This cohort study evaluates postsurgical outcomes among Medicare beneficiaries with rural vs nonrural residence undergoing common surgical procedures.
Key Points
Question
Do postoperative outcomes differ between rural and nonrural Medicare beneficiaries undergoing common inpatient general surgery operations?
Findings
In this national cohort study of 2 317 497 beneficiaries, rural residence was associated with significantly higher 30-day mortality, in-hospital mortality, complications, and 30-day readmissions even after risk adjustment for patient, hospital, and secular factors. These disparities persisted regardless of whether surgery occurred at rural or nonrural hospitals.
Meaning
Rural residence was independently associated with worse surgical outcomes, suggesting that upstream structural barriers are an important driver of surgical inequities in the rural population.
Abstract
Importance
Rural hospital-level surgical quality has been extensively evaluated. However, rural people in the US face growing inequities in care, and quality of surgical care experienced by rural patients nationally remains poorly defined.
Objective
To evaluate surgical quality among rural vs nonrural Medicare beneficiaries undergoing common general surgery procedures.
Design, Setting, and Participants
This retrospective cohort study used 100% Medicare inpatient claims linked with the American Hospital Association Annual Survey between 2016 and 2023. The cohort included beneficiaries aged 65 to 99 years who underwent admission for appendectomy, cholecystectomy, colectomy, or incisional hernia repair. This analysis was undertaken between August and October 2025.
Exposure
Rural vs nonrural residence, defined using Rural-Urban Commuting Area codes based on patient home zip code (1-3: nonrural; 4-10: rural).
Main Outcomes and Measures
Risk-adjusted 30-day mortality, in-hospital mortality, complications, 30-day readmission, discharge disposition, and hospital length of stay. Multivariable logistic regression models adjusted for patient factors, hospital factors, and year of surgery.
Results
Among 2 317 497 beneficiaries (55.5% female; mean [SD] age, 75.2 [7.2] years), 462 358 (19.9%) were rural. Rural patients were more often male (46.4% vs 44.1%) and traveled longer for surgery (median, 45.0 [IQR, 22.0-77.0] minutes vs 20.0 [IQR, 13.0-31.0] minutes). Rural patients had higher adjusted 30-day mortality (6.78% [95% CI, 6.65%-6.90%] vs 5.84% [95% CI, 5.76%-5.93%]; odds ratio [OR], 1.21 [95% CI, 1.18-1.24]; P < .001), in-hospital mortality (3.65% [95% CI, 3.56%-3.74%] vs 3.20% [95% CI, 3.14%-3.25%]; OR, 1.17 [95% CI, 1.14-1.21]; P < .001), and 30-day readmission (14.31% [95% CI, 14.14%-14.48%] vs 13.57% [95% CI, 13.45%-13.69%]; OR, 1.07 [95% CI, 1.05-1.08]; P < .001). Complication rates were higher (29.31% [95% CI, 29.04%-29.57%] vs 28.58% [95% CI, 28.40%-28.76%]; OR, 1.05 [95% CI, 1.03-1.07]; P < .001). Rural patients were less likely to be discharged home (75.56% [95% CI, 75.24%-75.88%] vs 77.61% [95% CI, 77.36%-77.86%]; OR, 0.85 [95% CI, 0.83-0.88]; P < .001) and more likely to be transferred to another facility (1.40% [95% CI, 1.33%-1.47%] vs 0.70% [95% CI, 0.67%-0.73%]; OR, 2.04 [95% CI, 1.92-2.17]; P < .001).
Conclusions and Relevance
In this cohort study of Medicare beneficiaries undergoing common general surgery procedures, rural residence was independently associated with worse clinical outcomes across most measures. These findings identify significant opportunities for quality improvement focused on common rural surgical needs.
Introduction
People living in rural areas of the US face growing inequities in obtaining surgical care. Decades of hospital closures, growing workforce shortages, care centralization efforts, and declining procedural volume have eroded the local capacity to deliver common operations, forcing many rural residents to travel long distances for essential surgical care.1,2,3,4,5,6 However, numerous federal policy responses have attempted to stabilize this fragile infrastructure, including creating new hospital designations such as critical access hospitals (CAHs) and rural emergency hospitals and, more recently, the creation of the $50 billion rural health transformation fund.7 Despite these ongoing initiatives to preserve care locally, half of rural patients bypass their nearest surgery-capable hospital to undergo surgery at more distant facilities, and traveling greater distances is associated with lower-quality surgical care.8,9,10
Quality of surgical care for rural patients has been predominately evaluated at the hospital level (eg, rural vs nonrural hospitals) rather than the patient level (eg, rural vs nonrural patients). We have growing evidence that when patients receive their care at small rural hospitals, they often have similar surgical outcomes to those of nonrural hospitals for commonly performed operations.11,12,13,14,15 However, many rural patients do not receive their care locally, with half or more patients bypassing their nearby hospitals even for low-risk operations like cholecystectomy or incisional hernia repair.8,9,16 As such, we have a much more limited understanding of surgical quality for rural patients more broadly. Existing research at the patient level with rural residence as the primary exposure has been limited to a narrow set of conditions or nongeneralizable geography.17,18,19,20,21 Nonetheless, concern has been raised that rural residents, regardless of where they receive their care, experience worse surgical outcomes. Whether or not these concerns are generalizable to a broad community of rural US residents across common surgical conditions is currently unclear.
In this context, we sought to evaluate surgical quality among rural vs nonrural Medicare beneficiaries who underwent admission for common general surgery procedures (appendectomy, cholecystectomy, colectomy, or incisional hernia repair) using contemporary Medicare claims data. These findings are particularly timely as leaders decide how to most effectively disperse much of the $50 billion rural health transformation fund to best serve rural patients.
Methods
Data Sources and Cohort
In this cohort study, we used 100% of claims from the Centers for Medicare & Medicaid Services (CMS) Medicare Provider Analysis and Review (MEDPAR) file between 2016 and 2023. Beneficiary claims in the MEDPAR file were linked to hospital data where beneficiaries underwent admission for surgery using corresponding years of American Hospital Association (AHA) Annual Survey data, which were linked to claims using unique hospital identification codes. The University of Michigan institutional review board deemed this study exempt from approval and informed consent due to our use of retrospective deidentified claims data. Our study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.22
Patient-level datapoints from claims data included beneficiary age, sex, home zip code, race and ethnicity, Elixhauser comorbidities, admission type, discharge disposition, and whether the beneficiary was enrolled in Medicare Advantage (MA) or in traditional fee-for-service Medicare. Race and ethnicity data, included because these are typically reported in health services research, were abstracted from Medicare enrollment data derived from administrative records maintained by CMS. Categories were Asian, Black, Hispanic, Native American, White, and other (refers to individuals not classified into 1 of the other aforementioned race and ethnicity categories abstracted by CMS). Hospital-level datapoints, included to characterize the facility where beneficiaries obtained care, included hospital bed capacity, hospital zip code, region in which the hospital was located, teaching hospital designation status, and patient-to-nurse ratio.
