Abstract
Objective:
To determine the rate of emergency versus elective lower extremity amputations in the United States
Background:
Lower extremity amputation is a common endpoint for patients with poorly controlled diabetes and multilevel peripheral vascular disease. While the procedure is ideally performed electively, patients with limited access may present later and require an emergency operation. To what extent rates of emergency amputation for lower extremity vary across the United States is unknown.
Methods:
Evaluation of Medicare beneficiaries who underwent lower extremity amputation between 2015–2020. The rate was determined for each zip code and placed into rank order from lowest to highest rate. We merged each beneficiary’s place of residence and location of care with the American Hospital Association Annual Survey using Google Maps Application Programming Interface to determine the travel distance for patients to undergo their procedure.
Results:
Of 233,084 patients, 66.3%(154,597) were men, 69.8%(162,786) were White. Average age(SD) was 74 year(8). There was wide variation in rates of emergency lower extremity amputation. The lowest quintile of zip codes demonstrated an emergency amputation rate of 3.7% while the highest quintile demonstrated 90%. Median travel distance in the lowest emergency surgery rate quintile was 34.6 miles compared to 10.5 miles in the highest quintile of emergency surgery (p<0.001).
Conclusion:
There is wide variation in the rate of emergency lower extremity amputations among Medicare beneficiaries, suggesting variable access to essential vascular care. Travel distance and rate amputation have an inverse relationship, suggesting that barriers other than travel distance are playing a role.
Keywords: Lower Extremity Amputations, Emergency Amputations, Medicare Beneficiaries, Peripheral Vascular Disease, Diabetes
Mini-abstract:
Lower extremity amputation is a common endpoint for patients with poorly controlled diabetes and multilevel peripheral vascular disease. The purpose of our study was to determine the rate of emergency versus elective lower extremity amputations in the United States. We found there is wide variation in the rate of emergency amputations and an inverse relationship to travel distance.
INTRODUCTION
Lower extremity amputations are commonly performed in the United States as a result of poorly controlled diabetes and multilevel peripheral arterial disease. For patients with diabetes, lower extremity amputation rates increased by 50% in the last decade.1 For those with peripheral arterial disease, about 11% go on to develop chronic limb-threatening ischemia putting them at high risk for an amputation, which is associated with higher rates of morbidity, mortality and hospital readmission.2–4 Furthermore, patients with combined diabetes and peripheral arterial disease are four times as likely to receive an amputation compared to the national average.2 While a lower extremity amputation is ideally performed electively, patients with limited access may not present until sepsis or severe local infection, or acute-on-chronic ischemia occur and mandates an emergency operation (Figure 1). As such, emergency surgery rates for lower extremity amputation is increasingly seen as a potential measure of quality and access to optimal vascular care.
Figure 1:
Conceptual Overview for Access to Lower Extremity Amputation
To what extent rates of emergency amputation for lower extremity vary across the United States is unknown. Prior work studying similar access-sensitive surgical conditions, such as abdominal aortic aneurysm which can rupture or ventral hernias which can strangulate, have been proposed as an indicator of surgical access given that a delay in care can result in an emergency operation.5–8 These studies have shown that rates of emergency surgery for access-sensitive surgical conditions vary widely across the United States with unclear underlying mechanisms. Despite the growing area of interest of these conditions, lower extremity amputation has not yet been rigorously evaluated as an access-sensitive surgical condition and its variation in emergency rates is not well understood.
In that context, we evaluated Medicare beneficiaries who underwent a lower extremity amputation between 2015–2020 stratified by their location in the country. We then evaluated rates of emergency lower extremity amputations, time and distance traveled to hospital. We hypothesized that there will be a wide variation in the rate of emergency lower extremity amputations in the United States and travel may be a barrier to timely access.
METHODS
Data Source, Procedures, Study Cohort
Data from the Medicare Provider Analysis and Review (MEDPAR) files between fourth quarter of 2015 and 2020 were used for this study. We excluded patients who received care during the COVID-19 pandemic. Beneficiaries undergoing lower extremity amputations were identified using International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10) codes (supplement 1). Lower extremity amputations included foot, below the knee and above the knee amputations. We excluded minor amputations such as toe or transmetatarsal amputations. Patient demographic data included age, race, ethnicity, demographic information, and comorbidities. Elixhauser comorbidities were used to stratify number of comorbidities, as used in prior analyses of surgical cohorts using Medicare claims data.9,10 11 Beneficiaries younger than 65 years or older than 99 years were excluded. Race and ethnicity was provided by the MEDPAR file and was used as a social construct, not a biological risk factor, in our analysis.
