Hysterectomy is the second most common surgical procedure performed in the United States, with 400,000–600,000 procedures performed each year.1,2 Hysterectomies for benign conditions significantly reduce morbidity and improve quality of life for patients who undergo the procedure, but not all patients benefit from this surgery equally.3 Differences in access to minimally invasive surgical (MIS) procedures, delays in care, differences in outcomes, and varying rates of complications have all previously been reported among different populations with racial, ethnic, socioeconomic, and geographic disparities.3–7

As knowledge of health care disparities grows, the need to address these inequities becomes increasingly urgent. Although numerous studies have documented health care disparities surrounding hysterectomy for benign indications, the precise nature of these disparities varies across studies. Systematically defining the scope of these disparities in hysterectomy can more accurately identify gaps in equity, and, thus, create opportunities to construct targeted interventions to ensure improved access and outcomes for all patients who are seeking hysterectomy for benign indications. The aim of this analysis was to systematically review the literature and evaluate how markers of health care disparities are associated with outcomes such as access to care and surgical and patient level outcomes among patients in the United States who are seeking and undergoing hysterectomy for benign indications.

SOURCES

The Society of Gynecologic Surgeons (SGS) Systematic Review Group includes members with clinical and surgical expertise in performing gynecologic surgery and expertise in the conduct of systematic review and guideline development. No institutional review board approval was required for this work. The protocol was developed in discussion with the full Systematic Review Group. The full protocol was registered with PROSPERO (registration number CRD42021234511).

We searched Medline (via PubMed), EMBASE, and SocIndex from inception through January 23, 2022. The search included terms for health care disparities, socioeconomic markers, social conditions, medically underserved, races and ethnicities, sexual and gender minorities, older adults, and related factors (Appendix 1, Population, Intervention, Comparison, Outcomes, Study design, available online at https://links.lww.com/AOG/D411). These terms were crossed with a wide range of gynecologic surgeries for both benign and malignant conditions (the current analysis was restricted to hysterectomy for benign indications). Search limits were included to restrict to studies based in the United States. The search was limited to primary studies in humans and existing systematic reviews.

STUDY SELECTION

We included studies based in the United States of any population that sought or underwent hysterectomy by any approach (abdominal, vaginal, laparoscopic, robotic) for benign indications (gynecology, minimally invasive gynecologic surgery, and female pelvic medicine and reconstructive surgery). We analyzed the hysterectomies grouped together as MIS (ie, vaginal, laparoscopic, robotic) and as separate approaches (ie, just vaginal, laparoscopic, robotic) based on how they were reported in studies. Studies could be cross-sectional (eg, survey, some registry studies) or longitudinal (prospective or retrospective), single group (eg, all underwent the same surgery), comparative (eg, of different surgeries), or database (eg, multiple surgeries or conditions analyzed together). Studies had to report at least one complete regression analysis that included and reported a beta coefficient (or equivalent) for at least one patient characteristic or risk marker related to health care disparities and its association with at least one outcome pertaining to access to surgery (provider access, indication detection, progression to surgery, likelihood of hysterectomy, receipt of optimal care, route of hysterectomy), patient outcomes (symptom recurrence, subjective surgical success, satisfaction with care, validated care measures), and surgical outcomes (objective disease recurrence, objective surgical success, surgical complications, surgical quality metrics), which are described more fully in Appendix 1 (https://links.lww.com/AOG/D411). Patient characteristics or risk markers related to health care disparities, decided a priori, included race; ethnicity; socioeconomic status; income; insurance status; education; geographic location (including ZIP code, eg, medically underserved area); and other (language, stress, marital status, sex, immigration status, literacy, lack of trust, toxic stress, LGBTQ+ [lesbian, gay, bisexual, transgender, queer+], older age). Provider characteristics related to health care disparities included age, race, sex or other, agreement of provider characteristics with patient characteristics, and provider implicit bias.