We included all beneficiaries in the MEDPAR file who were aged 65 to 99 years and underwent admission for 1 of 4 common general surgery operations: appendectomy, cholecystectomy, colectomy, or incisional hernia repair. These 4 procedures have been frequently used to evaluate outcomes from common operations and have also been extensively evaluated in rural hospital cohorts. Our coding strategy to identify these 4 procedures is outlined in eTable 1 in Supplement 1. Any beneficiaries with claims that had incomplete information for variables we included in our study were removed from our analysis.
Exposure
The primary exposure for comparison in our study was to evaluate surgical quality among rural vs nonrural beneficiaries. We used Rural-Urban Commuting Area (RUCA) codes cross-walked from beneficiary home zip codes to identify rural and nonrural beneficiaries who underwent admission for common general surgery procedures. Beneficiaries with RUCA scores 1 to 3 were designated nonrural and 4 to 10 were designated rural.
Variables and Outcomes
Admission types in MEDPAR are coded as being elective, urgent, or emergent. First, we collapsed urgent and emergent admissions into unplanned admissions for surgery as has been done previously.6,9,14,23 Enrollment in MA plans was determined by beneficiary enrollment in Medicare Part C during the month of the beneficiary’s operation within the MEDPAR file. We determined dual eligibility enrollment status in Medicare and Medicaid using the Medicare Master Beneficiary Summary File. To estimate travel time for rural and nonrural beneficiaries, we used zip code centroids based on beneficiary home zip codes and zip codes of the hospitals where they underwent surgery. We then used a Google Maps plugin in SAS, version 9.4M9 (SAS Institute Inc), to estimate driving travel time between these 2 zip code centroids, as our group has done previously.3,9,15 To identify rural hospitals, we used hospital location zip codes from the AHA Annual Survey and corresponding RUCA codes. To identify CAHs, we used a binary indicator in the AHA Annual Survey data and confirmed this with CMS certification numbers (CAH numbers end in 13xx).
The main clinical outcomes we sought to evaluate in this analysis included 30-day mortality, in-hospital mortality, complications, serious complications, and 30-day readmissions. We also evaluated hospital length of stay and discharge disposition. The beneficiary denominator file was used to ascertain 30-day mortality following discharge from the index hospitalization for surgery. We identified in-hospital mortality based on patient vital status at the time of discharge. Complications evaluated in this study included pulmonary failure, pneumonia, myocardial infarction, deep venous thromboembolism, acute kidney failure, hemorrhage, surgical site infection, and gastrointestinal bleeding, which were identified using International Statistical Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes. Beneficiaries with a complication were coded as such if they had 1 or more of these documented complications. Patients with serious complications were defined as those who had 1 of the 8 previously mentioned complications and had an index hospital length of stay above the 75th percentile based on the average length of hospital stay for each of the 4 procedures. Patients who were transferred to another inpatient facility had their outcomes attributed to the hospital where they received their operation. We categorized discharge disposition into any home discharge, home with home health, skilled nursing facility or rehabilitation, transfer, hospice, or other, as has been done previously.23,24 The “other” category represents numerous alternative dispositions that are encountered substantially less often and are less relevant for surgical cohorts.25
Statistical Analysis
The overall goal of this analysis was to compare outcomes from common general surgery procedures among rural vs nonrural patients. We used a series of multivariable logistic regression models to estimate risk-adjusted surgical outcomes among rural vs nonrural beneficiaries who underwent admission for common general surgery procedures. We used marginal effects from our regressions to estimate rates of risk-adjusted outcomes (eg, 30-day mortality) and compared the groups using odds ratios (ORs). Models in our primary analysis were risk-adjusted to account for patient characteristics (sex, age, Elixhauser comorbidities, admission type, and procedure type), hospital characteristics (patient-to-nurse ratio and teaching hospital status), and year of surgery.26,27
For our subgroup analyses within each procedure group, we ran these models similarly but removed procedure type as a covariate. We also performed sensitivity analyses to evaluate differences in rural vs nonrural beneficiary outcomes who had elective admissions or unplanned admissions. In these analyses, admission type was removed as a covariate from our models. In addition, to better understand associations with outcomes for beneficiaries based on where they obtained care, we compared risk-adjusted outcomes using the same approach as in our primary analysis but separated rural beneficiaries based on whether they underwent surgery at a rural or nonrural hospital and compared them with a reference population of beneficiary patients who were nonrural and received surgery at a nonrural hospital.
Statistical analyses were performed using SAS, version 9.4, and Stata, version 19 (Stata Corp LLC). All statistical tests were 2-tailed, and P < .05 was used as our threshold for statistical significance. This analysis was undertaken between August and October 2025.
Results
Patient and Hospital Characteristics
A total of 2 317 497 Medicare beneficiaries (462 358 [19.9%] rural) underwent a common general surgery procedure between 2016 and 2023. Mean (SD) beneficiary age was 75.2 (7.2) years; 44.5% were men and 55.5% were women. The study population was 1.7% Asian, 8.4% Black, 2.6% Hispanic, 0.5% Native American, 85.1% White, and 1.8% other race and ethnicity. Compared with nonrural beneficiaries, rural beneficiaries were more often male (46.4% vs 44.1%) and White (91.8% vs 83.5%), had slightly fewer documented comorbidities (78.6% vs 79.5% had ≥2 Elixhauser comorbidities), and were more likely to be admitted for elective surgery (42.3% vs 38.9%). Rural patients experienced substantially longer travel times to the treating hospital (median, 45.0 minutes [IQR, 22.0-77.0 minutes] vs 20.0 minutes [IQR, 13.0-31.0 minutes]). Other beneficiary demographics are summarized in Table 1 and eTable 2 in Supplement 1.
