How to ensure social determinants of health actually improve health care

Given 80 percent of a person’s health is influenced by non-medical factors, it’s no surprise that both health care providers and health plans are looking for ways to better manage the broader set of social and economic conditions that impact health. Emblematic of the ongoing shift from volume to value, an increasing number of Medicaid-managed care contracts are requiring health plans to measure and address the social determinants of health (SDoH), with the ultimate goal of decreasing health disparities and increasing overall health. While moving in the right direction, the ability for health plans to implement evidence-based interventions to improve health equity is significantly hampered by a lack of provider Z code utilization. If you can’t measure it, you can’t manage it.

In 2016, diagnosis codes Z55-Z65 were introduced to the medical coding system to allow providers to report the presence of non-clinical factors that are known to influence health outcomes (such as employment, housing, food insecurity, etc.). When appropriately documented, these Z codes are an effective way for providers and health plans to coordinate care and to develop targeted community-based interventions. However, uptake has been slow due to administrative burden, a lack of standards, a lack of provider awareness, as well as providers being ill-equipped to address these needs.

Learning from Z code utilization

In October 2021, Centers for Medicare and Medicaid Services (CMS) released a report, which demonstrated that Z codes are largely unreported in Medicare fee-for-service claims. By 2019, homelessness was the most frequently used Z code, however Z codes were only documented on 0.11 percent of all claims.

We analyzed data through 2022 and found that the use of Z codes across commercially insured, Medicare Advantage and Medicaid populations continues to stall. Annually, the proportion of patients with a Z code ranges from 0.13 percent in 2017 to 0.15 percent in 2019 and 2020. In major metropolitan areas, the proportion of patients with a Z code is as low as 0.03 percent in Atlanta, Georgia to 0.17 percent in San Francisco, California.

Despite the current state of low adoption, federal and state policy efforts continue to double down on the importance of improving documentation and measurement of social factors, ranging from the Medicaid and CHIP Payment and Access Commission’s (MACPAC) latest recommendations to Congress, to Centers for Disease Control and Prevention’s (CDC) release of additional Z codes, which go into effect April 1, 2023. The exacerbation of health inequities on full display during the COVID-19 pandemic undoubtedly supports the rationale behind these policy initiatives and the continued focus on improved measurement. Even so, policymakers continue to overlook a critical point: Facilitating access does not guarantee adoption.

As we have seen many times before (including with COVID-19 telehealth expansion), policies that simply make something available, independent of how valuable that service or item is, do not necessarily translate to meaningful use or adoption. If utilization of Z Codes from 2017 to 2022 is only a tenth of a percent, what is to say that adding more codes will increase adoption of existing codes, let alone new codes? If the priority is to increase measurement, and therefore, deliver more targeted social care, then shouldn’t policy efforts be focused on overcoming existing barriers to use?

Driving Z code adoption

Well-intentioned policies like The American Rescue Plan Act of 2021 included efforts to address food and housing insecurity, such as developing a standard approach to measuring and collecting outcomes related to health equity. However, both federal and state policies related to this issue continue to miss the target — while providing a process in which to achieve the intended outcome, they do not change the mechanism that leads to the desired behavior, which is increased documentation. Illustrating this disconnect, researchers have found that even among the minority of providers that document social needs via clinical notes, an even smaller share of those providers are translating those notes into Z codes.

Numerous levers need to be pulled to meaningfully spur Z code adoption on a national level. The aforementioned CMS report from 2021 acknowledges the absence of financial incentives and providers’ perceived ability to address SDOH-related issues as being persistent barriers to greater adoption of Z coding in clinical practices.

Ultimately, screening for health-related social problems is fundamentally different from screening for medical problems, which raises the question: What policies are being implemented to provide training for both the screening and “treatment” of SDoH? The solution requires recognition of the fact that primary care providers are at the “front lines” of health care and are increasingly screening and treating patients for more specialized conditions, like depression. In a health economy where provider supply is already significantly constrained, policymakers must consider the evolving (and ever-increasing) responsibilities of providers and what that means for their capacity to take on additional social screening tasks.

Policymakers will need to calibrate their investment in expanding provider capacity (including social workers) to meet the demands of population-based screening and documentation. Ultimately, as the health care industry has seen with the adoption of other novel CMS measures, incentivizing the use of Z codes as a part of value-based care arrangements may be the best way to integrate them into a part of everyday practice.

In the meantime, if the goal is to connect patients quickly and efficiently to social care resources, policymakers and payers can focus on non-individual measures to predict individual needs. While not perfect, econometrics have demonstrated that Z codes are associated with a high Area Deprivation Index, and there is plenty of Zip Code-specific health care utilization, demographic and behavioral data already available to use. If analyzed appropriately, the need for Z codes could become less salient.

To make meaningful and lasting change in health equity, and, in turn, health outcomes, through improved coordination and connectivity between social and medical care, CMS should not merely create new diagnosis codes, but thoughtfully incentivize the behaviors required to create adoption.

Allison Oakes, Ph.D., is the director of research at healthcare analytics company Trilliant Health.

Sanjula Jain, Ph.D., is the senior vice president of market strategy and chief research officer at Trilliant Health.