Abstract
Background.
While hepatocellular carcinoma (HCC) is ideally diagnosed outpatient by screening at-risk patients, many are diagnosed in Emergency Departments (ED) due to undiagnosed liver disease and/or limited access-to-healthcare. This study aims to identify sociodemographic/clinical factors associated with being diagnosed with HCC in the ED to identify patients who may benefit from improved access-to-care.
Methods.
HCC patients diagnosed between 2012 and 2014 in the ED or an outpatient setting [Primary Care Physician (PCP) or hepatologist] were identified from the US Safety-Net Collaborative database and underwent retrospective chart-review. Multivariable regression identified predictors for an ED diagnosis.
Results.
Among 1620 patients, median age was 60, 68% were diagnosed outpatient, and 32% were diagnosed in the ED. ED patients were more likely male, Black/Hispanic, uninsured, and presented with more decompensated liver disease, aggressive features, and advanced clinical stage. On multivariable regression, controlling for age, gender, race/ethnicity, poverty, insurance, and PCP/navigator access, predictors for ED diagnosis were male (odds ratio [OR] 1.6, 95% confidence interval [CI]: 1.1–2.2, p = 0.010), black (OR 1.7, 95% CI: 1.2–2.3, p = 0.002), Hispanic (OR 1.6, 95% CI: 1.1–2.6, p = 0.029), > 25% below poverty line (OR 1.4, 95% CI: 1.1–1.9, p = 0.019), uninsured (OR 3.9, 95% CI: 2.4–6.1, p < 0.001), and lack of PCP (OR 2.3, 95% CI: 1.5–3.6, p < 0.001) or navigator (OR 1.8, 95% CI: 1.3–2.5, p = 0.001).
Conclusions.
The sociodemographic/clinical profile of patients diagnosed with HCC in EDs differs significantly from those diagnosed outpatient. ED patients were more likely racial/ethnic minorities, uninsured, and had limited access to healthcare. This study highlights the importance of improved access-to-care in already vulnerable populations.
The incidence of hepatocellular carcinoma (HCC) has nearly tripled in the United States (US) over the past two decades.1–3 In the United States, HCC is primarily associated with liver cirrhosis due to hepatitis C virus (HCV) or nonalcoholic steatohepatitis (NASH).2 Given that 80–90% of patients with HCC have cirrhosis, biannual HCC screening is recommended in this population.4,5
HCC screening should be performed with ultrasound and alpha-fetoprotein (AFP) every 6 months in those with cirrhosis and chronic hepatitis B virus (HBV).4 Screening often is performed by either a primary care physician (PCP) or a specialist (e.g., gastroenterologist or hepatologist).6–8 As a result, access to a PCP or specialist is an important factor to ensure adequate and timely HCC screening. Unfortunately, according to the Center for Disease Control and Prevention (CDC), approximately 16.8% of Americans lack access to a usual source of healthcare and often present to the emergency department (ED) for primary care.9,10
Lack of HCC screening in an outpatient setting can lead to both a delay in diagnosis and later stage disease at presentation.11 While hepatocellular carcinoma (HCC) is ideally diagnosed outpatient by screening at-risk patients with cirrhosis, many are diagnosed in the ED due to undiagnosed liver disease and/or limited access to healthcare.12 The primary goal of this study was to identify the sociodemographic and clinical factors associated with the diagnosis of HCC in the ED compared with an outpatient setting and to identify patients who may benefit from improved access to care. A secondary goal was to determine if patients with cirrhosis, who normally require continued surveillance, are receiving adequate screening. We hypothesized that underrepresented vulnerable populations consisting of racial/ethnic minorities, as well as patients with limited insurance coverage, will be more likely to be diagnosed with HCC in the ED.
MATERIALS AND METHODS
Data Source
The United States Safety-Net Collaborative (USSNC) database was utilized for this retrospective study. The USSNC incorporates data from five academic institutions and their adjacent safety-net hospitals. The United States Department of Health and Human Services defines a safety-net hospital (SNH) as one where providers organize and deliver a significant level of both healthcare and other health-related services to the uninsured, Medicaid, and other vulnerable populations.13 Hospitals included in this consortium are NYU Langone Health, Bellevue Hospital, Baylor College of Medicine, Ben Taub Hospital, Emory University Hospital, Grady Health System, The University of Texas Southwestern Medical Center, Parkland Memorial Hospital, The University of Miami Hospital, and Jackson Memorial Hospital. Institutional review board approval for this study was obtained at each investigative site waiving the need for individual patient consent, because this was a retrospective chart review. De-identified data was shared across the consortium.
