Abstract
Background
Although outcomes following spinal fusion for intervertebral disc disorders have been studied, factors influencing discharge disposition and health care resource utilization have not been determined. This study sought to clarify perioperative risk factors for non-routine discharge and prolonged hospital stay in patients undergoing fusion for intervertebral disc disorders.
Methods
The National Hospital Discharge Survey was queried to identify all patients discharged from U.S. hospitals following spinal fusion for intervertebral disc disorders between 1990 and 2007. A cohort representative of 1,943,707 patients was identified and separated into those who were discharged home and those who were discharged to rehabilitation facilities. Multivariable logistic regression analysis was used to identify independent predictors of non-routine discharge to another inpatient facility and prolonged hospital stay.
Results
The strongest risk factors for non-routine discharge were age>65 years, congestive heart failure, atrial fibrillation, any general in-hospital complication, diabetes mellitus, osteoporosis, hypertension and any surgery-related complication. Patients younger than 50 years and males had the lowest rate of non-routine discharge. The strongest risk factors for prolonged hospital stay were any surgery-related complication, congestive heart failure, any general in-hospital complication, atrial fibrillation, age > 65 years, osteoporosis and diabetes mellitus. Patients 36–50 years of age had the lowest risk of increased length of hospital stay.
Conclusions
Knowledge of these risk factors may aid in better resource allocation and improved strategies for managing patients with spondylosis in order to decrease healthcare costs.
Level of evidence
3
Keywords: spinal fusion, intervertebral disc disorder, discharge, length of stay, hospital stay, comorbidities, post-hospitalization care, epidemiology
Introduction
Intervertebral disc disorders are a common cause of pain that affects mobility and quality of life and are increasing in prevalence1-3. Spinal fusion is often utilized for treatment of intervertebral disc disorders and studies have demonstrated improved outcomes in bodily pain and physical function compared to conservative therapy among persistently symptomatic patients who have failed nonoperative management4,5. Factors influencing clinical outcomes and operative success among patients undergoing spinal fusion have been studied at length6-8. However, risk factors for nonroutine discharge to other inpatient facilities and variables associated with prolonged hospital stays have not been identified. Early hospital discharge to home has been shown to be an important contributor to better postoperative outcomes, improved quality of life and less health care resource utilization among orthopaedic patients9-11. Knowledge of risk factors associated with nonroutine discharge and prolonged hospital stays may help identify patients at greater risk of prolonged post-hospitalization care, which may aid in proper resource allocation and reduce healthcare costs.
This study sought to identify risk factors associated with nonroutine discharge to inpatient facilities in patients undergoing spinal fusion for intervertebral disc disorders. We also sought to analyze variables associated with prolonged hospital stay and increased post-hospitalization utilization.
Methods
National Hospital Discharge Survey
The National Hospital Discharge Survey (NHDS), developed by the National Center for Healthcare Statistics division of the Centers for Disease Control and Prevention (CDC)12, was used to estimate incidence and to evaluate risk factors for nonroutine discharge and prolonged length of hospital stay for patients undergoing spinal fusion for intervertebral disc disorders. The NHDS is a publically available survey providing demographic and medical data for inpatients discharged from non-federal, short stay hospitals in the United States13. The NHDS is the principal database for the U.S. government to monitor hospital use and is considered the most comprehensive of all inpatient surgical databases13. The survey uses International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes14 to classify medical diagnoses and procedures. The NHDS uses a stratified, multistage probability design to collect demographic information (age, gender, race), expected source of payment (insurance status), medical information of up to seven discharge diagnoses and up to four procedures, length of care, hospital size, U.S. region, and inpatient outcomes including discharge destination15. To ensure an unbiased national sampling of inpatient records, the NHDS uses a three-stage probability design including: inflation by reciprocals of the probabilities of sample selection, adjustment for no response and population weighting ratio adjustments13. This study did not require approval by the institutional review board because the NHDS is a publically available database with no patient identifying information.
Patient selection
All patients admitted to hospitals in the U.S. who underwent spinal fusion for intervertebral disc disorders between 1990 and 2007 were identified using ICD-9-CM codes. Discharges with a diagnosis code (ICD-9-CM) of displacement of cervical (722.0), thoracic/lumbar (722.1) or unspecified (722.2) intervertebral disc without myelopathy, degeneration of cervical (722.4), thoracic/lumbar (722.5), or unspecified (722.6) intervertebral disc, intervertebral disc disorder with myelopathy (722.7) or unspecified intervertebral disc disorder (722.9) were identified using previously described techniques16. The database was subsequently queried to identify patients treated using spinal fusion (ICD-9 procedure code 81.0x). Patients were split into two groups: (1) patients discharged to home (routine discharge) after spinal fusion and (2) patients transferred to an inpatient facility (nonroutine discharge). Demographic variables were then collected including: age, sex, primary diagnosis, prevalence of comorbidities, length of stay, discharge destination, geographic region, hospital size, and insurance status. The complication screening package17 was used to determine the incidence of complications. The variable adverse event was created based on the variables: postoperative wound complication (998.3), postoperative bleeding (998.1), acute postoperative infection (998.5), acute postoperative anemia (285.1), acute renal failure (584), acute myocardial infarction (410), pulmonary embolism (415.1), induced mental disorder (293), pneumonia (480–486), pulmonary insufficiency (518.5), deep venous thrombosis (453.4), intubation (96.xx) and transfusion of blood (99.x).
