Abstract
Background:
Low back pain (LBP)-driven inpatient stays are resource-intensive and costly, yet data on contemporary national trends are limited.
Materials and methods:
This study used repeated cross-sectional analyses through a nationally representative sample (US National Inpatient Sample, 2016–2019). Outcomes included the rate of LBP-driven inpatient stays; the resource utilization (the proportion of receiving surgical treatments and hospital costs) and prognosis (hospital length of stay and the proportion of nonroutine discharge) among LBP-driven inpatient stays. LBP was classified as overall, nonspecific, and specific (i.e. cancer, cauda equina syndrome, vertebral infection, vertebral compression fracture, axial spondyloarthritis, radicular pain, and spinal canal stenosis). Analyses were further stratified by age, sex, and race/ethnicity.
Results:
292 987 LBP-driven inpatient stays (weighted number: 1 464 690) were included, with 269 080 (91.8%) of these for specific LBP and 23 907 (8.2%) for nonspecific LBP. The rate of LBP-driven inpatient stays varied a lot across demographic groups and LBP subtypes (e.g. for overall LBP, highest for non-Hispanic White 180.4 vs. lowest for non-Hispanic Asian/Pacific Islander 42.0 per 100 000 population). Between 2016 and 2019, the rate of nonspecific LBP-driven inpatient stays significantly decreased (relative change: 46.9%); however, substantial variations were found within subcategories of specific LBP-significant increases were found for vertebral infection (relative change: 17.2%), vertebral compression fracture (relative change: 13.4%), and spinal canal stenosis (relative change: 19.9%), while a significant decrease was found for radicular pain (relative change: 12.6%). The proportion of receiving surgical treatments also varied a lot (e.g. for overall LBP, highest for non-Hispanic White 74.4% vs. lowest for non-Hispanic Asian/Pacific Islander 62.8%), and significantly decreased between 2016 and 2019 (e.g. for nonspecific LBP, relative change: 28.6%). Variations were also observed for other outcomes.
Conclusions:
In the US, the burden of LBP-driven inpatient stays (i.e. rates of LBP-driven inpatient stays, resource utilization, and prognosis among LBP-driven inpatient stays) is enormous. More research is needed to understand why the burden varies considerably according to the LBP subtype (i.e. nonspecific and specific LBP as well as subcategories of specific LBP) and the subpopulation concerned (i.e. stratified by age, sex, and race/ethnicity).
Keywords: inpatient stay, low back pain, subpopulation, subtype, surgery, trend
Introduction
Highlights
Between 2016 and 2019, there were more than 1.4 million LBP-driven inpatient stays in the US.
The rate of nonspecific LBP-driven inpatient stays significantly decreased.
No significant change was observed in the rate of overall and specific LBP-driven inpatient stays, though some trends indicating increases or decreases were observed within subcategories of specific LBP.
The proportion of receiving surgical treatments among LBP-driven inpatient stays significantly decreased.
Low back pain (LBP) has been the leading cause of disability for almost three decades, with a large-scale systematic review suggesting a lifetime prevalence of around 40%1,2. Although most patients with LBP are managed in primary care, some patients are admitted to hospitals, which can be resource-intensive and costly3,4. According to a recent systematic review, no relevant studies were identified on LBP hospital admissions per population in the United States (US)5. Previous US studies have focused on admissions as a proportion of emergency department (ED) presentations or were not designed to evaluate recent national-level estimates. For example, one relatively new study used 2012–2014 data from an urban, university-affiliated ED, and another study used nationally representative ED data from 2002 to 20066,7. Another important issue that has not been addressed in previous studies is the sub-classification of LBP. Depending on whether specific underlying pathophysiological mechanisms can be identified, LBP is often classified as specific (e.g. spinal canal stenosis) or nonspecific (i.e. simple backache with no radicular symptoms or neurological deficit)8. Current clinical guidelines state that specific and nonspecific LBP should be managed differently, depending on the specific LBP condition9,10. It can be difficult to classify patients as having specific or nonspecific LBP using diagnostic coding information from administrative databases, due to the lack of specificity in the codes. However, compared to the International Classification of Disease, 9th Revision, the 10th (ICD-10-CM) includes expanded codes for identifying diseases (implemented since October 2015), providing increased specification and improved ability to classify LBP conditions11.
To address these gaps, this study aimed to assess the rate and trend of LBP-driven inpatient stays overall and by LBP subtype (nonspecific and specific) and within subcategories of specific LBP, in the US from 2016 to 2019. Trends in resource utilization (the proportion of receiving surgical treatments and hospital costs) and prognosis (hospital length of stay and the proportion of nonroutine discharge) among LBP-driven inpatient stays were also assessed.
Methods
This study used repeated cross-sectional analyses. As a secondary analysis of anonymized data, this study did not involve human participants. Thus, informed consent and institutional review board approval were not required. This study followed the strengthening the reporting of cohort studies in surgery (STROCCS, Supplemental Digital Content 1, http://links.lww.com/JS9/B497) statement12.
Data sources
The data used in this study came from two sources: 1) the National Inpatient Sample (NIS), Healthcare Cost and Utilization Project (HCUP), Agency for Healthcare Research and Quality; 2) the U.S. Census Bureau. The NIS is based on the data gathered from about 7 million hospital stays and is considered the largest all-payer inpatient care database in the United States13. Unweighted data from the NIS represent about 20% of all hospital stays in the US, and weighted data cover more than 97% of the US population13. Hospitals included in the NIS are defined as short-term, non-Federal, general, and other hospitals13. Aggregate data on the US population were obtained from U.S. Census Bureau. Four cycles (2016–2019) were included as 2016 is the first full calendar year with ICD-10-CM coded data and 2019 is the latest year with data available at the time of analysis.
Primary outcome
The primary outcome was the rate of LBP-driven inpatient stays overall and by LBP type (nonspecific and specific) and within subcategories of specific LBP, which were cancer, cauda equina syndrome, vertebral infection, vertebral compression fracture, axial spondyloarthritis, radicular pain or radiculopathy (previously called sciatica; hereafter referred to as radicular pain), and spinal canal stenosis14. Detailed definitions can be found in Table A and Figure A (Supplemental Digital Content, http://links.lww.com/JS9/B496).
