Artificial IntelligenceData Science

Humanizing Uses of Data

Wider Inclusion of Social Determinants of Health

By Valmeek (Vick) Kudesia, VP Clinical Informatics and Advanced Analytics, Commonwealth Care Alliance®

“I’m a doctor and an engineer. I build things to take care of people.”

The first overnight of my medical internship was spent working in the medical intensive care unit (ICU). One of my patients, “John,” suffered an esophageal perforation—a serious side effect of cancer treatment. Soon after John’s arrival to the ICU, I called my attending physician to discuss the results of the many laboratory tests and procedures. He listened quietly as I interpreted the long list of data and then asked, “Vick, when do you think he will die? Would he want his family by his side? Would they want to be by his side?” At that moment, I had a sobering realization. My attending physician helped me understand that all the data pointed to a complete story about John—he would die on my watch, unable to advocate for himself, and my job was to keep him alive so that he could pass away (humanely) with his family by his side.

In healthcare, data could be the vehicle for decision-making and learning. Unfortunately, some of the increased use of data and electronic documentation in healthcare has also led to undesirable (or de-humanizing) outcomes (such as risk stratification algorithms that reinforce systemic racism by underestimating the medical needs of African Americans). To minimize these undesirable outcomes, data should proactively show clinicians the “whole story” associated with a person’s needs, particularly if that person is unable to ask for help or doesn’t know all the ways that help is needed.

In my current role at Commonwealth Care Alliance® (CCA) leading Clinical Informatics and Advanced Analytics, I have seen firsthand the power of data when these invisible factors are delivered directly to clinicians daily.

The COVID-19 pandemic brought greater emphasis to the “invisible factors” that impact health. These can include systemic racism, housing and food insecurities, loneliness, fear, inability to visit pharmacies or grocery stores, inability to visit clinics, closures of food pantries, closures of community services, changes in services or common areas in senior housing, and other relevant social determinants of health (SDOH). These factors are very important to a person’s whole story, but they are often invisible to both clinicians and patients. Broader use of data to capture and reveal the effects of these invisible factors is needed to humanize—instead of de-humanizing—data-informed processes in healthcare. This is specifically important in value-based care or other risk-bearing contracts where the whole story is critical to achieve high-quality care.

The recent rise of reverse extract transform load (ETL) data technologies will allow data and the latest analytical insights to more easily travel from an analytic environment to “everyday work software” and inform employees when that insight carries the most value (such as when speaking with a customer via phone or chat). Data and insights will play a broader and proactive role in employees’ daily experience—like an “ally” that delivers specific insights even if the employee doesn’t know what to ask.

Imagine what might happen if healthcare

1) broadened its use of data and analytics by describing interactions between SDoH factors and clinical outcomes and

2) proactively informed clinicians (at the point of care) of SDoH factors and outcome interactions specific to their patient.

Data would be a proactive therapeutic ally that unveiled a complete story of how to help a patient, even if neither clinician nor patient knew to ask. For example, a patient might have a higher risk of decompensated congestive heart failure than suggested by their level of heart function because they do not have reliable transportation to a grocery store to obtain healthier foods. This is an essential information to display to a clinician in an EHR at the point of care. Value-based or risk-bearing care arrangements are also likely to gain greater financial advantages from this complete and proactive information.

In my current role at Commonwealth Care Alliance® (CCA) leading Clinical Informatics and Advanced Analytics, I have seen firsthand the power of data when these invisible factors are delivered directly to clinicians daily. At CCA, every day during the COVID-19 pandemic resulted in a deeper appreciation for a patient’s whole story and how these invisible factors can impact health and quality of life. During COVID-19, CCA accelerated its use of technology to meet the new understanding of patients’ needs. For instance, to better meet the medical, behavioral, and social needs of our members—many of whom didn’t know how to ask for help—we launched medical and behavioral health virtual care visits, deployed smart-speakers in homes to help monitor patients remotely, and utilized proactive paramedic home visits with remote patient monitoring and predictive analytics to reduce the need for unplanned acute care. We also faced and overcame many obstacles related to data and system integration/interoperability, wireless/cellular broadband availability, and rapidly changing logistics (e.g., timed expiration of COVID-19 vaccine vials once opened).

Clinicians often work to “pull the right data” or “put in the right data” so that they can “do the right work.” In contrast, imagine a world in which, every day, the right clinicians, without asking, received the right data needed to fully care for every patient. Healthcare has an opportunity to use the same emerging technologies that maximize commerce but direct those technologies to maximize our understanding of every patient. Through this humanizing use of data, we create a therapeutic ally that unveils patients’ needs and differences in an actionable, humane way and reinforces person-centered care.

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