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Missed opportunities: racial and neighborhood socioeconomic disparities in emergency colorectal cancer diagnosis and surgery

  • Sandi L Pruitt1, 2Email author,
  • Nicholas O Davidson3, 4,
  • Samir Gupta5, 6,
  • Yan Yan4, 7 and
  • Mario Schootman8
BMC Cancer201414:927

https://doi.org/10.1186/1471-2407-14-927

Received: 26 September 2013

Accepted: 26 November 2014

Published: 9 December 2014

Abstract

Background

Disparities by race and neighborhood socioeconomic status exist for many colorectal cancer (CRC) outcomes, including screening use and mortality. We used population-based data to determine if disparities also exist for emergency CRC diagnosis and surgery.

Methods

We examined two emergency CRC outcomes using 1992–2005 population-based U.S. SEER-Medicare data. Among CRC patients aged ≥66 years, we examined racial (African American vs. white) and neighborhood poverty disparities in two emergency outcomes defined as: 1) newly diagnosed CRC or 2) CRC surgery associated with: obstruction, perforation, or emergency inpatient admission. Multilevel logistic regression (patients nested in census tracts) analyses adjusted for sociodemographic, tumor, and clinical covariates.

Results

Of 83,330 CRC patients, 29.1% were diagnosed emergently. Of 55,046 undergoing surgery, 26.0% had emergency surgery. For both outcomes, race and neighborhood poverty disparities were evident. A significant race by poverty interaction (p < .001) was noted: poverty rate was associated with both outcomes among African Americans, but not whites. Compared to whites in low poverty (<10%) neighborhoods, African Americans in high poverty (≥20%) neighborhoods had increased odds of emergency diagnosis (AOR: 1.50, 95% CI: 1.38-1.63) and surgery (AOR: 1.63, 95% CI: 1.47-1.81).

Conclusions

Emergency CRC outcomes are associated with high poverty residence among African Americans in this population-based study, potentially contributing to observed disparities in CRC morbidity and mortality. Targeted efforts to increase CRC screening among African Americans living in high poverty neighborhoods could reduce preventable disparities.

Keywords

Colorectal cancer Emergency outcomes Disparities Race Socioeconomic status SEER-Medicare

Background

Colorectal cancer (CRC) screening results in dramatically improved survival [1, 2] and can prevent late-stage disease and associated serious and emergent complications including obstruction, perforation, hemorrhage, and peritonitis. These complications, when presenting acutely, are considered emergencies—posing immediate risks to life or long-term impairment—and require immediate intervention including surgical management and intensive care unit stays. Of those diagnosed emergently and receiving curative resection, both short- and long-term outcomes, including mortality and medical and surgical complications, are significantly worse than those receiving elective curative resection [35]. For example, a U.S. National Inpatient Sample study demonstrated that emergency resection was associated with a 3-fold increase of in-hospital mortality, longer hospital stays, and greater hospital costs [6]. Emergency resection is also associated with suboptimal long-term outcomes. A U.S. Surveillance Epidemiology and End Results (SEER)-Medicare study of 30,685 stage I-III colon cancer patients found that non-elective resection was associated with significantly worse five-year disease-specific survival (Hazard Ratio: 1.30, p < .001), even after adjustment for pre-, peri-, and post-operative covariates [7].

CRC emergencies may disproportionately affect African Americans and low socioeconomic status (SES) populations. For example, in a U.S. population-based study of 127,975 CRC patients undergoing resection in 2002, African Americans were more likely to have emergency resection [6]. However, in the same study, median income of patients’ zip code was not associated with emergency resection [6]. Studies from England and Canada, however, demonstrate that CRC patients living in low SES neighborhoods are more likely to be diagnosed emergently[4, 8, 9]. African American and disadvantaged, low-SES populations are less likely to have obtained and maintained cancer screening than their counterparts and partly as a result, experience a disproportionate cancer burden across numerous CRC outcomes [1012]. For example, compared to whites, African American men and women have a 22-23% higher CRC incidence rate and a 46-53% higher CRC mortality rate, respectively [13]. In a study comparing those living in counties where <10% population lived in poverty, both African Americans (OR: 1.13; 95% CI: 1.03-1.25) and whites (OR: 1.10; 95% CI: 1.06-1.15) living in counties with ≥20% poverty had higher odds of distant stage CRC [14].