Table 1. Patient Characteristics of Rural vs Nonrural Medicare Beneficiaries Who Underwent Common General Surgery Procedures Between 2016 and 2023.
| Characteristic | Patients, No. (%) | P value | ||
|---|---|---|---|---|
| Total (N = 2 317 497) | Rural (N = 462 358) | Nonrural (N = 1 855 139) | ||
| Age, mean (SD), y | 75.2 (7.2) | 75.1 (7.1) | 75.2 (7.2) | <.001 |
| Sex | ||||
| Men | 1 032 038 (44.5) | 214 305 (46.4) | 817 733 (44.1) | <.001 |
| Women | 1 285 459 (55.5) | 284 053 (53.6) | 1 037 406 (55.9) | <.001 |
| Race and ethnicity | ||||
| Asian | 38 682 (1.7) | 1013 (0.2) | 37 669 (2.0) | <.001 |
| Black | 194 490 (8.4) | 23 342 (5.0) | 171 148 (9.2) | <.001 |
| Hispanic | 59 318 (2.6) | 4283 (0.9) | 55 035 (3.0) | <.001 |
| Native American | 11 209 (0.5) | 6000 (1.3) | 5209 (0.3) | <.001 |
| White | 1 973 062 (85.1) | 424 401 (91.8) | 1 548 661 (83.5) | <.001 |
| Othera | 40 736 (1.8) | 3319 (0.7) | 37 417 (2.0) | <.001 |
| Elixhauser comorbidities, No.b | ||||
| 0 | 146 939 (6.3) | 30 807 (6.7) | 116 132 (6.3) | <.001 |
| 1 | 333 003 (14.4) | 68 112 (14.7) | 264 891 (14.3) | <.001 |
| ≥2 | 1 837 555 (79.3) | 363 439 (78.6) | 1 474 116 (79.5) | <.001 |
| Discharge disposition | ||||
| Home (any) | 1 789 200 (77.2) | 352 510 (76.2) | 1 436 690 (77.4) | <.001 |
| Home health | 450 425 (19.4) | 77 362 (16.7) | 373 063 (20.1) | <.001 |
| SNF or rehabilitation | 390 053 (16.8) | 73 067 (15.8) | 316 986 (17.1) | <.001 |
| Transferred | 19 826 (0.9) | 7360 (1.6) | 12 466 (0.7) | <.001 |
| Otherc | 90 134 (3.9) | 24 236 (5.2) | 65 898 (3.6) | <.001 |
| Hospice | 28 284 (1.2) | 5185 (1.1) | 23 099 (1.2) | <.001 |
| Admission type | ||||
| Elective | 916 328 (39.5) | 195 430 (42.3) | 720 898 (38.9) | <.001 |
| Unplanned | 1 401 169 (60.5) | 266 928 (57.7) | 1 134 241 (61.1) | <.001 |
| Type of operation | ||||
| Appendectomy | 182 278 (7.9) | 34 041 (7.4) | 148 237 (8.0) | <.001 |
| Cholecystectomy | 795 937 (34.3) | 155 467 (33.6) | 640 470 (34.5) | <.001 |
| Colectomy | 965 175 (41.6) | 201 300 (43.5) | 763 875 (41.2) | <.001 |
| Incisional hernia repair | 374 107 (16.1) | 71 550 (15.5) | 302 557 (16.3) | <.001 |
| Insurance type | ||||
| Medicare Advantage | 912 319 (39.4) | 140 832 (30.5) | 771 487 (41.6) | <.001 |
| Dual eligible | 364 710 (15.7) | 73 392 (15.9) | 291 318 (15.7) | .004 |
| Travel time to surgical site, min | ||||
| Median (IQR) | 22.0 (13.0-39.0) | 45.0 (22.0-77.0) | 20.0 (13.0-31.0) | <.001 |
| <30 | 1 491 943 (64.4) | 151 365 (32.7) | 1 340 578 (72.3) | <.001 |
| 30-60 | 512 926 (22.1) | 145 654 (31.5) | 367 272 (19.8) | <.001 |
| >60 | 312 628 (13.5) | 165 339 (35.8) | 147 289 (7.9) | <.001 |
Abbreviation: SNF, skilled nursing facility.
Refers to individuals not classified into 1 of the other categories abstracted by the Centers for Medicare & Medicaid Services.
Specific Elixhauser comorbidities are referenced in eTable 2 in Supplement 1.
Represents alternative dispositions that are encountered substantially less often and are less relevant for surgical cohorts.
Hospitals caring for rural vs nonrural beneficiaries were smaller (51.2% vs 31.0% had <250 beds) and were less often teaching facilities (68.5% vs 82.2%). Nearly half of rural patients received surgery at a rural hospital (42.8%), 4.9% of which were at a CAH, compared with 1.5% and 0.2%, respectively, among nonrural patients. Other hospital demographics are summarized in Table 2.
Table 2. Hospital Characteristics Where Rural vs Nonrural Medicare Beneficiaries Underwent Admission for Common General Surgery Procedures.
| Characteristic | Patients, No. (%) | P value | ||
|---|---|---|---|---|
| Total (N = 2 317 497) | Rural (N = 462 358) | Nonrural (N = 1 855 139) | ||
| Hospital size, beds, No. | ||||
| 1-49 | 62 828 (2.7) | 41 047 (8.9) | 21 781 (1.2) | <.001 |
| 50-149 | 316 537 (13.7) | 107 542 (23.3) | 208 995 (11.3) | <.001 |
| 150-249 | 432 183 (18.6) | 87 972 (19.0) | 344 211 (18.6) | <.001 |
| 250-499 | 812 014 (35.0) | 117 664 (25.4) | 694 350 (37.4) | <.001 |
| ≥500 | 693 935 (29.9) | 108 133 (23.4) | 585 802 (31.6) | <.001 |
| Hospital region | ||||
| Northeast | 387 546 (16.7) | 45 210 (9.8) | 342 336 (18.5) | <.001 |
| Midwest | 518 407 (22.4) | 149 835 (32.4) | 368 572 (19.9) | <.001 |
| South | 949 506 (41.0) | 195 671 (42.3) | 753 835 (40.6) | <.001 |
| West | 462 038 (19.9) | 71 642 (15.5) | 390 396 (21.0) | <.001 |
| Teaching hospital | 1 840 810 (79.4) | 316 767 (68.5) | 1 524 043 (82.2) | <.001 |
| Patient-to-nurse ratio | 9.4 (4.1) | 10.5 (5.5) | 9.1 (3.6) | <.001 |
| Critical access hospital | 27 415 (1.2) | 22 795 (4.9) | 4620 (0.2) | <.001 |
| Rural hospital | 225 523 (9.7) | 197 900 (42.8) | 27 623 (1.5) | <.001 |
Risk-Adjusted Outcomes
After adjustment for patient, hospital, and temporal factors, rural beneficiaries had significantly worse outcomes across most measures. The adjusted 30-day mortality rate was 6.78% (95% CI, 6.65%-6.90%) for rural vs 5.84% (95% CI, 5.76%-5.93%) for nonrural patients (OR, 1.21; 95% CI, 1.18-1.24; P < .001) (Figure). In-hospital mortality followed a similar pattern (3.65% [95% CI, 3.56%-3.74%] vs 3.20% [95% CI, 3.14%-3.25%]; OR, 1.17; 95% CI, 1.14-1.21; P < .001). Overall complication rates were modestly higher for rural beneficiaries (29.31% [95% CI, 29.04%-29.57%] vs 28.58% [95% CI, 28.40%-28.76%]; OR, 1.05; 95% CI, 1.03-1.07; P < .001), whereas rates of serious complications were slightly lower (13.58% [95% CI, 13.36%-13.80%] vs 13.96% [95% CI, 13.81%-14.11%]; OR, 0.96; 95% CI, 0.93-0.98; P = .001). Thirty-day readmissions were more frequent among rural patients (14.31% [95% CI, 14.14%-14.48%] vs 13.57% [95% CI, 13.45%-13.69%]; OR, 1.07; 95% CI, 1.05-1.08; P < .001). When examined by procedure, our findings were similar to our overall primary analysis (Table 3 and Figure).
