Abstract
Acute pancreatitis (AP) is a leading cause of gastrointestinal-related hospitalizations in the United States. Rural–urban healthcare disparities may influence access to care, disease severity, and outcomes; however, national data comparing these populations remain limited. We compared inpatient outcomes and healthcare utilization between rural and urban AP hospitalizations. We performed a retrospective cohort study using the National Inpatient Sample (2016–2021) to identify adult hospitalizations with a primary diagnosis of AP. Hospitalizations were classified as rural or urban. Multivariable logistic regression estimated adjusted odds ratios (aORs) for in-hospital mortality and complications. Multivariable linear regression assessed differences in length of stay and inflation-adjusted hospitalization costs after adjusting for demographics, comorbidities, and hospital characteristics. A total of 1,549,845 weighted AP hospitalizations were identified, including 1,289,970 (83.23%) urban and 259,875 (16.77%) rural hospitalizations. Rural hospitalizations had higher in-hospital mortality (0.59% vs 0.56%; aOR 1.38, 95% confidence interval: 1.18–1.62; P < .001). Rural patients had greater odds of complications, including acute kidney injury (aOR 1.06), vasopressor use (aOR 1.55), invasive mechanical ventilation (aOR 1.46), noninvasive ventilation (aOR 1.37), hemodialysis (aOR 1.31), acute respiratory distress syndrome (aOR 1.41), acute liver failure (aOR 1.27), necrotizing pancreatitis (aOR 1.61), and packed red blood cell transfusion (aOR 1.22; all P ≤ .016). Despite worse outcomes, rural hospitalizations had a shorter length of stay (−0.32 days; P < .001) and lower inflation-adjusted costs (−$11,343.80; P = .005). Rural AP hospitalizations were associated with higher mortality and severe complications despite shorter stays and lower costs, highlighting geographic disparities and the need to improve access to specialized care.
Keywords: acute pancreatitis, healthcare utilization, in-hospital outcomes, National Inpatient Sample, rural–urban disparities
1. Introduction
In the United States, acute pancreatitis (AP) is a leading cause of hospital admissions for gastrointestinal disorders, with an estimated 275,000 emergency department visits and over 100,000 hospitalizations annually.[1] The mortality rate for AP has been reported at approximately 5% to 10% for hospitalized patients, with higher mortality rates observed in severe cases, underscoring the critical need for effective management strategies.[1] Despite the increasing number of cases, outcomes of AP vary greatly and depend on multiple factors, including comorbidities, treatment protocols, and geographic location.
Notable disparities in healthcare outcomes have been observed when comparing rural and urban populations, and this gap is also evident in the management of AP. Rural patients are often at a disadvantage due to limited access to specialized care, fewer healthcare resources, and delayed interventions, which may contribute to worse clinical outcomes, such as longer hospitalization and increased mortality.[2,3] In contrast, urban settings tend to offer more timely access to advanced diagnostic tools, specialized medical staff, and intensive care units, which can lead to better outcomes.[1] However, despite these recognized differences, few studies have comprehensively analyzed how rural–urban disparities specifically affect the outcomes of AP.
2. Methods
2.1. Data source and study population
We conducted a retrospective cohort study using the National Inpatient Sample (NIS) from 2016 to 2021.[4] The NIS is the largest publicly available all-payer inpatient database in the United States and is designed to produce national estimates of hospital utilization, outcomes, and healthcare costs. It contains approximately 7 million unweighted hospital discharges annually, representing over 33 million hospitalizations nationwide after applying discharge weights.
Adult hospitalizations (age ≥ 18 years) with a primary diagnosis of AP were identified using International Classification of Diseases, Tenth Revision diagnosis codes. Hospitalizations were categorized into urban and rural cohorts based on the patient residence classification provided within the NIS dataset. Table S1, Supplemental Digital Content, provides the International Classification of Diseases, Tenth Revision diagnosis and procedure codes used to identify exposures, outcomes, comorbidities, and cohort classification.