Secondary outcomes
To assess resource utilization and prognosis among LBP-driven inpatient stays, secondary outcomes included the proportion of receiving surgical treatments, hospital costs, hospital length of stay, and the proportion of nonroutine discharge. Surgical treatment was defined as a surgical procedure performed in the lumbar spinal, sacral, coccygeal, or sacroiliac region (Details in Supplemental Digital Content, Table B, http://links.lww.com/JS9/B496). Hospital costs and length of stay were presented as median with interquartile range (IQR). Hospital costs were calculated through a 2-step way: step one, hospital charges were converted to costs based on Cost-to-Charge Ratio Files15,16; step two, costs from step one were adjusted for inflation to 2019 US dollars using the gross domestic product price index. The discharge status was classified as a binary variable: nonroutine versus routine or other17.
Demographic characteristics
Based on data available in both the NIS and from the U.S. Census Bureau, demographic characteristics selected for analysis included age, sex, and race/ethnicity. Age was classified as 18–44, 45–64, 65–84, and 85 or more. Sex was classified as male and female. Race/ethnicity was classified as non-Hispanic White, non-Hispanic Black, Hispanic, non-Hispanic Asian/Pacific Islander, and Native American.
Statistical analysis
For each included data cycle, the rate of LBP-driven inpatient stays overall and by LBP type (nonspecific and specific) and within subcategories of specific LBP per 100 000 population was calculated. The proportion of receiving surgical treatments, hospital costs, hospital length of stay, and the proportion of nonroutine discharge among LBP-driven inpatient stays overall and by LBP type (nonspecific and specific) and within subcategories of specific LBP were calculated. Analyses were further stratified by demographic characteristics as subgroup analyses. To avoid potential understatement of the magnitude of differences and causal misinterpretation of results due to inappropriate adjustment, estimates were not adjusted by covariates in the primary analysis18. For primary outcomes, age-adjusted rates were calculated as a sensitivity analysis. Differences in the rate of LBP-driven inpatient stays, the proportion of receiving surgical treatments, and the proportion of nonroutine discharge were compared using both absolute differences (estimate in 2019–estimate in 2016) and corresponding percentage changes [(estimate in 2019–estimate in 2016)/estimate in 2016×100%] with 95% CIs15. Given that hospital costs and length of stay are skewed parameters, log(y) and the quasipoisson family through the generalized linear model were used, respectively19,20. The above analyses were based on the estimate from the first and last cycle, and can be considered as a measure of overall change. Several other sensitivity analyses were performed to assess the reliability of the coding: first, excluding the visit that received chemotherapy (because the visit could have been related to the cancer itself, not to the cancer) for cancer-involved specific LBP; second, including spondylolisthesis as an additional subcategory of specific LBP21,22; third, extending the surgical region to the whole spine. Details for sensitivity analyses can be found in Table C (Supplemental Digital Content, http://links.lww.com/JS9/B496). As the NIS collected data through the complex sampling strategy, weights were used to ensure that the estimates were nationally representative, and weights and design variables were included to obtain unbiased estimates and standard errors. Based on the requirements for publishing with HCUP data, cell sizes less than or equal to 10 were not reported. Complete case analysis was performed, as the proportion of missing data is small (Table 1 and Supplemental Digital Content Table D, http://links.lww.com/JS9/B496)23. Data were analyzed through R version 4.2.2 (R Group for Statistical Computing), Stata version 17.0 (StataCorp) and SPSS version 27.0 (IBM Corp).
Table 1.
Demographic distribution of all included low back pain-driven inpatient stays.
| Overall LBP | Specific LBP | Nonspecific LBP | |
|---|---|---|---|
| Unweighted No. | 292 987 | 269 080 | 23 907 |
| Weighted No. | 1 464 935 (1 436 384–1 493 485) | 1 345 400 (1 318 539–1 372 261) | 119 535 (116 475–122 595) |
| Age, mean (95% CI), y | 63.4 (63.3–63.5) | 63.8 (63.7–63.9) | 58.5 (58.3–58.8) |
| Age, % (95% CI) | |||
| 18–44 | 12.4 (12.3–12.6) | 11.5 (11.3–11.6) | 23.2 (22.6–23.8) |
| 45–64 | 36.0 (35.8–36.3) | 35.9 (35.6–36.1) | 37.8 (37.1–38.5) |
| 65–84 | 44.3 (44.0–44.6) | 45.5 (45.2–45.8) | 31.4 (30.7–32.0) |
| 85 or more | 7.2 (7.1–7.4) | 7.2 (7.1–7.3) | 7.6 (7.3–8.0) |
| Missing, No. (%) | NR | NR | NR |
| Sex, % (95% CI) | |||
| Male | 47.5 (47.3–47.7) | 47.6 (47.4–47.9) | 45.8 (45.1–46.4) |
| Female | 52.5 (52.3–52.7) | 52.4 (52.1–52.6) | 54.2 (53.6–54.9) |
| Missing, No. (%) | 35 (0.0) | 33 (0.0) | NR |
| Race, % (95% CI) | |||
| Non-Hispanic White | 78.9 (78.4–79.3) | 79.1 (78.7–79.6) | 75.6 (74.8–76.3) |
| Non-Hispanic Black | 9.0 (8.8–9.3) | 8.9 (8.7–9.1) | 10.7 (10.2–11.1) |
| Hispanic | 7.4 (7.1–7.7) | 7.3 (7.0–7.6) | 9.2 (8.6–9.7) |
| Non-Hispanic Asian or Pacific Islander | 1.7 (1.6–1.8) | 1.8 (1.6–1.9) | 1.3 (1.2–1.5) |
| Native American | 0.5 (0.4–0.5) | 0.5 (0.4–0.5) | 0.4 (0.3–0.5) |
| Other | 2.5 (2.4–2.7) | 2.5 (2.3–2.6) | 2.8 (2.6–3.2) |
| Missing, No. (%) | 9174 (3.1) | 8464 (3.1) | 710 (3.0) |
LBP, low back pain; NR, not reported.