Statistical analysis
Because of the large sample size, a normal distribution of the data was assumed. In bivariate analysis, the routine discharge and nonroutine discharge groups were compared using Pearson's chi-square test for categorical data and independent-samples t test for continuous data. To determine independent predictors of nonroutine discharge to inpatient facilities, all variables present in at least 2% of the population18 were included in a multivariable binary logistic regression model. For in-hospital adverse events, a 1% cutoff was used due to their lower rates of occurrence, as previously described19. A multivariable regression model allows for the control of potential confounders, isolating the effect of individual variables on inpatient outcomes. The dichotomous variables were 1) nonroutine discharge to inpatient facility and 2) prolonged hospital stay. We defined prolonged hospital stay when the average length of stay was greater than the 75th percentile, as previously described20,21. Covariates accounted for in the regression model included: gender, age, region of the country, and preexisting comorbidities (anemia, obesity, diabetes mellitus, hypertension, congestive heart failure, coronary artery disease, atrial fibrillation, prior myocardial infarction, and osteoporosis). To assess for the association between individual variables and inpatient outcomes, odds ratios and confidence intervals were calculated. A P value of <0.001 was used to define statistical significance, correcting for multiple comparisons, as previously described19. United States census data were used to obtain national population estimates for each year of the study 1990–200722. Rates were presented as the number of fusions for per 100,000 standard population. All data were analyzed using the software-statistical package for social sciences [SPSS] version 20 (Chicago, IL, USA).
Source of funding
No external funding source was used for the conduct of this study.
Results
Incidence and Demographics
A cohort representative of 1,943,707 patients who underwent spinal fusion for intervertebral disc disorders was identified between 1990 and 2007, with the routine discharge group comprising 1,780,071 patients (91.6%) and the nonroutine discharge group comprising 65,966 patients (3.4%) (Table 1). The remaining 5.0% of patients were excluded from the subgroup analysis because their discharge status was either alive with no discharge status stated (3.6%), dead (0.1%) or not reported (1.3%) (Table 1).
Table 1.
Characteristics for patients who underwent fusion for intervertebral disc disorders in the United States from 1990 to 2007
| Parameter | Total 1990–2007, (%) | Discharge to Home (%) | Discharge to Inpatient Facility (%) | P |
|---|---|---|---|---|
| N= | 1,943,707 | 1780071 | 65966 | |
| % Total | 100.0% | 91.6% | 3.4% | |
| Gender | ||||
| Male | 50.8 | 51.8 | 33.1 | <0.001 |
| Female | 49.2 | 48.2 | 66.9 | |
| Age | ||||
| ≤35 | 14.7 | 15.3 | 3.6 | <0.001 |
| 36–50 | 48.6 | 50.6 | 21.0 | |
| 51–65 | 26.7 | 26.7 | 27.4 | |
| >65 | 10.0 | 7.4 | 48.0 | |
| Region | ||||
| Northeast | 14.7 | 14.6 | 17.5 | <0.001 |
| Midwest | 22.5 | 22.2 | 21.2 | |
| South | 43.0 | 43.8 | 28.5 | |
| West | 19.8 | 19.3 | 32.8 | |
| Bedsize | ||||
| 6–99 | 4.0 | 4.1 | 5.1 | <0.001 |
| 100–199 | 23.2 | 23.4 | 25.9 | |
| 200–299 | 27.6 | 27 | 32.5 | |
| 300–499 | 29.7 | 29.9 | 23.4 | |
| 500 or more | 15.6 | 15.6 | 13.1 | |
| Insurance | ||||
| Medicare | 13.7 | 11.2 | 51.6 | <0.001 |
| Medicaid | 4.7 | 4.7 | 6.3 | |
| Workmens comp | 15.5 | 16.1 | 6.7 | |
| Private | 56.4 | 58.4 | 30 | |
| Self pay | 1.9 | 2.1 | 0.1 | |
| Other | 7.6 | 5.8 | 4.4 | |
| Not stated | 1.9 | 1.8 | 0.8 | |
| Primary Diagnosis | ||||
| 722.0x cervical disc displacement | 41.1 | 43.4 | 7.4 | <0.001 |
| 722.10 lumbar disc displacement | 20.0 | 19.2 | 29.8 | |
| 722.52 lumbar disc degeneration | 18.9 | 17.8 | 33.7 | |
| 722.71 cervical disc disorder with myelopathy | 7.6 | 7.4 | 10.7 | |
| 722.4x cervical disc degeneration | 5.3 | 5.6 | 2.8 | |
| Comorbities | 27.6 | 25.7 | 58.5 | <0.001 |
| Adverse Events | 8.1 | 6.9 | 20.6 | <0.001 |
| Discharge Dispostion | ||||
| Routine/home (1) | 91.6 | 100 | - | <0.001 |
| Left AMA (2) | 0 | - | - | |
| Short term fac (3) | 1.2 | - | 35.4 | |
| Long term fac (4) | 2.2 | - | 64.6 | |
| Alive, not stated (5) | 3.6 | - | - | |
| Dead (6) | 0.1 | - | - | |
| Not reported (9) | 1.3 | - | - | |
| Age (years), mean (SD) | 47.83(12.26) | 46.90(11.48) | 61.62(14.22) | <0.001 |
| Days of Care, mean (SD) | 3.41(1.25) | 3.15(3.50) | 7.10(7.73) | <0.001 |
Patients in the nonroutine discharge group were mostly female (66.9% vs 48.2%, P < 0.001), were significantly older (62± 14 years vs 47 ± 11 years, P < .001; 48% >65 years vs 7.4% >65 years, P < .001), living in the West (33% vs 19%, P < .001), and mainly admitted to medium-sized hospitals with 200–299 beds (32.5 vs 277%; P < .001) compared to patients in the routine discharge group. Length of hospital stay was 7.1 ± 7.7 days in the non-routine discharge group and 3.2 ± 3.5 days in the home discharge group. The most common primary diagnosis in the nonroutine discharge group was lumbar disc degeneration (33.7% vs 17.8%; P < 0.001) followed by lumbar disc displacement (29.8% vs 19.2%; P < 0.001) compared with the routine discharge group. Among patients in the nonroutine discharge group, Medicare was the most common form of payment (51.6% vs 11.2%; P < 0.001) compared with the routine discharge group (Table 1).