We extracted patient-level variables, including age, sex, race, median household income based on ZIP code, expected primary payer (insurance status), length of stay, total hospitalization charges, and discharge disposition. Hospital-level variables included hospital region (geographic division) and hospital bed size. Recorded comorbidities included alcohol use, hypertension, diabetes mellitus, cancer, obesity, drug abuse, and smoking. We also identified in-hospital complications, including acute kidney injury, vasopressor use, invasive mechanical ventilation, noninvasive mechanical ventilation, hemodialysis, intestinal perforation, acute respiratory distress syndrome, acute liver failure, necrotizing pancreatitis, and packed red blood cell transfusion. Hospitalizations involving patients younger than 18 years, those with a co-diagnosis of COVID-19, or those with missing data for variables of interest were excluded from the analysis. Because the NIS contains deidentified publicly available data, this study was exempt from institutional review board approval. Hospitalization charges were adjusted for inflation using the Consumer Price Index Python package (version 2.0.9), converting costs from 2016 to 2020 into 2021 US dollars. The study was conducted and reported in accordance with the recommendations outlined in the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.[5] Ethical approval was not required for this study, as all analyses were conducted using aggregate, deidentified data in accordance with applicable regulations. Because no identifiable patient information was used, the requirement for informed consent was also waived.
2.2. Statistical analysis
Descriptive statistics were calculated for patient and hospital characteristics across the rural and urban cohorts. Categorical variables were compared using chi-squared tests, with a P-value < .05 considered statistically significant. Multivariable logistic regression models were constructed to evaluate the association between rural hospitalization and the odds of in-hospital mortality and each recorded complication, with results reported as adjusted odds ratios (aORs) with 95% confidence intervals (CIs). Covariates included patient demographics, socioeconomic factors, hospital characteristics, and the comorbidities described above. Length of stay and inflation-adjusted hospitalization costs were analyzed using multivariable linear regression models including the same covariates. A backward elimination approach was used to determine the optimal set of predictors for the final regression models. All analyses accounted for the complex survey design of the NIS and were weighted using the discharge weights provided in the dataset to generate nationally representative estimates. Data extraction was performed using SAS version 9.4 (SAS Institute Inc., Cary). Inflation adjustments were performed using Python version 3.11.4 (Python Software Foundation, Wilmington), and statistical analyses were conducted using R version 4.4.3 (R Foundation for Statistical Computing, Vienna, Austria). The analytical code used to perform the statistical analyses and cost adjustments is provided in Supplementary Appendices A and B, Supplemental Digital Content.
3. Results
A total of 1,549,845 weighted hospitalizations for AP were identified from the NIS between 2016 and 2021. Among these, 83.23% occurred in urban hospitals and 16.77% in rural hospitals.
3.1. Baseline demographics and socioeconomic characteristics
Baseline demographic, socioeconomic, and comorbidity characteristics of the study population are presented in Table 1.
Table 1.
Baseline demographic, socioeconomic, hospital characteristics, and comorbidities among adult hospitalizations with acute pancreatitis in the United States, stratified by rural versus urban residence (National Inpatient Sample 2016–2021).