Results
Summary statistics
Between 2016 and 2019, 292 987 LBP-driven inpatient stays were included, representing a weighted total of 1 464 690 inpatient stays: the weighted mean age was 63.4 years, 47.5% were female, 78.9% were non-Hispanic White, 9.0% were non-Hispanic Black, 7.4% were Hispanic, 1.7% were non-Hispanic Asian or Pacific Islander, and 0.5% were Native American (Table 1). For the LBP type, 91.8% (n=269 080, which represented a weighted total of 1 345 155) were specific LBP and 8.2% (n=23 907, which represented a weighted total of 119 535) were nonspecific LBP. For the subcategories of specific LBP, 50.1% (n=134 734, which represented a weighted total of 673 670) were spinal canal stenosis, followed by radicular pain (31.8%, n=85 495, which represented a weighted total of 427 475), vertebral compression fracture (11.1%, n=29 849, which represented a weighted total of 149 245), vertebral infection (5.9%, n=15 982, which represented a weighted total of 79,910), cauda equina syndrome (1.0%, n=2728, which represented a weighted total of 13 640), axial spondylitis (1.0%, n=2667, which represented a weighted total of 13 335), and cancer (0.9%, n=2327, which represented a weighted total of 11 635) (Supplemental Digital Content Table E, http://links.lww.com/JS9/B496).
Primary outcomes
In 2019, the rate of overall LBP-driven inpatient stays was higher in older age groups [aged 18–44 years 36.1 (95% CI: 34.0–38.3) vs. aged 85 or more years 416.3 (95% CI: 393.0–439.6) per 100 000 population] and highest among non-Hispanic White [180.4 (95% CI: 170.2–190.6) vs. lowest among non-Hispanic Asian/Pacific Islander 42.0 (95% CI: 36.4–47.6) per 100 000 population)], but similar in both sexes [male 143.3 (95% CI: 135.3–151.2) vs. female 151.0 (95% CI: 143.0–159.1) per 100 000 population) (Table 2). The similar pattern was observed in specific and nonspecific LBP-driven inpatient stays except the rate of nonspecific LBP-driven inpatient stays was higher in female (Table 2). Variations were observed within subcategories of specific LBP, such as the rate of inpatient stays for cancer was higher in male, and the rate of spinal canal stenosis was highest in aged 65 to 84 years.
Table 2.
The rate of low back pain-driven inpatient stays per 100 000 population stratified by demographic characteristics, 2016–2019.
| Characteristics | 2016 | 2017 | 2018 | 2019 | Absolute difference (95% CI) from 2016 to 2019 | Relative change (95% CI) from 2016 to 2019, % |
|---|---|---|---|---|---|---|
| Overall LBP | ||||||
| Overall | 146.0 (138.1–153.8) | 142.6 (134.9–150.3) | 144.8 (136.9–152.6) | 147.3 (139.3–155.2) | 1.3 (−9.9 to 12.4) | 0.9 (−6.8 to 8.5) |
| Age | ||||||
| 18–44 | 43.1 (40.5–45.7) | 39.2 (36.8–41.6) | 37.2 (34.9–39.5) | 36.3 (34.2–38.5) | −6.7 (−10.2 to −3.3) | −15.7 (−23.6 to −7.7) |
| 45–64 | 160.9 (151.5–170.2) | 157.3 (148.1–166.5) | 153.6 (144.6–162.5) | 157.7 (148.6–166.7) | −3.2 (−16.2 to 9.8) | −2.0 (−10.1 to 6.1) |
| 65–84 | 357.8 (338.2–377.4) | 349.3 (330.0–368.6) | 365.0 (344.5–385.5) | 366.9 (346.5–387.3) | 9.1 (−19.1 to 37.4) | 2.6 (−5.3 to 10.4) |
| 85 or more | 398.2 (375.8–420.6) | 398.9 (376.7–421) | 416.3 (393.4–439.3) | 416.3 (392.9–439.6) | 18.1 (−14.3 to 50.5) | 4.5 (−3.6 to 12.7) |
| Sex | ||||||
| Male | 142.7 (134.7–150.6) | 139.3 (131.5–147.1) | 140.5 (132.6–148.5) | 143.3 (135.3–151.3) | 0.6 (−10.7 to 11.9) | 0.4 (−7.5 to 8.3) |
| Female | 149.0 (141.0–156.9) | 145.7 (137.9–153.6) | 148.8 (140.8–156.7) | 151.0 (143.0–159.1) | 2.1 (−9.2 to 13.4) | 1.4 (−6.2 to 9.0) |
| Race/ethnicity | ||||||
| Non-Hispanic White | 172.0 (162.1–181.9) | 170.3 (160.5–180.1) | 174.9 (164.8–185.0) | 180.4 (170.1–190.6) | 8.3 (−5.9 to 22.5) | 4.8 (−3.4 to 13.1) |
| Non-Hispanic Black | 103.7 (95.8–111.6) | 99.1 (91.6–106.6) | 105.1 (96.9–113.2) | 110.5 (102.1–119.0) | 6.8 (−4.7 to 18.4) | 6.6 (−4.6 to 17.7) |