The overwhelming majority of studies on emergency diagnosis or surgery of CRC originate from Europe or Canada, include small samples, and are not population-based. Thus, the U.S. experience, particularly race and SES disparities, has not been adequately studied. Further, while there is documented geographic variation in CRC outcomes such as screening and mortality, [1520] the extent of neighborhood variation in CRC emergencies is unknown. Neighborhood variation indicates that shared neighborhood-level characteristics, in addition to individual characteristics, are associated with emergencies, which could suggest a role for geographically-targeted prevention strategies.

To our knowledge, there is only one population-based U.S. study on emergency CRC diagnosis, [21] and none that concurrently examine both emergency diagnosis and surgery. Many patients diagnosed emergently have advanced disease, multimorbidity, low functional status, or poor prognosis, which could postpone or preclude curative resection, particularly African Americans and those of low SES who often present with more advanced disease [14]. Thus, there is a paucity of information about the distribution and correlates of emergency diagnosis (with or without emergency curative resection) in the U.S.

Here we describe 1) variation across neighborhoods and 2) race and neighborhood SES disparities in two outcomes, emergency CRC diagnosis and surgery, among U.S. CRC patients aged ≥66 years. Given lower rates of screening and worse CRC morbidity and mortality among African Americans [6, 10, 12, 13] and patients in low SES neighborhoods [4, 8, 9, 14], we hypothesized these populations would have higher rates of both emergency outcomes.

Methods

Data sources

Data were obtained from an existing linkage of the 1992–2005 National Cancer Institute’s (NCI) SEER program data with 1991–2006 Medicare claims files from the Centers for Medicare and Medicaid. Data access was granted by the NCI. As detailed elsewhere, [22] linked SEER-Medicare data provide a rich source of information on Medicare patients included in SEER, a nationally representative collection of population-based cancer registries. Ninety-four percent of cancer patients reported to SEER aged 65 years or older have been successfully linked with Medicare data [22]. Data for this study were available from 12 registries representing approximately 14% of the U.S. population, [23] including states (Connecticut, Hawaii, Iowa, New Mexico, and Utah), metropolitan areas (Atlanta, Detroit, Los Angeles, San Francisco-Oakland, San Jose-Monterey, and Seattle), and rural Georgia. This study was reviewed by the Institutional Review Board at Washington University and determined to be exempt from IRB oversight.

Study population

The study population included male and female patients aged ≥66 with a diagnosis of a first primary invasive colorectal cancer occurring from 1992 through 2005. We included only those aged ≥66 to allow for one-year of complete claims data pre-diagnosis to determine comorbidity. All patients had full coverage by both Medicare Parts A and B from one year pre-diagnosis until 120 days past primary surgery or until initiation of adjuvant chemotherapy, whichever came first. We excluded patients with appendix cancer, only autopsy or death certificate records, and members of HMOs. We excluded patients with a diagnosis of Crohn’s disease, ulcerative colitis, inflammatory bowel disease, or diverticulitis (ICD-9 556.X, 555.X, 562.01, 562.03, 562.11, 562.13) in the year prior to diagnosis. Finally, we also excluded patients (n = 5,529) missing year 2000 census tract in the SEER-Medicare data.

For the emergency surgery analysis, we included only patients with CRC surgeries (identified using ICD9 procedure codes described below) and excluded patients with abdominal or pelvic postoperative adhesions (ICD-9 560.81, 568.0, 614.6) in the pre-surgery year due to a high likelihood of emergency surgery for these conditions. We further excluded patients with neoadjuvant chemotherapy or radiation occurring in the year until 7 days before surgery as an emergency in this situation could merely reflect complications of a preexisting cancer [24].

Study variables

Emergency diagnosis and surgery

We defined emergency diagnosis and surgery as yes/no variables by the presence of any of 3 emergency Medicare claims indicators based on ICD9 codes and an inpatient admission type indicator, including: 1) obstruction (560.89, 560.9); 2) perforation (569.83); or 3) emergency inpatient admission (admtype = 1; patient required immediate medical intervention as a result of severe, life threatening, or potentially disabling conditions). These indicators were identified from previous literature [6, 7, 9, 2426] and were selected because they are highly correlated with CRC emergencies; emergency surgeries are commonly a result of obstruction and/or perforation [7]. Further, chosen indicators are unlikely to identify nonemergent symptoms or unrelated conditions (e.g. rectal bleeding is relatively nonspecific and could indicate minor bleeding or hemorrhoids). For inclusion as an emergency outcome, we specified that dates associated with the emergency indicators fall within 1) SEER month and year of initial CRC diagnosis (because day of diagnosis is not available in SEER) (emergency diagnosis); or 2) within ±3 days of the first of any CRC surgery (e.g. resections, pelvic exenteration, colostomy, [not including colostomy reversals]) (emergency surgery).