Figure. Bar Graph Showing Risk-Adjusted 30-Day Mortality Among Rural vs Nonrural Medicare Beneficiaries After Undergoing Common General Surgery Procedures.
Table 3. Comparison of Risk-Adjusted Outcomes Among Rural vs Nonrural Medicare Beneficiaries Who Underwent Common General Surgery Procedures.
| Outcome | Risk-adjusted rate (95% CI), %a | Odds ratio (95% CI) | P value | |
|---|---|---|---|---|
| Rural patients | Nonrural patients | |||
| All procedures | ||||
| Mortality | ||||
| 30 d | 6.78 (6.65-6.90) | 5.84 (5.76-5.93) | 1.21 (1.18-1.24) | <.001 |
| In-hospital | 3.65 (3.56-3.74) | 3.20 (3.14-3.25) | 1.17 (1.14-1.21) | <.001 |
| Complications | ||||
| Any | 29.31 (29.04-29.57) | 28.58 (28.40-28.76) | 1.05 (1.03-1.07) | <.001 |
| Any serious | 13.58 (13.36-13.80) | 13.96 (13.81-14.11) | 0.96 (0.93-0.98) | .001 |
| Readmissions, 30 d | 14.31 (14.14-14.48) | 13.57 (13.45-13.69) | 1.07 (1.05-1.08) | <.001 |
| Appendectomy | ||||
| Mortality | ||||
| 30 d | 3.42 (3.22-3.62) | 2.86 (2.77-2.96) | 1.23 (1.14-1.33) | <.001 |
| In-hospital | 1.62 (1.48-1.75) | 1.45 (1.38-1.52) | 1.13 (1.01-1.25) | .03 |
| Complications | ||||
| Any | 24.95 (24.47-25.42) | 24.34 (24.09-24.60) | 1.04 (1.01-1.08) | .02 |
| Any serious | 10.64 (10.30-10.97) | 10.53 (10.35-10.71) | 1.02 (0.96-1.07) | .57 |
| Readmissions, 30 d | 11.40 (11.03-11.78) | 10.51 (10.33-10.68) | 1.10 (1.05-1.15) | <.001 |
| Cholecystectomy | ||||
| Mortality | ||||
| 30 d | 3.92 (3.80-4.05) | 3.26 (3.18-3.34) | 1.24 (1.19-1.29) | <.001 |
| In-hospital | 1.58 (1.50-1.66) | 1.41 (1.36-1.45) | 1.13 (1.07-1.20) | <.001 |
| Complications | ||||
| Any | 27.54 (27.20-27.88) | 26.64 (26.42-26.86) | 1.06 (1.04-1.08) | <.001 |
| Any serious | 11.83 (11.58-12.08) | 12.18 (12.01-12.35) | 0.96 (0.93-0.99) | .01 |
| Readmissions, 30 d | 12.80 (12.59-13.02) | 12.15 (12.03-12.28) | 1.06 (1.04-1.09) | <.001 |
| Colectomy | ||||
| Mortality | ||||
| 30 d | 10.13 (9.94-10.32) | 8.87 (8.74-8.99) | 1.20 (1.17-1.24) | <.001 |
| In-hospital | 5.90 (5.76-6.05) | 5.20 (5.11-5.30) | 1.17 (1.13-1.21) | <.001 |
| Complications | ||||
| Any | 30.88 (30.57-31.19) | 30.54 (30.33-30.74) | 1.02 (1.00-1.05) | .03 |
| Any serious | 15.07 (14.82-15.32) | 15.89 (15.72-16.06) | 0.92 (0.89-0.94) | <.001 |
| Readmissions, 30-d | 15.99 (15.77-16.21) | 15.17 (15.02-15.31) | 1.07 (1.05-1.09) | <.001 |
| Incisional hernia repair | ||||
| Mortality | ||||
| 30 d | 5.75 (5.55-5.95) | 5.02 (4.91-5.13) | 1.18 (1.13-1.24) | <.001 |
| In-hospital | 3.13 (2.98-3.29) | 2.69 (2.61-2.76) | 1.19 (1.13-1.26) | <.001 |
| Complications | ||||
| Any | 30.82 (30.43-31.21) | 29.82 (29.59-30.04) | 1.07 (1.04-1.10) | <.001 |
| Any serious | 14.75 (14.42-15.08) | 14.48 (14.29-14.67) | 1.03 (0.99-1.07) | .10 |
| Readmissions, 30 d | 14.58 (14.27-14.90) | 14.18 (14.01-14.35) | 1.03 (1.01-1.06) | .02 |
Risk-adjusted rates were estimated based on marginal effects of multivariable logistic regression models.
Rural vs nonrural beneficiaries were less likely to be discharged directly home (75.56% [95% CI, 75.24%-75.88%] vs 77.61% [95% CI, 77.36%-77.86%]; OR, 0.85; 95% CI, 0.83-0.88; P < .001) and more likely to be transferred to another facility (1.40% [95% CI, 1.33%-1.47%] vs 0.70% [95% CI, 0.67%-0.73%]; OR, 2.04; 95% CI, 1.92-2.17; P < .001). Rural beneficiaries were also significantly less likely to be to be discharged to home with home health (16.87% [95% CI, 16.39%-17.35%] vs 20.07% [95% CI, 19.61%-20.53%]; OR, 0.80; 95% CI, 0.77-0.84; P < .001) or to rehabilitation and skilled nursing facilities (16.46% [95% CI, 16.18%-16.74%] vs 16.92% [95% CI, 16.71%-17.13%]; OR, 0.96; 95% CI, 0.94-0.99; P = .002). Other disposition measures and procedure-specific findings are summarized in Table 4.