| Hispanic | 65.0 (58.6–71.4) | 64.0 (57.9–70.2) | 67.3 (60.9–73.7) | 63.6 (57.7–69.5) | −1.4 (−10.1 to 7.3) | −2.1 (−15.5 to 11.3) |
| Non-Hispanic Asian or Pacific Islander | 38.1 (32.7–43.4) | 39.4 (34.0–44.9) | 41.6 (35.6–47.6) | 42.0 (36.4–47.6) | 3.9 (−3.8 to 11.7) | 10.3 (−10.0 to 30.6) |
| Native American | 86.4 (65.7–107.2) | 88.2 (72.5–103.9) | 92.8 (72.9–112.7) | 97.6 (74.6–120.6) | 11.2 (−19.8 to 42.1) | 12.9 (−22.9 to 48.8) |
| Specific LBP | ||||||
| Overall | 129.3 (122.2–136.3) | 130.6 (123.5–137.8) | 134.8 (127.3–142.2) | 138.4 (130.9–145.9) | 9.1 (−1.2 to 19.4) | 7.0 (−0.9 to 15.0) |
| Age | ||||||
| 18–44 | 34.4 (32.3–36.6) | 33.4 (31.3–35.5) | 32.1 (30.1–34.2) | 32.1 (30.1–34.1) | −2.3 (−5.3 to 0.6) | −6.8 (−15.4 to 1.8) |
| 45–64 | 141.9 (133.5–150.2) | 143.5 (135.0–152.1) | 142.5 (134.1–150.9) | 147.7 (139.1–156.3) | 5.8 (−6.2 to 17.8) | 4.1 (−4.4 to 12.6) |
| 65–84 | 327.5 (309.3–345.7) | 328.4 (310.0–346.8) | 347.5 (327.7–367.2) | 351.6 (331.9–371.3) | 24.1 (−2.7 to 50.9) | 7.4 (−0.8 to 15.6) |
| 85 or more | 357.7 (337.2–378.2) | 361.2 (340.7–381.7) | 384.1 (362.5 to 405.6) | 385.9 (364.0 to 407.9) | 28.3 (−1.8 to 58.3) | 7.9 (−0.5 to 16.3) |
| Sex | ||||||
| Male | 126.7 (119.5–133.8) | 127.9 (120.6–135.1) | 131.4 (123.8–138.9) | 135.3 (127.6–142.9) | 8.6 (−1.9 to 19.1) | 6.8 (−1.5 to 15.1) |
| Female | 131.7 (124.6–138.8) | 133.3 (126.0–140.6) | 138.0 (130.5–145.5) | 141.4 (133.8–149.0) | 9.7 (−0.7 to 20.1) | 7.4 (−0.6 to 15.3) |
| Race/ethnicity | ||||||
| Non-Hispanic White | 152.7 (143.8–161.6) | 156.5 (147.3–165.7) | 163.5 (154.0–173.1) | 170.1 (160.4–179.9) | 17.4 (4.2–30.6) | 11.4 (2.7–20.0) |
| Non-Hispanic Black | 90.9 (83.8–98.0) | 89.3 (82.4–96.2) | 95.9 (88.4–103.5) | 101.8 (93.9–109.7) | 10.9 (0.2–21.5) | 11.9 (0.2–23.6) |
| Hispanic | 56.0 (50.4–61.6) | 57.4 (51.7–63.0) | 61.3 (55.4–67.1) | 59.0 (53.4–64.5) | 3.0 (−4.9 to 10.9) | 5.3 (−8.8 to 19.4) |
| Non-Hispanic Asian or Pacific Islander | 35.1 (30.1–40.2) | 36.4 (31.3–41.5) | 39.3 (33.6–45.0) | 39.9 (34.6–45.3) | 4.8 (−2.5 to 12.1) | 13.7 (−7.1 to 34.6) |
| Native American | 76.7 (58.4–95.1) | 80.4 (65.7–95.0) | 88.1 (68.7–107.5) | 91.8 (69.3–114.3) | 15.1 (−14.0 to 44.1) | 19.6 (−18.2 to 57.5) |
| Nonspecific LBP | ||||||
| Overall | 16.7 (15.7–17.7) | 12.0 (11.2–12.7) | 10.0 (9.4–10.6) | 8.8 (8.3–9.4) | −7.8 (−9.0 to −6.7) | −46.9 (−53.9 to −40.0) |
| Age | ||||||
| 18–44 | 8.7 (8.0–9.3) | 5.8 (5.4–6.3) | 5.0 (4.6–5.4) | 4.2 (3.9–4.6) | −4.4 (−5.2 to −3.7) | −51.0 (−59.6 to −42.4) |
| 45–64 | 19.0 (17.6–20.4) | 13.8 (12.8–14.8) | 11.1 (10.2–11.9) | 10.0 (9.2–10.8) | −9.0 (−10.6 to −7.4) | −47.4 (−55.8 to −39.0) |
| 65–84 | 30.3 (28.2–32.3) | 20.9 (19.4–22.4) | 17.5 (16.2–18.8) | 15.3 (14.2–16.4) | −15.0 (−17.3 to −12.6) | −49.5 (−57.3 to −41.7) |
| 85 or more | 40.5 (36.4–44.6) | 37.7 (33.9–41.4) | 32.2 (28.8–35.7) | 30.4 (26.9–33.8) | −10.2 (−15.5 to −4.8) | −25.1 (−38.3 to −11.8) |
| Sex | ||||||
| Male | 16.0 (14.9–17.1) | 11.4 (10.7–12.2) | 9.2 (8.5–9.8) | 8.0 (7.4–8.5) | −8.0 (−9.2 to −6.8) | −50.2 (−57.7 to −42.6) |
| Female | 17.3 (16.2–18.4) | 12.5 (11.7–13.3) | 10.8 (10.1–11.5) | 9.7 (9.0–10.3) | −7.6 (−8.9 to −6.3) | −44.0 (−51.4 to −36.7) |
| Race/ethnicity | ||||||
| Non-Hispanic White | 19.3 (18.0–20.6) | 13.8 (12.9–14.7) | 11.4 (10.6–12.1) | 10.2 (9.5–10.9) | −9.1 (−10.5 to −7.6) | −47.1 (−54.6 to −39.6) |
| Non-Hispanic Black | 12.8 (11.5–14.1) | 9.8 (8.7–10.8) | 9.1 (8.1–10.2) | 8.8 (7.8–9.7) | −4.0 (−5.7 to −2.4) | −31.5 (−44.3 to −18.7) |
| Hispanic | 9.0 (7.9–10.1) | 6.7 (5.8–7.6) | 6.1 (5.3–6.8) | 4.6 (4.0–5.3) | −4.3 (−5.6 to −3.0) | −48.4 (−62.8 to −33.9) |
| Non-Hispanic Asian or Pacific Islander | 2.9 (2.2–3.6) | 3.1 (2.4–3.8) | 2.3 (1.5–3.1) | 2.0 (1.5–2.6) | −0.9 (−1.8 to 0.0) | −30.2 (−60.7 to 0.4) |
| Native American | 9.7 (5.9–13.4) | 7.9 (4.7–11.1) | 4.7 (2.5–7.0) | 5.8 (3.1–8.5) | −3.9 (−8.5 to 0.7) | −40.3 (−88.2 to 7.7) |
LBP, low back pain.
