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Oakland University William Beaumont School of Medicine, Rochester, MISection of Plastic Surgery, Department of Surgery, University of Michigan Medical School, Ann Arbor, MI
Corresponding author: Jennifer F. Waljee, MD, MPH, Section of Plastic Surgery, Department of Surgery, Michigan Medicine, 2130 Taubman Center, SPC 5340, 3401500 E, Medical Center Drive, Ann Arbor, MI 48109-5340.
The rates of upper extremity reconstruction for patients with tetraplegia remain low. We performed a retrospective study to assess recent reconstruction rates and delineate factors associated with the occurrence of reconstruction.
Methods
We examined the National Inpatient Sample database (2012–2017) for the rate of reconstruction for patients with tetraplegia. The details of provider distribution characteristics and neighborhood attributes were obtained from the American Medical Association Physician Masterfile and based on the area deprivation index, respectively. We calculated the mean reconstruction rate per year and generated multivariable logistic regression models to examine the influence of patient factors, hospital characteristics, and provider distribution on the odds of undergoing functional reconstruction for tetraplegia patients.
Results
Among 404,660 encounters with patients with tetraplegia, only 1,430 (0.4%) patients underwent upper extremity reconstruction from 2012 to 2017, with a mean rate of 238 procedures per year. We identified 5,450 hand surgeons, 12,751 physiatrists, and 444 spinal cord injury specialists, with variation in their national distribution. A greater number of surgeons near SCIS was associated with increased probability of reconstruction (odds ratio [OR] 1.07, 95% confidence interval [CI] 1.03–1.12). The odds of surgery were greater for patients receiving care at urban teaching (OR 5.00, 95% CI 3.35–7.47) or urban nonteaching (OR 1.71, 95% CI 1.11–2.63) hospitals, whereas those at private nonprofit (OR 0.67, 95% CI 0.58-0.78) or investor-owned (OR 0.65, 95% CI 0.52–0.82) hospitals had lower odds. Although most patients had insurance coverage, patients with a higher income or those who received subsidized care had greater odds of undergoing reconstruction.
Conclusions
Reconstruction rates remain low and are correlated with the environment of care, financial factors, and provider availability. Policies that focus on reducing these factors in addition to increasing interspecialty collaboration could improve access to surgery for patients with tetraplegia.
Dr. Graham interviews Dr. Jennifer Waljee regarding her paper entitled “Patterns of Upper Extremity Reconstruction for Patients With Tetraplegia Across the United States: A Retrospective Study” , the lead article in the November 2021 issue of the Journal of Hand Surgery.
Affected patients experience disturbances in their sensory, motor, and autonomic functions, consequently altering their physical, psychological, and social wellbeing.
Improvements in upper extremity function are essential for regaining independence, and 60%–75% of patients with tetraplegia are candidates for some type of a functional upper extremity reconstruction (UER).
The restoration of hand function enhances the abilities of eating and writing, whereas improvements in elbow function increase independence through enhanced abilities of grooming, operating wheelchairs, and driving automobiles.
Patients’ personal preferences and experience can shape their decision about pursuing UER. For example, patients’ dissatisfaction with their functionality, knowledge of UER procedures, and acceptance of operative treatment have been noted as factors affecting the selection of nonsurgical treatment over operative treatment for patients with tetraplegia.
Checkpoints to progression: qualitative analysis of the personal and contextual factors that influence selection of upper extremity reconstruction among patients with tetraplegia.
For example, the availability of specialists who can provide care for patients with tetraplegia is directly related to the proximity of providers to patients with tetraplegia. Provider proximity to each other and to patients can affect their participation in the care team. Although the distribution of hand surgeons is unequal across the United States (US), the distribution of physiatrists and spinal cord injury subspecialists (SCIS) compared with that of hand surgeons remains unknown.