The incidence of patients undergoing spinal fusion for intervertebral disc disorders increased from 23.2 per 100,000 capita in 1990 to 53.3 per 100,000 capita in 2007. From 1990 to 2007 there was in increase in comorbidities (9.9% vs 45.2%; P < 0.001), adverse events (2.7% vs 7.3%; P < 0.001) and blood transfusions (0.6% vs 2.0%; P < 0.001). Nonroutine discharge to inpatient facilities increased from 3.3% in 1990 to 5.5% in 2007 while mean days of in-hospital care decreased from 5.9 ± 4.1 in 1990 to 3.2 ± 3.0 in 2007 for the entire patient cohort (Table 2).
Table 2.
Characteristics in 1990, 1995, 1999, 2003 and 2007 among patients who underwent fusion for intervertebral disc disorders. SD, Standard deviation
| 1990 | 1995 | 1999 | 2003 | 2007 | Comparison between 2007 and 1990 (p) | |
|---|---|---|---|---|---|---|
| N | 65510 | 70669 | 116904 | 144368 | 150448 | |
| Incidence per 100,000 capita | 23.21 | 25.04 | 41.43 | 51.16 | 53.31 | |
| Gender (%) | ||||||
| Male | 61 | 61.3 | 56.2 | 48.6 | 49.1 | <0.001 |
| Female | 39 | 38.7 | 43.8 | 51.4 | 50.9 | |
| Comorbidities (%) | 9.9 | 24.0 | 19.8 | 29.4 | 45.2 | <0.001 |
| Adverse events (%) | 2.7 | 5.9 | 6.7 | 10.1 | 7.3 | <0.001 |
| Transfusion (%) | 0.6 | 1.4 | 3.0 | 3.3 | 2.0 | <0.001 |
| Discharge (%) | ||||||
| Routine | 93.9 | 91 | 92.2 | 92.1 | 91.7 | <0.001 |
| Non-routine | 3.3 | 3.7 | 3 | 3.3 | 5.5 | |
| Mean Age (yrs) (SD) | 43.14(11.8) | 45.70(11.55) | 46.83(11.69) | 48.46(12.1) | 50.91(12.78) | <0.001 |
| Mean DOC (days) (SD) | 5.92(4.07) | 3.41(3.22) | 3.26(8.3) | 3.23(4.99) | 3.16(3.02) | <0.001 |
Comorbidities and Adverse Events
Patients in the nonroutine discharge group had higher rates of all comorbidities including diabetes mellitus (21% vs 6%; P <0.001), obesity (4% vs 3%; P < 0.001), hypertension (44% vs 20%; P < 0.001), old myocardial infarction (1.33% vs 1.04%; P <0.001), coronary artery disease (4% vs 2%; P < 0.001), atrial fibrillation (3% vs 1%; P < 0.001), congestive heart failure (2.6% vs 0.4%; P < 0.001), and osteoporosis (2.5% vs 0.7%; P < 0.001) compared with patients in the routine discharge group (Table 3). When compared to patients discharged home, those discharged to inpatient facilities had a significantly increased incidence of adverse events including acute postoperative anemia (10% compared to 4%, P < .001), wound complications (0.13% compared to 0.01%, P < .001), acute renal failure (1.4% compared to 0.04%, P < .001), pneumonia (2.4% compared to 0.2%, P < .001), pulmonary insufficiency (1.4% compared to 0.3%, P < .001), and blood transfusion (6.2% compared to 2.3%, P <.001) (P<.001) (Table 4).
Table 3.