Between 2016 and 2019, no significant change was observed in the rate of overall [147.3 (95% CI: 139.3–155.2) in 2019 per 100 000 population) and specific (138.4 [95% CI: 130.9–145.9) in 2019 per 100 000 population] LBP-driven inpatient stays; no significant changes were also found for all subgroups except for non-Hispanic White and non-Hispanic Black, in whom stays significantly increased (Table 2). Substantial variations were observed within subcategories of specific LBP-significant increases were found for the rate of inpatient stays for vertebral infection (from 7.4 (95% CI, 6.9 to 7.9] in 2016 to 8.7 [95% CI, 8.2 to 9.3] in 2019 per 100,000 population, relative change: 17.2% [95% CI, 7.1% to 27.4%]), vertebral compression fracture (from 13.8 [95% CI, 13.1 to 14.6] in 2016 to 15.7 [95% CI, 14.8 to 16.5] in 2019 per 100,000 population, relative change: 13.4% [95% CI, 5.3% to 21.6%]), and spinal canal stenosis (from 60.5 [95% CI, 56.6 to 64.3] in 2016 to 72.5 [95% CI, 68.0 to 77.0] in 2019 per 100,000 population, relative change: 19.9% [95% CI, 10.1% to 29.7%]), while a significant decrease was found for the rate of radicular pain [from 45.8 (95% CI: 43.1–48.5) in 2016 to 40.0 (95% CI: 37.7–42.4) in 2019 per 100 000 population, relative change: 12.6% (95% CI: 20.5–4.6%)]. Subgroup analyses showed variations, such as the rate of cancer-involved specific LBP-driven inpatient stays significantly increased in non-Hispanic Black (Supplemental Digital Content, Table F, http://links.lww.com/JS9/B496). The rate of nonspecific LBP-driven inpatient stays significantly decreased from 16.7 (95% CI: 15.7–17.7) in 2016 to 8.8 (8.3–9.4) in 2019 per 100 000 population, representing a relative decrease of 46.9% (95% CI: 40.0–53.8%). Significant decreases were also found for all subgroups except for non-Hispanic Asian or Pacific Islander and Native American who showed no significant changes (Table 3).
Table 3.
The rate of specific low back pain-driven inpatient stays per 100 000 population stratified by subcategories, 2016–2019.
| 2016 | 2017 | 2018 | 2019 | Absolute difference (95% CI) from 2016 to 2019 | Relative change (95% CI) from 2016 to 2019, % | |
|---|---|---|---|---|---|---|
| Cancer | 1.1 (1.0–1.2) | 1.2 (1.0–1.3) | 1.1 (1.0–1.3) | 1.2 (1.1–1.3) | 0.1 (−0.1 to 0.2) | 6.4 (−8.3 to 21.1) |
| Vertebral infection | 7.4 (6.9–7.9) | 7.5 (7.0–7.9) | 8.0 (7.5–8.6) | 8.7 (8.2–9.3) | 1.3 (0.5–2.0) | 17.2 (7.1–27.4) |
| Cauda equina syndrome | 1.4 (1.2–1.5) | 1.3 (1.2–1.4) | 1.3 (1.2–1.4) | 1.4 (1.3–1.6) | 0.1 (−0.1 to 0.3) | 4.2 (−9.9 to 18.4) |
| Vertebral compression fracture | 13.8 (13.1–14.6) | 14.4 (13.6–15.1) | 15.2 (14.4–16.0) | 15.7 (14.8–16.5) | 1.9 (0.7–3.0) | 13.4 (5.3–21.6) |
| Axial spondyloarthritis | 1.4 (1.2–1.6) | 1.3 (1.1–1.4) | 1.3 (1.1–1.5) | 1.3 (1.2–1.5) | −0.1 (−0.3 to 0.2) | −4.2 (−21.6 to 13.3) |
| Radicular pain | 45.8 (43.1–48.6) | 42.7 (40.1–45.2) | 41.0 (38.5–43.4) | 40.0 (37.6–42.4) | −5.8 (−9.4 to −2.1) | −12.6 (−20.5 to −4.6) |
| Spinal canal stenosis | 60.5 (56.6–64.3) | 64.7 (60.6–68.8) | 69.2 (64.8–73.6) | 72.5 (68.0–77.0) | 12.0 (6.1–18.0) | 19.9 (10.1–29.7) |
Secondary outcomes
In 2019, the proportion of receiving surgical treatments for overall, specific, and nonspecific LBP-driven inpatient stays was 72.7% (95% CI: 71.9–73.6%), 74.7% (95% CI: 73.8–75.5%), and 42.7% (95% CI: 40.4–44.9%), respectively (Table 4). The median hospital costs for overall, specific, and nonspecific LBP-driven inpatient stays were $18 582 (IQR $9767–$31 493), $19 169 (IQR $10 211–$32 064), and $9864 (95% CI: $5350–$20 450), respectively (Table 4). The median hospital length of stay for overall, specific, and nonspecific LBP-driven inpatient stays was 3 days (IQR, 2 days to 5 days), 3 days (IQR, 2 days to 5 days), and 2 days (IQR, 1 day to 4 days), respectively (Table 4). The proportion of nonroutine discharge for overall, specific, and nonspecific LBP-driven inpatient stays was 24.6% (95% CI: 24.1–25.2%), 24.9% (95% CI: 24.3–25.4%), and 20.8% (95% CI: 19.5–22.2%), respectively (Table 4). Results within subcategories of specific LBP and from subgroup analyses can be found in Table 4 and Table G (Supplemental Digital Content, http://links.lww.com/JS9/B496).
Table 4.