Table 4. Comparison of Risk-Adjusted Discharge Disposition Expressed as Percentage Among Rural vs Nonrural Medicare Beneficiaries Who Underwent Common General Surgery Procedures.
| Discharge disposition | Risk-adjusted rate (95% CI), %a | OR (95% CI) | P value | |
|---|---|---|---|---|
| Rural patients | Nonrural patients | |||
| All cohorts | ||||
| Discharge to home (any) | 75.56 (75.24-75.88) | 77.61 (77.36-77.86) | 0.85 (0.83-0.88) | <.001 |
| Discharge to home health | 16.87 (16.39-17.35) | 20.07 (19.61-20.53) | 0.80 (0.77-0.84) | <.001 |
| Discharge to SNF or rehabilitation | 16.46 (16.18-16.74) | 16.92 (16.71-17.13) | 0.96 (0.94-0.99) | .002 |
| Discharge or transfer to another facility | 1.40 (1.33-1.47) | 0.70 (0.67-0.73) | 2.04 (1.92-2.17) | <.001 |
| Discharge to hospice | 1.21 (1.16-1.26) | 1.22 (1.19-1.26) | 0.99 (0.94-1.04) | .65 |
| Appendectomy | ||||
| Discharge to home (any) | 84.45 (84.02-84.88) | 86.57 (86.33-86.81) | 0.80 (0.76-0.84) | <.001 |
| Discharge to home health | 12.27 (11.72-12.81) | 15.22 (14.81-15.62) | 0.77 (0.73-0.82) | <.001 |
| Discharge to SNF or rehabilitation | 10.84 (10.46-11.22) | 10.52 (10.31-10.74) | 1.04 (0.99-1.10) | .14 |
| Discharge or transfer to another facility | 1.06 (0.94-1.17) | 0.45 (0.41-0.49) | 2.38 (2.07-2.74) | <.001 |
| Discharge to hospice | 0.67 (0.58-0.77) | 0.66 (0.62-0.71) | 1.02 (0.87-1.19) | .84 |
| Cholecystectomy | ||||
| Discharge to home (any) | 80.84 (80.50-81.17) | 82.91 (82.67-83.15) | 0.84 (0.82-0.87) | <.001 |
| Discharge to home health | 13.38 (12.93-13.83) | 16.92 (16.48-17.36) | 0.75 (0.72-0.78) | <.001 |
| Discharge to SNF or rehabilitation | 13.50 (13.21-13.79) | 13.80 (13.59-14.01) | 0.97 (0.94-1.00) | .06 |
| Discharge or transfer to another facility | 1.85 (1.73-1.97) | 0.87 (0.82-0.91) | 2.16 (2.01-2.33) | <.001 |
| Discharge to hospice | 0.72 (0.67-0.77) | 0.67 (0.64-0.70) | 1.08 (0.99-1.17) | .07 |
| Colectomy | ||||
| Discharge to home (any) | 69.32 (68.94-69.70) | 71.44 (71.15-71.73) | 0.86 (0.83-0.88) | <.001 |
| Discharge to home health | 19.85 (19.31-20.40) | 22.86 (22.37-23.35) | 0.83 (0.80-0.87) | <.001 |
| Discharge to SNF or rehabilitation | 19.77 (19.43-20.11) | 20.49 (20.24-20.74) | 0.95 (0.92-0.97) | <.001 |
| Discharge or transfer to another facility | 1.23 (1.15-1.30) | 0.64 (0.61-0.68) | 1.94 (1.80-2.08) | <.001 |
| Discharge to hospice | 1.78 (1.70-1.87) | 1.87 (1.81-1.93) | 0.95 (0.90-1.00) | .07 |
| Incisional hernia repair | ||||
| Discharge to home (any) | 76.52 (76.07-76.97) | 77.79 (77.49-78.09) | 0.91 (0.88-0.94) | <.001 |
| Discharge to home health | 18.45 (17.76-19.14) | 22.03 (21.37-22.68) | 0.80 (0.76-0.84) | <.001 |
| Discharge to SNF or rehabilitation | 16.67 (16.26-17.07) | 17.54 (17.28-17.81) | 0.93 (0.90-0.96) | <.001 |
| Discharge or transfer to another facility | 1.01 (0.93-1.09) | 0.59 (0.56-0.63) | 1.72 (1.56-1.90) | <.001 |
| Discharge to hospice | 1.04 (0.96-1.12) | 1.00 (0.96-1.05) | 1.04 (0.95-1.14) | .37 |
Abbreviations: OR, odds ratio; SNF, skilled nursing facility.
Risk-adjusted measures were estimated based on marginal effects of multivariable logistic regression models.
Mean length of stay was similar for rural vs nonrural patients overall (7.39 [95% CI, 7.32-7.47] days vs 7.45 [95% CI, 7.38-7.51] days; absolute difference, −0.05 [95% CI, −0.19 to 0.09] days; P = .17) and for colectomy (8.91 [95% CI, 8.82-9.00] days vs 8.98 [95% CI, 8.90-9.05] days; absolute difference, −0.07 [95% CI, −0.23 to 0.10] days; P = .15) and incisional hernia repair (7.44 [95% CI, 7.33-7.54] days vs 7.37 [95% CI, 7.29-7.46] days; absolute difference, 0.06 [95% CI, −0.13 to 0.25] days; P = .20) procedures. However, length of stay was significantly longer for rural vs nonrural patients undergoing appendectomy (5.78 [95% CI, 5.71-5.86] days vs 5.59 [95% CI, 5.54-5.65] days; absolute difference, 0.19 [95% CI, 0.06-0.32] days; P < .001) and shorter for rural vs nonrural patients undergoing cholecystectomy (5.89 [95% CI, 5.82-5.96] days vs 6.04 [95% CI, 5.98-6.11] days; absolute difference, −0.15 [−0.29 to −0.02] days; P < .001).
Sensitivity Analyses
In sensitivity analyses stratified by admission type, rural patients again had higher adjusted mortality and readmission rates (eTables 3 and 4 in Supplement 1). Among elective admissions, 30-day mortality was 3.03% (95% CI, 2.92%-3.14%) for rural vs 2.46% (95% CI, 2.39%-2.53%) for nonrural patients (OR, 1.27; 95% CI, 1.22-1.33; P < .001); in unplanned admissions, mortality was 9.15% (95% CI, 8.99%-9.32%) vs 8.07% (95% CI, 7.96%-8.18%) (OR, 1.18; 95% CI, 1.15-1.21; P < .001). Patterns in discharge disposition and length of stay were similarly consistent across both strata (eTables 5 and 6 in Supplement 1). Notably, the magnitude of differences between rural and nonrural patient outcomes was greater in the unplanned admission cohort. In addition, in stratified analyses that jointly examined patient and hospital rurality, rural beneficiaries had worse outcomes than nonrural beneficiaries across nearly all measures, regardless of whether surgery was performed at a rural or nonrural hospital (eTable 7 in Supplement 1).