Characteristics
Urban, N (%)
Rural, N (%)
P-value
N = 1549,845
1,289,970 (83.23)
259,875 (16.77)
–-
Gender (%)
<.001
Female
594,620 (46.1)
121,185 (46.63)
Male
695,350 (53.9)
138,690 (53.37)
Mean age, yr (SD)
Female
52.36 ± 17.61
54.19 ± 17.43
Male
50.37 ± 15.72
52.88 ± 15.81
Age groups (%)
<.001
18–29
123,945 (9.61)
20,010 (7.7)
30–49
487,530 (37.79)
88,465 (34.04)
50–69
481,930 (37.36)
103,560 (39.85)
≥70
196,565 (15.24)
47,840 (18.41)
Race (%)
<.001
Asian or Pacific Islander
31,580 (2.45)
1330 (0.51)
Black
237,115 (18.38)
27,165 (10.45)
Hispanic
188,310 (14.6)
13,245 (5.1)
Native American
7375 (0.57)
5635 (2.17)
Other
40,220 (3.12)
3365 (1.29)
White
785,370 (60.88)
209,135 (80.48)
Median household income (%)
<.001
≤51,999
359,985 (27.91)
143,870 (55.36)
52K–65,999
326,250 (25.29)
87,470 (33.66)
66K–87,999
337,435 (26.16)
25,400 (9.77)
≥88K
266,300 (20.64)
3135 (1.21)
Insurance status (%)
<.001
Medicaid
330,195 (25.6)
55,640 (21.41)
Medicare
366,885 (28.44)
93,595 (36.02)
No charge
11,260 (0.87)
1015 (0.39)
Other
38,495 (2.98)
8135 (3.13)
Private insurance
420,645 (32.61)
76,480 (29.43)
Hospital division (%)
<.001
East North Central
199,555 (15.47)
48,685 (18.73)
East South Central
73,840 (5.72)
45,320 (17.44)
Middle Atlantic
169,460 (13.14)
14,760 (5.68)
Mountain
84,835 (6.58)
16,655 (6.41)
New England
72,185 (5.6)
10,470 (4.03)
Pacific
184,970 (14.34)
12,545 (4.83)
South Atlantic
286,025 (22.17)
46,655 (17.95)
West North Central
65,480 (5.08)
28,965 (11.15)
West South Central
153,620 (11.91)
35,820 (13.78)
Hospital bed size (%)
<.001
Large
552,240 (42.81)
136,175 (52.4)
Medium
399,455 (30.97)
64,845 (24.95)
Small
338,275 (26.22)
58,855 (22.65)
Comorbidities (%)
Alcohol
427,605 (33.15)
68,470 (26.35)
<.001
HTN
736,930 (57.13)
155,570 (59.86)
<.001
Diabetes
354,755 (27.5)
74,695 (28.74)
<.001
Cancer
40,105 (3.11)
8090 (3.11)
.914
Obesity
240,655 (18.66)
46,845 (18.03)
<.001
Drug abuse
82,780 (6.42)
13,205 (5.08)
<.001
Smoking
614,255 (47.62)
125,365 (48.24)
<.001
Disposition (%)
<.001
Against medical advice
56,340 (4.37)
9130 (3.51)
Died in hospital
7250 (0.56)
1535 (0.59)
Discharged alive, unknown destination
15 (0)
0 (0)
Home healthcare
68,175 (5.29)
12,650 (4.87)
Routine
1087,154 (84.28)
213,645 (82.21)
Transfer other
46,410 (3.6)
10,220 (3.93)
Transfer to short-term hospital
24,625 (1.91)
12,695 (4.89)
Rural patients were slightly older than their urban counterparts (mean age for females: 54.19 vs 52.36 years; mean age for males: 52.88 vs 50.37 years). Age distribution differed significantly, with rural patients more likely to be ≥70 years old (18.41% vs 15.24%) and less likely to be 18 to 29 years old (7.7% vs 9.61%; P < .001). Rural hospitalizations occurred predominantly among White patients (80.48% vs 60.88%, P < .001), whereas Black (10.45% vs 18.38%) and Hispanic (5.1% vs 14.6%) patients were more commonly treated in urban hospitals. Medicare was the most common insurance among rural patients (36.02% vs 28.44% urban, P < .001), whereas private insurance was more frequent among urban patients (32.61% vs 29.43%). Rural patients had higher rates of hypertension (59.86% vs 57.13%) and diabetes (28.74% vs 27.5%) (both P < .001). Conversely, alcohol abuse (26.35% vs 33.15%) and drug abuse (5.08% vs 6.42%) were more prevalent among urban patients. Obesity rates were similar between groups (18.66% urban vs 18.03% rural, P < .001).
3.2. Mortality and complications
Adjusted outcomes and complication rates are summarized in Table 2 and Figure 1.
Table 2.
In-hospital outcomes, complications, and healthcare utilization among adult hospitalizations with acute pancreatitis comparing rural and urban populations (National Inpatient Sample 2016–2021).