After pilot screening rounds to establish standardized eligibility criteria, 12 reviewers independently screened abstracts and potentially relevant full-text articles in duplicate. For abstract screening, liberal eligibility criteria were applied related to the possibility of a reported regression analysis of interest. Discrepancies were resolved by a third reviewer (C.K.W.). Abstract screening was conducted using Abstrackr (http://abstrackr.cebm.brown.edu). Sufficiently complete reporting of regression analyses was confirmed during full-text screening (in duplicate). Double data extraction was completed by the same 12 independent reviewers into customized forms in SRDRplus (https://srdrplus.ahrq.gov/) for study design and characteristics, and in Excel for regression data. Conflicts were resolved by a third reviewer (C.K.W.). Study and participant characteristics, surgery or procedure information, outcome definitions, risk marker or predictor definitions, multivariable model, reporting completeness, and results were extracted. Extraction of results was focused on the multivariable-adjusted estimates of association (ie, risk ratio, odds ratio, hazard ratio, beta) between health care disparity markers of interest and outcomes of interest, their CIs, and P values. As needed, reported estimates of association were converted to standardize the direction of the comparisons to be more compared with less vulnerable populations.

After data extraction and standardization, each health care disparity marker–outcome association was categorized based on direction (positive: health care disparity marker [eg, Black race] associated with worse outcome), strength of association, and statistical significance, as described in Figure 1. Based on this categorization, for each risk marker–outcome association, we developed heat maps to aid in visualization of the associations across studies (presented in Appendix 2, available online at https://links.lww.com/AOG/D411). Our analyses summarize only risk marker–outcome category pairs that were reported by at least three studies. Within each association figure, risk markers were sorted based on consistency (in direction of association), strength of association, and number of studies. We determined consistency of associations across studies based on the following criteria: consistent (80% or greater agreement in direction and statistical significance across studies, irrespective of strength of association), mostly consistent (between 67% and 79% agreement across studies, irrespective of strength of association), and variable (less than 67% agreement across studies). We did not conduct meta-analyses due to the heterogeneity across studies in both the specific definitions of health care disparity markers and outcomes, which covariates were adjusted for, and what analytic methods were used; thus, these associations are graphically represented in heat maps instead of numerical meta-analysis.

Fig. 1.: Code to interpret heat maps of multivariable analyses for Figures 3–5. Pink indicates positive association (presence or magnitude of marker associated with increased likelihood of outcome); blue indicates negative association (presence or magnitude of marker associated with decreased likelihood of outcome). Dark pink indicates strong positive association: measure of association (eg, relative risk [RR]≥2.0 and statistically significant). Dark blue indicates strong negative association: measure of association (eg, RR≤0.5 and statistically significant). Light pink indicates weak positive association: measure of association (eg, RRLight blue indicates weak negative association: measure of association (eg, RR>0.5 and statistically significant). Consistent indicates 80% or greater agreement in direction and statistical significance across studies, irrespective of strength of association. Mostly consistent indicates between 67% and 79% agreement across studies, irrespective of strength of association. Variable indicates less than 67% agreement across studies.

The initial findings were presented at the SGS annual Scientific Meeting on June 28, 2021. The draft guideline was presented to the SGS executive committee and circulated to the SGS membership on October 11, 2022, for member comment before submission for publication.

RESULTS

Our literature search identified 6,499 abstracts, including 17 found in existing systematic reviews, from which 347 articles were retrieved for full-text screening. Ultimately, based on our search criteria to include only multivariable analyses that reported a beta coefficient for at least one patient characteristic or risk marker related to health care disparities and its association with at least one outcome (access to surgery, patient outcome, surgical outcome), we found 39 studies with a total of 46 multivariable analyses (Fig. 2). Most full-text articles were rejected because they did not report multivariable analyses, the regression analyses did not report numerical data, the reported analyses did not include disparities predictors, the studies did not include gynecologic surgery, or they were not restricted to gynecologic surgeries. Study characteristics are tabulated in Appendix 1: Figure 1.1–1.3 (https://links.lww.com/AOG/D411).

Fig. 2.:

Literature flow diagram. *Eleven studies reported multiple multivariable analyses.