Race and socioeconomic (SES) status

We compared non-Hispanic African Americans to non-Hispanic whites. We defined SES as the percent of population living in poverty in the patient’s residential census tract at time of CRC diagnosis. We selected this indicator because census tract-level poverty rate is a robust indicator of SES, is associated with a variety of health outcomes in diverse populations and across time, and has relevance for policymakers [27, 28]. We used 2000 U.S. Census data using the following commonly used categories: <9.9%, 10–19.9%, and ≥20% [29, 30].

Covariates

Multiple covariates associated with emergency CRC outcomes in earlier studies [6, 7, 9, 21] were examined. Covariates obtained from SEER data included: year of diagnosis, age (66–69, 70–74, 75–79, 80–84, ≥85), sex, SEER historic stage (localized, regional, distant), tumor location (right [cecum: 18.0, ascending colon: 18.2, hepatic flexure of colon: 18.3, and transverse colon: 18.4] vs. left [splenic flexure of colon: 18.5, descending colon: 18.6, sigmoid colon: 18.7, rectosigmoid: 19.9, rectum: 20.9]), histology (mucinous adenocarcinoma/signet ring cell, other adenocarcinoma, other, unknown), and tumor grade (low [well/moderately differentiated] or high [poorly differentiated/ undifferentiated/anaplastic] or unknown).

Covariates obtained from Medicare claims included: prior hospitalizations, comorbidity, preventable hospitalizations, number of endoscopies, and Medicaid and Medicare (“dual eligibility”). Prior hospitalizations occurring between 12–1 months prior to diagnosis were measured as yes/no. To measure comorbidity, we searched inpatient or carrier claims for multiple chronic conditions (e.g. myocardial infarction, diabetes, dementia, or AIDS) occurring between 12–1 months pre-diagnosis using Charlson comorbidity index-Klabunde adaptation [31, 32]. We further classified comorbidity as none, one, or two or more following common practice. Preventable hospitalizations identify poor ambulatory health care outcomes and can represent a breakdown in access to or processes of primary care. Following methods described elsewhere, [33] we searched one-year pre-diagnosis of inpatient claims for potentially preventable hospitalizations, including asthma, diabetes, hypertension, pneumonia, and compared those with one or more preventable hospitalizations to those with none. Because claims provide accurate information on endoscopy procedures but are less reliable for stool blood testing and cannot distinguish screening from diagnostic tests, [34] we measured total number of endoscopies (colonoscopies and sigmoidoscopies) in the pre-diagnosis year, but were not able to control for complete CRC screening history starting at age 50. Dual-eligibility was defined as Medicaid eligibility for at least 1 month during the pre-diagnosis year. Census-tract urban/rural status (metropolitan, micropolitan, or rural) was measured using 2000 Census Rural Urban Continuum Area codes [35].

Statistical analysis

We describe sample characteristics and frequency of emergency diagnosis and emergency surgery using descriptive and chi-square statistics. We examine associations of race and neighborhood poverty rate, including a race by poverty interaction term, with both outcomes. We present 6 models: 1) empty model; 2) unadjusted race model; 3) unadjusted poverty model; 4) unadjusted race and poverty model; 5) adjusted race and poverty main effects model; and 6) adjusted race and poverty interaction model. Empty models include no predictor variables, but include a hierarchical structure, and are fit for the purpose of quantifying variation (random effects) at the census tract level. We multiplied race and poverty rate variables to determine if an interaction was present on a synergistic scale and retained the main effects of race and poverty in the model. Covariates were retained if they were associated with outcomes in bivariate analyses (p < .05). All models were fit using multilevel logistic regression to account for nesting of patients within residential census tracts, using SAS PROC GLIMMIX (SAS Institute Inc, Cary, NC).

To facilitate interpretation of census-tract (“neighborhood”) level random effects, we present variance and standard error and Median Odds Ratio (MOR). The MOR quantifies unexplained cluster heterogeneity [36, 37] on a scale directly comparable to odds ratios associated with other model variables [38]. MOR is based on the random effects variance component (V) from the regression model: MOR = exp 0.95 V . It is interpreted as the median value of the ratio of predicted odds of the outcome for two patients with equivalent covariates randomly chosen from two different neighborhoods. MOR is always ≥1; 1.0 indicates no variation between neighborhoods and larger values indicate greater geographic variation.