Discussion
This study of rural vs nonrural Medicare beneficiaries who underwent admission between 2016 and 2023 for common general surgery procedures had 3 principal findings. First, rural beneficiaries had fewer documented comorbidities and more frequently received elective admissions for surgery compared with their nonrural counterparts. Second, rural beneficiaries had significantly worse risk-adjusted outcomes across most measures. Specifically, rural beneficiaries had significantly higher rates of 30-day mortality, in-hospital mortality, complications, and 30-day readmissions. Third, rural beneficiaries were less likely to be discharged with home health or to a rehabilitation facility, despite having similar hospital length of stay as nonrural beneficiaries. Taken together, these findings provide contemporary evidence that highlights the persistent challenges of delivering high-quality surgical care to rural patients amid a uniquely complex policy environment and rapidly evolving hospital landscape.
Prior patient-level analyses of surgical care by rurality have been limited to specific procedures or limited geography. For example, studies of emergency general surgery have found higher complication and mortality rates among rural residents, particularly those requiring transfer to larger centers.17,18 Geospatial analyses further showed that rural patients faced reduced spatial access to hospitals capable of performing emergency operations and were more likely to bypass their nearest hospital for common elective procedures.16,28,29 In contrast, several condition-specific studies, such as of colorectal surgery, have found smaller or inconsistent differences once adjusted for patient and hospital characteristics.19,20,30 Similar disparities have been described for other surgical conditions, including higher postoperative complications and limb loss after lower-extremity bypass and longer time to surgery and worse survival for rural women with breast cancer.21,31 Together, these investigations indicate that geography meaningfully influences access to and quality of surgical care but that existing evidence remains fragmented and procedure-specific. Our study extends this literature by providing a contemporary, national analysis of multiple commonly performed general surgery procedures among Medicare beneficiaries, demonstrating persistent disparities in postoperative mortality and readmission associated with rural residence.
These findings also highlight a paradox within rural surgical care: hospitals designated as CAHs and other rural facilities have consistently demonstrated the ability to deliver safe, high-quality surgical care, yet rural patients overall continue to experience worse outcomes. Prior national analyses of CAHs have shown mortality and complication rates comparable to larger hospitals when procedures are performed locally, although these facilities generally treat less complex, lower-acuity patients.11,13,14 Our stratified sensitivity analysis helped reconcile this divergence where we found rural patients experienced worse outcomes than nonrural patients, regardless of where they received surgery. These findings point toward upstream structural factors, such as travel burden, delayed presentation, and fragmented care, to which rural residents may be more prone prior to and after receiving care for surgery.3,32 While hospital bypass may also be associated with higher morbidity and mortality in some settings, as has been described previously,8,9 bypass alone likely does not fully explain the persistent rural disparity observed in our cohort. This finding was supported by our sensitivity analysis given that we observed rural patients experienced worse clinical outcomes following surgery, regardless of the site where they obtained care (eTable 7 in Supplement 1). Collectively, these findings highlight that improving surgical quality for rural patients will require addressing upstream structural barriers that impede access, care coordination, and recovery support rather than modulating the setting where rural patients receive care.
These findings have important implications for the future of rural surgical care. The rural health delivery landscape is undergoing rapid transformation, marked by accelerating hospital closures, private equity acquisitions, and the expanding use of the Rural Emergency Hospital designation, which removes inpatient surgical capacity in exchange for financial stabilization.33,34,35,36,37,38,39 At the same time, recent analyses have shown a sharp rise in urban hospitals taking advantage of rural hospital subsidies (eg, sole community hospital status, rural referral center status, or Medicare-dependent small rural hospital status) to access the enhanced reimbursements and policy advantages intended to support financially struggling rural facilities.40 This reclassification trend risks diluting already limited federal support. These structural and policy shifts are unfolding even as rural patients continue to experience worse surgical outcomes than their nonrural counterparts, underscoring that financial stabilization alone is insufficient to ensure equitable, high-quality surgical care. Sustaining rural surgery will require payment and workforce reforms explicitly tied to maintaining local operative capability and postoperative infrastructure. In prior work, we have argued that rural surgery needs a coordinated national strategy rather than a collection of disconnected training or policy efforts and that rural hospitals deserve a unified framework to replace the current patchwork of designations with outcome-oriented funding models.41,42 The recently passed $50 billion Rural Health Transformation Fund offers an unprecedented opportunity to realize that vision by linking federal investment to global budgets, workforce development, and preservation of local surgical capacity.7 Together, these strategies could move rural hospital policy from reactive stabilization toward proactive system design that secures high-quality care close to home.
Limitations
These findings should be interpreted in the context of important limitations. First, we used administrative claims data to evaluate clinical surgical outcomes. However, we evaluated outcomes that are reliably coded in Medicare claims data and studied a nationally generalizable sample within the US. Second, our sample was limited to older adults who underwent surgery, although these beneficiaries are more likely to have complications, given their age and comorbidity profiles, which may actually make this population more sensitive to identifying differences in surgical quality. Third, although several outcome differences were statistically significant, some absolute differences were modest and may be less clinically meaningful at the individual level. Despite this, even small differences have important population-level implications given our generalizable population-based cohort study of Medicare beneficiaries. Fourth, rural residence was defined using RUCA codes cross-walked from patient zip codes, which may misclassify some beneficiaries near urban-rural boundaries. However, this approach aligns with national, validated definitions used in policy work and in prior studies and reflects the broader access environment experienced by rural patients.
Conclusions
In this cohort study of Medicare beneficiaries who underwent common general surgery procedures, rural residence was independently associated with higher postoperative mortality, complications, and readmissions despite similar baseline characteristics. These findings persisted across site of care setting, suggesting that structural factors like travel burden, delays in care, and fragmentation play a central role in care disparities for rural beneficiaries. Addressing these challenges will require policy approaches that strengthen local capacity and improve care coordination. Modernizing and supporting rural health systems through policy must ensure not only access to surgical care but equitable outcomes for the millions of rural patients who rely on it.