Patient Selection
Patients diagnosed with HCC were identified through the individual university cancer registry databases between 2012 and 2014. International Classification of Diseases (ICD) codes were used to determine a diagnosis of HCC (ICD-9 155.0 and ICD-10 C22.0), and presence of HCC was confirmed through review of the medical record, imaging, or pathology. Patients were eligible for inclusion in the USSNC if they were between the ages of 18 and 90 years. Of the 1910 patients included in the USSNC, a total of 1,620 patients were included in this study. Patients were excluded if their location of diagnosis was not identified or if their location of diagnosis was labeled as “incidental,” which means we do not know the setting (outpatient vs. ED) of the incidentally found HCC.
Variables
Sociodemographic (age, gender, race, ethnicity, housing status, poverty status by zip code, citizenship, and health insurance status), health information (PCP and hepatology visit information, presence of a patient navigator, presentation to the ED within the last 6 months, number of comorbidities, alcohol use history, smoking status, presence of cirrhosis, history of hepatitis, and treatment history of hepatitis), presenting signs and symptoms (abdominal mass, abdominal pain, ascites, variceal bleeding, and weight loss), diagnostic information (screening imaging, screening AFP, Model for End-Stage Liver Disease score, Child–Pugh Score, and AFP level), and tumor characteristics at presentation (radiologic tumor size, nodal involvement, presence of metastatic disease, macrovascular invasion, and stage at diagnosis—AJCC 8th edition) data were collected.14 A combination of review of information within physician notes, hospital and clinical encounter information, and clinical information was used to ascertain the above data points. For example, some patients visited a PCP outside of the primary institutional networks, but the physician notes within primary institutions referenced the outside PCP visits. Similar methods were used for abstracting all other data points.
Statistical Analysis
Sociodemographic and clinical characteristics associated with HCC diagnosis in the ED or outpatient setting were initially assessed by means of χ2, Student t test, Mann–Whitney U test, or Fisher exact test as appropriate to the data. Factors meeting criteria of P < 0.1 were considered for entry into the predictive model for presentation in the ED. A manual stepwise binary logistic regression was performed. Successive models were evaluated by use of change in deviance, in which only variables that had a statistically significant improvement in model performance were included. The final model included age, gender, race, ethnicity, percent below poverty line in area of residence, insurance status, presence of a PCP, and presence of a navigator. A subgroup analysis in patients with cirrhosis (n = 1339) was performed using a binary logistic regression model controlling for age, gender, race, ethnicity, percent below poverty line in area of residence, insurance status, presence of a primary care physician, presence of a patient navigator, and a history of screening for HCC (by imaging or laboratory AFP level) within the previous year to identify predictors of presentation to the ED for initial HCC diagnosis to identify patients who should undergo screening. All P values were from two-sided tests, and results were deemed statistically significant at P < 0.05. Statistical analysis was performed using SPSS version 25 (IBM Corporation, Armonk, NY, copyright 2017).
RESULTS
Sociodemographics
Of the 1910 patients included in the USSNC, 1620 patients met inclusion criteria for this study (Fig. 1). Median age was 60.4 (interquartile range: 50.3–70.5), and 76% were male. The majority were white (54%), 33% were black, and 11% were Asian. A total of 23% were Hispanic. Two percent were homeless, and 30% lived in a zip code where greater than 25% of the population is below the poverty level. The majority (55%) had government insurance (Medicare or Medicaid), 29% had private insurance, and 14% were uninsured.
FIG. 1.