The American Hospital Association Annual Survey was linked to the hospital identifiers from the MEDPAR file. Admissions were identified as elective, urgent or emergency based on the Medicare Claim Inpatient Admission Type Code.12 Records with missing data (1.62%) were excluded from the analysis. The study was deemed exempt by the Institutional Review Board at the University of Michigan.
Outcomes
The primary outcome of interest was the rate of emergency lower extremity amputation. As stated above, emergency surgery was defined by the clinical inpatient admission type code. Secondary analysis included evaluation of time and distance traveled to hospital, and differences in the Rural-Urban Commuting Area codes. These codes use population density, levels of urbanization and daily commuting to classify all United States census tracts into rural or urban status.13 A score of 1–3 is indicated as a metropolitan area, 4–6 as a micropolitan, 7–9 as a small town, and 10 as rural areas. We also calculated distance and time traveled.
Statistical analysis
The purpose of this analysis was to, first, evaluate the rate of emergency lower extremity amputations across the United States and, second, evaluate the patient and geographical characteristics of elective versus emergency lower extremity amputations. Patient ZIP codes were placed into rank order from lowest to highest rate of emergency amputations to assess the degree to which emergency rates differ between areas. We then calculated the distance between the patient’s ZIP code of residence and ZIP code of location of care. Google Maps was used through the statistical software SAS to assess the travel distance required for patients to receive care.
Patient characteristics were compared using t-tests. Hospital characteristics from the American Hospital Association Annual Survey were compared using ANOVA. Teaching status and nursing ratio were included to account for hospital characteristics. Robust standard errors were applied. Statistical analyses were performed using Stata, version 17 (College Station, TX). All p-values were two-tailed and p<0.05 was considered statistically significant.
RESULTS
In this study, out of a total of 233,084 patients, 66.3% of were men with an average age of 74 (8.0) (Table 1). Approximately 70% of patients were White, 23% Black, 3.7% Hispanic and 1% for both Asian and Native American. In this cohort, 72.3% of patients were documented to carry a diagnosis of diabetes, while 45.4% of patients had peripheral vascular disease. Almost all patients had greater than or equal to 2 Elixhauser comorbidities.
Table 1:
Patient Characteristics and Admission Type
| Quintiles of Zip Codes by Emergency Procedure Rate | |||||||
|---|---|---|---|---|---|---|---|
| Total | Lowest rate | Below average | Average | Above average | Highest Rate | P-value | |
| No. of Patients | 233,084 | 13,388 | 55,476 | 59,820 | 75,222 | 29,178 | |
| Demographic characteristics | |||||||
| Age, mean(SD) | 74.0 (8.0) | 74.7 (7.8) | 74.1 (7.9) | 73.9 (7.9) | 73.8 (8.0) | 74.7 (8.4) | <0.001 |