We used a national database to investigate the rates of UER following SCI in patients with tetraplegia. Additionally, we examined how patient factors, hospital factors, and the distribution of tetraplegia specialty providers, including hand surgeons, physiatrists, and SCIS, influence the occurrence of reconstructive surgery. We hypothesized that the distribution of tetraplegia specialists and the occurrence of UER would be unequal across the US. In addition, we hypothesized that areas with greater provider availability would correlate with more frequent hand and UER procedures.
Materials and Methods
Data source
We investigated claims data using the Healthcare Cost and Utilization Project’s National Inpatient Sample (NIS) database from 2012 to 2017. This is the largest database of inpatient hospital stays, encompassing over 8 million inpatient admissions across more than 1,000 hospitals in the US.
We selected the NIS database because the altered physiology in patients with tetraplegia often requires overnight recovery after a major surgery in an inpatient setting, and therefore, most surgical procedures could be captured using this data source.
This retrospective study using deidentified claims data was classified as exempt by our institution’s review board.
Study cohort selection
We identified patients with tetraplegia using diagnosis codes from the International Classification of Diseases (ICD), ninth and tenth revision, clinical modification for tetraplegia (previously known as quadriplegia) (Table E1, available online on the Journal’s website at www.jhandsurg.org). Surgical patients were selected using ICD-9 and ICD-10 procedure codes relating to nerve transfers, tendon surgeries, and procedures commonly performed simultaneously, such as tenodesis, joint fusions, and tendon graft harvest (Table E2, available online on the Journal’s website at www.jhandsurg.org). Patients with injuries coded as C1 through C4 were excluded. We also excluded patients with values missing from our multivariable regression analysis (Fig. E1 and Table E3, available online on the Journal’s website at www.jhandsurg.org). Our primary outcome was the annual UER rate in the study cohort.
Patient factors
From the NIS database, the independent categorical variables included were sex, race (White, Black, Hispanic, Asian/Pacific Islander, Native American, and other), Elixhauser comorbidity index (1–4 and ≥5), insurance type (Medicare, Medicaid, private, self-pay, no charge, and other), and residential income categories (Table E4, available online on the Journal’s website at www.jhandsurg.org).
From the NIS database, hospital type (rural, urban nonteaching, and urban teaching) and hospital control (government, private nonprofit, and private investor-owned) were included as independent categorical variables. The American Medical Association (AMA) Physician Masterfile for 2016 was used to identify the supply network of physicians across the US because it contained demographic information for all allopathic and osteopathic providers, regardless of their AMA membership status.
We identified specialists based on their active board certification using the AMA Physician Masterfile database. Hand surgeons were defined as providers with a primary or secondary specialty in “Hand Surgery,” physiatrists as providers with primary specialization in “Physical Medicine & Rehabilitation,” and SCIS as physiatrists with subspecialization in “Spinal Cord Injury.” All providers practicing outside of the US were excluded. To determine provider proximity, we compared the raw number of tetraplegia specialists within each geographical division captured in the NIS. We calculated the ratio of surgeons to specialists within a geographical division to estimate the density of a referral network in the geographical division (ratios of hand surgeons to physiatrists and hand surgeons to SCIS). Higher ratios represented a larger referral network (ie, many hand surgeons available for referral), whereas lower ratios represented a smaller network (ie, a limited number of hand surgeons) and were examined as a continuous variable.
Neighborhood geographical factors
We used the individual income tax zip code data generated by the Statistics of Income Division of the Internal Revenue Service (IRS) for 2017 to determine neighborhood characteristics. This database contains summary statistics of individual income tax returns for each zip code in a given year.
The data extrapolated from the IRS dataset were used as continuous variables, including elderly (mean percentage of those over 60 years old), self-employment rate (mean percentage of those self-employed), unemployment rate (mean percentage of those unemployed), and low-income households (mean percentage of those with adjusted gross incomes ≤$25,000). We used the 2015 area deprivation index (ADI) developed by the Health Resources and Services Administration and the University of Wisconsin, Madison, to estimate the socioeconomic disadvantage status.
The ADI stratifies individual city blocks (ie, zip + 4 code) on a national scale, with 1 representing the least deprived and 100 representing the most deprived. The domains considered in the cumulative percentile score included household income, poverty, education, employment, and housing quality.