Patient selection with inclusion and exclusion criteria
Disease Presentation and Tumor Characteristics
Of 1620 patients with HCC, 68% were diagnosed in an outpatient setting, and 32% were diagnosed in the ED (Table 1). Patients diagnosed in the ED compared to outpatient were more likely to be black (44.4% vs. 27.7%, p < 0.001), Hispanic (26.2% vs. 21.4%, p = 0.036), homeless (5.2% vs. 0.6%, p < 0.001), non-US citizens (11.1% vs. 6.6%, p = 0.028), and uninsured (25.8% vs. 8.1%, p < 0.001). Patients who presented to the ED were more likely to have evidence of decompensated cirrhosis, with an increased incidence of ascites, variceal bleeding, abdominal pain, and self-reported or measured weight loss (Table 2). Fewer patients who presented to the ED had a PCP, had a PCP visit in last year, had a hepatology visit last year, or had a patient navigator. ED patients had increased untreated HCV, higher model for end-stage liver disease (MELD) scores, an increased incidence of Child Pugh Class C disease, and advanced stage III/IV (Table 2). There was no significant difference between the patients presenting to ED compared with those presenting with HCC at an outpatient facility regarding liver cirrhosis or history of hepatitis.
TABLE 1.
Sociodemographics and health information for patients diagnosed outpatient compared with the emergency department
| Combined (n = 1620) n (%) | Diagnosed outpatient (n = 1100) n (%) | Diagnosed in ED (n = 520) n (%) | p | |
|---|---|---|---|---|
| Demographics | ||||
| Age (median, 95% CI) | 60.4 (60.0–60.8) | 60.9 (60.4–61.3) | 59.6 (58.6–60.2) | 0.005 |
| Gender | ||||
| Female | 388 (24.0) | 282 (25.6) | 106 (20.4) | 0.021 |
| Male | 1232 (76.0) | 818 (74.4) | 414 (79.6) | |
| Race | ||||
| Asian | 147 (10.8) | 114 (12.2) | 33 (7.7) | < 0.001 |
| Black | 451 (33.0) | 260 (27.7) | 191 (44.4) | |
| White | 747 (54.4) | 545 (58.2) | 202 (47.0) | |
| Ethnicity | ||||
| Hispanic | 362 (22.9) | 229 (21.4) | 133 (26.2) | 0.036 |
| Not Hispanic | 1215 (77.0) | 841 (78.6) | 374 (73.6) | |
| Homeless | 34 (2.1) | 7 (0.6) | 27 (5.2) | < 0.001 |
| Below poverty line by zip code | ||||
| 0–5% | 54 (3.4) | 44 (4.1) | 10 (2.0) | < 0.001 |
| 5–15% | 544 (34.5) | 411 (38.4) | 133 (26.2) | |
| 15–25% | 510 (32.3) | 340 (31.8) | 170 (33.5) | |
| > 25% | 470 (29.8) | 275 (25.7) | 195 (38.4) | |
| U.S. citizen | 847 (92.0) | 592 (93.4) | 255 (88.9) | 0.028 |
| Health insurance | ||||
| Government | 835 (55.3) | 586 (56.8) | 249 (52.2) | < 0.001 |
| Private | 437 (29.0) | 346 (33.5) | 91 (19.1) | |
| Uninsured | 207 (13.7) | 84 (8.1) | 123 (25.8) | |
| Health information | ||||
| Primary care physician | 1006 (62.2) | 754 (68.7) | 252 (48.5) | < 0.001 |
| Primary care visit in past year | 499 (49.9) | 413 (55.1) | 86 (34.1) | < 0.001 |
| Hepatology visit in past year | 533 (40.8) | 462 (51.2) | 71 (17.5) | < 0.001 |
| Patient navigator | 996 (61.9) | 739 (67.6) | 257 (49.9) | < 0.001 |
| Presented to ED in past 6 months | 211 (16.4) | 81 (9.1) | 130 (32.6) | < 0.001 |
| Number of comorbidities (mean, SD) | 1.2 ± 1.0 | 1.3 ± 1.0 | 1.1 ± 1.0 | < 0.001 |
| Current or former alcohol abuse | 700 (43.3) | 448 (40.8) | 252 (48.5) | 0.006 |
| Current or former smoker | 628 (38.9) | 394 (35.9) | 234 (45.3) | < 0.001 |
| Cirrhosis | 1339 (87.1) | 921 (87.1) | 418 (87.1) | 0.978 |
| History of hepatitis | 1192 (77.6) | 819 (78.1) | 373 (76.3) | 0.715 |
| Untreated hepatitis C | 554 (51.7) | 349 (47.4) | 205 (61.2) | < 0.001 |
TABLE 2.