| Men | 154,597 (66.3%) | 9,133 (68.2%) | 37,258 (67.2%) | 39,965 (66.8%) | 49,474 (65.8%) | 18,767 (64.3%) | <0.001 |
| Race | |||||||
| White | 162,786 (69.8%) | 11,543 (86.2%) | 42,180 (76.0%) | 42,843 (71.6%) | 48,118 (64.0%) | 18,102 (62.0%) | <0.001 |
| Black | 53,118 (22.8%) | 1,184 (8.8%) | 9,373 (16.9%) | 12,850 (21.5%) | 21,781 (29.0%) | 7,930 (27.2%) | <0.001 |
| Asian | 2,206 (0.9%) | 104 (0.8%) | 595 (1.1%) | 562 (0.9%) | 658 (0.9%) | 287 (1.0%) | 0.001 |
| Hispanic | 8,642 (3.7%) | 145 (1.1%) | 1,484 (2.7%) | 2,077 (3.5%) | 2,935 (3.9%) | 2,001 (6.9%) | <0.001 |
| Native American | 2,504 (1.1%) | 239 (1.8%) | 1,025 (1.8%) | 559 (0.9%) | 526 (0.7%) | 155 (0.5%) | <0.001 |
| Other | 3,828 (1.6%) | 173 (1.3%) | 819 (1.5%) | 929 (1.6%) | 1,204 (1.6%) | 703 (2.4%) | <0.001 |
| Comorbidities | |||||||
| Hypertension | 202,918 (87.1%) | 11,436 (85.4%) | 47,984 (86.5%) | 52,258 (87.4%) | 66,032 (87.8%) | 25,208 (86.4%) | <0.001 |
| Diabetes | 168,621 (72.3%) | 9,004 (67.3%) | 39,279 (70.8%) | 43,432 (72.6%) | 55,149 (73.3%) | 21,757 (74.6%) | <0.001 |
| Renal failure | 107,949 (46.3%) | 5,667 (42.3%) | 25,143 (45.3%) | 28,182 (47.1%) | 35,812 (47.6%) | 13,145 (45.1%) | <0.001 |
| Peripheral vascular disease | 105,714 (45.4%) | 5,801 (43.3%) | 25,146 (45.3%) | 26,949 (45.1%) | 34,623 (46.0%) | 13,195 (45.2%) | <0.001 |
| Electrolyte disorders | 102,817 (44.1%) | 4,817 (36.0%) | 22,855 (41.2%) | 26,534 (44.4%) | 35,324 (47.0%) | 13,287 (45.5%) | <0.001 |
| Congestive heart failure | 81,550 (35.0%) | 4,453 (33.3%) | 19,383 (34.9%) | 21,245 (35.5%) | 26,907 (35.8%) | 9,562 (32.8%) | <0.001 |
| COPD | 55,093 (23.6%) | 3,395 (25.4%) | 13,820 (24.9%) | 14,374 (24.0%) | 17,595 (23.4%) | 5,909 (20.3%) | <0.001 |
| Weight loss | 41,414 (17.8%) | 1,843 (13.8%) | 9,297 (16.8%) | 11,021 (18.4%) | 14,371 (19.1%) | 4,882 (16.7%) | <0.001 |
| Obesity | 38,232 (16.4%) | 2,492 (18.6%) | 9,730 (17.5%) | 9,949 (16.6%) | 12,092 (16.1%) | 3,969 (13.6%) | <0.001 |
| Hypothyroidism | 33,561 (14.4%) | 2,100 (15.7%) | 8,447 (15.2%) | 8,882 (14.8%) | 10,439 (13.9%) | 3,693 (12.7%) | <0.001 |
| Depression | 31,252 (13.4%) | 1,869 (14.0%) | 7,838 (14.1%) | 8,213 (13.7%) | 10,129 (13.5%) | 3,203 (11.0%) | <0.001 |
| Neurological disorders | 22,891 (9.8%) | 1,234 (9.2%) | 5,698 (10.3%) | 5,744 (9.6%) | 7,200 (9.6%) | 3,015 (10.3%) | <0.001 |
| Valvular disease | 22,248 (9.5%) | 1,310 (9.8%) | 5,150 (9.3%) | 5,649 (9.4%) | 7,360 (9.8%) | 2,779 (9.5%) | 0.026 |
| Coagulopathy | 15,097 (6.5%) | 762 (5.7%) | 3,328 (6.0%) | 3,883 (6.5%) | 5,277 (7.0%) | 1,847 (6.3%) | <0.001 |
| Rheumatoid arthritis | 9,232 (4.0%) | 680 (5.1%) | 2,412 (4.3%) | 2,456 (4.1%) | 2,831 (3.8%) | 853 (2.9%) | <0.001 |
| Liver disease | 6,908 (3.0%) | 348 (2.6%) | 1,523 (2.7%) | 1,820 (3.0%) | 2,372 (3.2%) | 845 (2.9%) | <0.001 |
| Psychoses | 4,955 (2.1%) | 214 (1.6%) | 1,173 (2.1%) | 1,259 (2.1%) | 1,629 (2.2%) | 680 (2.3%) | <0.001 |
| Solid tumor | 4,314 (1.9%) | 236 (1.8%) | 950 (1.7%) | 1,106 (1.8%) | 1,484 (2.0%) | 538 (1.8%) | 0.013 |