Complications (%)
Urban areas, n (%)
Rural areas, n (%)
Adjusted odds ratio for rural*
95% CI lower limit
95% CI upper limit
P-value
In-hospital mortality
7250 (0.56)
1535 (0.59)
1.38
1.18
1.62
<.001
AKI
154,850 (12)
28,625 (11.01)
1.06
1.01
1.10
.016
Vasopressor use
3115 (0.24)
460 (0.18)
1.55
1.20
2.00
.001
Invasive mechanical ventilation
16,895 (1.31)
3345 (1.29)
1.46
1.32
1.62
<.001
Noninvasive mechanical ventilation
8890 (0.69)
1845 (0.71)
1.37
1.17
1.60
<.001
Hemodialysis
20,940 (1.62)
3145 (1.21)
1.31
1.17
1.46
<.001
Intestinal perforation
610 (0.05)
105 (0.04)
1.58
0.95
2.63
.076
ARDS
4520 (0.35)
960 (0.37)
1.41
1.14
1.74
.002
Acute liver failure
8925 (0.69)
1680 (0.65)
1.27
1.08
1.49
.003
Acute pancreatitis with necrosis
26,040 (2.02)
5100 (1.96)
1.61
1.48
1.76
<.001
Packed red blood cell transfusion
14,915 (1.16)
2865 (1.1)
1.22
1.08
1.39
.002
Mean inflation-adjusted cost ($)
$47,057.99
$33,230.87
—
—
—
.005
Adjusted Mean Inflation-adjusted cost* = $11,343.80 lower for Rural
Mean length of stay (d)
4.31
4.06
<0.001
<0.001
<0.001
<.001
Adjusted length of stay* = 0.32 d lower for Rural
P-trend for in-hospital mortality
.707
Figure 1.
Forest plot of adjusted odds ratios (aORs) and 95% confidence intervals for in-hospital complications comparing rural versus urban hospitalizations with acute pancreatitis (National Inpatient Sample, 2016–2021). The dashed vertical line represents the null value (aOR = 1). Values to the right of the line indicate higher odds of the outcome among rural hospitalizations compared with urban hospitalizations. ARDS = acute respiratory distress syndrome, NIS = National Inpatient Sample, PRBC = packed red blood cells.
Rural hospitalization was associated with higher odds of in-hospital mortality (0.59% vs 0.56%, aOR 1.38, 95% CI: 1.18–1.62, P < .001) and acute kidney injury (11.0% vs 12.0%, aOR 1.06, 95% CI: 1.01–1.10, P = .016). Use of vasopressors (0.18% vs 0.24%, aOR 1.55, 95% CI: 1.20–2.00, P = .001), invasive mechanical ventilation (1.29% vs 1.31%, aOR 1.46, 95% CI: 1.32–1.62, P < .001), and noninvasive ventilation (0.71% vs 0.69%, aOR 1.37, 95% CI: 1.17–1.60, P < .001) were also more likely among rural patients. AKI requiring hemodialysis was more frequent among rural patients compared with urban patients (1.21% vs 1.62%, aOR 1.31, 95% CI: 1.17–1.46, P < .001). There was no statistically significant difference in intestinal perforation between rural and urban hospitalizations (0.04% vs 0.05%, aOR 1.58, 95% CI: 0.95–2.63, P = .076). The likelihood of developing acute respiratory distress syndrome (0.37% vs 0.35%, aOR 1.41, 95% CI: 1.14–1.74, P = .002) and AP with necrosis (1.96% vs 2.02%, aOR 1.61, 95% CI: 1.48–1.76, P < .001) was also higher among rural patients. Rural patients had increased odds of requiring packed red blood cell transfusion (1.10% vs 1.16%, aOR 1.22, 95% CI: 1.08–1.39, P = .002).
3.3. Resource utilization
Rural hospitalizations were associated with a shorter mean length of stay (4.06 vs 4.31 days, adjusted difference −0.32 days, P < .001) and lower mean inflation-adjusted hospitalization costs ($33,230.87 vs $47,057.99, adjusted difference −$11,343.80, P = .005).
4. Discussion
In this large, nationally representative analysis of 1.5 million AP hospitalizations, significant disparities in clinical outcomes, demographics, and healthcare utilization between rural and urban populations in the United States were identified. Our findings highlight inequalities in rural healthcare systems, particularly in the management of high-acuity conditions such as AP.
