Health Equity and Antibiotic Prescribing in the United States: A Systematic Scoping Review

Abstract

We performed a scoping review of articles published from 1 January 2000 to 4 January 2022 to characterize inequities in antibiotic prescribing and use across healthcare settings in the United States to inform antibiotic stewardship interventions and research. We included 34 observational studies, 21 cross-sectional survey studies, 4 intervention studies, and 2 systematic reviews. Most studies (55 of 61 [90%]) described the outpatient setting, 3 articles were from dentistry, 2 were from long-term care, and 1 was from acute care. Differences in antibiotic prescribing were found by patient's race and ethnicity, sex, age, socioeconomic factors, geography, clinician's age and specialty, and healthcare setting, with an emphasis on outpatient settings. Few studies assessed stewardship interventions. Clinicians, antibiotic stewardship experts, and health systems should be aware that prescribing behavior varies according to both clinician- and patient-level markers. Prescribing differences likely represent structural inequities; however, no studies reported underlying drivers of inequities in antibiotic prescribing.

antibiotic prescribing, antibiotic stewardship, health disparities, health equity

Antibiotics are among the most commonly prescribed medications in the United States (US) [1, 2]. Providing equitable healthcare is one of the National Academy of Medicine's (formerly the Institute of Medicine [IOM]) 6 domains of healthcare quality, and advancing health equity is a public health priority [3]. Consistent with the IOM, the Centers for Disease Control and Prevention (CDC) [4] is committed to integrating health equity efforts, including improvement of health equity science, across the agency [5]. Disparities in disease prevalence and diagnosis, access to care, and healthcare quality have been documented related to patients’ race and ethnicity, income, insurance status, and location of residence [6]. However, there are limited studies exploring characteristics of populations experiencing antibiotic-related inequities (markers) and the factors that cause or perpetuate the inequity (drivers) to ensure equitable access to high-quality medicines (pharmacoequity) (Table 1). Inequities in overprescribing may impact health outcomes, resulting in more antibiotic resistance or antibiotic-associated adverse events in some populations. The potential for undertreatment of infections is also a concern that could disproportionately affect certain populations and lead to poor outcomes.

Table 1.

Definitions of Health Equity Terms

Term	Definition
Health equity	The state in which everyone has a fair and just opportunity to attain their highest level of health. Achieving health equity requires focused and ongoing societal efforts to address historical and contemporary injustices; overcome economic, social, and other obstacles to health and healthcare; and eliminate preventable health disparities.a
Health disparity	Preventable differences in the burden of disease, injury, violence, or opportunities to achieve optimal health that are experienced by populations that have been socially, economically, geographically, and environmentally disadvantaged.a
Health inequity	Particular types of health disparities that stem from unfair and unjust systems, policies, and practices and limit access to the opportunities and resources needed to live the healthiest life possible.a
Pharmacoequity	A health equity goal that ensures that “individuals, regardless of race, ethnicity, and socioeconomic status, have access to the highest-quality medications required to manage their health needs” (Essien et al, 2021b).
Markers of health inequity	Characteristics of subpopulations experiencing a health inequity. Examples are race, ethnicity, and nationality.a
Drivers of health inequity	Factors that create, perpetuate, or exacerbate a health inequity. Examples are racism and other systems of oppression and discrimination, residential segregation, inequity in income, and inequity in health insurance coverage.a

a

Centers for Disease Control and Prevention. What is health equity? 2022. Available at: https://www.cdc.gov/healthequity/whatis/index.html. Accessed 8 December 2022.

b

Essien UR, Dusetzina SB, Gellad WF. A policy prescription for reducing health disparities—achieving pharmacoequity. JAMA 2021; 326:1793–4.

Achieving health equity requires focused and ongoing societal efforts to address historical and contemporary injustices; overcome economic, social, and other obstacles to health and healthcare; and eliminate preventable health disparities. We conducted a scoping review of published literature with 2 objectives: (1) characterize inequities or types of disparities that contribute to inequities in antibiotic prescribing and use across US healthcare settings, and (2) assess gaps in knowledge to identify research priorities to improve healthcare quality.

METHODS

Scope of Review

We conducted a scoping exercise to assess the landscape of published literature including heterogeneous studies by healthcare setting, populations, and study designs as well as to identify gaps in knowledge [7]. We followed the scoping review methodology and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for scoping review reporting [7–9]. The primary review question was: What is the scope of the published literature on health equity markers and drivers in antibiotic prescribing, use, and stewardship in the US? Table 1 includes definitions of health equity terms used throughout this study.