We averaged the ADIs of the zip + 4 codes within each zip code because the IRS dataset consists of 5-digit zip codes. The ADIs were further classified into 4 quartiles: first (1st–24th), second (25th–49th), third (50th–74th), and fourth (75th–100th). The IRS and AMA Physician Masterfile datasets were matched using the 5-digit zip codes. Provider availability at the neighborhood level was represented as density (per 100,000 population).
Statistical analysis
Data were presented using descriptive statistics. We calculated the mean annual UER rate in our study cohort between 2012 and 2017. The average use of reconstruction was calculated by dividing the mean number of yearly procedures in our study by the number of eligible candidates. We assessed differences in the patient, hospital, and provider factors between nonsurgical and surgical patients using the chi-square test for categorical variables and analysis of variance for continuous variables. We also compared the neighborhood attributes among the 4 ADI quartiles using analysis of variance. To control for potential confounding effects, we used multivariable logistic regression models to evaluate patient, hospital, and provider factors that may influence the receipt of reconstructive surgery. We evaluated variables for collinearity and removed 3 (the absolute of number of hand surgeons, physiatrists, and SCIS per division) that were found to be correlated in the analysis. A second logistic regression analysis was performed using a separate model to investigate the association between the neighborhood characteristics and the availability of providers for each specialty.
Results
Cohort characteristics
Using our univariate analysis, we identified 404,660 encounters with patients with tetraplegia, and 1,430 (0.4%) of them underwent a UER procedure between 2012 and 2017 (Table 1). In our study, a mean yearly reconstruction rate of 238 procedures was identified. Our cohort was predominantly White (58%) and male (68%). We found a significant difference between patients who underwent a UER and those who did not in terms of age, sex, race, insurance type, comorbidity index, residential income, total hospital discharge, hospital type, and geographic location of care (P < .05; Table 1). Patients who underwent reconstruction were significantly younger (P < .05). As the patient’s comorbidity index increased, the reconstruction rate decreased. Patients with public insurance, such as Medicare or Medicaid, had significantly higher rates of reconstruction compared with those with private insurance (P < .05). The UER rates were similar among the 4 residential income groups; however, almost one-third of all patients were classified in the bottom residential income group, whereas only one-fifth were classified in the top group. Most of the reconstructive procedures occurred at urban teaching hospitals (87%) or private nonprofit hospitals (74%).
Table 1Demographics and Hospital Characteristics of Patients With Tetraplegia Based on the Receipt of Reconstructive Surgery
”Private” insurance category includes Blue Cross, commercial carriers, private health maintenance organizations, and preferred provider organizations. “Other” insurance category includes workers’ compensation, CHAMPUS, CHAMPVA, Title V of the McKinney-Vento Homeless Assistance Act, and other government programs.
Classification of divisions:Division 1: New England (Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont)Division 2: Mid-Atlantic (New Jersey, New York, and Pennsylvania)Division 3: East North Central (Illinois, Indiana, Michigan, Ohio, and Wisconsin)Division 4: West North Central (Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, and South Dakota)Division 5: South Atlantic (Delaware, Florida, Georgia, Maryland, North Carolina, South Carolina, Virginia, District of Columbia, and West Virginia)Division 6: East South Central (Alabama, Kentucky, Mississippi, and Tennessee)Division 7: West South Central (Arkansas, Louisiana, Oklahoma, and Texas)Division 8: Mountain (Arizona, Colorado, Idaho, Montana, Nevada, New Mexico, Utah, and Wyoming)Division 9: Pacific (Alaska, California, Hawaii, Oregon, and Washington)
<.05
New England
55 (4)
16,450 (4)
16,505 (4)
Mid-Atlantic
200 (14)
47,315 (12)
47,515 (12)
East North Central
215 (15)
67,855 (17)
68,070 (17)
West North Central
150 (10)
29,450 (7)
29,600 (7)
South Atlantic
240 (17)
78,520 (19)
78,760 (19)
East South Central
70 (5)
26,855 (7)
26,925 (7)
West South Central
175 (12)
49,045 (12)
49,220 (12)
Mountain
135 (9)
22,830 (6)
22,965 (6)
Pacific
190 (13)
64,910 (16)
65,100 (16)
CHAMPUS, Civilian Health and Medical Program of the Uniformed Services; CHAMPVA, Civilian Health and Medical Program of the Department of Veterans Affairs.