In a sensitivity analysis, we disaggregated each emergency outcome into 2 component variables (emergencies defined as obstruction and/or perforation [because only 1.1% and 1.2% of all diagnoses and surgeries, respectively, were associated with perforations] and emergency admission type [admtype = 1]) and re-fit all multilevel logistic regression models separately for each outcome.

Results

Of all 83,330 eligible patients, 29.1% had an emergency diagnosis. Of all patients undergoing surgery (n = 55,046), 26.0% had an emergency surgery. Table 1 presents sample characteristics by presence of emergency diagnosis and surgery status. All but one of the sample characteristics differed (p < .001) by emergency status and were included in the adjusted models. Occurrence of emergency diagnosis and emergency surgery did not significantly change over time (p > .05); therefore year of diagnosis was not included in the adjusted models. Of patients diagnosed emergently and undergoing surgery, 84.0% had emergency surgery. Of patients undergoing emergency surgery, nearly all (94.0%) were also classified as having an emergency diagnosis (data not shown).
Table 1

Sample characteristics of colorectal cancer patients, by emergency diagnosis and emergency surgery status

 

Diagnosis (n = 83,330)a

Surgery (n = 55,046)a

Characteristic

No emergency diagnosis (n = 59,082)

Emergency diagnosis (n = 24,248)

p (Chi2)

No emergency surgery (n = 40,740)

Emergency surgery (n = 14,306)

p (Chi2)

 

n

%

n

%

 

n

%

n

%

 

Race

          

White

54527

71.90

21313

28.10

<.0001

37957

75.01

12643

24.99

<.0001

African American

4555

60.81

2935

39.19

 

2783

62.60

1663

37.40

 

Neighborhood poverty rate

          

<10%

35999

71.72

14198

28.28

<.0001

25254

74.81

8505

25.19

<.0001

10-19.9%

14902

71.98

5801

28.02

 

10170

75.09

3374

24.91

 

≥20%

8181

65.82

4249

34.18

 

5316

68.66

2427

31.34

 

Sex

          

Male

27154

73.36

9860

26.64

<.0001

18215

75.71

5843

24.29

<.0001

Female

31928

68.94

14388

31.06

 

22525

72.69

8463

27.31

 

Age (mean [SD])

77.2

7.1

79.6

7.6

<.0001

76.8

6.8

78.9

7.4

<.0001

Year

          

1992-1996

24621

70.68

10214

29.32

0.4126

9311

74.05

3263

25.95

0.9327

1997-2001

13092

71.21

5292

28.79

 

14847

74.08

5195

25.92

 

2002-2005

21369

70.97

8742

29.03

 

16582

73.93

5848

26.07

 

Medicaid enrollee

          

No

52170

72.54

19753

27.46

<.0001

36395

75.51

11802

24.49

<.0001

Yes

6912

60.59

4495

39.41

 

4345

63.44

2504

36.56

 

Rural urban commuting area

          

Metropolitan

46093

69.38

20346

30.62

<.0001

31657

72.45

12037

27.55

<.0001

Micropolitan

5246

76.23

1636

23.77

 

3595

78.91

961

21.09

 

Rural

7743

77.36

2266

22.64

 

5488

80.75

1308

19.25

 

Stage

          

Local

25470

78.60

6936

21.40

<.0001

17622

79.48

4549

20.52

<.0001

Regional

20160

69.12

9006

30.88

 

16936

72.69

6363

27.31

 

Distant

9840

60.94

6307

39.06

 

5436

64.66

2971

35.34

 

Tumor location

          

Left

31557

73.93

11127

26.07

<.0001

20204

75.47

6568

24.53

<.0001

Right

25162

68.09

11790

31.91

 

19953

73.04

7366

26.96

 

Tumor Grade

          

Low

40222

72.40

15337

27.60

<.0001

30066

75.09

9976

24.91

<.0001

High

10551

68.11

4941

31.89

 

8134

72.08

3150

27.92

 

Histology

          

Other adenocarcinoma

49541

71.73

19526

28.27

<.0001

35208

74.46

12078

25.54

<.0001

Mucinous adenocarcinoma/signet ring cell

6252

68.95

2816

31.05

 

4920

73.01

1819

26.99

 

Other

2365

64.09

1325

35.91

 

544

61.40

342

38.60

 

Comorbidity

          

0

34535

73.76

12284

26.24

<.0001

24359

76.19

7613

23.81

<.0001

1

14000

69.73

6077

30.27

 

9889

73.86

3500

26.14

 

≥2

9628

62.06

5887

37.94

 