Eligibility Criteria, Search Strategy, and Source Selection

Eligible studies were written in English, geographically focused on the US, and evaluated antibiotic prescribing, use, or stewardship (aiming to improve prescribing) and included information about at least 1 marker of inequity and its relationship to antibiotic prescribing. Potential markers were identified from social determinants of health literature and expert knowledge and included age, race, ethnicity, income, education, social vulnerability [4], geography, rurality, homelessness, immigrant status, gender identity, sexual orientation, substance use, or chronic health conditions/comorbid conditions. We included peer-reviewed systematic reviews, randomized controlled trials, and observational studies. We included studies using multivariate models, trend analyses, or spatial analyses including at least 1 marker of inequity and excluded studies using only descriptive statistics without controlling for other possible confounding factors. We did not exclude qualitative or mixed-methods studies. We excluded guidelines, professional society position statements, study protocol descriptions, stewardship implementation methods, and professional education literature focused on delivery of education to healthcare providers. We also excluded studies focused on animal use or environmental sampling and articles describing antimicrobial susceptibility.

A comprehensive search strategy was employed in collaboration with the CDC library that included Medline, Embase, and Scopus databases for publications from 1 January 2000 to 4 January 2022. Search criteria included titles, abstracts, and keywords of original research articles published based on our eligibility criteria. Health equity search terms were selected based on “MEDLINE/PubMed Health Disparities and Minority Health Search Strategy,” available on the National Library of Medicine's website (search terms are shown in Supplementary Table 1) [10]. We applied a “backward snowballing” technique with systematic reviews identified through the initial search by reviewing references and including relevant articles [11]. We also solicited input from known experts (n = 2) in this field for relevant articles.

Two researchers iteratively reviewed (C. K. and W. C. D.) relevant titles, abstracts, and eligible full texts from the search results. The first reviewer initially screened the titles and abstracts for relevance to antibiotic prescribing, use, or stewardship, and then screened for markers of inequity. The second reviewer conducted a confirmatory review of included full texts against eligibility criteria. Disagreements were resolved on study selection by consensus and discussion between the 2 reviewers.

Framework of Factors Contributing to Inequities in Antibiotic Prescribing in the US

Based on the reviewed literature, we developed a nested capsule framework of factors contributing to health inequities in antibiotic prescribing in the US (Figure 1). Building on the socioecological model, the framework shows individual-, healthcare-, community-, and national-level factors potentially related to antibiotic prescribing inequities [12]. We used this framework to guide our search strategy and synthesis of the literature.

Figure 1.

Factors contributing to inequities in antibiotic prescribing in the United States.

Examples of individual factors that may be indicators of inequities include patient and caregiver markers such as age, race and ethnicity, sex, language, or health literacy. Clinician markers may include specialty and years of experience. Clinical interactions are influenced by patient expectations, clinician implicit bias, communication barriers, and cultural and power dynamics. Healthcare factors such as the type of clinical setting, healthcare access, workforce diversity, and healthcare quality including guideline-concordant care or availability of antibiotic stewardship expertise were another category. Community factors include factors like geography, availability of nonclinical resources, and health information sources. Although some factors, such as cultural norms and beliefs, can be considered individual factors, they can influence health behaviors of different groups of people and were included in community factors [13]. Finally, national factors include policies that combat antibiotic resistance, diversify the clinical and public health workforce, or affect access to health insurance. The historical and contemporaneous context of discriminatory treatment of people based on their race, ethnicity, sex, gender identity, age, or sexual orientation, which has negative health consequences, is also included under national factors [14–16].

Data Synthesis

Data on study design, methods, population, healthcare setting, key findings on equity markers and drivers, intersectionality of markers, and year of publication were charted using a standardized Microsoft Excel spreadsheet by the 2 reviewers. The table of extracted variables is shown in Supplementary Table 2. Results were synthesized by our framework categories both quantitatively (eg, enumeration of key concepts) and qualitatively (eg, summary of characteristics and themes).

RESULTS

Selection and Characteristics of Sources

After removing 388 duplicates, we screened 870 titles and abstracts; 431 studies were excluded that did not include antibiotic prescribing or use, leaving 439 studies for full text review. Of these, 61 were selected for inclusion (Supplementary Figure 1). Study designs included 34 observational studies, 21 cross-sectional survey studies, 4 intervention studies, and 2 systematic reviews. No qualitative or mixed-methods studies were identified. Data sources included Medicaid/Medicare, commercial claims, electronic health records, surveillance, and survey data, mainly from the National Ambulatory Medical Care Survey and/or the National Hospital Ambulatory Medical Care Survey.