While older studies have suggested that rural patients had longer hospitalizations because of limited resources, our study revealed a shorter length of stay for the rural population despite the higher complication rates.[6] This is a paradoxical outcome, as shorter hospitalizations usually are not associated with worse outcomes. This may be explained by potential resource constraints in rural hospitals, as patients may be discharged earlier to free up beds. However, this early discharge pattern may lead to incomplete recovery and thus higher rates of readmission, compounding the observed disparities in AP outcomes.[7]
The higher mortality and complication rates among rural patients may be attributed to several factors. First, rural patients were older and had a higher baseline comorbidity burden, including higher rates of hypertension (59.86% vs 57.13%) and diabetes (28.74% vs 27.5%), both of which are known risk factors for increased severity and complications of AP.[8] Furthermore, these comorbidities may contribute to the worse outcomes observed in the rural population. Additionally, limited access to specialized care services, including internal medicine subspecialties such as gastroenterology, interventional radiology (for cases of progression to necrotizing pancreatitis), and intensive care unit level of care in rural settings, may exacerbate these risks.[9–11]
Socioeconomic factors may also play a role in rural versus urban disparities. Rural populations tend to have lower median household incomes and a higher reliance on Medicare, which may affect access to timely care as well as the overall resilience of patients to critical illness.[12] Differences in hospital resources, staffing, and clinical management practices between rural and urban hospitals may also influence outcomes, although these could not be directly assessed in the current study. Lastly, the higher rates of dependency on Medicare and lower income levels in rural areas further contribute to delayed care and a greater likelihood of worsened outcomes due to financial constraints or limited access to preventive healthcare services.[6]
Perhaps the most interesting finding in our study was the paradoxical trend of worse outcomes in the rural population but shorter adjusted length of stay and significantly lower hospitalization costs. As mentioned previously, this may be secondary to early discharges in rural hospitals due to limited bed availability or perhaps financial pressures. Early discharge has been shown to potentially play a role in compromising the recovery process, increasing the likelihood of readmission or post-discharge complications.[13,14] This may also be indicative of systemic disparities and resource allocation, where rural hospitals may prioritize bed turnover over extended patient care.
Our findings in this study emphasized the need for focused interventions to continue addressing these disparities between the rural and urban populations. While efforts to improve access are underway, key tenets of improved outcomes likely depend on access to specialized care through telemedicine, enhanced funding for rural hospitals and incentivization of healthcare providers to practice in rural areas through either financial or benefit-based compensation. Additionally, public health initiatives aimed at alcohol cessation (known to be a primary cause of AP), early diagnosis, and better outpatient management of patients with pancreatitis could help improve outcomes. Continuing to strengthen healthcare infrastructure in rural areas by incorporating strategies to improve social determinants of health may also contribute to better health equity across the rural and urban populations.[15,16]
5. Limitations
Our study has several important limitations. As a retrospective analysis using the NIS, the findings are subject to inherent risks of coding inaccuracies and misclassification bias. The use of administrative International Classification of Diseases codes to identify AP and its complications may not fully capture clinical nuances or distinguish between primary and secondary diagnoses. Additionally, the NIS lacks detailed clinical information, including laboratory values, imaging findings, disease severity scores (such as BISAP or the Revised Atlanta Classification), and the timing of interventions. Key process-of-care factors, including transfer status, access to specialty consultation, procedural interventions, and availability of critical care resources, are also not captured in the database, limiting insights into the mechanisms underlying the observed disparities. Despite adjustment for a wide range of patient demographics, hospital characteristics, and comorbidities, the possibility of residual confounding remains, particularly from unmeasured social determinants of health and prehospital or post-discharge factors. Finally, these findings are specific to hospitalized patients and may not be generalizable to outpatient settings.