| Elixhauser comorbidities | |||||||
| 0 | 1,197 (0.5%) | 117 (0.9%) | 342 (0.6%) | 271 (0.5%) | 300 (0.4%) | 167 (0.6%) | <0.001 |
| 1 | 5,703 (2.4%) | 517 (3.9%) | 1,575 (2.8%) | 1,372 (2.3%) | 1,509 (2.0%) | 730 (2.5%) | <0.001 |
| ≥2 | 226,184 (97.0%) | 12,754 (95.3%) | 53,559 (96.5%) | 58,177 (97.3%) | 73,413 (97.6%) | 28,281 (96.9%) | <0.001 |
| Admission Type | |||||||
| Elective | 59,354 (25.5%) | 6,343 (47.4%) | 19,841 (35.8%) | 16,875 (28.2%) | 14,582 (19.4%) | 1,713 (5.9%) | <0.001 |
| Urgent | 47,731 (20.5%) | 6,546 (48.9%) | 17,777 (32.0%) | 12,550 (21.0%) | 9,749 (13.0%) | 1,109 (3.8%) | <0.001 |
| Emergency | 125,999 (54.1%) | 499 (3.7%) | 17,858 (32.2%) | 30,395 (50.8%) | 50,891 (67.7%) | 26,356 (90.3%) | <0.001 |
Overall, 25.5% of patients underwent an elective lower extremity amputation while 20.5% were urgent and 54.1% were an emergency amputation (Table 1). The rate of emergency amputation in the lowest quintile of ZIP codes was 3.7% compared to 90.3% in the highest quintile (p<0.001). Conversely for elective amputations, the rate in the lowest quintile was 47.4% compared to 5.9% in the highest quintile. Patients in the highest quintile lived in more urban areas with a RUCA score of 1–3 compared to those in the lowest quintile (90.2% vs. 42.4%, p <0.001) (Table 2). A breakdown of rate of emergency amputation by RUCA score 1–10 can be seen in supplement Table 2. These patients also had shorter distance traveled to the hospital location of care and fewer travel minutes.
Table 2:
Rural/Urban Commuting Area Codes, Hospital Characteristics and Travel
| Quintiles of Zip Codes by Emergency Procedure Rate | |||||||
|---|---|---|---|---|---|---|---|
| Total | Lowest Rate | Below Average | Average | Above Average | Highest Rate | P-value | |
| RUCA Score | |||||||
| missing | 398 (0.2%) | 46 (0.3%) | 71 (0.1%) | 24 (0.0%) | 160 (0.2%) | 97 (0.3%) | <0.001 |
| 1–3 | 183,949 (78.9%) | 5,680 (42.4%) | 35,109 (63.3%) | 49,047 (82.0%) | 67,787 (90.1%) | 26,326 (90.2%) | <0.001 |
| 4–6 | 25,748 (11.0%) | 2,730 (20.4%) | 11,367 (20.5%) | 6,367 (10.6%) | 4,065 (5.4%) | 1,219 (4.2%) | <0.001 |
| 7–9 | 14,148 (6.1%) | 2,429 (18.1%) | 6,135 (11.1%) | 2,775 (4.6%) | 2,175 (2.9%) | 634 (2.2%) | <0.001 |
| 10 | 8,841 (3.8%) | 2,503 (18.7%) | 2,794 (5.0%) | 1,607 (2.7%) | 1,035 (1.4%) | 902 (3.1%) | <0.001 |
| Hospital Size | |||||||
| Has fewer than 250 beds | 70,371 (30.2%) | 5,068 (37.9%) | 19,317 (34.8%) | 17,673 (29.5%) | 20,018 (26.6%) | 8,295 (28.4%) | <0.001 |
| Has between 250 and 499 beds | 87,178 (37.4%) | 4,736 (35.4%) | 20,349 (36.7%) | 22,746 (38.0%) | 28,987 (38.5%) | 10,360 (35.5%) | <0.001 |
| Has 500 or more beds | 75,535 (32.4%) | 3,584 (26.8%) | 15,810 (28.5%) | 19,401 (32.4%) | 26,217 (34.9%) | 10,523 (36.1%) | <0.001 |
| Hospital Region | |||||||
| Northeast | 40,861 (17.5%) | 1,298 (9.7%) | 4,305 (7.8%) | 7,358 (12.3%) | 14,999 (19.9%) | 12,901 (44.2%) | <0.001 |
| Midwest | 48,346 (20.7%) | 5,180 (38.7%) | 12,938 (23.3%) | 12,295 (20.6%) | 15,046 (20.0%) | 2,887 (9.9%) | <0.001 |