Most studies (55 of 61 [90%]) described the outpatient setting, 3 articles were from dentistry, 2 were from long-term care, and 1 was from acute care. The most common outcome assessed in the studies was antibiotic use or prescribing (83%) followed by inappropriate prescribing or guideline-concordant treatment (10%). Only 4 studies assessed antibiotic prescribing related to stewardship programs. The most common conditions reported were respiratory tract infections (n = 22; acute respiratory tract infections including upper respiratory tract infections and acute otitis media), skin and soft tissue infections (n = 5), and urinary tract infections (n = 3). Since 2000, the number of studies published on antibiotic prescribing has steadily increased along with studies with a specific equity objective (n = 14/61 [23%]) or studies assessing general patient or clinician characteristics with antibiotic prescribing or use (any equity inclusion; n = 29/61 [48%]) (Figure 2). Almost half (n = 20/43 [47%]) of the studies with an equity focus or any equity inclusion were published between 2018 and 2021, with 65% of those studies published in 2020 and 2021.

Figure 2.

Number of studies with a health equity and antibiotic prescribing focus by publication year. Any equity inclusion is defined as articles with the aim of assessing general patient and/or provider characteristics associated with any of the target outcomes (eg, antibiotic prescribing, inappropriate prescribing, stewardship) without an explicit equity-focused objective, but identifying equity-related results.

Individual Factors

Individual patient factors associated with antibiotic prescribing included race and ethnicity, age, sex, socioeconomic status, insurance status, comorbid conditions, and education (Table 2). While there was variability in prescribing across studies and in how race and ethnicity were defined, in general, people of racial or ethnic minority groups were less likely to be diagnosed with a condition warranting antibiotics (guideline concordant), less likely to receive antibiotics overall, and less likely to receive broad-spectrum antibiotics. Fleming-Dutra et al found that diagnosis of otitis media was 30% lower among Black children compared with children of other races or ethnicities, despite similar rates of otitis media visits between the 2 groups, and Black children were 41% less likely to receive a broad-spectrum antibiotic when diagnosed [17]. Similarly, Gerber et al found that Black children were 21%–40% less likely to be diagnosed with an acute respiratory tract infection, 25% less likely to receive an antibiotic, and 12% less likely to receive a broad-spectrum antibiotic from the same clinician compared to other children [18]. Kornblith et al also found that Black children were 28% less likely to receive antibiotics when they were indicated for acute respiratory tract infections [19]. Among hospitalized adults, Wurcel et al found that Black patients were less likely to receive first-line treatment for skin and soft tissue infections compared to White patients [20]. There were fewer studies overall that assessed inappropriate prescribing and guideline-concordant treatment by race and ethnicity (Supplementary Table 3). Four studies showed that inappropriate prescribing was more common among Black patients [21–24], while 1 study showed more guideline-concordant treatment prescribed [25]. Wattles et al [22] found that despite higher rates of antibiotic prescribing to White children, inappropriate prescribing was more common among Black children, but Gerber et al [18] found higher prescribing rates of broad-spectrum antibiotics to White children, possibly reflective of inappropriate prescribing.

Table 2.

Studies Showing Increased, Decreased, or No Associations With Markers Contributing to Health Inequities and Antibiotic Prescribing