6492

67.03

3193

32.97

 

Preventable hospitalization

          

No

55900

72.62

21077

27.38

<.0001

38522

75.20

12704

24.80

<.0001

Yes

3182

50.09

3171

49.91

 

2218

58.06

1602

41.94

 

Prior hospitalization

    

<.0001

     

No

38866

82.62

8178

17.38

 

23910

82.93

4920

17.07

 

Yes

20216

55.71

16070

44.29

 

16830

64.20

9386

35.80

 

Endoscopies/prior year

          

None

32028

67.93

15118

32.07

<.0001

19435

69.11

8685

30.89

<.0001

1

16806

75.27

5521

24.73

 

13345

80.29

3277

19.71

 

≥2

10248

73.96

3609

26.04

 

7960

77.25

2344

22.75

 

aNumbers may not add up to total due to missing data.

Emergency diagnosis

Table 2 presents results from unadjusted and adjusted multilevel analyses. Patients in the diagnosis sample (n = 83,330) were nested within 14,191 census tracts (range: 1–87 patients per tract). In all unadjusted and adjusted main effects models, emergency diagnosis was more likely for African Americans compared to whites, and those living in the highest poverty census tracts, compared to those in the lowest poverty census tracts. In the adjusted main effects model (Model 5), African Americans (vs. whites) (OR 1.28 [95% CI: 1.20-1.37]) and those living in census tracts with the highest poverty rates (≥20% vs. <10%) (OR 1.11 [95% CI: 1.04-1.18]) were more likely to have emergency diagnosis.
Table 2

The unadjusted and adjusted main effects between race and neighborhood poverty rate on emergency diagnosis and emergency surgery and neighborhood random effects

Emergency diagnosis (n = 83,330 patients, 14,191 census tracts)

Characteristic

Model 1 emptya model Model

Model 2 unadjusted race model

Model 3 unadjusted poverty model

Model 4 unadjusted race and poverty model

Model 5 adjustedbrace and poverty main effects model

 

Odds ratios and 95% confidence intervals

Race

          

White

-

 

1

 

-

 

1

 

1

 

African American

-

 

1.58

1.50-1.67

-

 

1.48

1.40-1.57

1.28 (1.20-1.37)

Neighborhood poverty rate

          

<10%

-

 

-

 

1

 

1

 

1

 

10-19.9%

-

 

-

 

1.01

0.97-1.05

0.98

0.94-1.02

0.98 (1.04-1.18)

≥20%

-

   

1.32

1.26-1.39

1.17

1.11-1.23

1.11 (1.04-1.18)

 

Neighborhood random effects

Variance (se)

.4317 (.0114)

.4073 (.0110)

.4225 (.0112)

.4061 (.0110)

.4887 (.0157)

Median odds ratio

1.87

1.84

1.86

1.84

1.95

Emergency surgery (n = 55,046 patients, 12,886 census tracts)

Characteristic

Model 1 a

Model 2

Model 3

Model 4

Model 5 b

 

Odds ratios and 95% confidence intervals

Race

          

White

-

 

1

 

-

 

1

 

1

 

African American

-

 

1.74

1.63-1.87

-

 

1.63

1.51-1.76

1.33

1.23-1.44

Neighborhood poverty rate

          

<10%

-

 

-

 

1

 

1

 

1

 

10-19.9%

-

 

-

 

1.01

0.96-1.06

0.97

0.92-1.02

0.98

0.92-1.03

≥20%

-

 

-

 

1.36

1.28-1.45

1.17

1.10-1.25

1.11

1.04-1.19

 

Neighborhood random effects

Variance (se)

.5086 (.0160)

.4843 (.0155)

.4994 (.0157)

.4826 (.0154)

.4410 (.0170)

Median odds ratio

1.97

1.94

1.96

1.94

1.88

aModel 1 is an empty model.

bModel 5 includes the following covariates: sex, urban/rural, Medicaid, comorbidity, prior hospitalization, preventable hospitalization, endoscopies in prior year, stage, grade, histology, and tumor location.

Values in bold represent odds ratios for which the 95% confidence interval does not include the value one.

Emergency surgery

Patients in the surgery sample (n = 55,046) were nested within 12,886 census tracts (range: 1–66 patients per tract). In all unadjusted and adjusted main effects models, African Americans, compared to whites, and those living in the highest poverty census tracts, compared to those in the lowest poverty tracts, were more likely to have emergency surgery. In the adjusted main effects model (Model 5), African Americans (vs. whites OR: 1.33 [95% CI: 1.23-1.44]) and those living in the highest poverty census tracts (≥20% vs. <10% poverty: OR: 1.11 [95% CI: 1.04-1.19]) were more likely to have emergency surgery.