Resource utilization and prognosis among low back pain-driven inpatient stays stratified by demographic characteristics, 2019.
| Overall LBP | Specific LBP | Nonspecific LBP | |
|---|---|---|---|
| Proportion of receiving surgical treatments, % (95% CI) | |||
| Overall | 72.7 (71.9–73.6) | 74.7 (73.8–75.5) | 42.7 (40.4–44.9) |
| Age | |||
| 18–44 | 73.1 (71.8–74.5) | 75.3 (73.9–76.6) | 57.2 (53.6–60.7) |
| 45–64 | 79.9 (79.0–80.7) | 81.7 (80.8–82.5) | 52.9 (49.9–55.9) |
| 65–84 | 73.8 (72.9–74.7) | 75.6 (74.7–76.5) | 31.6 (28.7–34.8) |
| 85 or more | 31.2 (29.8–32.7) | 33.4 (31.9–34.9) | 3.7 (2.3–6.1) |
| Sex | |||
| Male | 76.3 (75.4–77.1) | 78.1 (77.3–78.9) | 45.4 (42.6–48.2) |
| Female | 69.5 (68.5–70.5) | 71.5 (70.6–72.5) | 40.5 (38.0–43.2) |
| Race/ethnicity | |||
| Non-Hispanic White | 74.4 (73.5–75.3) | 76.1 (75.3–77.0) | 45.3 (42.8–47.8) |
| Non-Hispanic Black | 65.0 (63.2–66.7) | 68.0 (66.3–69.7) | 29.5 (25.5–33.9) |
| Hispanic | 67.2 (65.3–69.2) | 69.5 (67.5–71.4) | 38.8 (33.4–44.5) |
| Non-Hispanic Asian or Pacific Islander | 62.8 (59.7–65.9) | 64.5 (61.4–67.5) | 29.7 (19.0–43.1) |
| Native American | 69.0 (61.2–75.9) | 71.6 (63.8–78.2) | 28.6 (13.0–51.6) |
| Hospital costs, median (IQR), $ | |||
| Overall | 18 582 (9767–31 493) | 19 169 (10 211 –32 064) | 9864 (5350–20 450) |
| Age | |||
| 18–44 | 16 537 (8957–28 066) | 17 130 (9574–28 859) | 11 498 (5517–22 723) |
| 45–64 | 21 534 (11 532 –34 559) | 22 119 (12 061 –35 140) | 12 139 (5883–23 561) |
| 65–84 | 18 952 (10 020 –32 054) | 19 402 (10 415 –32 536) | 8827 (5156–18 273) |
| 85 or more | 9663 (6123–15 675) | 10 019 (6307–16 111) | 6625 (4412–9920) |
| Sex | |||
| Male | 19 028 (10 170 –32 049) | 19 518 (10 604 –32 604) | 10 520 (5413–22 126) |
| Female | 18 214 (9365–31 032) | 18 861 (9868–31 605) | 9392 (5279–19 260) |
| Race/ethnicity | |||
| Non-Hispanic White | 18 672 (9856–31 401) | 19 194 (10 272 –31 905) | 10 074 (5388–20 802) |
| Non-Hispanic Black | 18 263 (9337–31 551) | 19 142 (9992–32 428) | 8484 (5250–18 297) |
| Hispanic | 17 996 (9401–32 156) | 18 754 (9934–33 010) | 9042 (5334–18 824) |
| Non-Hispanic Asian or Pacific Islander | 17 133 (9201–30 466) | 17 624 (9618–31 042) | 8156 (5213–13 903) |
| Native American | 19 534 (10 400 –32 229) | 19 710 (10 978 –32 309) | 9634 (4448–20 589) |
| Hospital length of stay, median (IQR), d | |||
| Overall | 3 (2–5) | 3 (2–5) | 2 (1–4) |
| Age | |||
| 18–44 | 3 (1–4) | 3 (2–4) | 2 (1–3) |
| 45–64 | 3 (2–4) | 3 (2–5) | 2 (1–4) |
| 65–84 | 3 (2–5) | 3 (2–5) | 3 (2–4) |
| 85 or more | 4 (3–6) | 4 (3–6) | 3 (2–5) |
| Sex | |||
| Male | 3 (2–5) | 3 (2–5) | 2 (1–4) |
| Female | 3 (2–5) | 3 (2–5) | 3 (2–4) |
| Race/ethnicity | |||
| Non-Hispanic White | 3 (2–5) | 3 (2–5) | 2 (1–4) |
| Non-Hispanic Black | 4 (2–6) | 4 (2–6) | 3 (2–5) |
| Hispanic | 3 (2–5) | 3 (2–5) | 3 (1–4) |
| Non-Hispanic Asian or Pacific Islander | 3 (2–5) | 3 (2–5) | 2 (1–3) |
| Native American | 3 (2–6) | 3 (2–6) | 3 (2–5) |
| Proportion of nonroutine discharge, % (95% CI) | |||
| Overall | 8.2 (7.5–8.9) | 4.3 (3.2–5.8) | 7.7 (7.1–8.4) |
| Age | |||
| 18–44 | 7.7 (7.1–8.4) | 8.2 (7.5–8.9) | 4.3 (3.2–5.8) |
| 45–64 | 13.1 (12.6–13.7) | 13.3 (12.7–13.8) | 11.0 (9.5–12.8) |
| 65–84 | 31.6 (30.9–32.3) | 31.6 (30.9–32.3) | 32.6 (30.2–35.1) |
| 85 or more | 61.5 (60.1–62.8) | 61.6 (60.2–63.0) | 59.9 (55.1–64.4) |
| Sex | |||
| Male | 20.5 (19.9–21.1) | 20.6 (20.0–21.3) | 18.0 (16.3–19.9) |
| Female | 28.3 (27.7–29.0) | 28.7 (28.1–29.4) | 23.0 (21.3–24.8) |
| Race/ethnicity | |||
| Non-Hispanic White | 24.7 (24.1–25.3) | 24.9 (24.3–25.5) | 21.8 (20.2–23.5) |
| Non-Hispanic Black | 27.4 (26.2–28.7) | 27.8 (26.5–29.1) | 22.8 (19.4–26.4) |
| Hispanic | 20.8 (19.4–22.1) | 21.3 (19.9–22.8) | 13.9 (10.8–17.6) |
| Non-Hispanic Asian or Pacific Islander | 28.0 (25.2–31.1) | 28.4 (25.4–31.5) | 21.9 (13.6–33.3) |
| Native American | 25.9 (21.1–31.4) | 27.2 (22.2–32.9) | 4.8 (0.7–27.3) |
IQR, interquartile range; LBP, low back pain.