Factors and Equity Markers	Articles With Increased Association With Antibiotic Prescribing (No.)	Articles With Decreased Association With Antibiotic Prescribing (No.)	Articles With No Association (No.)	Total, No.
Community
Geography
Region	Southern (11) Northeast (2) Midwest (1)	Western (1) Northeast (1)	Region (2)	18
Rurality	Rural (8) Suburb (2)	…	Rurality (3)	13
County characteristics	% poverty (5) % females (3) % White (2) % with obesity (2) % aged ≤2 y (1) % aged <65 y (1) % aged >65 y (1)	…	…	15
Healthcare
Setting
Clinical setting	ED (3) Public clinic (1)	ED (3) Hospital outpatient (1)	Setting (1)	9
Access
Clinician density	Prescribers per capita (2)	…	…	2
Quality
Wait time	>2 h (1)	…	…	1
Individual
Patient
Race and ethnicity	White (5) Black (1) Hispanic (1)	Black (8) Hispanic (3) Racial and ethnic minorities (2) Asian (2)	Race (6)	28
Age	<2 y (3) <6 y (3) ≥5 y (1) 2–5 y (1) <18 y (1) ≥65 y (1)	1–3 y, >6 y (1) 5–14 y (1) <18 y (1)	Age (9)	22
Sex	Female (5) Male (2)	Female (1)	Sex (9)	17
Income	Low income (1) High income (1)	…	…	1
Insurance status	Private (5) Self-pay/uninsured (2)	Self-pay/uninsured (4) Medicaid (3) Public and other (3) Private (1)	Insurance (6)	25
Comorbid conditions	Presence (7)	…	Heart failure (1) Comorbid conditions (1)	9
Education	<High school (2) High school degree (1)	…	…	3
Clinician
Age	Advanced age (1) Born in 1960s (1) Older age (51–60 y) (1)	Born in 1980s (1)	…	4
Sex	Male (1)	…	…	1
Years of experience	>20 y (1)	<10 y (1)	Experience (1)	3
Specialty	NP/PA (4) General/family medicine (2) Non–internal medicine (1) Dentists (1) Emergency medicine (1) Primary care (1)	Pediatrician (3) ENT/surgery (1) Internal medicine (1)	Specialty (3)	18

Abbreviations: ED, emergency department; ENT, ear, nose, and throat; NP, nurse practitioner, PA, physician assistant.

Articles varied in specific populations studied by age: 25 (41%) articles focused on children and adolescents, 19 (31%) articles focused on adults (including 5 only on older adults and 2 only on adult women), and 17 (28%) articles on patients of all ages. Studies assessing age were also highly variable in their definitions of age groups, making comparisons across studies challenging. Younger children (aged <5 years) or older adults (aged ≥65 years) were generally more likely to receive antibiotics than their older-aged children or younger-aged adult comparison groups, respectively. Wattles et al found that children aged ≤2 years receiving Medicaid in Kentucky were more likely to receive an inappropriate antibiotic prescription than those aged 10–19 years (adjusted odds ratio, 1.39 [95% confidence interval, 1.37–1.41]) [22]. A study of women with uncomplicated urinary tract infection in the outpatient setting by Langner et al found that women aged ≥45 years were 3 times more likely to be given non-guideline-concordant care (overuse of fluoroquinolones and the underuse of first-line antibiotic agents) compared to younger women aged 18–44 years [25]. In a dental study, Suda et al found that while adults aged ≥65 years were more likely to be prescribed antibiotic prophylaxis, they were more likely to receive appropriate therapy compared with those aged 18–34 years [26].

Some studies showed that women were more likely than men to receive antibiotics, broad-spectrum antibiotics [27–31], and inappropriate treatment [26]. It is unclear whether these differences were clinically warranted, and many studies showed no differences by sex as recorded in health records [19, 32–38]. Gender identity may also be a marker of disparity but was not evaluated in included studies, which focused on sex at birth.

Three socioeconomic factors were identified and included in the review: income, education, and insurance type/status. The most common socioeconomic factors assessed were insurance type and status. People with private insurance were more likely to receive antibiotic prescriptions compared to people with public insurance (Medicare or Medicaid) [24, 38–40] or no insurance [24, 39].

Comorbid conditions were often measured as presence or absence of any chronic conditions or specific conditions identified such as asthma, renal disease, or substance use disorder. Congestive heart failure was associated with higher rates of antibiotic prescribing [41], and patients with at least 1 comorbid condition were more likely to receive an antibiotic prescription [22, 33, 40, 42–44]. Tobacco use was another individual factor associated with increased likelihood of antibiotic prescribing [38, 44].

Associations with antibiotic prescribing and clinician factors included clinician age, sex, years of experience, and specialty. Older physicians [24, 25, 45, 46], male clinicians [46], advanced practice clinicians [24, 31, 32], non–internal medicine clinicians [25, 38, 46, 47], and non–pediatric clinicians [34, 40, 48] had higher rates of antibiotic prescribing.

Healthcare Factors

A limited number of healthcare factors were measured in the studies and included clinical setting, clinician density as a proxy for access, and wait time as a measure for quality. Specific clinical settings varied across studies, but the most assessed setting associated with antibiotic prescribing was the emergency department (ED). Antibiotic prescribing in an ED was associated with longer duration of antibiotics [29], greatest increase in prescribing rates over time [49], and higher prescribing rates compared with a physician's office [49]. Studies found that higher clinician density, at the county level and per capita, was associated with higher antibiotic prescribing rates [50–52]. Waiting time longer than 2 hours in the ED was significantly associated with increased odds of receiving an antibiotic prescription [53].