Presenting signs/symptoms, diagnostic information, and tumor characteristics at presentation for patients diagnosed outpatient compared with the emergency department
| Combined (n = 1620) n (%) | Diagnosed outpatient (n = 1100) n (%) | Diagnosed in ED (n = 520) n (%) | p | |
|---|---|---|---|---|
| Disease presentation | ||||
| Abdominal mass | 63 (4.9) | 30 (3.4) | 33 (8.2) | <0.001 |
| Abdominal pain | 588 (36.7) | 237 (21.9) | 351 (67.8) | <0.001 |
| Ascites | 512 (32.0) | 292 (27.0) | 220 (42.5) | <0.001 |
| Variceal bleeding | 200 (13.5) | 119 (11.5) | 81 (17.9) | 0.001 |
| Weight loss | 227 (14.2) | 113 (10.4) | 114 (22.1) | <0.001 |
| Diagnostic information | ||||
| Screening imaging within 1 year | 399 (26.6) | 361 (35.6) | 38 (7.8) | <0.001 |
| Screening AFP within 1 year | 360 (25.5) | 294 (30.7) | 66 (14.5) | <0.001 |
| Initial diagnostic imaging | ||||
| CT scan | 740 (46.3) | 402 (37.1) | 338 (65.8) | <0.001 |
| MRI | 532 (33.3) | 444 (41.0) | 88 (17.1) | |
| Ultrasound | 326 (20.4) | 238 (22.0) | 88 (17.1) | |
| MELD (mean, SD) | 12.3 ± 7.1 | 11.6 ± 7.0 | 13.9 ± 7.0 | <0.001 |
| Childs class | ||||
| A | 737 (48.7) | 548 (54.0) | 189 (37.9) | <0.001 |
| B | 512 (33.8) | 324 (31.9) | 188 (37.7) | |
| C | 251 (16.6) | 135 (13.3) | 116 (23.2) | |
| AFP level (mean, SD) | 300.2 ± 2648.9 | 143.9 ± 814.7 | 2175.0 ± 9126.4 | 0.001 |
| Tumor characteristics at presentation | ||||
| Radiologic tumor size (mean, SD) | 5.2 ± 5.3 | 4.2 ± 5.1 | 7.5 ± 4.9 | <0.001 |
| Nodal involvement | 206 (13.1) | 84 (7.8) | 122 (24.8) | <0.001 |
| Metastatic disease | 171 (10.6) | 62 (5.7) | 109 (21.2) | <0.001 |
| Macrovascular invasion | 314 (19.6) | 123 (11.3) | 191 (37.0) | <0.001 |
| Stage at diagnosis | ||||
| Ia | 249 (16.0) | 225 (20.9) | 24 (4.9) | <0.001 |
| Ib | 419 (26.9) | 337 (31.4) | 82 (16.9) | |
| II | 326 (20.9) | 261 (24.3) | 65 (13.4) | |
| IIIA | 99 (6.4) | 54 (5.0) | 45 (9.3) | |
| IIIB | 175 (11.2) | 80 (7.4) | 95 (19.6) | |
| IVA | 122 (7.8) | 56 (5.2) | 66 (13.6) | |
| IVB | 169 (10.8) | 61 (5.7) | 108 (22.3) | |
AFP alpha fetoprotein; MELD model for end-stage liver disease
Predictors of Presenting to the ED
In multivariable logistic regression models, patients diagnosed with HCC in the ED were more likely to be male (odds ratio [OR] 1.6, 95% confidence interval [CI]: 1.1–2.2, p = 0.010), black race (OR 1.7, 95% CI: 1.2–2.3, p = 0.002), Hispanic ethnicity (OR 1.6, 95% CI: 1.1–2.6, p = 0.029), live in an area with greater than 25% of residents below the poverty line (OR 1.4, 95% CI: 1.1–1.9, p = 0.019), uninsured (OR 3.9, 95% CI: 2.4–6.1, p < 0.001), and lack a PCP (OR 2.3, 95% CI: 1.5–3.6, p < 0.001) or patient navigator (OR 1.8, 95% CI: 1.3–2.5, p = 0.001) (Table 3).