Race by neighborhood poverty interactions for emergency diagnosis and surgery

Race by neighborhood poverty interactions (p < .001) were evident for both outcomes in the final adjusted interaction models (Model 6). Table 3 presents the number of patients and the percent with both outcomes by group as well as the adjusted race and poverty interaction effects. In the interaction models, neighborhood poverty was no longer associated with either outcome among whites. African Americans living in the lowest poverty neighborhoods were equally likely to have emergency outcomes as whites living in similar conditions. Compared to whites in the lowest poverty neighborhoods (<10%), African Americans living in neighborhoods with ≥10% poverty rate demonstrated higher odds of both outcomes. African Americans living in the highest poverty neighborhoods (≥20%) had the greatest odds of both emergency diagnosis (AOR: 1.50, 95% CI: 1.38-1.63) and surgery (AOR: 1.63, 95% CI: 1.47-1.81).
Table 3

Interaction between race and neighborhood poverty rate on emergency diagnosis and emergency surgery and neighborhood random effects in adjusted race and poverty interaction models (Model 6) a

 

Emergency diagnosis

Emergency surgery

 

Total

Percent emergencies

Odds ratios and 95% confidence intervals

Total

Percent emergencies

Odds ratios and 95% confidence intervals

White

        

<10%

48767

28.1

1

 

32922

25.0

1

 

10-19.9%

18903

27.3

0.97

0.92-1.02

12433

24.0

0.99

0.93-1.05

≥20%

8170

29.9

1.04

0.98-1.12

5245

26.8

1.06

0.98-1.15

Black

        

<10%

1430

33.9

1.09

0.95-1.25

837

31.1

1.09

0.92-1.30

10-19.9%

1800

35.8

1.16

1.02-1.31

1111

34.6

1.27

1.09-1.47

≥20%

4260

42.4

1.50

1.38-1.63

2498

40.8

1.63

1.47-1.81

Variance (se)

  

.4881 (.0157)

  

.6254 (.0221)

Median odds ratio

  

1.95

  

2.13

aModels adjusted for the following covariates: sex, urban/rural, Medicaid, comorbidity, prior hospitalization, preventable hospitalization, endoscopies in prior year, stage, grade, histology, and tumor location, and the main effects of race and neighborhood poverty.

Values in bold represent odds ratios for which the 95% confidence interval does not include the value one.

Neighborhood variation

Statistically significant variability in emergency diagnosis was present across census tracts for both outcomes in all models (Tables 2 and 3). In empty models (including no predictor variables), the MOR for census-tract variability in emergency diagnosis was 1.87. This can be interpreted as follows: if a patient switched from living in a randomly selected tract with low emergency diagnosis rate to randomly selected tract with a higher emergency diagnosis rate, her odds of emergency diagnosis would be 1.87 times higher (in the median). Neighborhood variability in emergency surgery (MOR = 1.97) was of similar magnitude. Neighborhood variability persisted, with similar magnitude, in multivariable models, suggesting that none of the covariates, including census tract poverty rate, accounted for census-tract variability in either outcome.

In sensitivity analyses, we examined, separately, two different indicators of both emergency diagnosis and surgery (data not shown). For both outcomes, in all models, African Americans and those living in higher poverty neighborhoods had higher odds of both 1) obstruction and/or perforations; and 2) emergency admissions (p < .001 for all comparisons).

Discussion

To our knowledge this is the first U.S. population-based study to demonstrate neighborhood variation and race and SES disparities in both emergency CRC diagnosis and surgery. Observed disparities persisted after adjustment for a diverse array of socioeconomic, clinical, and tumor covariates. Among the strengths of this study is that we utilized multilevel models to demonstrate neighborhood variation in emergency CRC diagnosis and surgery.

Observed disparities and neighborhood variation in CRC emergencies indicate that breakdowns are occurring across the CRC diagnosis and treatment continuum that are systematically influenced by race, poverty, and/or neighborhood. Conceptual models of the CRC diagnosis and treatment continuum provide a framework for understanding where these break-downs are occurring. For example, the CRC screening process continuum delineates transitions from risk assessment to screening, detection, diagnosis, and treatment for asymptomatic patients undergoing CRC screening [39]. Likewise, for symptomatic CRC patients, The Aarhus statement [40] reviews models [41, 42] that describe the events and time intervals leading from CRC symptom appraisal and detection to diagnosis and treatment. There may be multiple identifiable break-down points across these continuums contributing to suboptimal screening uptake or delayed diagnosis and/or treatment, thus leading to CRC emergencies. Future interventions designed to prevent CRC emergencies and eliminate disparities will need to explicitly acknowledge the role of race, SES, and neighborhood influences throughout the CRC continuum.

