Utilization of Social Determinants of Health ICD-10 Z-Codes Among Hospitalized Patients in the United States, 2016–2017

Abstract

Background: The inclusion of Z-codes for social determinants of health (SDOH) in the 10th revision of the International Classification of Diseases (ICD-10) may offer an opportunity to improve data collection of SDOH, but no characterization of their utilization exists on a national all-payer level. Objective: To examine the prevalence of SDOH Z-codes and compare characteristics of patients with and without Z-codes and hospitals that do and do not use Z-codes. Research Design: Retrospective cohort study using 2016 and 2017 National Inpatient Sample. Participants: Total of 14,289,644 inpatient hospitalizations. Measures: Prevalence of SDOH Z-codes (codes Z55–Z65) and descriptive statistics of patients and hospitals. Results: Of admissions, 269,929 (1.9%) included SDOH Z-codes. Average monthly SDOH Z-code use increased across the study period by 0.01% per month (P<0.001). The cumulative number and proportion of hospitals that had ever used an SDOH Z-code also increased, from 1895 hospitals (41%) in January 2016 to 3210 hospitals (70%) in December 2017. Hospitals that coded at least 1 SDOH Z-code were larger, private not-for-profit, and urban teaching hospitals. Compared with admissions without an SDOH Z-code, admissions with them were for patients who were younger, more often male, Medicaid recipients or uninsured. A higher proportion of admissions with SDOH Z-codes were for mental health (44.0% vs. 3.3%, P<0.001) and alcohol and substance use disorders (9.6% vs. 1.1%, P<0.001) compared with those without. Conclusions: The uptake of SDOH Z-codes has been slow, and current coding is likely poorly reflective of the actual burden of social needs experienced by hospitalized patients.

Sensitivity and Specificity of Real-World Social Factor Screening Approaches

“…Nevertheless, our findings add to the growing evidence that ICD-10 Z codes are significantly underutilized as a method of documenting diagnoses [13,[17][18][19]. In this sample, nearly 15% of patients had at least one ICD-10 Z code, whereas other studies have reported the prevalence of ICD-10 Z codes at around 2% [17,39]. Even in this instance of more common usage, ICD-10 Z codes still underestimated the prevalence of social risk factors and are limited in their potential to effectively infer the presence of a social factor for a patient.…”

“…As identification of patients' social factors is critical to organizational operations, population health, and current health policy, current The introduction of ICD-10 Z codes for social risks factors has been an exciting development for those interested in population health and an important step towards potential reimbursement for health care organizations [38]. Nevertheless, our findings add to the growing evidence that ICD-10 Z codes are significantly underutilized as a method of documenting diagnoses [13,[17][18][19]. In this sample, nearly 15% of patients had at least one ICD-10 Z code, whereas other studies have reported the prevalence of ICD-10 Z codes at around 2% [17,39].…”

“…For one, evidence suggests both ICD-10 Z codes and screening questions, even when integrated in the EHR, face limited adoption. The little available evidence on ICD-10 Z codes and earlier incarnations of non-medical diagnosis codes indicates substantial underusage and potentially biased usage [17][18][19]. Research and demonstration projects have successfully implemented screening questions in practice [3,9,15], but overall uptake remains low and inconsistent [20].…”

A qualitative assessment of barriers and facilitators associated with addressing social determinants of health among members of a health collaborative in the rural Midwest

“…Beginning in 2015, with the expansion of disease codes under the 10th revision of International Classification of Diseases, providers can code for SDOH with Z-codes. Expanding codes to include SDOH is an opportunity to document the extent of specific SDOH needs within the health care system; however, they are underutilized [ 8 ]. States have also incentivized collaborations between communities and HCOs, including several that specifically help rural communities advance population health [ 9 ].…”

Moving Beyond Simple Risk Prediction: Segmenting Patient Populations Using Consumer Data

“…One drawback of reliance on insurance claims data and EHRs is that they miss social and behavioral factors that complicate care (21). Although, there is a subset of ICD-10-CM codes, the Z codes, for documenting SDOH in EHRs, these codes are underutilized (22,23). As such, SDOH Z codes may not reflect the actual burden of social needs experienced by patients.…”