∗ US dollar ranges for quartiles vary by year in the NIS (Table E4).
† ”Private” insurance category includes Blue Cross, commercial carriers, private health maintenance organizations, and preferred provider organizations. “Other” insurance category includes workers’ compensation, CHAMPUS, CHAMPVA, Title V of the McKinney-Vento Homeless Assistance Act, and other government programs.
‡ Classification of divisions:
Division 1: New England (Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont)
Division 2: Mid-Atlantic (New Jersey, New York, and Pennsylvania)
Division 3: East North Central (Illinois, Indiana, Michigan, Ohio, and Wisconsin)
Division 4: West North Central (Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, and South Dakota)
Division 5: South Atlantic (Delaware, Florida, Georgia, Maryland, North Carolina, South Carolina, Virginia, District of Columbia, and West Virginia)
Division 6: East South Central (Alabama, Kentucky, Mississippi, and Tennessee)
Division 7: West South Central (Arkansas, Louisiana, Oklahoma, and Texas)
Division 8: Mountain (Arizona, Colorado, Idaho, Montana, Nevada, New Mexico, Utah, and Wyoming)
Division 9: Pacific (Alaska, California, Hawaii, Oregon, and Washington)
We identified a total of 5,450 hand surgeons, 12,751 physiatrists, and 444 SCISs, with substantial variability across the US (Fig. 1). The New England division had low numbers of each specialty but the highest availability of hand surgeons relative to referring providers. Our bivariate analysis demonstrated a significant negative correlation between UER and the ratio of available hand surgeons to physiatrists (P < .05) (Table E5, available online on the Journal’s website at www.jhandsurg.org), which suggested that the rate of UER was lower in areas with relatively more hand surgeons per physiatrist.
Figure 1Regional distribution of provider availability and the occurrence of UER.
Our multivariable analysis revealed a significant association between provider availability as well as area deprivation and the neighborhood characteristics (Table 2, Table 3). Greater area deprivation correlated with lower odds of provider availability across all 3 specialties. Compared to the least deprived neighborhoods, the odds of a provider being available in the most deprived neighborhoods decreased by 87% (95% confidence interval [CI] 0.11–0.16, P < .05) for hand surgery, 90% (95% CI 0.09–0.13, P < .05) for physiatry, and 77% (95% CI 0.13–0.42, P < .05) for SCIS.
Table 2Neighborhood Characteristics and Provider Availability Based on the ADI Percentile
Our multivariable logistic regression analysis revealed that female patients (odds ratio [OR] 0.77, 95% CI 0.67–0.87, P < .05) and those with more comorbidities (OR 0.51, 95% CI 0.44–0.59, P < .05) had lower odds of undergoing reconstruction (Table 4). With respect to financial status, the odds of undergoing surgery were significantly greater for patients in the highest residential income group; patients who were not charged for their care; or those who received care at a subsidized price through workers’ compensation, Title V of the McKinney-Vento Homeless Assistance Act, or other government programs (P < .05). For instance, patients with a household income of over $74,000 were 20% more likely to undergo surgery than patients with a household income of less than $44,000. Furthermore, those who received care at no cost were nearly 6 times (95% CI 3.04–11.00, P < .05) more likely to undergo reconstructive surgery, whereas self-pay patients were 55% (95% CI 0.24–0.85, P < .05) less likely. The odds of reconstruction were lower in private hospitals, such as nonprofit (OR 0.67, 95% CI 0.58–0.78, P < .05) and investor-owned (OR 0.65, 95% CI 0.52–0.82, P < .05) hospitals, than in government-funded facilities. In addition, urban centers, regardless of their teaching status, were more likely to perform reconstructive surgery than rural hospitals. The referral network of tetraplegia specialists was a significant predictor of reconstruction (P < .05). For instance, areas with higher ratios of surgeons to physiatrists were associated with lower odds of reconstruction (OR 0.16, 95% CI 0.07–0.39, P < .05). In comparison, areas with higher ratios of hand surgeons to SCISs were associated with slightly higher odds (OR 1.07, 95% CI 1.03–1.12, P < .05).