Race and SES disparities evident in our study have been observed in some but not all previous U.S. studies, and no studies to our knowledge have tested whether neighborhood poverty affects emergency outcomes in African Americans and whites equally. Previous large, multi-state U.S. studies have demonstrated that African Americans face higher risk of emergency resection [6, 7]. In one of these same studies, however, zip code median income was not associated with emergency resection [6]. In another study from Michigan, African American race and lower census tract median annual household income were associated with increased odds of emergency CRC diagnosis in bivariate but not in multivariate analyses [21]. Differences in study design, populations, and case ascertainment may explain these divergent findings. For example, the Michigan study did not measure the urgency/emergency of the CRC diagnosis itself, but classified patients as to whether they had an ED visit within the month of or month before CRC diagnosis [21]. Further, other studies used zip code- or census tract- level median income, whereas we used a measure of census tract poverty rate with a priori cut-points that allow for nonlinear trends, as recommended by Krieger et al. [27, 43, 44].

There are several possible explanations for the interactive effects of race and neighborhood poverty we observed. African American and disadvantaged, low-SES populations are less likely to have obtained and maintained cancer screening than their counterparts [1012]. They also may delay seeking care or experience health system delays once engaged in the healthcare system. These populations are less likely to have a regular primary care physician and have reduced access to care [4547]. However, emerging evidence suggests that insurance and access to care alone do not entirely explain observed disparities [48, 49]. Even in a study of Medicare beneficiaries with a usual physician, rates of recent CRC screening were considerably lower among patients with low SES [49, 50]. Other factors such as patient-physician communication, discrimination in health care, logistical challenges such as transportation, the ability to take time off of work, and capacity to navigate health system bureaucracies may also play a role. The race by poverty interaction (p < .001) whereby poverty rate was associated with both outcomes only among African Americans suggests that African Americans in high poverty neighborhoods face additional, substantial barriers to CRC screening and/or timely diagnosis. More research is needed to better understand the dual effects and mechanisms of neighborhood poverty and race on CRC outcomes.

Notably, the neighborhood variability observed in our study persisted even after controlling for all covariates, including neighborhood poverty rate, indicating significant unexplained neighborhood variation in both outcomes. These results confirm a growing body of research suggesting that CRC outcomes, including screening, incidence, stage, and mortality, vary across geography [17, 19, 5153]. For example, a prior study identified significant census-tract level variation in CRC survival that remained unexplained after accounting for individual covariates and neighborhood SES [19]. A more recent study identified census tract level variation in CRC screening that persisted even after accounting for the impact of physician and clinic- level influences using cross-classified statistical models [53]. Observed geographic variations in CRC outcomes remain poorly understood but may be a result of many factors such as practice patterns, managed care spillover, endoscopic capacity, or organizational culture within and across health systems.

Our finding of race and neighborhood SES disparities provides additional evidence of the disproportionate burden of CRC morbidity and mortality borne by African Americans and low-SES populations. CRC emergencies result in both short-and long-term negative impacts on morbidity, including postoperative complications, length of hospital stay, hospital readmissions, treatment cost, and mortality, [6, 7, 5456] and likely also influence psychosocial outcomes and quality of life. The higher number of CRC emergencies among African Americans in high poverty neighborhoods may account for some of the disproportionate burden in CRC morbidity and mortality in these populations. Future research should examine interactions between race and poverty and should explore the extent to which race and SES disparities in emergency diagnosis account for observed disparities in morbidity and mortality.

It is difficult to directly compare the rate of emergencies we observed to other studies given different sampling strategies, populations, time periods under study, and methods of ascertaining CRC emergencies. Among 4 population-based U.S. studies, numbers range considerably. A National Inpatient Sample study reported 10.6% of CRC patients aged 65 and older had emergency resections in 2002, defined as surgery in the presence of perforation, peritonitis, or obstruction [6]. In Michigan, 23% of CRC patients aged 66 years and older, diagnosed 1996–2000, had emergency diagnoses [21]. Using a measure of inpatient resection acuity, a SEER-Medicare study of Stage I-III colon cancer patients diagnosed 1996–2003 found that 40% of patients had urgent/emergent resections [7]. Another SEER-Medicare study of colon cancer patients with adenocarcinoma diagnosed 1991–1996, found that 19.7% had emergent hospitalizations and 9.1% had obstruction or perforation [26]. This last study by Schrag et al. used the same ICD9 codes as in the present study, together with the same or similar Medicare claim code for emergent hospital admission [26]. A validated and widely used measure of emergent diagnoses and surgeries would facilitate comparisons across populations and over time.