Community Factors

Community-level factors explored in the studies were limited to geography (region and rurality) and county characteristics. Many studies showed a strong association between residence in the US Southern region and antibiotic prescribing across clinical settings, clinician specialty, and diagnoses [30, 36, 42, 49, 52, 54–59]. Hersh et al found that children living in the South were 82% more likely to be prescribed a broad-spectrum antibiotic than those living in the West census region [39]. Langner et al found that physicians in all other regions had a 29%–35% significantly higher likelihood of prescribing guideline-concordant treatment than physicians in the South Atlantic [25]. People living in rural areas were also more likely to receive an antibiotic prescription [21, 46, 54, 56, 60] and were more likely to receive inappropriate prescriptions [21, 22, 28, 31] than their urban counterparts. Five studies conducted county-level analyses of antibiotic prescribing and found that counties with high proportions of people with incomes below the federal poverty level [30, 52, 60, 61], women, [30, 50, 52] and people who are White [30, 50, 51] were associated with higher prescribing rates.

Methodologic Limitations

None of the studies assessed drivers of inequities in antibiotic prescribing. Also, interaction between health equity markers was assessed by only 1 study. Dantuluri et al included subgroup analyses of their primary analysis between rurality of residence and antibiotic prescribing for acute respiratory infections (ARI) and inappropriate prescribing for ARI among children aged ≤5 years enrolled in Tennessee's Medicaid program [21]. Interaction terms between race and rurality and median household income and rurality found that the strength of association between rurality and prescribing varied by race (significantly higher inappropriate prescribing among Black children) and median household income (significantly higher inappropriate prescribing among children from households with lower median income). Another gap in the studies’ assessment of interaction was the exclusion of at least 1 health equity marker by 4 studies in their multivariate models because they were not statistically significant in univariate analyses. Race and ethnicity [45, 49, 62], sex, [45, 62] region [42, 62], comorbid conditions [62], and insurance status [42] were excluded from some models, and interactions were not assessed.

DISCUSSION

In our review of the published literature examining the association between health equity markers and drivers with antibiotic prescribing in the US, differences in prescribing were found by patient's race and ethnicity, sex, age, socioeconomic factors (ie, income, insurance type/status, and education), geography, clinician's age and specialty, and healthcare setting, with an emphasis on outpatient settings. These differences likely represent healthcare inequities; however, no drivers of inequities in antibiotic prescribing were reported, and most studies did not have a prespecified health equity objective. Studies that specified a health equity objective were more recently published, which follows the growth of social justice movements [63], commitment to address racism as a public health problem by leading public health organizations [5, 64], and evidence of the coronavirus disease 2019 (COVID-19) pandemic exacerbating longstanding systemic health inequities [65, 66]. Within this context of health equity research, we found that prescribing rates and appropriateness varied by certain factors, and several gaps in knowledge were identified requiring future evaluation.

While there was variability across study findings, we found that most associations with inequity markers were at the individual, healthcare, or community levels. Some differences in prescribing may be clinically indicated such as by sex or age but, based on these studies, appropriateness cannot be determined. However, patterns of prescribing disparities by race and ethnicity, place of residence (Southern region and rural) [67], socioeconomic status [68], and differential clinician treatment [69] reflect similar disparities to those documented in healthcare access [70], diabetes care and medication prescribing [71, 72], and pain management [73]. For instance, Black people were less likely than White people to receive antibiotics. Similarly, racial disparities have been found in pain management where Black people were less likely to be prescribed any pain medication and less likely to be prescribed opioids for severe pain compared to White people [74, 75]. During the COVID-19 pandemic, despite disproportionately higher rates of infections, hospitalizations, and death among people of race and ethnic minority groups, there were continued disparities in access and receipt of COVID-19 therapeutics including monoclonal antibodies and oral antivirals [76]. In cancer care research, disparities in outcomes in rural areas have been well characterized and are likely due to the impact of rurality on access to oncology infrastructure (eg, cancer prevention, diagnosis, and guideline-concordant treatment services), health insurance, and transportation, as well as higher rates of risk factors such as smoking and obesity [77]. Similarly, geographic disparities in antibiotic prescribing may be because people living in rural areas are more likely to receive care in an urgent care or ED setting [78] or by clinician specialties with higher rates of inappropriate prescribing [79–81].