Prevalence of comorbidities in patients who underwent fusion for intervertebral disc disorders between 1990 and 2007. (N=1,943,707)
| Parameter (ICD-9) | Total (%) | Routine Discharge (%) (N=1,780,071) | Nonroutine Discharge (%) (N=65,966) | p |
|---|---|---|---|---|
| Diabetes mellitus (250) | 7.08% | 6.29% | 21.42% | <0.001 |
| Obesity(278.00, 278.01) | 3.07% | 2.99% | 4.44% | <0.001 |
| Hypertensive disease (401–405) | 21.16% | 20.05% | 43.98% | <0.001 |
| Old myocardial infarction (412) | 1.10% | 1.04% | 1.33% | <0.001 |
| Coronary artery disease (414.01) | 1.90% | 1.74% | 3.96% | <0.001 |
| Atrial fibrillation (427.31) | 0.90% | 0.62% | 3.41% | <0.001 |
| Congestive heart failure (428) | 0.60% | 0.43% | 2.61% | <0.001 |
| Osteoporosis (733.0) | 0.84% | 0.74% | 2.52% | <0.001 |
Table 4.
Prevalence of adverse events among patients who underwent fusion for intervertebral disc disorders between 1990 and 2007. (N=1,943,707)
| Parameter (ICD-9) | Total, (%) | Routine Discharge (%) (N=1780071) | Nonroutine Discharge (%) (N=65966) | p |
|---|---|---|---|---|
| Post Surgery Complications: | ||||
| Postoperative wound complication (998.3) | 0.03% | 0.01% | 0.13% | <0.001 |
| Postoperative bleeding (998.1) | 0.73% | 0.61% | 1.85% | <0.001 |
| Acute postoperative infection (998.5) | 0.20% | 0.16% | 0.69% | <0.001 |
| Acute postoperative anemia (285.1) | 5.01% | 4.41% | 10.06% | <0.001 |
| General Complications: | ||||
| Acute renal failure (584) | 0.16% | 0.04% | 1.40% | <0.001 |
| Acute myocardial infarction (410) | 0.90% | 0.04% | 0.58% | <0.001 |
| Pulmonary embolism (415.1) | 0.05% | 0.02% | 0.60% | <0.001 |
| Induced mental disorder (293) | 0.10% | 0.07% | 0.51% | <0.001 |
| Pneumonia (480486) | 0.36% | 0.23% | 2.39% | <0.001 |
| Pulmonary insufficiency (518.5) | 0.41% | 0.31% | 1.40% | <0.001 |
| Deep venous thrombosis (453.4) | 0.04% | 0.04% | 0.00% | <0.001 |
| Intubation (96.x) | 0.25% | 0.19% | 1.07% | <0.001 |
| Transfusion of blood (99.0) | 2.69% | 2.25% | 6.17% | <0.001 |
Nonroutine Discharge
Multivariable logistic regression analysis showed the strongest independent predictors of nonroutine discharge following spinal fusion for intervertebral disc disorders were age > 65 years (OR 11.52 range: 11.33–11.71, P < 0.001), congestive heart failure (OR 6.19 range: 5.87–6.52, P < 0.001), atrial fibrillation (OR 5.69 range: 5.43–5.95, P < 0.001), any general in-hospital complication (OR 4.52 range: 4.41–4.64, P < 0.001), diabetes mellitus (OR 4.1 range: 3.98–4.14, P < 0.001), osteoporosis (OR 3.48 range: 3.30–3.66, P < 0.001), hypertension (OR 3.13 range: 3.08–3.18, P < 0.001), and any surgery related complication (OR 2.54 range: 2.48–2.61, P < 0.001). Factors associated with decreased odds of nonroutine discharge include age ≤ 35 years (OR 0.21 range: 0.20–0.22, P < 0.001), age 36–50 years (OR 0.26 range: 0.25–0.26, P < 0.001), and male sex (OR 0.53 range: 0.52–0.54, P < 0.001) (model fit: omnibus test of model coefficients: X2 = 18,397, P < 0.001, Nagelkerke R2 = 0.177; Table 5).
Table 5.
Logistic regression for predictors of non-routine discharge among patients who underwent fusion for intervertebral disc disorders (N=1,943,707) CI, confidence interval; OR, odds ratio.