Nine studies with multivariable analyses reported on demographic health care disparity risk markers associated with likelihood of hysterectomy from 1986 to 2018.8–16Figure 3 summarizes the results by health care disparity risk markers associated with likelihood of hysterectomy, including geographic location, race, ethnicity, and education level. More detailed heat maps of each included study with information on the number of patients and the adjusted estimates of association can be found in Appendix 2: Figures 2.01–2.07 (https://links.lww.com/AOG/D411). Of these studies, four did not state whether patients with cancer were included9,11,14,16; in another two studies, fewer than 18% of participants had cancer.12,15

Fig. 3.: Consistency and direction of associations of health care disparities with likelihood of hysterectomy. This figure includes only health care disparity risk marker–outcome pairs that were reported by at least three studies. Health care disparity risk markers are sorted based on consistency, strength of association, and number of studies. See Figure 1 for code interpretation. Study-level data in Appendix 2, Figures 2.01–2.07 (available online at https://links.lww.com/AOG/D411). NS, not statistically significant.

Geographic location was associated with the likelihood of hysterectomy. As indicated in Figure 3, three studies showed a consistent, strong, increased association between living in the South or Southeast (vs living in the Northeast or West) and likelihood of hysterectomy.9,10,13 The three studies also evaluated Midwestern U.S. residence (vs other regions). Two of three studies showed an increased likelihood of having a hysterectomy for residents of the Midwestern United States, but one study found no significant association; thus, overall, there was a weak, mostly consistent association between Midwestern U.S. residence and the likelihood of having a hysterectomy.9,10,13

Race and ethnicity were associated with the likelihood of hysterectomy. As shown in Figure 3, three studies showed a consistent, weak, decreased association between Hispanic ethnicity and having had a prior hysterectomy.8,9,11 Five studies found variable, unclear associations between having a Black racial identity (vs having a White racial identity) and having had a prior hysterectomy.8–10,12,15 Finally, education level was associated with the likelihood of having had a prior hysterectomy. Seven studies showed a consistent, weak, increased association between having less than a high school education (vs being a college graduate) and having had a prior hysterectomy.8,9,11–13,15,16 Similarly, six studies showed a consistent, weak, increased association between having a high school diploma (vs being a college graduate) and having had a prior hysterectomy.8,9,12–14,16 Four studies showed a mostly consistent, weak, increased association between having some college education (vs being a college graduate) and having had a prior hysterectomy.8,9,14,16

There were not enough data (fewer than three studies) to adequately evaluate the association between income level and having had a prior hysterectomy. No studies meeting our inclusion criteria were identified that evaluated the association of older age and having had a prior hysterectomy.

Fifteen studies with multivariable analyses reported on health care disparity risk markers associated with access to MIS hysterectomy from 2008 to 2020.4,5,17–29 Three controlled for uterine weight,4,24,28 seven controlled for myoma,5,17–21,26,29 and one performed a sensitivity analysis including myomas.23 The remaining three studies did not control for uterine weight or myomas.22,25,27 In one study, 5.2% of participants had cancer29 the rest of the studies excluded patients with cancer.

Racial groups that did not identify as White were associated with a decreased likelihood of having access to MIS hysterectomy (Fig. 4). Fourteen studies (20 models) showed consistent, weak or strong, decreased associations between having a Black racial identity (vs having a White racial identity) and the likelihood of having access to MIS hysterectomy.4,5,17–24,26–29 Similarly, seven studies (nine models) showed mostly consistent, weak or strong, decreased associations between having a Asian or Pacific Islander racial identity (vs White) and a lower likelihood of having access to MIS hysterectomy.20,21,23,26–29 Twelve studies (17 models) showed a variable, unclear association between being of Hispanic ethnicity (vs having a White racial identity) and access to MIS hysterectomy.4,5,17,18,20–24,26–28

Fig. 4.: Consistency and direction of associations of health care disparity markers with less access to specific hysterectomy surgeries. This figure includes only health care disparity risk marker–outcome pairs that were reported by at least three studies. Health care disparity risk markers are sorted based on consistency, strength of association, and number of studies. See Figure 1 for code interpretation. Study-level data in Appendix 2, Figures 3.01–3.48 (available online at https://links.lww.com/AOG/D411). *Old vs young is defined in Appendix 2, Figure 3.10 (https://links.lww.com/AOG/D411). MIS, minimally invasive surgery; TAH, total abdominal hysterectomy; NS, not statistically significant; TVH, total vaginal hysterectomy.