Between 2016 and 2019, the proportion of receiving surgical treatments for overall [from 74.2% (73.3–75.0%) in 2016 to 72.7% (71.9–73.6%) in 2019, relative change: 1.9% (95% CI: 3.6–0.3%)], specific [from 76.0% (95% CI: 75.2–76.8%) in 2016 to 74.7% (73.8–75.5%) in 2019, relative change: 1.8% (95% CI: 3.3–0.3%)], and nonspecific [from 59.8% (95% CI: 58.0–61.5%) in 2016 to 42.7% (40.4–44.9%) in 2019, relative change: 28.6% (95% CI: 23.8–33.4%)] LBP-driven inpatient stays significantly decreased (Table 5). For the hospital costs, significantly increases were observed for overall [from $17,176 (IQR $9018–$30 025) in 2016 to $18 582 (IQR $9767–$31 493) in 2019] and specific [from $17 615 (IQR $9424–$30 452) in 2016 to $19 169 (IQR $10 211–$32 064) in 2019] LBP-driven inpatient stays between 2016 and 2019, but a significant decrease [from $13 126 (IQR $6453–$26 361) in 2016 to $9864 (IQR $5350–$20 450) in 2019] was observed for nonspecific LBP-driven inpatient stays (Table 5). For the hospital length of stay, significantly increases were observed for overall and specific LBP-driven inpatient stays, but no significant change was observed for nonspecific LBP-driven inpatient stays (Table 5). For the proportion of nonroutine discharge, significantly increase [from 18.2% (95% CI: 17.2–19.1%) in 2016 to 20.8% (95% CI: 19.5–22.2%) in 2019, relative change: 14.6% (95% CI: 5.6–23.7%)] were observed for nonspecific LBP-driven inpatient stays, but no significant change was observed for overall and specific LBP-driven inpatient stays (Table 5). Results within subcategories of specific LBP and from subgroup analyses can be found in Table 5 and Table H (Supplemental Digital Content, http://links.lww.com/JS9/B496).
Table 5.
Resource utilization and prognosis among low back pain-driven inpatient stays, 2016–2019.
| 2016 | 2017 | 2018 | 2019 | Absolute difference (95% CI) from 2016 to 2019 | Relative change (95% CI) from 2016 to 2019, % | |
|---|---|---|---|---|---|---|
| Proportion of receiving surgical treatments, % (95% CI) | ||||||
| Overall LBP | 74.2 (73.3–75.0) | 73.8 (72.9–74.6) | 73.4 (72.5–74.2) | 72.7 (71.9–73.6) | −1.4 (−2.6 to −0.2) | −1.9 (−3.6 to −0.3) |
| Specific LBP | 76.0 (75.2–76.8) | 75.8 (75.0–76.6) | 75.3 (74.4–76.1) | 74.7 (73.8–75.5) | −1.4 (−2.5 to −0.2) | −1.8 (−3.3 to −0.3) |
| Nonspecific LBP | 59.8 (58.0–61.5) | 51.8 (49.8–53.9) | 47.5 (45.5–49.6) | 42.7 (40.4–44.9) | −17.1 (−20.0 to −14.2) | −28.6 (−33.4 to −23.8) |
| Proportion of nonroutine discharge, % (95% CI) | ||||||
| Overall LBP | 23.9 (23.3–24.4) | 24.4 (23.8–24.9) | 24.8 (24.2–25.4) | 24.6 (24.1–25.2) | 0.8 (0.0–1.5) | 3.2 (−0.1 to 6.4) |
| Specific LBP | 24.6 (24.0–25.2) | 24.7 (24.2–25.3) | 25.2 (24.6–25.8) | 24.9 (24.3–25.4) | 0.3 (−0.5 to 1.1) | 1.1 (−2.2 to 4.3) |
| Nonspecific LBP | 18.2 (17.2–19.1) | 20.1 (19.0–21.3) | 19.4 (18.2–20.6) | 20.8 (19.5–22.2) | 2.7 (1.0–4.3) | 14.6 (5.6–23.7) |
| 2016 | 2017 | 2018 | 2019 | Estimate | P | |
| Hospital costs, median (IQR), $ | ||||||
| Overall LBP | 17 176 (9018–30 025) | 17 742 (9275–30 095) | 17 809 (9324–30 122) | 18 582 (9767–31 493) | 0.03 | <0.001 |
| Specific LBP | 17 615 (9424–30 452) | 18 201 (9703–30 534) | 18 310 (9760–30 640) | 19 169 (10 211 –32 064) | 0.03 | <0.001 |
| Nonspecific LBP | 13 126 (6453–26 361) | 11 601 (5833–24 635) | 10 293 (5456–22 452) | 9864 (5350–20 450) | −0.10 | <0.001 |
| Hospital length of stay, median (IQR), d | ||||||
| Overall LBP | 3 (2–5) | 3 (2–5) | 3 (2–5) | 3 (2–5) | 0.04 | <0.001 |
| Specific LBP | 3 (2–5) | 3 (2–5) | 3 (2–5) | 3 (2–5) | 0.04 | 0.003 |
| Nonspecific LBP | 3 (2–4) | 3 (2–4) | 3 (1–4) | 2 (1–4) | −0.02 | 0.31 |
LBP, low back pain; IQR, interquartile range.
Additional analyses
Results from sensitivity analyses were similar with main analyses (Supplemental Digital Content, Table I, http://links.lww.com/JS9/B496).
Discussion
Principal findings
From 2016 to 2019, among US adults, no significant change was observed in the rate of overall and specific LBP-driven inpatient stays; however, the rate of nonspecific LBP-driven inpatient stays significantly decreased. Substantial variations were found within subcategories of specific LBP-significant increases were found for the rate of inpatient stays for vertebral infection, vertebral compression fracture, and spinal canal stenosis, while a significant decrease was found for the rate of radicular pain. Similar results from sensitivity analyses indicated that age and potential coding uncertainties were unlikely to account for the changes, suggesting the need for further research to understand other factors that may be driving changes.
Comparison with previous studies
To our knowledge, this is the first study to estimate the rate and trend of LBP-driven inpatient stays among a nationwide sample of US adults. Studies in other countries showed wide variation, with Mexico having the lowest rate (14.3 per 100 000 population) and Korea, Republic having the highest rate (817.7 per 100 000 population)24. Looking at countries with similar GDP per capita to the US, rates still varied widely, with Iceland and Norway having rates of 72.6 and 165.6 per 100 000 population, respectively24. But it is still difficult to make a direct comparison with rates in the US because the definition of LBP varied across studies5. For example, some studies used M54 (dorsalgia) and M51 (intervertebral disk disorders), while others did not provide detailed diagnostic codes5. Consensus on the definition of LBP and diagnostic codes used for different LBP conditions across countries is needed so that comparable estimates can be obtained from further studies.