6. Conclusion
In this large, nationally representative analysis of AP hospitalizations, rural patients experienced significantly higher odds of severe inpatient complications and in-hospital mortality compared with their urban counterparts, despite having shorter hospital stays and lower hospitalization costs. These findings suggest a greater burden of illness during hospitalization among rural patients and highlight persistent geographic disparities in AP outcomes. While the exact drivers of these differences cannot be determined from administrative data, a higher baseline comorbidity burden and potential differences in access to specialized care may contribute. Further prospective studies incorporating clinical severity assessments and healthcare delivery factors are warranted to better address the underlying causes of these disparities.
Author contributions
Conceptualization: Fatima Rashid, Abu Baker Sheikh.
Data curation: Fatima Rashid, Kasim Syed Jafri, Niloy Ghosh, Humza Saeed, Muhammad Husnain Ahmad, Eyad Mando-Dakkak, Abu Baker Sheikh.
Formal analysis: Fatima Rashid, Kasim Syed Jafri, Niloy Ghosh, Mariam Alamgir, Humza Saeed, Muhammad Husnain Ahmad, Mohammed A. Quazi.
Investigation: Fatima Rashid.
Methodology: Fatima Rashid, Kasim Syed Jafri, Mariam Alamgir, Humza Saeed, Muhammad Husnain Ahmad, Eyad Mando-Dakkak, Mohammed A. Quazi, Amir H. Sohail.
Project administration: Kasim Syed Jafri, Humza Saeed, Muhammad Husnain Ahmad, Eyad Mando-Dakkak, Amir H. Sohail, Abu Baker Sheikh.
Resources: Niloy Ghosh, Abu Baker Sheikh.
Software: Niloy Ghosh, Humza Saeed, Mohammed A. Quazi, Amir H. Sohail, Abu Baker Sheikh.
Validation: Niloy Ghosh, Mariam Alamgir.
Supervision: Mariam Alamgir, Eyad Mando-Dakkak, Amir H. Sohail, Abu Baker Sheikh.
Visualization: Fatima Rashid, Kasim Syed Jafri, Muhammad Husnain Ahmad, Eyad Mando-Dakkak, Abu Baker Sheikh.
Writing – original draft: Fatima Rashid, Kasim Syed Jafri, Niloy Ghosh, Mariam Alamgir, Muhammad Husnain Ahmad, Mohammed A. Quazi, Amir H. Sohail, Abu Baker Sheikh.
Writing – review & editing: Fatima Rashid, Kasim Syed Jafri, Niloy Ghosh, Mariam Alamgir, Humza Saeed, Muhammad Husnain Ahmad, Eyad Mando-Dakkak, Mohammed A. Quazi, Amir H. Sohail, Abu Baker Sheikh.
Abbreviations:
aOR
adjusted odds ratio
AP
acute pancreatitis
ARDS
acute respiratory distress syndrome
CI
confidence interval
NIS
National Inpatient Sample.
The authors have no funding and conflicts of interest to disclose.
The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.
How to cite this article: Rashid F, Jafri KS, Ghosh N, Alamgir M, Saeed H, Ahmad MH, Mando-Dakkak E, Quazi MA, Sohail AH, Sheikh AB. Rural–urban disparities in acute pancreatitis outcomes: A retrospective cohort study using the National Inpatient Sample (2016–2021). Medicine 2026;105:23(e49138).
Contributor Information
Fatima Rashid, Email: fatimasrashid12@gmail.com.
Kasim Syed Jafri, Email: jafri.kasim1@gmail.com.
Niloy Ghosh, Email: nghosh@salud.unm.edu.
Mariam Alamgir, Email: mariam.alamgir02@gmail.com.
Humza Saeed, Email: hamzasaeed309@gmail.com.
Eyad Mando-Dakkak, Email: eyad.mando.dakkak@outlook.com.
Mohammed A. Quazi, Email: mmquazi@hsc.wvu.edu.
Amir H. Sohail, Email: ameer.hamzasohail@gmail.com.
Abu Baker Sheikh, Email: ABSheikh@salud.unm.edu.
References
-
[1].Huang Y, Badurdeen DS. Acute pancreatitis review.
Turk J Gastroenterol. 2023;34:795–801.
[DOI] [PMC free article] [PubMed] [Google Scholar] -
[2].Khetpal N, Sharbatji M, Asfari MM, Ahmad S. Outcomes of acute pancreatitis hospitalizations with obesity.