There were inconsistent associations between insurance status and the likelihood of having access to MIS hysterectomy across studies. Eight studies showed a variable, unclear association between having Medicaid insurance (vs private insurance) and access to MIS hysterectomy.5,17,20–22,24–26 Similarly, seven studies showed a variable, unclear association between Medicare insurance (vs private insurance) and access to MIS hysterectomy.5,20–22,24–26

Geographic location was associated with increased access to MIS hysterectomy (Fig. 4). Living in the Western United States (vs the Northeast) was mostly consistent with a weak, increased association of having increased access to MIS hysterectomy across three studies.20–22 The same three studies showed mostly consistent lack of associations between living in the South or Midwest (vs the Northeast) or living in a rural area (vs an urban area) and having access to MIS hysterectomy. There also were inconsistent associations across six studies between being of older age (vs younger age) and access to MIS hysterectomy.5,21,22,25–27

There were not enough data (fewer than three studies) to adequately evaluate the association between Native American racial identities, hospital characteristics (teaching or safety-net), specific age categories, and access to MIS hysterectomy. We were unable to standardize and thus compare income level and access to MIS hysterectomy. No studies meeting our inclusion criteria were identified that evaluated the association of other health care disparity markers and having MIS hysterectomy.

Eight studies with multivariable analyses reported on health care disparity risk markers associated with access to laparoscopic hysterectomy (vs open hysterectomy) from 2008 to 2020, including race and ethnicity and insurance status.17,19,21–24,27,29 Of these eight studies, 5.2% of patients had cancer in one study29 and the rest contained no patients with cancer.

Patients in certain racial and ethnicity groups were associated with decreased access to laparoscopic hysterectomy compared with open hysterectomy (Fig. 4). Eight studies (10 models) showed a consistent, strong or weak, decreased association between having a Black racial identity (vs having a White racial identity) and access to laparoscopic hysterectomy compared with open hysterectomy,17,19,21–24,27,29 and four studies (five models) showed a consistent, strong or weak, decreased association between having a Asian or Pacific Islander racial identity (vs having a White racial identity) and access to laparoscopic hysterectomy compared with open hysterectomy.21,23,27,29 Similarly, seven studies (nine models) showed a mostly consistent, strong or weak, decreased association between being of Hispanic ethnicity (vs having a White racial identity) and access to laparoscopic hysterectomy.17,19,21–24,27

Insurance status was associated with decreased access to laparoscopic compared with open hysterectomy. Medicare insurance (vs private insurance) was mostly consistently, weakly associated with decreased access to laparoscopic hysterectomy (vs open hysterectomy), according to three studies.21,22,24 In contrast, four studies found a variable, unclear association between having Medicaid insurance (vs private insurance) and access to laparoscopic hysterectomy.17,21,22,24

Geographic location was associated with decreased access to laparoscopic hysterectomy. Three studies showed a mostly consistent, weakly decreased association between living in a rural area (vs an urban area) and having access to a laparoscopic hysterectomy (vs open hysterectomy).17,21,22

There were not enough data (fewer than three studies) to evaluate the association of having Native American racial identities, age, hospital characteristic, income or geographic region and access to laparoscopic hysterectomy compared with open hysterectomy. No studies meeting our inclusion criteria were identified that evaluated the association of other health care disparity markers and having a laparoscopic hysterectomy compared with open hysterectomy.

Three studies with multivariable analyses reported on health care disparity risk markers associated with access to robotic hysterectomy from 2013 to 2020 including race (Fig. 4).24,30,31 Having a Black racial identity (vs White) was consistently, weakly associated with decreased access to robotic hysterectomy compared with nonrobotic hysterectomy, according to the three studies.24,30,31 There were not enough data (fewer than three studies) to be able to evaluate the association of other racial identities, ethnicity, age, insurance status, income, and geographic region on the access to robotic hysterectomy.