| Variable | OR (95% CI) | P |
|---|---|---|
| Age >65 years | 11.517 (11.331-11.706) | <0.001 |
| Congestive heart failure | 6.187 (5.869-6.523) | <0.001 |
| Atrial fibrillation | 5.685 (5.429-5.953) | <0.001 |
| Any general complication | 4.522 (4.410-4.637) | <0.001 |
| Diabetes mellitus | 4.06 (3.981-4.140) | <0.001 |
| Osteoporosis | 3.478 (3.303-3.662) | <0.001 |
| Hypertension | 3.132 (3.083-3.182) | <0.001 |
| Any surgery complication | 2.544 (2.482-2.607) | <0.001 |
| Coronary artery disease | 2.333 (2.240-2.430) | <0.001 |
| Obesity | 1.508 (1.452-1.567) | <0.001 |
| Old myocardial infarction | 1.283 (1.199-1.374) | <0.001 |
| Age 51-65 years | 1.036 (1.018-1.054) | <0.001 |
| Region | 0.956 (0.803-1.139) | 0.614 |
| Sex (M) | 0.532 (0.523-0.542) | <0.001 |
| Age 36-50 years | 0.259 (0.254-0.264) | <0.001 |
| Age ≤35 years | 0.209 (0.201-0.218) | <0.001 |
Omnibus X 18,397, P < 0.001
Nagelkerke R2, P=0.177
Prolonged Length of Hospital Stay
Multivariable logistic regression analysis showed the strongest independent risk factors for prolonged hospital stay following spinal fusion for intervertebral disc disorders were any surgery related complication (OR 7.85 range: 7.74–7.95, P < 0.001), congestive heart failure (OR 6.90 range: 6.63–7.17, P < 0.001), any general in-hospital complication (OR 5.94 range: 5.85–6.03, P < 0.001), atrial fibrillation (OR 3.21 range: 3.12–3.31, P < 0.001), age > 65 years (OR 2.64 range: 2.61–2.67, P < 0.001), osteoporosis (OR 2.32 range: 2.25–2.39, P < 0.001), and diabetes mellitus (OR 1.64 range: 1.63–1.66, P < 0.001). The strongest independent predictor of normal or decreased length of hospital stay was age 36–50 years (OR 0.55 range: 0.53–0.56, P < 0.001) (model fit: omnibus test of model coefficients: X2 = 18,397, P < 0.001, Nagelkerke R2 = 0.033; Table 6).
Table 6.
Logistic regression for predictors of prolonged hospital stay among patients who underwent fusion for intervertebral disc disorders (N=1,943,707) CI, confidence interval; OR, odds ratio.
| Variable | OR (95% CI) | P |
|---|---|---|
| Any Surgery complication | 7.845 (7.743-7.948) | <0.001 |
| Congestive heart failure | 6.895 (6.633-7.168) | <0.001 |
| Any General complication | 5.938 (5.847-6.031) | <0.001 |
| Atrial fibrillation | 3.21 (3.116-3.307) | <0.001 |
| Age >65 years | 2.639 (2.614-2.665) | <0.001 |
| Osteoporosis | 2.32 (2.248-2.394) | <0.001 |
| Diabetes mellitus | 1.644 (1.625-1.664) | <0.001 |
| Old Myocardial infarction | 1.45 (1.408-1.494) | <0.001 |
| Coronary artery disease | 1.393 (1.362-1.425) | <0.001 |
| Hypertension | 1.244 (1.234-1.254) | <0.001 |
| Age 51-65 years | 1.174 (1.165-1.182) | <0.001 |
| Age ≤35 years | 1.113 (1.103-1.123) | <0.001 |
| Sex (M) | 1.041 (1.033-1.048) | <0.001 |
| Region | 1.009 (0.949-1.974) | 0.77 |
| Obesity | 0.971 (0.953-0.990) | 0.003 |
| Age 36-50 years | 0.546 (0.532-0.560) | <0.001 |
Omnibus X 18397, P < 0.001
Nagelkerke R2, P=0.0325
Discussion
This study identified perioperative risk factors associated with nonroutine discharge and prolonged hospital stay among patients undergoing spinal fusion for intervertebral disc disorders. Between 1990 and 2007, we identified an increasing incidence (23.2 per 100,000 capita in 1990 to 53.3 per 100,000 capita in 2007) of spinal fusion for intervertebral disc disorders as well as an increasing rate of nonroutine discharge to inpatient facilities (3.3% in 1990 to 5.5% in 2007). Concurrently, this study demonstrated a decreased mean length of hospital stay (5.9 days in 1990 to 3.2 days in 2007). It is possible the decreased length of stay and higher proportion of nonroutine discharges over time is related to earlier transfer to inpatient rehabilitation facilities. The trends found in this study demonstrate a growing use of postoperative care facilities, such as inpatient rehabilitation facilities, which is similar to previous reports23-25.
In this study, patients over the age of 65 had the highest odds of nonroutine discharge and also had higher odds of prolonged length of hospital stay, which is in line with previous studies26,27. Interestingly, this study found females were at greater risk of nonroutine discharge. This finding is similar to the results reported by Katz et al28 in which women had worse functional outcomes than men following laminectomy for spinal stenosis, as well unilateral hip and knee arthroplasty. Their study found that women had significantly worse preoperative functional status than men, suggesting they may have been treated at more advanced disease stages and alluding to possible gender differences in preferences for symptom relief, attitudes toward surgery, or access to operative procedures28. This is supported by several studies that demonstrated women are less likely to undergo cardiac catheterization and revascularization, or renal transplantation then men with similar coronary or renal disease severity29-34.
Another finding of this study was that patients in the nonroutine discharge group had higher rates of all comorbid medical conditions compared with those patients in the routine discharge group. Multivariate logistic regression showed that all comorbidities analyzed in this study, except obesity, were independent predictors of both nonroutine discharge and prolonged hospital stays. This is similar to work by Deyo et al25, showing that major medical complications, mortality and healthcare utilization were higher in patients with comorbidities such as diabetes, obesity or coronary artery disease who underwent various surgeries for lumbar stenosis. Additionally, Slover et al35 showed patients with comorbidities had worse scores on bodily pain, physical function and physical component assessments following lumbar spine surgery. Among patients undergoing ankle fusion, Menendez et al23 showed that diabetes was linked to higher nonroutine discharge and prolonged hospitalization, though obesity was not linked to prolonged hospital stay in this study. One possible explanation for this is coding bias by the NHDS database towards more stable diseases, leading to underestimation of certain conditions. Indeed, of the total patient cohort, only 3.07% had a diagnosis of obesity, which is far below the national prevalence36 and illustrates its underestimation in this study.