TABLE 3.
Predictors of HCC diagnosis in the emergency department compared to an outpatient facility
| Variable | OR (95% CI) | p value |
|---|---|---|
| Age at diagnosis | ||
| Increasing age | 1.00 (0.98–1.01) | 0.636 |
| Gender | ||
| Female gender | 1 [Reference] | |
| Male gender | 1.55 (1.11–2.15) | 0.010 |
| Race | ||
| White | 1 [Reference] | |
| Black race | 1.66 (1.20–2.31) | 0.002 |
| Asian | 0.76 (0.46–1.25) | 0.278 |
| Ethnicity (Hispanic) | ||
| No | 1 [Reference] | |
| Yes | 1.64 (1.05–2.55) | 0.029 |
| Percentage in zip below poverty | ||
| 0–5% of population | 1 [Reference] | |
| 6–15% of population | 0.80 (0.61–1.05) | 0.103 |
| 16–25% of population | 1.07 (0.82–1.41) | 0.605 |
| > 25% of population | 1.42 (1.06–1.89) | 0.019 |
| Insurance | ||
| Private insurance | 1 [Reference] | |
| Government insurance | 1.31 (0.95–1.81) | 0.101 |
| Hospital card insurance | 2.75 (1.02–7.42) | 0.046 |
| Uninsured | 3.85 (2.42–6.14) | < 0.001 |
| Primary care physician | ||
| Yes | 1 [Reference] | |
| No | 2.34 (1.53–3.59) | < 0.001 |
| Patient navigator | ||
| Yes | 1 [Reference] | |
| No | 1.76 (1.25–2.49) | 0.001 |
Subgroup binary logistic regression model of only cirrhotic patients revealed that patients diagnosed with HCC in the ED were more likely to be male (OR 1.7, 95% CI: 1.2–2.5, p = 0.007), black (OR 1.6, 95% CI: 1.1–2.3, p = 0.014), uninsured (OR 4.2, 95% CI: 2.5–7.1, p < 0.001), did not have a PCP (OR 2.0, 95% CI: 1.2–3.2, p = 0.004), did not have a patient navigator (OR 1.7, 95% CI: 1.2–2.5, p = 0.005), or did not have screening imaging or labs within the year before diagnosis (OR 3.0, 95% CI: 2.0–4.4, p < 0.001; Table 4).
TABLE 4.
Subgroup analysis in cirrhotic patients of factors predictive of HCC diagnosis in the emergency department compared with an outpatient facility
| Variable | OR (95% CI) | p value |
|---|---|---|
| Age at diagnosis | ||
| Increasing age | 1.00 (0.98–1.02) | 0.999 |
| Gender | ||
| Female gender | 1 [Reference] | |
| Male gender | 1.70 (1.16–2.51) | 0.007 |
| Race | ||
| White | 1 [Reference] | |
| Black race | 1.60 (1.10–2.32) | 0.014 |
| Asian | 0.68 (0.38–1.21) | 0.189 |
| Ethnicity (Hispanic) | ||
| No | 1 [Reference] | |
| Yes | 1.63 (0.99–2.68) | 0.550 |
| Percentage in zip below poverty | ||
| 0–5% of population | 1 [Reference] | |
| 6–15% of population | 0.79 (0.58–1.08) | 0.144 |
| 16–25% of population | 1.13 (0.83–1.54) | 0.443 |
| > 25% of population | 1.35 (0.97–1.88) | 0.075 |
| Insurance | ||
| Private insurance | 1 [Reference] | |
| Government insurance | 1.34 (0.93–1.93) | 0.114 |
| Hospital card insurance | 2.80 (0.95–8.30) | 0.063 |
| Uninsured | 4.23 (2.51–7.13) | < 0.001 |
| Primary care physician | ||
| Yes | 1 [Reference] | |
| No | 1.99 (1.25–3.17) | 0.004 |
| Patient navigator | ||
| Yes | 1 [Reference] | |
| No | 1.72 (1.18–2.52) | 0.005 |
| Screening within past year | ||
| Yes | 1 [Reference] | |
| No | 2.98 (2.03–4.37) | < 0.001 |
DISCUSSION
This large multi-institutional USSNC study revealed significant differences in sociodemographics and clinical presentations of patients diagnosed with HCC in the ED compared with those diagnosed in an outpatient setting. Patients diagnosed in the ED were more likely racial/ethnic minorities, uninsured, and had limited access to healthcare. These patients presented with advanced disease, including larger tumors, a greater incidence of metastatic disease, and signs of decompensated liver failure, including ascites and variceal bleeding. Additionally, patients who presented to the ED were less likely to have a PCP, hepatology visit within the year before diagnosis, or a patient navigator. These findings highlight that both individual disparities consisting of race/ethnicity and socioeconomic status, as well as healthcare system factors, such as lack of insurance, lack of PCP, or lack of patient navigator access, are associated with a diagnosis of HCC in the ED.
