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Enhancing Health Care Equity Through Analytics
Recent research highlights the potential for an analytics-based “decision framework” to improve health care equity by considering the socioeconomic and demographic characteristics of patients. This framework aims to enhance the management of chronic diseases, particularly diabetes, as discussed by Ujjal Kumar Mukherjee, a business administration professor at the University of Illinois Urbana-Champaign, who focuses on technology adoption in the health sector.
The study reveals that utilizing data to inform the scheduling of patient interactions with healthcare providers could reduce diabetes management risks by as much as 19.4%, particularly within underrepresented communities, according to Mukherjee.
“Chronic diseases like diabetes present significant challenges for healthcare institutions, as they demand a sustained resource investment and high patient engagement,” Mukherjee stated. “The varied demographics of patients can influence their health risks and, in turn, their treatment outcomes. A customized approach based on a patient’s demographic background can lead to enhanced health results.”
Mukherjee worked alongside Dilip Chhajed from Purdue University and Han Ye from Lehigh University on this study, which aims to refine diabetes care by crafting a predictive and prescriptive model that more effectively allocates health care encounters among socioeconomically and demographically diverse groups.
He further noted, “Many patients at high risk do not receive the necessary frequency of healthcare encounters, highlighting the importance of tailoring chronic care to improve treatment outcomes.” A disparity in resource allocation can result in inefficient and inequitable management of chronic illnesses.
“It’s widely recognized that health inequity persists in the U.S., often compounded by inadequate chronic care capacity,” Mukherjee explained. “Progressive diseases like diabetes, chronic obstructive pulmonary disease (COPD), cancer, and heart disease, if neglected, can escalate to more severe and costly stages.” He emphasized that proactively treating these conditions can lead to better cost management, asserting, “Chronic diseases cannot be cured; instead, the focus should be on managing their progression and associated risks.”
The researchers analyzed data from over 10,000 diabetes patients derived from a multifacility clinic across the U.S., complemented by socioeconomic and demographic information sourced from the U.S. census.
Employing machine learning techniques, the team investigated whether future diabetes risk for individual patients could be forecasted based on historical clinical data alongside socioeconomic factors such as income and education levels.
The analysis revealed significant disparities in healthcare access: individuals from low-income, less-educated, or predominantly minority backgrounds were notably less likely to engage in regular health care, despite exhibiting higher average glucose levels.
This finding accentuates the necessity for risk-aware decision-making frameworks to enhance clinical decisions, as Mukherjee pointed out. “Many diabetes patients come from underserved communities and rarely consult with healthcare professionals. They miss out on preventive and primary care services, often leading them to emergency departments due to complications, including heart attacks, kidney failures, and other diabetes-related health issues.”
When patients are forced to visit emergency rooms, they incur far greater costs in both time and financial resources than if their conditions had been managed earlier. “Regular interactions with healthcare providers can help prevent unnecessary emergency hospitalizations,” Mukherjee remarked, emphasizing that disadvantaged patients greatly stand to gain from a well-optimized healthcare allocation system.
The research underscores how health care providers can leverage analytics to ensure that scarce clinical resources, like appointment slots, are distributed in a fair and effective manner. Mukherjee concluded by stating, “This approach can lead to fairer access to chronic care and holds the potential to diminish health disparities at the population level.”
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