Table 4Multivariable Analysis of the Influence of Patient, Hospital, and Provider Characteristics on the Receipt of Upper Extremity Reconstructive Surgery
”Private” insurance category includes Blue Cross, commercial carriers, private health maintenance organizations, and preferred provider organizations. “Other” insurance category includes worker’s compensation, CHAMPUS, CHAMPVA, Title V of the McKinney-Vento Homeless Assistance Act, and other government programs.
CHAMPUS, Civilian Health and Medical Program of the Uniformed Services; CHAMPVA, Civilian Health and Medical Program of the Department of Veterans Affairs; PMR, physiatrists.
∗ Denotes continuous variables.
† US dollar ranges for quartiles vary by year in the NIS (Table E4).
‡ ”Private” insurance category includes Blue Cross, commercial carriers, private health maintenance organizations, and preferred provider organizations. “Other” insurance category includes worker’s compensation, CHAMPUS, CHAMPVA, Title V of the McKinney-Vento Homeless Assistance Act, and other government programs.
Our study revealed that the rates of reconstruction among patients with tetraplegia have remained unchanged since 20 years, although the incidences of SCI and cervical level injury have increased.
We adopted an estimate from the literature indicating that up to 50% of these patients are candidate to undergo reconstructive surgery, and we would expect that nearly 2,950 reconstructive procedures are performed per year.
In this context, we estimated that only 8.1% of patients undergo reconstruction.
We found that various financial factors, such as household income, cost of care, and insurance type, were associated with the receipt of reconstructive surgery. Although the reasons for this are likely multifactorial, it is possible that the reconstructive procedures were centralized to care facilities that are nonprofit or academic centers, possibly owing to the financial assistance available, complex nature of the procedure, or limited availability of specialty services at rural or for-profit hospitals. Provider availability has been previously described in the literature and aligns with our findings.
In a large survey study, a physiatrist’s attitudes regarding surgery and the presence of an existing referral network were identified as significant predictors of referral.
Patients were 13 times more likely to be referred if the physiatrist knew an interested hand surgeon. Moreover, 52% of physiatrists wanted to refer more often, and 40% of hand surgeons wanted to perform more UERs.
These findings suggest that improving geographical proximity and collaborative efforts among tetraplegia specialists can potentially increase reconstruction rates in patients with tetraplegia. In our cohort, we observed that the probability of undergoing reconstructive surgery was correlated with the density of specialists among one another, and the probability of surgery increased in areas with higher hand surgeon-to-SCIS ratios. These findings suggest that subspecialty training in tetraplegia care among providers has a positive effect on the probability of referral and that concentrating surgeons with nearby subspecialists could increase access to reconstruction through the referral of appropriate surgical candidates or referral to willing surgeons. However, the probability was lower in areas with a greater ratio of hand surgeons to physiatrists not specialized as SCISs. A recent study demonstrated that physiatrists who were exposed to UER during residency were significantly more likely to believe that the risks of the surgery were worth the benefits compared with their colleagues who did not have early exposure.
Furthermore, in our study, it was identified that only 444 (3.5%) board-certified physiatrists were also board-certified for SCI. It is possible that not all physiatrists and hand surgeons care for patients with tetraplegia because of a variation in training and expertise or the lack of interspecialty collaboration.
In such cases, patients may lack access to subspecialist care and may be less likely to have the opportunity for receiving reconstructive care.
In a 2013 Canadian study, it was identified that the lifetime economic burden of SCI ranged from $1.5 million Canadian dollars per patient with incomplete paraplegia to $3.0 million Canadian dollars per patient with complete tetraplegia.