eTable 1. Coding Strategy to Identify Common General Surgery Operations
eTable 2. Specific Elixhauser Comorbidities Among Rural vs Nonrural Medicare Beneficiaries Who Underwent Common General Surgery Procedures
eTable 3. Comparison of Risk-Adjusted Outcomes Among Rural vs Nonrural Medicare Beneficiaries Who Underwent Common General Surgery Procedures With Elective Hospital Admissions
eTable 4. Comparison of Risk-Adjusted Outcomes Among Rural vs Nonrural Medicare Beneficiaries Who Underwent Common General Surgery Procedures With Unplanned Hospital Admissions
eTable 5. Comparison of Risk-Adjusted Discharge Disposition and Length of Stay Among Rural vs Nonrural Medicare Beneficiaries Who Underwent Common General Surgery Procedures With Elective Hospital Admissions
eTable 6. Comparison of Risk-Adjusted Discharge Disposition and Length of Stay Among Rural vs Nonrural Medicare Beneficiaries Who Underwent Common General Surgery Procedures With Unplanned Hospital Admissions
eTable 7. Comparison of Risk-Adjusted Outcomes Among Rural Beneficiaries Who Obtained Surgical Care Locally at a Rural Hospital or at a Nonrural Hospital vs Nonrural Beneficiaries Who Obtained Care at a Nonrural Hospital as the Reference Group
Data Sharing Statement
References
- 1.Mullens CL, Hernandez JA, Murthy J, et al. Understanding the impacts of rural hospital closures: a scoping review. J Rural Health. 2024;40(2):227-237. doi: 10.1111/jrh.12801 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Planey AM, Thomas SR, Friedman H, Hecht HK, Kent E, Holmes GM. Rural hospital closures: a scoping review of studies published between 1990 and 2020. J Health Care Poor Underserved. 2024;35(2):439-464. doi: 10.1353/hpu.2024.a928626 [DOI] [PubMed] [Google Scholar]
- 3.Mullens CL, Collins RA, Kunnath N, Probst JC, Ibrahim AM. Trends in travel time to obtain surgical care for rural patients. JAMA. 2025;333(16):1453-1455. doi: 10.1001/jama.2025.0447 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Mullens CL, Ibrahim AM, Clark NM, et al. Trends in timely access to high-quality and affordable surgical care in the United States. Ann Surg. 2024;281(2):265-272. doi: 10.1097/SLA.0000000000006586 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Mullens CL, Johnson PL, Probst JC, Dimick JB, Ibrahim AM, Diaz A. Changes in surgical quality and access after rural hospital closures. Health Aff Sch. 2025;3(5):qxaf089. doi: 10.1093/haschl/qxaf089 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Rentas CM, Picart J, Kunnath N, et al. Disparities across race, ethnicity, and rurality among surgical patients. Ann Surg Open. 2026;7(2):e655. doi: 10.1097/AS9.0000000000000655 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Howren MB, Hansen JR. The One Big Beautiful Bill Act—implications for rural health care. JAMA. 2025;334(13):1143-1144. doi: 10.1001/jama.2025.13518 [DOI] [PubMed] [Google Scholar]
- 8.Abid M, Malone T, Holmes M, Charles A. Clinical consequences associated with bypassing local surgical care for urgent and emergent surgery. J Surg Res. 2025;315:504-514. doi: 10.1016/j.jss.2025.09.034 [DOI] [PubMed] [Google Scholar]
- 9.Mullens CL, Johnson PL, Rentas C, et al. Half of rural patients bypassed their local hospital but received lower-quality surgical care elsewhere, 2016-20. Health Aff (Millwood). 2026;45(3):313-321. doi: 10.1377/hlthaff.2025.00640 [DOI] [PubMed] [Google Scholar]
- 10.Mullens CL, Johnson P, Rentas CM, Kunnath N, Ibrahim AM, Dimick JB. Hospital bypass and surgical outcomes for common surgical conditions among rural patients. J Am Coll Surg. 2025;241:S215-S244. [Google Scholar]
- 11.Gadzinski AJ, Dimick JB, Ye Z, Miller DC. Utilization and outcomes of inpatient surgical care at critical access hospitals in the United States. JAMA Surg. 2013;148(7):589-596. doi: 10.1001/jamasurg.2013.1224 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Gadzinski AJ, Dimick JB, Ye Z, Zeller JL, Miller DC. Transfer rates and use of post-acute care after surgery at critical access vs non-critical access hospitals. JAMA Surg. 2014;149(7):671-677. doi: 10.1001/jamasurg.2013.5694 [DOI] [PubMed] [Google Scholar]
- 13.Ibrahim AM, Hughes TG, Thumma JR, Dimick JB. Association of hospital critical access status with surgical outcomes and expenditures among Medicare beneficiaries. JAMA. 2016;315(19):2095-2103. doi: 10.1001/jama.2016.5618 [DOI] [PubMed] [Google Scholar]
- 14.Mullens CL, Probst JC, Johnson PL, Kunnath N, Dimick JB, Ibrahim AM. Trends in surgical quality at critical access hospitals. Ann Surg. Published online May 16, 2025. doi: 10.1097/SLA.0000000000006754 [DOI] [PubMed] [Google Scholar]
- 15.Mullens CL, Niba VS, Collins RA, et al. Quality of general surgery procedures in children at small rural hospitals. Ann Surg. 2026;283(2):353-355. doi: 10.1097/SLA.0000000000006981 [DOI] [PubMed] [Google Scholar]
- 16.Zhang Y, Malone TL, Scales CD Jr, Pink GH. Predictors of hospital bypass for rural residents seeking common elective surgery. Surgery. 2023;173(2):270-277. doi: 10.1016/j.surg.2022.06.009 [DOI] [PubMed] [Google Scholar]
- 17.Barthold LK, Burney CP, Baumann LE, Briggs A. Complexity of transferred geriatric adults requiring emergency general surgery: a rural tertiary center experience. J Surg Res. 2023;283:640-647. doi: 10.1016/j.jss.2022.10.088 [DOI] [PubMed] [Google Scholar]
- 18.Duncan AJ, Bloomsburg SJ, Hopper W, Sturdevant DA, Ahmeti M. Emergency general surgery outcomes for rural patients: a comparative analysis of rural, micropolitan, and metropolitan populations. Am Surg. 2026;92(1):15-21. doi: 10.1177/00031348251378896 [DOI] [PubMed] [Google Scholar]
- 19.Tadé Y, Timperley J, Dilsaver D, McDermott J, de Rosa N, Al-Refaie WB. High-risk rural surgical patients and poor access to elective colorectal cancer surgery: insight for multilevel intervention for rural America. J Gastrointest Surg. 2024;28(11):1883-1889. doi: 10.1016/j.gassur.2024.08.011 [DOI] [PubMed] [Google Scholar]
- 20.Timperley J, Dilsaver D, McClain M, et al. Geographic inequities and access to colorectal cancer surgery among rural residents: one size does not fit all! J Gastrointest Surg. 2025;29(6):102061. doi: 10.1016/j.gassur.2025.102061 [DOI] [PubMed] [Google Scholar]