Surgery-related and general in-hospital complications were among the strongest predictors of prolonged hospital stay and nonroutine discharge. The most common surgery related complication was acute postoperative anemia, followed by postoperative bleeding and infection. Blood transfusion was the most common general in-hospital complication followed by pneumonia and pulmonary insufficiency. These complications are similar to those reported by Shamji et al24 among patients undergoing cervical fusion for cervical spondylosis and are associated with increased health care utilization among patients with spinal stenosis37.
While large national databases have been recognized as suitable for epidemiological research38, our study has several limitations. Like all large databases, the NHDS is subject to coding error or error in data entry39. Additionally, the database only allows for seven diagnosis codes and four procedure codes per entry. As a result, the prevalence of comorbid conditions and adverse events may be underreported19. Moreover, the severity of a comorbid disease cannot be appreciated when classified dichotomously40.
Our study is also limited by the inability to distinguish between the types and extent of fusion procedures performed among our patient population. Although the use of instrumentation may lead to higher fusion rates41,42, these procedures have an increased operative time, blood loss, infection rate, as well as risk of nerve root injury or vascular injury from malpositioning43. Patients older than 65 may have more extensive disease with greater rates of instability requiring longer instrumented fusion constructs compared to younger patients. The higher odds of non-routine discharge and prolonged length of hospital stay among patients greater than 65 may be attributable to the more extensive surgical fusion procedures needed to treat this population. Also, the indication for surgery was not recorded, so it is unknown whether these patients had axial pain, radiculopathy or other symptoms. Another limitation of this database is that it only provides inpatient data, so complications that arise after discharge as well as follow up data, are unknown. Furthermore, the database does not provide billing information so cost analysis is unable to be performed. Future work should be conducted to evaluate the cost of length of stay and discharge to another inpatient facility. Lastly, the results of this study are limited to spinal fusion in the United States from 1990 to 2007.
In conclusion, this study provides the largest analysis of perioperative risk factors associated with nonroutine discharge and prolonged hospital stays among patients undergoing spinal fusion for intervertebral disc disorders. Identifying risk factors associated with increased healthcare utilization has the potential to change treatment strategies, improve preoperative optimization and resource allocation for this patient population in an attempt to prevent prolonged hospitalization and postoperative acute care utilization, while decreasing health care costs.
Acknowledgments
None reported
References
- 1.Rihn JA, Currier BL, Phillips FM, Glassman SD, Albert TJ. Defining the value of spine care. J Am Acad Orthop Surg. 2013;21:419–426. doi: 10.5435/JAAOS-21-07-419. [DOI] [PubMed] [Google Scholar]
- 2.Martin BI, Deyo RA, Mirza SK, et al. Expenditures and health status among adults with back and neck problems. JAMA. 2008;299:656–664. doi: 10.1001/jama.299.6.656. [DOI] [PubMed] [Google Scholar]
- 3.Martin BI, Turner JA, Mirza SK, Lee MJ, Comstock BA, Deyo RA. Trends in health care expenditures, utilization, and health status among US adults with spine problems, 1997-2006. Spine (Phila Pa 1976) 2009;34:2077–2084. doi: 10.1097/BRS.0b013e3181b1fad1. [DOI] [PubMed] [Google Scholar]
- 4.Weinstein JN, Lurie JD, Tosteson TD, et al. Surgical versus nonoperative treatment for lumbar disc herniation: Four-year results for the spine patient outcomes research trial (SPORT). Spine (Phila Pa 1976) 2008;33:2789–2800. doi: 10.1097/BRS.0b013e31818ed8f4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Lurie JD, Tosteson TD, Tosteson AN, et al. Surgical versus nonoperative treatment for lumbar disc herniation: Eight-year results for the spine patient outcomes research trial. Spine (Phila Pa 1976) 2014;39:3–16. doi: 10.1097/BRS.0000000000000088. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Anderson PA, Subach BR, Riew KD. Predictors of outcome after anterior cervical discectomy and fusion: A multivariate analysis. Spine (Phila Pa 1976) 2009;34:161–166. doi: 10.1097/BRS.0b013e31819286ea. [DOI] [PubMed] [Google Scholar]
- 7.Garvey TA, Transfeldt EE, Malcolm JR, Kos P. Outcome of anterior cervical discectomy and fusion as perceived by patients treated for dominant axial-mechanical cervical spine pain. Spine (Phila Pa 1976) 2002;27:1887–95. doi: 10.1097/00007632-200209010-00015. discussion 1895. [DOI] [PubMed] [Google Scholar]
- 8.Wright IP, Eisenstein SM. Anterior cervical discectomy and fusion without instrumentation. Spine (Phila Pa 1976) 2007;32:772–4. doi: 10.1097/01.brs.0000258846.86537.ad. discussion 775. [DOI] [PubMed] [Google Scholar]
- 9.Wukich DK, Shen JY, Ramirez CP, Irrgang JJ. Retrograde ankle arthrodesis using an intramedullary nail: A comparison of patients with and without diabetes mellitus. J Foot Ankle Surg. 2011;50:299–306. doi: 10.1053/j.jfas.2010.12.028. [DOI] [PubMed] [Google Scholar]
- 10.Kammerlander C, Gosch M, Kammerlander-Knauer U, Luger TJ, Blauth M, Roth T. Long-term functional outcome in geriatric hip fracture patients. Arch Orthop Trauma Surg. 2011;131:1435–1444. doi: 10.1007/s00402-011-1313-6. [DOI] [PubMed] [Google Scholar]
- 11.Orces CH, Alamgir AH. Trends in hip fracture- related mortality in texas, 1990-2007. South Med J. 2011;104:482–487. doi: 10.1097/SMJ.0b013e31821e9a4d. [DOI] [PubMed] [Google Scholar]
- 12.Centers for Disease Control and Prevention. National Hospital Discharge Survey. Available at: http://www.cdc.gov/nchs/nhds.htm Accessed June 6, 2014.