| South | 104,807 (45.0%) | 4,429 (33.1%) | 25,895 (46.7%) | 28,541 (47.7%) | 34,505 (45.9%) | 11,437 (39.2%) | <0.001 |
| West | 39,070 (16.8%) | 2,481 (18.5%) | 12,338 (22.2%) | 11,626 (19.4%) | 10,672 (14.2%) | 1,953 (6.7%) | <0.001 |
| Teaching Hospital | 190,193 (81.6%) | 10,363 (77.4%) | 42,856 (77.3%) | 48,489 (81.1%) | 63,158 (84.0%) | 25,327 (86.8%) | <0.001 |
| Patient to Nurse Ratio | 9.0 (3.5) | 9.9 (4.5) | 9.4 (3.8) | 9.1 (3.5) | 8.8 (3.2) | 8.1 (3.3) | <0.001 |
| Travel | |||||||
| Distance in miles, median (IQR) | 13.6 (5.9–31.7) | 34.6 (15.0–65.3) | 19.7 (8.4–43.9) | 13.4 (6.1–29.1) | 10.3 (5.0–22.2) | 10.5 (4.4–24.2) | <0.001 |
| Time in minutes, median (IQR) | 22.0 (13.0–38.0) | 41.0 (22.0–69.0) | 27.0 (16.0–50.0) | 21.0 (13.0–36.0) | 19.0 (12.0–30.0) | 20.0 (12.0–32.0) | <0.001 |
| Travel Time in minutes | |||||||
| <30 | 144,620 (62.0%) | 4,438 (33.1%) | 28,326 (51.1%) | 38,674 (64.7%) | 53,889 (71.6%) | 19,293 (66.1%) | <0.001 |
| 30–60 | 51,842 (22.2%) | 4,030 (30.1%) | 15,420 (27.8%) | 13,073 (21.9%) | 13,615 (18.1%) | 5,704 (19.5%) | <0.001 |
| >60 | 36,622 (15.7%) | 4,920 (36.7%) | 11,730 (21.1%) | 8,073 (13.5%) | 7,718 (10.3%) | 4,181 (14.3%) | <0.001 |
Figure 2 shows the rate of emergency lower extremity amputations in the United States stratified by ZIP code. The blue color represents areas with lower rates of amputations while the red color represents areas with high rates. This shows wide geographic variation of emergency amputations among Medicare Beneficiaries.
Figure 2:
Geographic Variation in Rate of Emergency Lower Extremity Amputations among Medicare Beneficiaries
DISCUSSION
Our present study on the rates of emergency lower extremity amputation among Medicare beneficiaries in the United States has two principal findings. First, there is wide variation in the emergency rates of lower extremity amputation ranging from 3.7% to 90%. Second, we found that travel distance has an inverse relationship to emergency lower extremity amputation rates. Taken together, these findings suggest variable access to essential vascular care and underscores the need to improve surgical access for these patients.
Prior work has evaluated rates of emergency surgery for access-sensitive surgical conditions as a measure of access. For example, patients from a more socially vulnerable population experienced worse postoperative outcomes following unplanned surgery for multiple access-sensitive surgical conditions.6 The authors propose that those living in more vulnerable neighborhoods experience delays in care secondary to structural barriers and have multiple factors that contribute to the location care is provided. Furthermore, several studies have demonstrated that transportation barriers lead to decreased healthcare access and worse outcomes.14 While this seems intuitively plausible, our present study contrasts this work by finding that patients who live closer to the hospital at which they received care are more likely to undergo an emergency lower extremity amputation.