Emergency colorectal cancer resection has been identified as “the clearest evidence on an individual level for a failure of screening” [54]. Thus, CRC emergencies may be an indicator to monitor progress in cancer screening initiatives over time [4, 24, 57]. In the absence of CRC screening, CRC emergencies may be the consequence of delays occurring after symptom presentation [40]. Accordingly, monitoring CRC emergencies over time may also provide insight into factors influencing diagnostic or treatment delays, such as access to care. Notably, unlike a Canadian study that documented a 24% relative decrease (from 24-18%) in emergency CRC surgeries between 1993–2001, [24] we found no significant change in either emergency outcome over time (p > .05). Given that an average of 10–15 years elapse between adenomatous polyp development and invasive cancer, [58, 59] and that Medicare began covering some CRC screening modalities in 1998, adding colonoscopy for screening of average risk adults in 2001, [60] it may be too soon to detect potential downward trends in CRC emergencies. Given recent shifts in economic and health policy trends, it is unclear whether race and SES disparities in CRC emergencies will persist, diminish, or potentially increase over time.

Our results should be interpreted in light of several limitations. First, we include only Medicare-insured patients aged 66 or older and therefore cannot generalize to younger or uninsured patients. Second, although we searched claims for symptoms and codes indicating emergencies in previous studies, [6, 7, 9, 2426] some misclassification may have occurred. For example, we may have missed additional emergencies indicated by rectal bleeding (the severity of which cannot be measured with Medicare claims), in which case true incidence may be higher. Last, while we measured the number of lower endoscopies in the pre-diagnosis year, we could not measure complete CRC screening history nor endoscopic procedure quality, nor could we distinguish between screening or diagnostic procedures.

Despite these limitations, our study has several advantages over previous research. We conducted a multilevel study using a large population-based sample of U.S. CRC patients, used complete inpatient and outpatient claim data, and were able to adjust for a diverse array of tumor, patient, and neighborhood-level covariates. We further provided the first evidence of neighborhood variation and race and SES disparities in both emergency diagnosis and surgery.

Conclusions

We documented neighborhood, race and SES disparities in CRC emergencies, where African Americans living in high poverty neighborhoods have the highest odds of two emergency outcomes and where significant neighborhood variation remains unexplained. Targeted interventions to increase screening in these vulnerable populations would reduce these preventable disparities.

Abbreviations

CRC: 

Colorectal cancer screening

SES: 

Socioeconomic status

OR: 

Odds ratio

AOR: 

Adjusted odds ratio

SEER: 

Surveillance epidemiology and end results program.

Declarations

Acknowledgements

We gratefully acknowledge James Struthers for his data management and programming services. This work was supported by the National Cancer Institute (CA137750) and the National Center for Research Resources Washington University-ICTS (KL2 RR024994) and the Cancer Prevention Research Institute of Texas (CPRIT R1208). NOD was supported in part by NIH grant DK52574. This study used the linked SEER-Medicare database. The authors acknowledge the efforts of the Applied Research Program, NCI; the Office of Research, Development and Information, CMS; Information Management Services (IMS), Inc.; and the Surveillance, Epidemiology, and End Results (SEER) Program tumor registries in the creation of the SEER-Medicare database. Contents of this paper are solely the responsibility of the authors and do not necessarily represent the official view of the NIH.

Authors’ Affiliations

(1)
Department of Clinical Sciences, University of Texas Southwestern Medical Center
(2)
Harold C. Simmons Comprehensive Cancer Center
(3)
Department of Medicine, Division of Gastroenterology, Washington University School of Medicine
(4)
Alvin J. Siteman Cancer Center at Barnes-Jewish Hospital, Washington University School of Medicine
(5)
Department of Internal Medicine, Division of Gastroenterology, Moores Cancer Center, University of California
(6)
Department of Veterans Affairs, San Diego Healthcare System
(7)
Department of Surgery, Division of Public Health Sciences, Washington University School of Medicine
(8)
College for Public Health and Social Justice, Saint Louis University

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  61. Pre-publication history

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