Black race and Hispanic ethnicity were predictive of presenting to the ED with advanced disease and/or liver decompensation, such as ascites, abdominal pain, weight loss, and variceal bleeding. Previous studies also have shown that racial/ethnic minorities have increased all-cause mortality from HCC compared with non-Hispanic whites.15,16 Furthermore, recent studies have shown that although black and Hispanic populations are experiencing the greatest increase in HCC incidence at 35% and 30%, respectively, they also are less likely to have access to a PCP compared with their white counterparts.6 Increasing PCP access in this rapidly growing HCC population is critical for screening and detection at an earlier stage.17
Clinical presentation also differed significantly amongst those who presented to the ED verses in an outpatient setting. ED patients had higher MELD scores, higher AFP levels, and a higher proportion of advanced liver disease (Child Pugh Class B or C). ED patients also had larger tumors, a higher proportion of nodal involvement, more macrovascular invasion, and a higher proportion of advanced stage (IIIa, IIIb, IVa, and IVb) oncologic disease. Patients who presented to the ED with known HCV were less likely to have received definitive HCV treatment at any time throughout their disease course, a potentially missed opportunity to prevent HCC.18,19 Patients presenting to the ED with more advanced disease and/or life-threatening liver decompensation require increased healthcare costs for prolonged intensive care stays and emergent interventional procedural costs.20,21
Potentially modifiable healthcare access-related disparities, such as lack of insurance, lack of a PCP, or lack of an HCC patient navigator, were independently associated with an HCC diagnosis in the ED. Patients diagnosed in the ED also were less likely to have been screened for HCC within the preceding year by imaging or serum AFP. Not surprisingly, suboptimal screening contributes to the high prevalence of untreated disease, and up to 85% of HCV patients in the United States are unaware of their status.22–24 Formalized screening programs are therefore critical for early detection and intervention, especially for at-risk patients.
According to the 2018 guidelines by the American Association for the Study of Liver Disease, patients at high risk for HCV consist of patients who are current or former intravenous drug users, have received solid organ transplantations, have received a blood transfusion before 1992, or those born between 1945 and 1965.24–26 Those with HCV require close follow-up, and if they develop cirrhosis, they are screened for HCC with an abdominal ultrasound and AFP levels every 6 months.17,24 To evaluate the effectiveness of screening in our vulnerable patient population, subgroup analysis of cirrhotic patients revealed that independent predictors of presentation to the ED with HCC included male gender, black race, lack of insurance, lack of a PCP, and lack of an HCC patient navigator (Table 4). This further supports a need for increased access to insurance for vulnerable populations to provide greater PCP access and in turn appropriate screening.