We also found large differences between different racial groups for LBP-driven inpatient stays. For example, non-Hispanic Asian or Pacific Islander had much lower rates compared with the non-Hispanic White (e.g. for the rate of overall LBP-driven inpatient stays, 42.0 vs. 180.4 per 100 000 population). Although the underlying reason should be explored by further studies, potential explanations include differences in access to care, impact of other social determinants of health, structural racism, and/or differences in severity of LBP.
The rate of nonspecific LBP-driven inpatient stays decreased, with consistent results in most subgroups, which may suggest successful implementation of clinical guidelines which recommend a limited role of imaging and surgery9. Results from relevant secondary outcomes also showed that the proportion of patients with nonspecific LBP who received surgical treatment decreased.
Current guidelines and reviews have mainly focused on the management of nonspecific LBP8,14,25, but our results showed that most patients with LBP admitted to hospital have specific LBP, with the rate of several subcategories (e.g. spinal canal stenosis) increasing. Meanwhile, these specific LBP-driven inpatient stays have higher resource utilization and poorer prognosis compared with nonspecific LBP-driven inpatient stays. In addition, further analyses based on subcategories of specific LBP and three demographic subgroups showed wide variations. For example, for the cancer group, the highest median hospital cost was $21 987 among Hispanic and the lowest was $9643 among Native American. Additional research is needed to explore potential driving factors (e.g. disease severity) to better understand the variability.
Limitations
Several limitations should be noted. First, as a study based on hospital discharge data, the reliability of the analysis depends on the reliability of the coding. Therefore, we performed several sensitivity analyses to assess the influence of the coding uncertainties. For specific LBP, as the categorization is not well standardized, we used the classification system from a previous review14. Although the results of the sensitivity analysis by adding spondylolisthesis as an additional subcategory did not change the main results, a valid and standardized definition of specific LBP is still needed to facilitate the future studies. For cancer-involved specific LBP, the definition may not be optimal as there is no existing validated algorithm. Although the sensitivity analysis by excluding the visit that received chemotherapy suggested that the relevant estimates are robust, further validation studies (e.g. by chart review) are still needed26. For surgical treatments, the anatomic region used to identify low back surgeries could lead to misclassification if a back surgery was not coded as having been done in the anatomic back area27. However, similar results obtained in the sensitivity analysis by extending the surgical region to the whole spine may indicate the robustness of this definition. Second, due to the space limitation, several potentially meaningful points were not investigated. For example, some factors that may drive changes in costs (e.g. use of bone morphogenic protein for surgery, or other changes in technologies/costs) and state-level data that showed geographic variation in rates, resource utilization, and prognosis, which should be explored in future studies. Third, the number of waves of data included in the analysis is not large, so our analysis only assessed the overall change, without considering potential fluctuations during this time period. As more new waves will be released in the coming years, a more advanced modeling method (e.g. through the Joinpoint Regression Program) should be considered28. However, the impact of COVID-19 will make it difficult to interpret data from 2020, 2021, and 2022. Fourth, analyses for major ambulatory surgeries were not performed as relevant data were included in the Nationwide Ambulatory Surgery Sample (NASS) rather than the NIS29. Finally, due to data availability, stratified analyses based on some potentially important risk factors (e.g. socioeconomic status, mental health status, and genetic information) for LBP, particularly among people with certain demographic characteristics (e.g. age and race/ethnicity), were not performed and should be explored further.
Conclusion
In the US, the burden of LBP-driven inpatient stays (i.e. rates of LBP-driven inpatient stays, resource utilization and prognosis among LBP-driven inpatient stays) is enormous. More research is needed to understand why the burden varies considerably according to the LBP subtype (i.e. nonspecific and specific LBP as well as subcategories of specific LBP) and the subpopulation concerned (i.e. stratified by age, sex, and race/ethnicity).
Ethical approval
This study was a database-based study and therefore ethical approval was not applicable.
Consent
This study was a database-based study and therefore informed consent was not applicable.
Sources of funding
This study received no funding. M.F. is funded by the National Health and Medical Research Council of Australia. H.Z. is funded by funded by Taishan Scholars Program of Shandong Province-Young Taishan Scholars (tsqn201909197).
Author contribution
L.C.: study design, data interpretation, and writing the original draft; Q.S.: study concept, data collection, data analysis, and writing the original draft; R.C. and B.S.: methodology and review the paper; D.B.A. and Y.C.: review the paper; X.L., S.F., H.Z., and M.L.F: supervision, investigation, and review the paper.
Conflicts of interest disclosure
The authors declare that they have no financial conflicts of interest with regard to the content of this report.
Research registration unique identifying number (UIN)
This study was a database-based study and therefore research registration was not applicable.
Guarantor
Hengxing Zhou.
Data availability statement
Access to data can be requested via application to HCUP (https://hcup-us.ahrq.gov/).
Supplementary Material
Footnotes
Lingxiao Chen and Qingyu Sun contributed equally to this work.
Shiqing Feng and Hengxing Zhou are co-corresponding authors.
Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article.
Supplemental Digital Content is available for this article. Direct URL citations are provided in the HTML and PDF versions of this article on the journal's website, www.lww.com/international-journal-of-surgery.
Published online 4 December 2023
Contributor Information
Lingxiao Chen, Email: lche4036@uni.sydney.edu.au.
Qingyu Sun, Email: 1025462126@qq.com.
Roger Chou, Email: chour@ohsu.edu.
David B. Anderson, Email: david.anderson1@sydney.edu.au.
Baoyi Shi, Email: bs3141@cumc.columbia.edu.
Yujie Chen, Email: yujie.jj.chen@gmail.com.
Xinyu Liu, Email: newyuliu@163.com.
Shiqing Feng, Email: shiqingfeng@sdu.edu.cn.
Hengxing Zhou, Email: zhouhengxing@sdu.edu.cn.
Manuela L. Ferreira, Email: manuela.ferreira@sydney.edu.au.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
Access to data can be requested via application to HCUP (https://hcup-us.ahrq.gov/).