Dig Dis Sci. 2025;70:1350–9.
[DOI] [PMC free article] [PubMed] [Google Scholar] -
[3].Butt MA, Gangu K, Ghosh N, et al. COVID-19 and acute pancreatitis clinical outcomes among hospitalized patients in the United States: a propensity matched analysis of National Inpatient Sample.
Pancreatology. 2023;23:935–41.
[DOI] [PubMed] [Google Scholar] - [4].Healthcare Cost and Utilization Project – National (Nationwide) Inpatient Sample (HCUP-NIS) – Healthy People 2030. odphp.health.gov. Available at: https://odphp.health.gov/healthypeople/objectives-and-data/data-sources-and-methods/data-sources/healthcare-cost-and-utilization-project-national-nationwide-inpatient-sample-hcup-nis. Accessed January 27, 2026.
-
[5].Cuschieri S. The STROBE guidelines.
Saudi J Anaesth. 2019;13:S31–4.
[DOI] [PMC free article] [PubMed] [Google Scholar] -
[6].Birrell L, McGuinness M, Elliott B, Harmston C. Effect of rurality and ethnicity in severity and outcomes in patients with acute pancreatitis.
ANZ J Surg. 2021;91:1558–62.
[DOI] [PubMed] [Google Scholar] -
[7].Aldhaleei WA, Wallace MB, Bi Y, Rusk AM, Bhagavathula AS. Racial, ethnic, and geographic disparities in digestive diseases mortality in the United States, 2000–2019.
Clin Gastroenterol Hepatol. 2025;23:59–68.e16.
[DOI] [PubMed] [Google Scholar] -
[8].Hidalgo NJ, Pando E, Mata R, et al. Impact of comorbidities on hospital mortality in patients with acute pancreatitis: a population-based study of 110,021 patients.
BMC Gastroenterol. 2023;23:81.
[DOI] [PMC free article] [PubMed] [Google Scholar] -
[9].MacCarthy S, Elliott MN, Martino SC, et al. Rural disparities in the quality of clinical care are notable and larger for males.
J Rural Health. 2023;39:636–42.
[DOI] [PubMed] [Google Scholar] -
[10].Kanter GP, Segal AG, Groeneveld PW. Income disparities in access to critical care services.
Health Aff (Millwood). 2020;39:1362–7.
[DOI] [PubMed] [Google Scholar] -
[11].Khan MA, Shahbaz H, Noorali AA, et al. Disparities in adult critical care resources across Pakistan: findings from a national survey and assessment using a novel scoring system.
Crit Care. 2022;26:209.
[DOI] [PMC free article] [PubMed] [Google Scholar] -
[12].Becker U, Timmermann A, Ekholm O, et al. Social disparity is associated with an increased risk of acute and chronic pancreatitis.
Alcohol Alcohol. 2024;59:agae051.
[DOI] [PubMed] [Google Scholar] - [13].Martinsen MI, de Lima MEB, Rudolph AM. Discharge and post-hospital Care. In: Hertz K, Santy-Tomlinson J, eds. Fragility Fracture and Orthogeriatric Nursing: Holistic Care and Management of the Fragility Fracture and Orthogeriatric Patient. Springer International Publishing; 2024:253–69. [Google Scholar]
-
[14].Sindayigaya R, Tribillon E, Ghedira A, et al. Predictors of discharge timing and unplanned readmission after laparoscopic liver resection.
HPB (Oxford). 2022;24:708–16.
[DOI] [PubMed] [Google Scholar] -
[15].de Souza CHA, Morbeck RA, Steinman M, et al. Barriers and benefits in telemedicine arising between a high-technology hospital service provider and remote public healthcare units: a qualitative study in Brazil.
Telemed J E Health. 2017;23:527–32.
[DOI] [PubMed] [Google Scholar] -
[16].Ramesh T, Klompas M, Yu H. Improving rural intensive care infrastructure in the USA.
Lancet Respir Med. 2024;12:268–9.
[DOI] [PMC free article] [PubMed] [Google Scholar]
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