- 13.Dennison C, Pokras R. Design and operation of the national hospital discharge survey: 1988 redesign. Vital Health Stat 1. 2000;(39):1–42. [PubMed] [Google Scholar]
- 14.CDC/National Center for Health Statistics. International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) http://www.cdc.gov/nchs/icd/icd9cm.htm Accessed February/12, 2014.
- 15.Memtsoudis SG, Gonzalez Delia Valle A, Besculides MC, Gaber L, Sculco TP. In-hospital complications and mortality of unilateral, bilateral, and revision TKA: Based on an estimate of 4,159,661 discharges. Clin Orthop Relat Res. 2008;466:2617–2627. doi: 10.1007/s11999-008-0402-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Stundner O, Kirksey M, Chiu YL, et al. Demographics and perioperative outcome in patients with depression and anxiety undergoing total joint arthroplasty: A population-based study. Psychosomatic. 2013;54:149–157. doi: 10.1016/j.psym.2012.08.009. [DOI] [PubMed] [Google Scholar]
- 17.Iezzoni LI, Daley J, Heeren T, et al. Using administrative data to screen hospitals for high complication rates. Inquiry. 1994;31:40–55. [PubMed] [Google Scholar]
- 18.Lemeshow S, Teres D, Klar J, Avrunin JS, Gehlbach SH, Rapoport J. Mortality probability models (MPM II) based on an international cohort of intensive care unit patients. JAMA. 1993;270:2478–2486. [PubMed] [Google Scholar]
- 19.Bot AG, Menendez ME, Neuhaus V, Ring D. The influence of psychiatric comorbidity on perioperative outcomes after shoulder arthroplasty. J Shoulder Elbow Surg. 2014;23:519–527. doi: 10.1016/j.jse.2013.12.006. [DOI] [PubMed] [Google Scholar]
- 20.Gonzalez Delia Valle A, Chiu YL, Ma Y, Mazumdar M, Memtsoudis SG. The metabolic syndrome in patients undergoing knee and hip arthroplasty: Trends and in-hospital outcomes in the united states. J Arthroplasty. 2012;27:1743–1749. doi: 10.1016/j.arth.2012.04.011. e1. [DOI] [PubMed] [Google Scholar]
- 21.Memtsoudis SG, Kirksey M, Ma Y, et al. Metabolic syndrome and lumbar spine fusion surgery: Epidemiology and perioperative outcomes. Spine (Phila Pa 1976) 2012;37:989–995. doi: 10.1097/BRS.0b013e31823a3a13. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.U.S. Department of Commerce. United States Census Bureau. Available at: http://www.census.gov/ Accessed June/6, 2014.