This study has potential limitations and several strengths. It was retrospective and observational in nature, which limits the conclusions that we can draw from our results. Our data source had limited ability to extract the clinical decision-making process for each patient. Furthermore, patients could have received treatment at other facilities not captured by the database. Additionally, the consortium database did not specify Medicare versus Medicaid patients under the category of GI. However, subgroup analysis of 145 patients with GI (100 patients with Medicare and 45 patients with Medicaid) from our institution showed that Medicaid patients are more likely to present with HCC in the ED than Medicare patients (64.4% vs. 24.0%, p < 0.001). An additional limitation is that the SNHs included in this study are located in large urban areas associated with academic medical centers. This affects the generalizability of the study as patients in rural communities have unique barriers. These challenges include limited access to specialty care, long distances required to travel for medical visits, and occupations that may not allow for visits during regular business hours.27 Additionally, urban patients may have greater access to a PCP than rural patients due to proximity to medical facilities.28 These factors may lead to increased screening for urban patients compared to those living in a rural setting. Given that patients in rural communities actually have a higher incidence of HCC than patients living in urban areas, it is critical to perform similar studies in rural settings.29 Nevertheless, this study was a large, contemporary multi-institutional collaborative eliminating single-institution bias allowing for improved generalizability in urban settings. Furthermore, this study is the largest to evaluate sociodemographics and disease presentation at SNHs across the United States, thus providing valuable insight into how this vulnerable population behaves when it is provided access to care. We found an association between earlier stage at presentation and presentation in the outpatient setting when SNH patients are afforded access to care to a PCP, hepatologist, and/or an HCC patient navigator. Another strength of this study was the level of detail related to access to PCPs, if patients saw the PCPs or hepatologists within the last year, access to screening and if it was performed, and access to patient navigators. Large national databases do not include this level of detail, thus making it difficult to draw potential health care policy conclusions on screening and access to care efforts.
CONCLUSIONS
The sociodemographic and clinical profile of patients diagnosed with HCC in the ED varies significantly from those diagnosed in an outpatient setting. Those diagnosed in the ED were more likely a racial/ethnic minority, uninsured, and have limited access to healthcare. This is the first multi-institutional study to reveal disparities in presentation at the time of HCC diagnosis. It highlights the importance of improved screening and access to care in an already vulnerable population.
ACKNOWLEDGMENT
This research was supported by the National Institute of Health under a training Grant, T32CA211034.
Footnotes
DISCLOSURES All authors have no conflicts of interest to disclose.
REFERENCES
- 1.HealthIT. Telemedicine and Telehealth. United States Department of Health and Human Services. https://www.healthit.gov/topic/health-it-initiatives/telemedicine-and-telehealth. Published 2017. Accessed 15 Apr 2020. [Google Scholar]
- 2.Ghouri YA, Mian I, Rowe JH. Review of hepatocellular carcinoma: Epidemiology, etiology, and carcinogenesis. J Carcinog. 2017;16:1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Sayiner M, Golabi P, Younossi ZM. Disease burden of hepatocellular carcinoma: a global perspective. Dig Dis Sci. 2019;64(4):910–7. [DOI] [PubMed] [Google Scholar]
- 4.Fateen W, Ryder SD. Screening for hepatocellular carcinoma: patient selection and perspectives. J Hepatocell Carcinoma. 2017;4:71–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Kim SY, An J, Lim YS, et al. MRI with liver-specific contrast for surveillance of patients with cirrhosis at high risk of hepatocellular carcinoma. JAMA Oncol. 2017;3(4):456–63. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Simmons OL, Feng Y, Parikh ND, Singal AG. Primary care provider practice patterns and barriers to hepatocellular carcinoma surveillance. Clin Gastroenterol Hepatol. 2019;17(4):766–73. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Goldberg DS, Valderrama A, Kamalakar R, Sansgiry SS, Baba-janyan S, Lewis JD. Hepatocellular carcinoma surveillance rates in commercially insured patients with noncirrhotic chronic hepatitis B. J Viral Hepat. 2015;22(9):727–36. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Goldberg DS, Valderrama A, Kamalakar R, Sansgiry SS, Baba-janyan S, Lewis JD. Hepatocellular carcinoma surveillance among cirrhotic patients with commercial health insurance. J Clin Gastroenterol. 2016;50(3):258–65. [DOI] [PubMed] [Google Scholar]
