The Equity Equation: Why What's Measured Matters in Healthcare
"Unveiling the Hidden Factors Influencing Health Technology Decisions and How We Can Ensure Fairness for All."
In the realm of healthcare, decisions about funding new technologies are often driven by quantitative evidence. Policy makers meticulously examine comparative effectiveness, cost-effectiveness, and budget impact— what we broadly term "efficiency" criteria. These metrics provide a seemingly objective basis for allocating resources, ensuring the greatest return on investment.
However, a critical dimension often receives less attention: equity. How do these decisions impact different population groups? Who benefits, and who bears the burden? Are those who gain already better off in terms of health compared to the rest of the population? These "equity" criteria, while ethically crucial, are often harder to quantify, leading to their marginalization in the decision-making process.
Two recent studies highlighted this imbalance, suggesting that the over-reliance on measurable efficiency metrics may inadvertently perpetuate inequities in healthcare access and outcomes. These studies underscore the adage that “what gets measured, gets done,” prompting a crucial discussion about how to better integrate equity considerations into health technology assessment (HTA).
Expanding Health Inequality Data
On March 3, 2026, WHO released an updated Health Inequality Data Repository (HIDR) and Health Equity Assessment Toolkit through its Health Inequality Monitor. WHO describes HIDR as the largest public repository of health inequality data, now containing more than 13 million data points from publicly available sources. The CDC also provides state and national indicators on topics including obesity, breastfeeding, physical activity, sugary drinks, and television viewing, with options to examine results by race, ethnicity, and other demographics.
The Quantifiable vs. The Qualitative: A Dangerous Divide?
Globally, healthcare decision-makers face the challenge of balancing limited resources with the ever-increasing demand for new technologies. The allure of quantitative data is undeniable. Metrics like cost-effectiveness provide a seemingly straightforward way to compare options and maximize health benefits for the population as a whole.
- Efficiency: Focuses on maximizing the overall health benefit from available resources.
- Equity: Aims to ensure fair distribution of healthcare resources and outcomes across different population groups.
From Measurement to Equity
Recent research is examining how health inequalities can be measured across populations and incorporated into healthcare decisions. A clinical practice research datalink study estimated diagnosed Alzheimer disease prevalence in England across deprivation groups, reporting prevalence per 100,000 people with corresponding 95% confidence intervals. In Canada, three experiments assessed preferences for reducing income-related health inequality versus improving overall population health, including comparisons involving universal and tailored vaccination, nonspecific prevention, and generic healthcare programs.
What Measurement Misses
Critiques of health technology assessment warn that important equity outcomes can be marginalised when assessment processes do not measure them. One analysis suggested that, if its findings are confirmed by future research, they could influence policymakers to reshape HTA processes in Israel and elsewhere. More recent work on usability evaluations uses failure modes and effects analysis to identify potential equity risks in heuristic evaluations and usability testing, while a proposed collaborative framework would standardise equity domains and dataset guidance in medicines assessment.
Efficiency and Equity in HTA
Comparative research finds that healthcare economic evaluation has traditionally focused on maximising health, treating health gains as equally valuable regardless of who receives them. This efficiency-oriented approach has significant implications for health systems addressing persistent and growing health inequities. Reviews of health technology assessment agencies describe their influential role in evaluating technologies and informing policies that affect healthcare access and resource allocation, while noting that traditional frameworks may inadequately incorporate equity considerations.
Moving Towards a More Equitable Future
The path forward involves a fundamental shift in how we approach health technology assessment. We must prioritize the development and application of methods that can quantify equity outcomes alongside traditional efficiency metrics. Distributional Cost-Effectiveness Analysis (DCEA) and approaches that measure and value severity of illness offer promising avenues for integrating equity into decision-making frameworks. By embracing these tools, we can ensure that healthcare decisions reflect our values and promote a fairer, more just healthcare system for all.
Quantifying Equity’s Complexity
A 2024 discussion of health technology assessment as a tool for advancing equity in universal health coverage identifies equity and ethical issues as challenges in the use of technology in health systems. It also highlights the difficulty of quantitatively assessing attributes such as equity. The issue shows why assessment methods must address not only measurable health outcomes but also ethical and distributional concerns.
Equity in Algorithms and Practice
Artificial intelligence has repeatedly been shown to encode historical inequities in healthcare, according to a study published in eClinicalMedicine. The researchers aimed to develop a framework for quantitatively assessing the performance equity of health AI technologies and to demonstrate its utility through a case study. Separately, HealthEquityGuide.org presents local health department case studies describing the factors that enabled health equity work, the actions departments took, resulting impacts, and advice for replication.