- 23.Menendez ME, Bot AG, Neuhaus V, Ring D, Johnson AH. Factors influencing discharge disposition after ankle arthrodesis. Foot Ankle Int. 2014;35:578–583. doi: 10.1177/1071100714528499. [DOI] [PubMed] [Google Scholar]
- 24.Shamji MF, Cook C, Pietrobon R, Tackett S, Brown C, Isaacs RE. Impact of surgical approach on complications and resource utilization of cervical spine fusion: A nationwide perspective to the surgical treatment of diffuse cervical spondylosis. Spine J. 2009;9:31–38. doi: 10.1016/j.spinee.2008.07.005. [DOI] [PubMed] [Google Scholar]
- 25.Deyo RA, Mirza SK, Martin BI, Kreuter W, Goodman DC, Jarvik JG. Trends, major medical complications, and charges associated with surgery for lumbar spinal stenosis in older adults. JAMA. 2010;303:1259–1265. doi: 10.1001/jama.2010.338. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Khandelwal D, Goel A, Kumar U, Gulati V, Narang R, Dey AB. Frailty is associated with longer hospital stay and increased mortality in hospitalized older patients. J Nutr Health Aging. 2012;16:732–735. doi: 10.1007/s12603-012-0369-5. [DOI] [PubMed] [Google Scholar]
- 27.Evans SJ, Sayers M, Mitnitski A, Rockwood K. The risk of adverse outcomes in hospitalized older patients in relation to a frailty index based on a comprehensive geriatric assessment. Age Ageing. 2014;43:127–132. doi: 10.1093/ageing/aft156. [DOI] [PubMed] [Google Scholar]
- 28.Katz JN, Wright EA, Guadagnoli E, Liang MH, Karlson EW, Cleary PD. Differences between men and women undergoing major orthopedic surgery for degenerative arthritis. Arthritis Rheum. 1994;37:687–694. doi: 10.1002/art.1780370512. [DOI] [PubMed] [Google Scholar]
- 29.Tobin JN, Wassertheil-Smoller S, Wexler JP, et al. Sex bias in considering coronary bypass surgery. Ann Intern Med. 1987;107:19–25. doi: 10.7326/0003-4819-107-1-19. [DOI] [PubMed] [Google Scholar]
- 30.Ayanian JZ, Epstein AM. Differences in the use of procedures between women and men hospitalized for coronary heart disease. N Engl J Med. 1991;325:221–225. doi: 10.1056/NEJM199107253250401. [DOI] [PubMed] [Google Scholar]
- 31.Steingart RM, Packer M, Hamm P, et al. Sex differences in the management of coronary artery disease, survival and ventricular enlargement investigators. N Engl J Med. 1991;325:226–230. doi: 10.1056/NEJM199107253250402. [DOI] [PubMed] [Google Scholar]
- 32.Krumholz HM, Douglas PS, Lauer MS, Pasternak RC. Selection of patients for coronary angiography and coronary revascularization early after myocardial infarction: Is there evidence for a gender bias? Ann Intern Med. 1992;116:785–790. doi: 10.7326/0003-4819-116-10-785. [DOI] [PubMed] [Google Scholar]
- 33.Held PJ, Pauly MV, Bovbjerg RR, Newmann J, Salvatierra O., Jr. Access to kidney transplantation, has the united states eliminated income and racial differences? Arch Intern Med. 1988;148:2594–2600. doi: 10.1001/archinte.148.12.2594. [DOI] [PubMed] [Google Scholar]
- 34.Bickell NA, Pieper KS, Lee KL, et al. Referral patterns for coronary artery disease treatment: Gender bias or good clinical judgment? Ann Intern Med. 1992;116:791–797. doi: 10.7326/0003-4819-116-10-791. [DOI] [PubMed] [Google Scholar]
- 35.Slover J, Abdu WA, Hanscom B, Weinstein JN. The impact of comorbidities on the change in short-form 36 and oswestry scores following lumbar spine surgery. Spine (Phila Pa 1976) 2006;31:1974–1980. doi: 10.1097/01.brs.0000229252.30903.b9. [DOI] [PubMed] [Google Scholar]
- 36.Nguyen DM, El-Serag HB. The epidemiology of obesity. Gastroenterol Clin North Am. 2010;39:1–7. doi: 10.1016/j.gtc.2009.12.014. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Cassinelli EH, Eubanks J, Vogt M, Furey C, Yoo J, Bohlman HH. Risk factors for the development of perioperative complications in elderly patients undergoing lumbar decompression and arthrodesis for spinal stenosis: An analysis of 166 patients. Spine (Fhila Pa 1976) 2007;32:230–235. doi: 10.1097/01.brs.0000251918.19508.b3. [DOI] [PubMed] [Google Scholar]
- 38.Bohl DD, Basques BA, Golinvaux NS, Baumgaertner MR, Grauer JN. Nationwide inpatient sample and national surgical quality improvement program give different results in hip fracture studies. Clin Orthop Relat Res. 2014;472:1672–1680. doi: 10.1007/s11999-014-3559-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Memtsoudis SG. Limitations associated with the analysis of data from administrative databases. Anesthesiology. 2009;111:449. doi: 10.1097/ALN.0b013e3181adf739. author reply 450-1. [DOI] [PubMed] [Google Scholar]
- 40.Neuhaus V, Swellengrebel CH, Bossen JK, Ring D. What are the factors influencing outcome among patients admitted to a hospital with a proximal humeral fracture? Clin Orthop Relat Res. 2013;471:1698–1706. doi: 10.1007/s11999-013-2876-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Abdu WA, Lurie JD, Spratt KF, et al. Degenerative spondylolisthesis: Does fusion method influence outcome? four-year results of the spine patient outcomes research trial. Spine (Phila Pa 1976) 2009;34:2351–2360. doi: 10.1097/BRS.0b013e3181b8a829. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Fischgrund JS, Mackay M, Herkowitz HN, Brower R, Montgomery DM, Kurz LT. 1997 volvo award winner in clinical studies, degenerative lumbar spondylolisthesis with spinal stenosis: A prospective, randomized study comparing decompressive laminectomy and arthrodesis with and without spinal instrumentation. Spine (Phila Pa 1976) 1997;22:2807–2812. doi: 10.1097/00007632-199712150-00003. [DOI] [PubMed] [Google Scholar]
- 43.Rao R, Smuck M North American Spine Society. Orthopaedic Knowledge Update. Rosemont, IL: American Academy of Orthopaedic Surgeons; 2012. Spine 4. p. 334. [Google Scholar]