While our study cannot determine the exact mechanisms underlying the differences in emergency lower extremity amputation rates, our data suggest at least a few possibilities. First, patients in the highest emergency amputation rate quintile were more likely to carry a diagnosis of diabetes. As poorly controlled diabetes is part of the disease process that can lead to ultimate amputation, these findings raise concern that patients may be presenting later on in their disease process secondary to poor endocrinologic care. In fact, prior work has addressed concerns about diabetes control and the number of available providers in an area.15 Second, our data identified that patients with higher emergency amputation rates were disproportionately Black beneficiaries. This finding builds on several prior studies and raises concern about potential structural disadvantages that prevent patients who identify as Black to access elective care.16,17 18 This is further underscored by our additional findings that travel distance was inversely related to rates of emergency surgery and that patients who underwent an emergent amputation were more likely to live in the Northeast or South. This highlights that part of the influence in this variation may be attributable to geographic location, specifically differences in urban versus rural locations, which is considered a social determinant of health.19,20 Taken together, there are likely several mechanisms at play further upstream in the care delivery process that require further investigations.
Our study should be interpreted within the context of multiple limitations. First, we used Medicare administrative claims data, which is may not capture the same granularity as clinical abstraction. To directly minimize this potential bias, we selected outcomes that are known to be well captured in claims data and widely used in health services research.21,22 In addition, Medicare claims data was chosen given that prior studies have been limited by single center or regional collaboratives rather than nationwide data. Second, utilizing Medicare claims data limits generalizability to parts of the population who are 65 and under.23 Poorly controlled diabetes or end-stage peripheral vascular disease leading to amputation tends to affect older adults and thus more likely to be represented among Medicare beneficiaries. Third, the difference between emergency surgery versus emergency admission is difficult to differentiate, so, there can be patients who had an emergency admission by the Medicare Claim Inpatient Admission Type Code but did not necessarily receive surgery on the same date of admission. If that is the case, the rate of emergency lower extremity amputation may be overestimated. Furthermore, the rate can also be estimated by transfer of patients between facilities. Last, in order to account for unknown factors contributing to a patient’s access to lower extremity amputation, we performed risk-adjusted analyses and multiple sensitivity analyses.
The present study has several implications for stakeholders engaged in improving surgical care for Medicare beneficiaries. Patients who ultimately undergo a lower extremity amputation should have multiple interaction points with the healthcare system including receiving care from a primary care provider, being referred to a medical specialist and evaluation by a surgeon. Because most of the emergency amputations were among patients with diabetes, our findings suggest that better coordination of multi-disciplinary care may better help patients present in an elective fashion.24 Some patients will ultimately require an amputation regardless but ensuring earlier access can lower the morbidity, mortality and increased resource utilization associated with emergency surgery. For public health leaders, this study highlights the burden of chronic disease can have on patients even if you live close to a hospital. Geographic proximity does not ensure timely access, even for the universally insured. Finally, for policy makers, this study builds upon others studying access-sensitive surgical conditions as a useful measure to evaluate surgical access and emergency rate of lower extremity amputations can be incorporated.
Overall, our findings show that there is wide variation in rates of emergency lower extremity amputations among Medicare beneficiaries, suggesting variable access to essential vascular care. Using the rate of emergency lower extremity amputations may be a useful proxy measure for timely access to surgical care, similar to other access-sensitive surgical conditions, and aid in targeting patients’ upstream interactions with the healthcare system to improve outcomes.
Supplementary Material
Funding:
Dr. Dualeh receives funding from The Fredrick A. Coller Surgical Society and is a post-doctoral fellow on grant 1T32AG062403 from the National Institute on Aging. Dr. Powell also receives funding from the NIA on grant 1T32AG062403. Dr. Corriere receives funding from the United States Food and Drug Administration, the Vascular Cures Foundation, and Carelon Medical Benefits Management as the Vascular Expert Advisory Panelist. Dr. Ibrahim receives funding from the Agency for Healthcare Research and Quality as a principal investigator on grant R01-HS028606 and a co-investigator on grant R18-HS028963. He also received funding from the National Institute of Diabetes and Digestive and Kidney Disease as a co-principal investigator on grant R01-DK137466.
Footnotes
Disclosures: Dr. Ibrahim is a Principal at HOK architects, a global design and architecture firm. The authors have no conflicts of interest pertaining to the work herein. Dr Corriere serves on the Vascular Expert Advisory Panel for AIM Specialty Health, Inc. The remaining authors have no financial disclosures.
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