- 21.Reddy KP, Berkowitz CL, Jarrell K, et al. The effect of rurality on time to surgery and overall survival among women with breast cancer. Ann Surg. Published online March 27, 2025. doi: 10.1097/SLA.0000000000006710 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP; STROBE Initiative . The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet. 2007;370(9596):1453-1457. doi: 10.1016/S0140-6736(07)61602-X [DOI] [PubMed] [Google Scholar]
- 23.Mullens CL, Rentas CM, Kunnath N, Dimick JB, Ibrahim AM. Surgical outcomes and post-acute care use among rural Medicare Advantage beneficiaries. Ann Surg Open. 2026;7(2):e663. doi: 10.1097/AS9.0000000000000663 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Isenberg EE, Bui E, Kunnath N, Harbaugh CM, Ibrahim A. Quality and utilization of surgical care among Medicare Advantage beneficiaries. Am J Surg. 2025;244:116300. doi: 10.1016/j.amjsurg.2025.116300 [DOI] [PubMed] [Google Scholar]
- 25.Research Data Assistance Center. Destination upon discharge from facility code. Accessed April 27, 2026. https://resdac.org/cms-data/variables/destination-upon-discharge-facility-code
- 26.Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care. 1998;36(1):8-27. doi: 10.1097/00005650-199801000-00004 [DOI] [PubMed] [Google Scholar]
- 27.Southern DA, Quan H, Ghali WA. Comparison of the Elixhauser and Charlson/Deyo methods of comorbidity measurement in administrative data. Med Care. 2004;42(4):355-360. doi: 10.1097/01.mlr.0000118861.56848.ee [DOI] [PubMed] [Google Scholar]
- 28.McCrum ML, Wan N, Han J, Lizotte SL, Horns JJ. Disparities in spatial access to emergency surgical services in the US. JAMA Health Forum. 2022;3(10):e223633. doi: 10.1001/jamahealthforum.2022.3633 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Han J, Wan N, Brewer SC, McCrum M. Spatial access to emergency general surgery (EGS) services and EGS bypass behaviours in California. Ann GIS. 2023;29(1):75-85. doi: 10.1080/19475683.2023.2165546 [DOI] [Google Scholar]
- 30.Lansing SS, Diaz A, Hyer M, Tsilimigras D, Pawlik TM. Rural hospitals are not associated with worse postoperative outcomes for colon cancer surgery. J Rural Health. 2022;38(3):650-659. doi: 10.1111/jrh.12596 [DOI] [PubMed] [Google Scholar]
- 31.Djapri GM, Constantinou C, Albright J, et al. Impact of rural status on lower extremity bypass outcomes for patients with chronic limb threatening ischemia. Ann Vasc Surg. 2025;117:44-55. doi: 10.1016/j.avsg.2025.03.025 [DOI] [PubMed] [Google Scholar]
- 32.Clark NM, Hernandez AH, Bertalan MS, et al. Travel time as an indicator of poor access to care in surgical emergencies. JAMA Netw Open. 2025;8(1):e2455258. doi: 10.1001/jamanetworkopen.2024.55258 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Schaefer SL, Mullens CL, Ibrahim AM. The emergence of rural emergency hospitals: safely implementing new models of care. JAMA. 2023;329(13):1059-1060. doi: 10.1001/jama.2023.1956 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Daly SB, You W, Merwin EI. The new Rural Emergency Hospital Designation Program: will it improve access to care for rural Americans? J Rural Health. 2025;41(4):e70079. doi: 10.1111/jrh.70079 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Rubin R. Federal funds for rural health care are on the chopping block—here’s what that could mean. JAMA. 2025;333(23):2040-2042. doi: 10.1001/jama.2025.7675 [DOI] [PubMed] [Google Scholar]
- 36.Robertson M. Private equity firms own at least 130 rural hospitals: 8 things to know. Becker’s Hospital Review. January 27, 2023. Accessed June 2, 2025. https://www.beckershospitalreview.com/finance/pe-firms-own-at-least-130-rural-hospitals-8-things-to-know/
- 37.Mead M, Clark NM, Probst JC, Dimick JB, Ibrahim AM, Mullens CL. Early evaluation of the rural emergency hospital program. JAMA Netw Open. 2026;9(4):e269217. doi: 10.1001/jamanetworkopen.2026.9217 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Kerr E, Malone TL, Thompson K, Pink GH, Holmes GM. Did rural emergency hospital converters avoid closure? Ann Emerg Med. 2026;87(6):785-788. doi: 10.1016/j.annemergmed.2026.02.004 [DOI] [PubMed] [Google Scholar]
- 39.Clark NM, Hernandez AH, Mullens CL, Riha G, Scott JW, Stewart BT. Trauma and emergency surgical care at rural emergency hospital-eligible facilities: Interstate variation and policy implications for rural health systems. J Trauma Acute Care Surg. 2026;100(5):768-776. doi: 10.1097/TA.0000000000004904 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Wang Y, Perkins J, Whaley CM, Bai G. Sharp rise in urban hospitals with rural status in Medicare, 2017-23. Health Aff (Millwood). 2025;44(8):963-969. doi: 10.1377/hlthaff.2025.00019 [DOI] [PubMed] [Google Scholar]
- 41.Mullens CL, Probst JC, Ibrahim AM. Rural hospitals deserve more than patchwork policies. JAMA. 2025;334(13):1141-1142. doi: 10.1001/jama.2025.14945 [DOI] [PubMed] [Google Scholar]
- 42.Mullens CL, Hughes TG. Rural surgery needs a strategy, not just another training track or rotation. Ann Surg. 2025;282(2):193-195. doi: 10.1097/SLA.0000000000006701 [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
eTable 1. Coding Strategy to Identify Common General Surgery Operations
eTable 2. Specific Elixhauser Comorbidities Among Rural vs Nonrural Medicare Beneficiaries Who Underwent Common General Surgery Procedures
eTable 3. Comparison of Risk-Adjusted Outcomes Among Rural vs Nonrural Medicare Beneficiaries Who Underwent Common General Surgery Procedures With Elective Hospital Admissions
eTable 4. Comparison of Risk-Adjusted Outcomes Among Rural vs Nonrural Medicare Beneficiaries Who Underwent Common General Surgery Procedures With Unplanned Hospital Admissions
eTable 5. Comparison of Risk-Adjusted Discharge Disposition and Length of Stay Among Rural vs Nonrural Medicare Beneficiaries Who Underwent Common General Surgery Procedures With Elective Hospital Admissions
eTable 6. Comparison of Risk-Adjusted Discharge Disposition and Length of Stay Among Rural vs Nonrural Medicare Beneficiaries Who Underwent Common General Surgery Procedures With Unplanned Hospital Admissions
eTable 7. Comparison of Risk-Adjusted Outcomes Among Rural Beneficiaries Who Obtained Surgical Care Locally at a Rural Hospital or at a Nonrural Hospital vs Nonrural Beneficiaries Who Obtained Care at a Nonrural Hospital as the Reference Group
Data Sharing Statement
