Household Income as a Predictor for Surgical Outcomes and Opioid Use After Spine Surgery in the United States

Barrie, Umaru; Montgomery, Eric Y.; Ogwumike, Erica; Pernik, Mark N.; Luu, Ivan Y; Adeyemo, Emmanuel; Christian, Zachary; Edukugho, Derrek; Johnson, Zachary D; Hoes, Kathryn; Tecle, Najib E. El; Hall, Kristen; Aoun, Salah G.; Bagley, Carlos A.

doi:10.1177/21925682211070823

Cited by 19 publications

(15 citation statements)

References 32 publications

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“…Low-income is also associated with longer postoperative lengths of stay, increased emergency department visits, and decreased accessibility to spinal imaging. 6,7 Medical literature has reported similar findings when examining other social determinants of health, including race, [8][9][10] ethnicity, 11,12 insurance status, 13 work status, 14,15 and education. 16 These studies highlight the importance of understanding a patient's socioeconomic profile to optimize their treatment and outcomes following spine surgery.…”

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confidence: 65%

Few Randomized Controlled Trials in Spine Surgery in the United States Include Sociodemographic Patient Data: A Systematic Review

Kirchner

Kim

Smith

et al. 2023

J Am Acad Orthop Surg

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Introduction:The importance of sociodemographic factors such as race, education, and income on spine surgery outcomes has been well established, yet the representation of sociodemographic data within randomized controlled trials (RCTs) in spine literature remains undefined in the United States (U.S). Methods: Medical literature was reviewed within PubMed for RCTs with "spine" in the title or abstract published within the last 8 years (2014 to 2021) in seven major spine journals. This yielded 128 results, and after application of inclusion criteria (RCTs concerning adult spine pathologies conducted in the U.S), 54 RCTs remained for analysis. Each article's journal of publication, year of publication, and spinal pathology was recorded. Pathologies included cervical degeneration, thoracolumbar degeneration, adult deformity, cervical trauma, and thoracolumbar trauma. Sociodemographic variables collected were race, ethnicity, insurance status, income, work status, and education. The Fisher's exact test was used to compare inclusion of sociodemographic data by journal, year, and spinal pathology. Results: Sociodemographic data were included in the results and in any section of 57.4% (31/54) of RCTs. RCTs reported work status in 25.9% (14/54) of results and 38.9% (21/54) of RCTs included work status in any section. Income was included in the results and mentioned in any section in 13.0% (7/54) of RCTs. Insurance status was in the results or any section of 9.3% (5/54) and 18.5% (10/54) of RCTs, respectively. There was no association with inclusion of sociodemographic data within the results of RCTs as a factor of journal (P = 0.337), year of publication (P = 0.286), or spinal pathology (P = 0.199). Discussion: Despite evidence of the importance of sociodemographic factors on the natural history and treatment outcomes of myriad spine pathologies, this study identifies a surprising absence of

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confidence: 65%

Few Randomized Controlled Trials in Spine Surgery in the United States Include Sociodemographic Patient Data: A Systematic Review

Kirchner

Kim

Smith

et al. 2023

J Am Acad Orthop Surg

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“…We intend our study to be foundational for development of granular models derived from multiple data sources. Moreover, variables such as socioeconomic status, education, and income level have shown potential in improving predictive accuracy 40. Measuring social support through the Risk Assessment and Prediction Tool (RAPT) presents a valuable future avenue 41.…”

Section: Discussionmentioning

confidence: 99%

“…Moreover, variables such as socioeconomic status, education, and income level have shown potential in improving predictive accuracy. 40 Measuring social support through the Risk Assessment and Prediction Tool (RAPT) presents a valuable future avenue. 41 Lastly, while this retrospective study utilized ICD10 codes to acquire components of patient data, some uncertainty on accuracy of ICD10 codes has been reported that could have resulted in an underestimation of risk factors.…”

Section: Discussionmentioning

confidence: 99%

Predictive Models for Length of Stay and Discharge Disposition in Elective Spine Surgery: Development, Validation, and Comparison to the ACS NSQIP Risk Calculator