- 9.Abdelsattar ZM, Hendren S, Wong SL. The impact of health insurance on cancer care in disadvantaged communities. Cancer. 2017;123(7):1219–27. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.CDC. No usual source of health care among adults aged 18–64, by selected characteristics: United States, average annual, selected years 1993–1994 through 2015–2016. US Department of Health and Human Services. https://www.cdc.gov/nchs/data/hus/2017/062.pdf. Published 2017. Accessed 18 March 2020. [Google Scholar]
- 11.Patel N, Yopp AC, Singal AG. Diagnostic delays are common among patients with hepatocellular carcinoma. J Natl Compr Canc Netw. 2015;13(5):543–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Ho CK, Maselli JH, Terrault NA, Gonzales R. High rate of hospital admissions among patients with cirrhosis seeking care in U.S. emergency departments. Dig Dis Sci. 2015;60(7):2183–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.ASPE. Definition of Safety Net Hospitals. United States Department of Health and Human Services. https://aspe.hhs.gov/report/environmental-scan-identify-major-research-questions-and-metrics-monitoring-effects-affordable-care-act-safety-net-hospitals/c-definition-safety-net-hospitals. Published 2013. Accessed 12 May 2020. [Google Scholar]
- 14.AJCC. AJCC Cancer Staging Manual, Eighth Edition. American College of Surgeons. https://cancerstaging.org/references-tools/deskreferences/Documents/AJCC. Published 2018. Accessed 16 July 2020. [Google Scholar]
- 15.Franco RA, Fan Y, Jarosek S, Bae S, Galbraith J. Racial and Geographic Disparities in Hepatocellular Carcinoma Outcomes. Am J Prev Med. 2018;55(5 Suppl 1):S40–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Yang B, Liu JB, So SK, et al. Disparities in hepatocellular carcinoma incidence by race/ethnicity and geographic area in California: Implications for prevention. Cancer. 2018;124(17):3551–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Zhang BH, Yang BH, Tang ZY. Randomized controlled trial of screening for hepatocellular carcinoma. J Cancer Res Clin Oncol. 2004;130(7):417–22. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Meringer H, Shibolet O, Deutsch L. Hepatocellular carcinoma in the post-hepatitis C virus era: Should we change the paradigm? World J Gastroenterol. 2019;25(29):3929–40. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Kim NJ, Magee C, Cummings C, Park H, Khalili M. Liver disease monitoring practices after hepatitis C cure in the underserved population. Hepatol Commun. 2018;2(10):1274–83. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Kaplan DE, Chapko MK, Mehta R, et al. Healthcare costs related to treatment of hepatocellular carcinoma among veterans with cirrhosis in the United States. Clin Gastroenterol Hepatol. 2018;16(1):106–14 e105. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Shetty A, Jun Yum J, Saab S. The Gastroenterologist’s Guide to Preventive Management of Compensated Cirrhosis. Gastroenterol Hepatol (N Y). 2019;15(8):423–30. [PMC free article] [PubMed] [Google Scholar]
- 22.CDC. Recommendations for the identification of chronic hepatitis C virus infection among persons born during 1945–1965. US Department of Health and Human Services. https://www.cdc.gov/mmwr/preview/mmwrhtml/rr6104a1.htm. Published 2012. Accessed 19 March 2020. [Google Scholar]
- 23.Ward JW. The hidden epidemic of hepatitis C virus infection in the United States: occult transmission and burden of disease. Top Antivir Med. 2013;21(1):15–9. [PMC free article] [PubMed] [Google Scholar]
- 24.Marrero JA, Kulik LM, Sirlin CB, et al. Diagnosis, staging, and management of hepatocellular carcinoma: 2018 Practice Guidance by the American Association for the Study of Liver Diseases. Hepatology. 2018;68(2):723–50. [DOI] [PubMed] [Google Scholar]
- 25.Harris PS, Hansen RM, Gray ME, Massoud OI, McGuire BM, Shoreibah MG. Hepatocellular carcinoma surveillance: an evidence-based approach. World J Gastroenterol. 2019;25(13):1550–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.CDC. Hepatitis C Questions and Answers for the Public. Department of Health and Human Services. https://www.cdc.gov/hepatitis/hcv/cfaq.htm. Published 2020. Accessed 18 March 2020. [Google Scholar]
- 27.Weisgrau S Issues in rural health: access, hospitals, and reform. Health Care Financ Rev. 1995;17(1):1–14. [PMC free article] [PubMed] [Google Scholar]
- 28.Coughlin SS, Clary C, Johnson JA, et al. Continuing Challenges in Rural Health in the United States. J Environ Health Sci. 2019;5(2):90–2. [PMC free article] [PubMed] [Google Scholar]
- 29.Li X, Deng Y, Tang W, et al. Urban-rural disparity in cancer incidence, mortality, and survivals in Shanghai, China, During 2002 and 2015. Front Oncol. 2018;8:579. [DOI] [PMC free article] [PubMed] [Google Scholar]