Five studies with multivariable analyses reported on health care disparity risk markers associated with access to vaginal hysterectomy (vs open hysterectomy) from 2017 to 2020, including race (Fig. 4).19,23,24,27,29 Five studies (six models) showed that for Black racial identities (vs White racial identities), there was a mostly consistent, weak or strong, decreased association with access to vaginal hysterectomy compared with abdominal hysterectomy.19,23,24,27,29 Three studies showed a consistent, weak, decreased association between access to vaginal hysterectomy compared with open hysterectomy and having Asian or Pacific Islander racial identity23,27,29; another four studies (five models) showed a consistent, strong or weak association between being of Hispanic ethnicity (vs White) and decreased access to vaginal hysterectomy.19,23,24,27

There were insufficient data (fewer than three studies) to be able to evaluate insurance status and income and the association with access to vaginal hysterectomy compared with open hysterectomy. No studies meeting our inclusion criteria were identified that evaluated the association of other health care disparity markers and access to vaginal hysterectomy compared with open hysterectomy.

Three studies with multivariable analyses reported on health care disparity risk markers associated with access to vaginal hysterectomy compared with laparoscopic hysterectomy from 2009 to 2018 including race (Fig. 4).21,27,32 Heat maps for all included studies can be found in the Appendix 2: Figures 3.35–3.44 (https://links.lww.com/AOG/D411).

Black racial identity (vs White) was mostly consistently, weakly associated with decreased access to vaginal hysterectomy compared with laparoscopic hysterectomy in three studies (four models).21,27,32 The same four models found variable, unclear, associations between having an Asian or Pacific Islander racial identity (vs White) and being of Hispanic ethnicity (vs White racial identity) and access to vaginal hysterectomy compared with laparoscopic hysterectomy. There were limited data (fewer than three studies) to evaluate age, insurance status, income and geographic region and the association of access to vaginal hysterectomy compared with laparoscopic hysterectomy.

Only one study with multivariable analysis reported on health care disparity risk markers associated with access to other hysterectomy comparisons,27 only one study reported on access to hysterectomy without prior medical management,33 and only one study reported on lack of success of hysterectomy34 (Appendix 2: Figures 3.45–3.48, Figures 3.49–3.50 and Figures 3.51–3.52 [https://links.lww.com/AOG/D411]). We were, thus, unable to draw conclusions about consistent associations for these topics.

Thirteen studies with multivariable analyses reported on health care disparity risk markers associated with hysterectomy complications from 1993 to 2020 including racial identity and insurance status (Fig. 5).4,5,18,35–44 Heat maps for all included studies can be found in Appendix 2: Figures 4.01–4.13 (https://links.lww.com/AOG/D411). Of these studies, one did not state whether patients with cancer were included,42 and, in another four, 12–20% of patients had cancer.37–39,43

Fig. 5.: Consistency and direction of associations of health care disparity markers with hysterectomy complications. This figure includes only health care disparity risk marker–outcome pairs that were reported by at least three studies. Health care disparity risk markers are sorted based on consistency, strength of association, and number of studies. See Figure 1 for code interpretation. Study-level data in Appendix 2, Figures 4.01–4.13 (available at https://links.lww.com/AOG/D411). NS, not statistically significant.

Black racial identity was consistently associated with an increased likelihood of having hysterectomy complications (Fig. 5). Ten studies showed consistent, weak, increased association between having a Black racial identity (vs White) and having a complication while undergoing hysterectomy.4,5,18,35–38,41,42,44 In four studies, there was, mostly consistently, no association between being of Hispanic ethnicity (vs having a White racial identity) and hysterectomy complications.5,18,37,42

Insurance status also was associated with the likelihood of having hysterectomy complications. Six studies showed a consistent, weak, increased association between having Medicaid insurance (vs private) and having hysterectomy complications.5,37–39,42,43 Similarly, five studies showed a consistent, weak, increased association between having Medicare insurance (vs private) and having hysterectomy complications.5,38,39,42,43 There was, mostly consistently, no associations between older age (vs younger age) and hysterectomy complications in four studies.5,36,38,39

There were no identified data on the following health care disparities and association with hysterectomy for benign indications: patient characteristics (including language, stress, marital status, sex, immigration status, literacy, lack of trust, toxic stress, LGBTQ+) and provider characteristics (including age, race, sex, agreement of provider characteristics with patient characteristics, and provider implicit bias). Despite the large number of studies included, there was heterogeneity in the data that prevented meta-analysis. Therefore, the data are represented in heat maps.