Conversely, we found that financial constraints were associated with decreased access to UER. This is in alignment with other studies that suggest that financial factors are associated with access to care and the receipt of surgery.
Inequality of access to surgical specialty health care: why children with government-funded insurance have less access than those with private insurance in Southern California.
Most patients with tetraplegia in our cohort had some form of health insurance; yet, the reconstruction rates remained low, and those who did not have to pay for their care or those for whom it was subsidized were the most likely to undergo surgery. Additionally, there were a disproportionate percentage of patients from the top-residential-income group who underwent reconstruction. In our study, we were not able to capture data about the time from injury, and most patients in our cohort had Medicare or Medicaid coverage. These findings suggest that patients are more likely to undergo surgery when the cost of care is substantially covered by an outside organization or they have the financial resources to afford it. Furthermore, this suggests that current insurance coverage is potentially insufficient to offset the high costs of surgical reconstruction. Notably, we did not know the ADI quartile of the patients prior to their injury, and future research examining the potential impact of preinjury sociodemographic factors on access to and the receipt of reconstruction for tetraplegia is warranted. We found that reconstruction procedures were centralized to nonprofit and urban teaching hospitals, which can benefit tetraplegia care because academic centers are more likely to have comprehensive multidisciplinary teams to coordinate surgery and rehabilitation.
Medical conditions and outcomes at 1 year after acute traumatic spinal cord injury in a Greek and a Swedish region: a prospective, population-based study.
Moreover, large academic centers provide more subsidized care to vulnerable individuals than other nonprofit hospitals; the financial assistance available at nonprofit centers can aid patients with tetraplegia who cannot afford the considerable cost incurred from routine care or from the cost of surgery and subsequent rehabilitation.
Various patient and provider barriers impede the delivery of surgical care for patients with tetraplegia. From a patient perspective, financial and transportation assistance have the greatest impact and can dramatically improve their quality of life.
Provider proximity to nearby referring physicians facilitates cooperation as well as the delivery of health services, improved patient outcomes, and decreased cost of care.
An overview of systematic reviews on the collaboration between physicians and nurses and the impact on patient outcomes: what can we learn in primary care?.
Therefore, increasing the distance between patients with tetraplegia and care providers can directly limit accessibility because these patients rely on others for activities of daily living, including transportation for doctor visits and physical therapy sessions.
Provider barriers range from financial obstacles, such as the potential lack of a financial incentive owing to low reimbursement rates, to insufficient knowledge. For example, providers may be unaware of the reimbursement policies and billing resources available through care centers with established SCI care programs.
In addition, improving provider education has the potential to increase access. Patients prefer to learn about treatment options from spine specialists early in the rehabilitation process.
Furthermore, a multidisciplinary approach by establishing SCI care programs can lead to improved survival; a decreased length of hospital stay; and earlier surgical intervention, with fewer readmissions.
Medical conditions and outcomes at 1 year after acute traumatic spinal cord injury in a Greek and a Swedish region: a prospective, population-based study.
Therefore, policy changes to negate patient and provider barriers are important and should be addressed to improve use.
Our study has several limitations inherent to each database and the nature of claims data. There was a possible variation in the coding practice during the conversion of ICD-9 diagnosis and procedure codes to the ICD-10 revision in 2015. Another limiting factor is that the NIS records individual visits rather than patients; we were, therefore, unable to account for multistage or bilateral procedures. For example, patients who underwent surgery on both upper extremities on separate dates would have generated 2 encounters. This may have led to an overestimation of the actual number of patients who underwent reconstruction. However, this possible overestimation further emphasizes our finding of persistently low reconstruction rates for patients with tetraplegia. Furthermore, the NIS captures data from inpatient stays and does not include data from outpatient surgery centers. This may have led us to underestimate the number of actual procedures, and it is possible that advances in perioperative care have allowed for more procedures to be performed on an outpatient basis in recent years.
In addition, details regarding patient preferences or surgical candidacy are currently not available in national data sources, including administrative and claims data. Nonetheless, the NIS represents claims data from more than 97% of the US population.