Not all levels of markers and drivers of inequities were evaluated, particularly at the national and community levels. At the individual level, potential markers not studied include gender identity, sexual orientation, language, refugee and immigrant status, and health literacy, with limited studies on inequities by Hispanic origin. At the healthcare level, while antibiotic stewardship programs are required for inpatient settings, most studies evaluating health equity markers were limited to outpatient settings. We found higher prescribing associated with visits to EDs compared to physicians’ offices, an opportunity for stewardship interventions by health systems. An article by Goodman et al on antibiotic prescribing in the inpatient setting, published after our search period, found higher prescribing rates in the Southern region and to male patients and lower prescribing rates to people of racial and ethnic minority groups [82]. Wojcik et al conducted a systematic review of qualitative studies on inpatient prescribing behaviors describing the complex and dynamic context of physicians’ antibiotic prescribing [83]. Only 3 of 15 included studies were from the US. They suggested that changes to practice were needed on managing failures in communication and information provision, promoting distribution of responsibility for antibiotic decisions, and reducing fear of consequences from not prescribing. Future quantitative and qualitative studies evaluating markers and drivers of inequities in antibiotic prescribing are needed to address these knowledge gaps, especially in acute care settings. Additionally, evaluation of the intersectionality and interaction of equity markers is needed for focused interventions. For instance, studies have shown that rural status confers additional disadvantage in healthcare access and among rural populations, people of racial and ethnic minority groups have less access to healthcare and poorer health outcomes compared to rural White populations [70, 84]. Schulman et al found that a patient's race and sex independently influenced physicians’ management of chest pain, and race–sex interactions showed that Black women were significantly less likely than White men to be referred for cardiac catheterization [85].

This review has several limitations. First, studies included in this scoping review vary by study design, variable definition, outcomes measured, and populations and conditions studied, limiting comparability. However, we aimed to broadly report the scope of literature on this topic and emphasize the importance of including equity-related variables in future research. Second, our search did not yield any relevant qualitative studies, which may be a valuable methodology to assess health equity drivers in different settings. Third, many potential markers of inequities were not collected or analyzed, and markers were mainly assessed in outpatient settings, limiting the number of markers with data and interpretation of findings to other settings. Fourth, we did not assess the risk of bias of studies included in the review because it is not applicable to the scoping review methodology. As more health equity–focused research in antibiotic prescribing is published, a systematic review with a critical appraisal of studies should be considered. Fifth, while we employed a systematic literature search, it is possible that relevant studies [86, 87] were missed, and future updates should be considered to capture the growing literature on health equity and antibiotic prescribing. Additionally, our study period may have been too short to capture studies related to the COVID-19 pandemic. Future studies may also specifically explore the COVID-19 pandemic's impact on disparities in antibiotic prescribing.

Clinicians, antibiotic stewardship experts, and health systems should be aware that prescribing behavior varies according to both clinician- and patient-level markers. In addition to studying the best approaches to providing feedback, assessing the drivers of these differences is an important next step (Supplementary Table 4). Antibiotic prescribing quality improvement activities and interventions should consider clinician prescribing feedback that incorporates a health equity lens and more broadly consider equitable care of infectious diseases. Family practice and advanced practice clinicians and their professional organizations need to be engaged in antibiotic stewardship to address differences in quality of prescribing by clinician type.

Researchers should include specific health equity–related objectives to improve characterization of equity markers and expand understanding of potential systemic and structural drivers of inequities in all clinical settings. Data on relevant markers of health inequities should be collected and included a priori in statistical models, and interactions between inequity markers should be assessed [88]. Boyd et al outlined a standard for publishing about racial health inequities, which researchers should use as a guide when embarking on this work [89]. Moving beyond documenting inequities, antibiotic stewardship interventions should be designed to address drivers of health inequities and examine the potential effects of interventions across inequity markers to optimize antibiotic use and incorporate the patient’s perspective. Additional resources and partnerships (eg, professional societies, payers, and public health) to improve access to stewardship expertise, especially in the South and in rural areas, are needed. Incorporating health equity principles into guidance and regulatory requirements is an important step in improving equitable antibiotic prescribing, access, and use. A new Joint Commission accreditation standard aiming to reduce healthcare disparities was made effective January 2023 [90]. Combining stewardship activities for quality improvement with a focus on health equity will help health systems meet quality and equity standards while improving population health outcomes.

Supplementary Data

Supplementary materials are available at Open Forum Infectious Diseases online. Consisting of data provided by the authors to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corresponding author.

Notes

Disclaimer. The findings and conclusions in this article are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.

Author notes

Potential conflicts of interest. All authors: No reported conflicts.