simply can’t rely on a healthcare system that has grown to over $4.5 trillion and 17% of the U.S. GDP.
Why is AI positioned to help clinicians collect PROs and shift to value? We’ve seen some of AI’s benefits play out with AI-enabled note-taking. This is just the tip of the iceberg. AI can capture questions, trigger care plan prompts, and automate data collection as well, reducing the friction between patients and care teams. It represents a first step towards transitioning the discourse between patients and care teams navigating the healthcare system to truly managing care.
Let's examine PRO collection. Gathering a broad set of text, numerical and image-based data is just step one. Care teams then need to rapidly assess the results and appropriately escalate while prioritizing which patients to address and when. Fitting this into a care team’s workflow in a way that saves them time and extracts the right signals from noise requires significant data and assessment to do at scale. For example, one comprehensive literature review identified a lack of time, knowledge and capacity to act upon PRO results as a key barrier to proper implementation.
With its ability to process ideas into actionable insights with relatively low oversight, AI is proving it could turn convoluted PRO processes into more effortless workflows. It can take time-consuming and manual data collection, automate it and use NLP to flexibly categorize results. But it doesn’t stop with automation and interpretation. Using AI for PRO collection can also benefit the patient experience. Some frustrations and inefficiencies emerge with the use of paper and pen for PROs—patients have to either take time to complete surveys at their appointments or mail them in. Electronic modes of delivering PRO instruments (known as ePROs) have streamlined the process by cutting down on manual paperwork and assisting with remote data collection.
However, ePROs alone have not addressed the delay between the patient journey and clinical intervention—a factor complicated by declining participation rates over time. For instance, a comprehensive study in Texas discovered ePRO compliance among oncology patients dropped from 72% to 52% over a 10-week period—with barriers including subpar follow-up notifications and insufficient discussions about ePRO use by clinicians with patients in person. AI’s ability to extend clinicians beyond the four walls and deliver high-touch care to close this gap solves this. Real-time engagement could identify when people drop off and deliver personalized outreach automatically. Trend analysis tools could help care teams detect complex trends from PRO data over time—enabling more thorough and personalized interventions. Intelligent technology is the vanguard of helping foster personalized experiences, empowering patients to self-manage their health and advancing value in healthcare.
Advancements in conversational AI can also reactively help patients by responding to emerging concerns reported through PRO collection. In this sense, AI can act as an extension of the care team, helping address PRO-reported issues upstream before they even need to be extracted and reviewed by the care team, saving doctors precious time they can instead spend on performing top-of-license care. Ultimately, finding scalable solutions for PRO collection is the path to the triple aim—unlocking population health and reducing costs while improving the patient experience and outcomes.
As quickly as AI has impacted care delivery, we’ve only scratched the surface. The vast data AI collects over time will have a multiplying effect at scale—launching a new era of data-driven healthcare in a way that is manageable for clinicians and makes our healthcare system respond at a pace that was previously unimaginable.
We will never get there, though, without taking the crucial step of transforming how we think of delivering care. Clinicians can not expect teams to meet mounting patient volumes, higher consumer expectations and robust PRO standards by using the same antiquated infrastructure. Leaders must seize on the opportunities for change now. The well-being of our communities and the solvency of our healthcare system depends on it. Doing what’s right for patients like Sam depends on it.
Manav Sevak is the co-founder and CEO of Memora Health, an intelligent care enablement platform. Recognized in Forbes 30 Under 30 2022 list and Business Insider's 30 Leaders Under 40 Changing Healthcare, Sevak and his co-founders founded Memora to make care more actionable, accessible and always-on