DISCUSSION

We demonstrated that patients in minoritized groups in the United States with public insurance, who live in the South or Midwest, and have lower educational levels were more likely to have poorer outcomes, including decreased access to less invasive hysterectomy procedures for benign indications and increased complications.

Disparities by race and insurance status are consistent with prior studies on health care disparities in both obstetrics (where Black patients and patients with Medicaid insurance have increased likelihood of pregnancy-related morbidity and mortality)45 and gynecologic oncology (where Black patients and patients with lower socioeconomic status have increased likelihood of mortality from ovarian cancer).46

Differences in access to MIS procedures can lead to disparities in outcomes due to increased rates of complications with more invasive procedures. Surgeon volume and comfort with laparoscopic procedures performed on large uteri may be a significant barrier to accessing MIS procedures,47 as Black patients disproportionately undergo hysterectomy by low-volume surgeons compared with White patients.48 Addressing disparities in access to high-volume surgeons may be an appropriate focus for disparities interventions, because more than 40% of all hysterectomies are performed by very low-volume surgeons.49 Quality improvement initiatives that reduced low-volume surgeons have been shown to eliminate racial disparities in access to MIS hysterectomy.28

Although there are disparities for race and access to MIS hysterectomy, it cannot be determined whether the differences relate to systemic biases, surgeon biases, patient decision factors, or other confounders. These studies do not prove that biases exist, but they do demonstrate differences. We recommend actively working to reduce the differences and any remaining biases.

It is important to note that the inequities that Black, Hispanic, and Asian or Pacific Islander patients experience are not due to biological differences. The American Medical Association states that accepting race as a biological construct can further exacerbate disparities in marginalized communities. Race is a social construct. Thus, the disparities by race are likely primarily due to bias and systemic racism, whether by individual decisionmakers, health care systems, or society as a whole. Further research should focus on how to eliminate these inequities and barriers to care.50

There are several strengths to this review. We comprehensively examined a large body of evidence from 39 articles, investigating multiple health care disparity risk markers. Our approach of including only studies with multivariable-adjusted regression allowed for acknowledgement of confounders.

There are several limitations to a systematic review that aims to summarize independent associations between patient characteristics and clinical outcomes. Each study took a unique analytic approach, including different cofactors in their multivariable regression analyses. The primary research questions varied across studies and not all directly addressed associations between health care disparity markers and outcomes. Thus, studies did not consistently adjust for potential confounders of associations between health care disparity markers and outcomes. For these reasons, we did not focus on the exact regression estimates and did not attempt to meta-analyze the associations. Instead, we aimed to focus on directionality, magnitude, and consistency of associations across studies. Additionally, as we included only studies with regression analyses, our search represents only a portion of the health care disparity literature and may have excluded many large surveillance studies that identified important health disparities. Most of the literature cited in this review contains data from structured survey responses or large databases, which limits establishing causal relationships. Some studies use data from the same national databases with overlapping time periods, introducing bias.

Furthermore, most studies lacked detail regarding race and ethnicity (such as Native American/American Indian populations), did not use recognized categories of race and ethnicity, or did not use self-identified race or ethnicity, practices recommended by the NIH.51 Additionally, relevant clinical variables involved in decisions about performing, or route of, hysterectomy were frequently omitted and were, thus, uncaptured confounders, such as prior nonsurgical treatment, uterine size, and parity. Also, we included hysterectomies performed as part of female pelvic medicine and reconstructive surgery procedures in this analysis. These hysterectomies are increasingly being performed primarily by fellowship-trained surgeons, many located within tertiary and quaternary care facilities, possibly introducing a regional confounder.

Research such as ours is the first step to identify and describe the inequities in our health care systems. Further research is needed to identify and understand the causes of these disparities and to develop and test targeted interventions to address them. Our study highlights the pervasive nature of inequities in hysterectomy access and outcomes, and the need for immediate changes to our health care system to improve opportunities for patients facing health care disparities.

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