Therefore, our results show the clinical environment faced by patients with tetraplegia in the US. With regard to the AMA Physician Masterfile, only providers with an active board certification were included. It is possible that there were practicing providers who previously held an active certification and were yet to renew it since its expiration. Nevertheless, the AMA Physician Masterfile data are provided directly from the Liaison Committee on Medical Education and the Accreditation Council for Graduate Medical Education, with information on over 1.4 million physicians, residents, and medical students in the US.
Finally, not all board-certified hand surgeons or physiatrists were tetraplegia experts or provided care for such patients, possibly owing to potential differences in training, experience, and interest. However, we believe that expanding subspeciality care focused on tetraplegia can enhance access to and the receipt of reconstruction for patients. Therefore, geographic location can be used as an approximation for provider availability, and future research examining patient volume and provider practices can further reveal the interplay of subspecialty availability and the patterns of care.
Tetraplegia has a devastating impact on the physical and psychological wellbeing of patients and their families. Upper extremity reconstruction rates remain low despite its potential to enhance functional independence. Expanding access to care will require a multifaceted approach, including a reduction in patient and provider financial barriers, improving patient education, expanding the availability of providers, and cultivating a collaboration among tetraplegia specialists.
Appendix A
Figure E1Schematic flowchart of patients included in multivariable regression analysis.
Significant difference between the total number of patients included in multivariable regression analysis and those excluded owing to missing values at 95% confidence level; the Welch 2-sample t test for continuous variables and chi-square test for categorical variables were used.
Significant difference between the total number of patients included in multivariable regression analysis and those excluded owing to missing values at 95% confidence level; the Welch 2-sample t test for continuous variables and chi-square test for categorical variables were used.
Significant difference between the total number of patients included in multivariable regression analysis and those excluded owing to missing values at 95% confidence level; the Welch 2-sample t test for continuous variables and chi-square test for categorical variables were used.
”Private” insurance category includes Blue Cross, commercial carriers, private health maintenance organizations, and preferred provider organizations. “Other” insurance category includes workers’ compensation and government programs.
Significant difference between the total number of patients included in multivariable regression analysis and those excluded owing to missing values at 95% confidence level; the Welch 2-sample t test for continuous variables and chi-square test for categorical variables were used.
Medicare
211,745 (57)
15,005 (50)
Medicaid
83,210 (22)
6,540 (22)
Private
61,265 (16)
6,005 (20)
Self-pay
5,520 (2)
375 (1)
No charge
370 (0)
25 (0)
Other
12,670 (3)
1,325 (4)
Missing
0 (0)
605 (2)
∗ Significant difference between the total number of patients included in multivariable regression analysis and those excluded owing to missing values at 95% confidence level; the Welch 2-sample t test for continuous variables and chi-square test for categorical variables were used.
† US dollar ranges for quartiles vary by year in the NIS (Table E4).
‡ ”Private” insurance category includes Blue Cross, commercial carriers, private health maintenance organizations, and preferred provider organizations. “Other” insurance category includes workers’ compensation and government programs.
Checkpoints to progression: qualitative analysis of the personal and contextual factors that influence selection of upper extremity reconstruction among patients with tetraplegia.
Inequality of access to surgical specialty health care: why children with government-funded insurance have less access than those with private insurance in Southern California.
Medical conditions and outcomes at 1 year after acute traumatic spinal cord injury in a Greek and a Swedish region: a prospective, population-based study.
An overview of systematic reviews on the collaboration between physicians and nurses and the impact on patient outcomes: what can we learn in primary care?.
H. E. Cho has received a surgical scientist training grant in Health Services and Translational Research (5-T32-GM008616-16A1) from the National Institutes of Health Ruth L. Kirschstein National Research Service Award. K. C. Chung receives funding from the National Institutes of Health and book royalties from Wolters Kluwer and Elsevier; and serves as a consultant for Axogen and Integra. No benefits in any form have been received or will be received by the other authors related directly or indirectly to the subject of this article.
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