Arora

Lituiev

Jain

et al. 2022

Spine

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Study Design. A retrospective study at a single academic institution.Objective. The purpose of this study is to utilize machine learning to predict hospital length of stay (LOS) and discharge disposition following adult elective spine surgery, and to compare performance metrics of machine learning models to the American College of Surgeon's National Surgical Quality Improvement Program's (ACS NSQIP) prediction calculator. Summary of Background Data. A total of 3678 adult patients undergoing elective spine surgery between 2014 and 2019, acquired from the electronic health record. Methods. Patients were divided into three stratified cohorts: cervical degenerative, lumbar degenerative, and adult spinal deformity groups. Predictive variables included demographics, body mass index, surgical region, surgical invasiveness, surgical approach, and comorbidities. Regression, classification trees, and least absolute shrinkage and selection operator (LASSO) were used to build predictive models. Validation of the models was conducted on 16% of patients (N = 587), using area under the receiver operator curve (AUROC), sensitivity, specificity, and correlation. Patient data were manually entered into the ACS NSQIP online risk calculator to compare performance. Outcome variables were discharge disposition (home vs. rehabilitation) and LOS (days). Results. Of 3678 patients analyzed, 51.4% were male (n = 1890) and 48.6% were female (n = 1788). The average LOS was 3.66 days. In all, 78% were discharged home and 22% discharged to rehabilitation. Compared with NSQIP (Pearson R 2 = 0.16), the predictions of poisson regression (R 2 = 0.29) and LASSO (R 2 = 0.29) models were significantly more correlated with observed LOS (P = 0.025 and 0.004, respectively). Of the models generated to predict discharge location, logistic regression yielded an AUROC of 0.79, which was statistically equivalent to the AUROC of 0.75 for NSQIP (P = 0.135). Conclusion. The predictive models developed in this study can enable accurate preoperative estimation of LOS and risk of rehabilitation discharge for adult patients undergoing elective spine surgery. The demonstrated models exhibited better performance than NSQIP for prediction of LOS and equivalent performance to NSQIP for prediction of discharge location.

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“…Numerous studies have linked components of SES to poor outcomes following spine surgery 5–7. The Area of Deprivation Index (ADI), a metric similar to DCI, found an association between SES and length of stay 13,14.…”

Section: Discussionmentioning

confidence: 99%

“…While health outcome disparities among patients of lower socioeconomic standing are likely multifactorial, limited access to care or a general fear of physicians may contribute 4. In spine surgery, extensive research has been performed on how individual factors contribute to SES including insurance status, income, race and education 5–8. However, each of these aspects are difficult to investigate in isolation as they are strongly correlated with each other.…”

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confidence: 99%

Patients from Socioeconomically Distressed Communities Experience Similar Clinical Improvements Following Anterior Cervical Discectomy and Fusion

Lambrechts

Toci

Issa

et al. 2022

Spine

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Objectives. The aim was to compare patient-reported outcome measures (PROMs) following anterior cervical discectomy and fusion (ACDF) when categorizing patients based on socioeconomic status. Secondarily, we sought to compare PROMs based on race. Summary of Background Data. Social determinants of health are believed to affect outcomes following spine surgery, but there is limited literature on how combined socioeconomic status metrics affect PROMs following ACDF. Materials and Methods. The authors identified patients who underwent primary elective one-level to four-level ACDF from 2014 to 2020. Patients were grouped based on their distressed community index (DCI) quintile (Distressed, At-Risk, Mid-tier, Comfortable, and Prosperous) and then race (White or Black). Multivariate regression for ΔPROMs was performed based on DCI group and race while controlling for baseline demographics and surgical characteristics. Results. Of 1204 patients included in the study, all DCI groups improved across all PROMs, except mental health component score (MCS-12) for the Mid-tier group (P = 0.091). Patients in the Distressed/At-Risk group had worse baseline MCS-12, visual analog scale (VAS) Neck, and neck disability index (NDI). There were no differences in magnitude of improvement between DCI groups. Black patients had significantly worse baseline VAS Neck (P = 0.002) and Arm (P = 0.012) as well as worse postoperative MCS-12 (P = 0.016), PCS-12 (P = 0.03), VAS Neck (P < 0.001), VAS Arm (P = 0.004), and NDI (P < 0.001). Multivariable regression analysis did not identify any of the DCI groupings to be significant independent predictors of ΔPROMs, but being White was an independent predictor of greater improvement in ΔPCS-12 (β = 3.09, P = 0.036) and ΔNDI (β = −7.32, P = 0.003). Conclusions. All patients experienced clinical improvements regardless of DCI or race despite patients in Distressed communities and Black patients having worse preoperative PROMs. Being from a distressed community was not an independent predictor of worse improvement in any PROMs, but Black patients had worse improvement in NDI compared with White patients.

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Household Income as a Predictor for Surgical Outcomes and Opioid Use After Spine Surgery in the United States

Cited by 19 publications

References 32 publications

Few Randomized Controlled Trials in Spine Surgery in the United States Include Sociodemographic Patient Data: A Systematic Review

Few Randomized Controlled Trials in Spine Surgery in the United States Include Sociodemographic Patient Data: A Systematic Review

Predictive Models for Length of Stay and Discharge Disposition in Elective Spine Surgery: Development, Validation, and Comparison to the ACS NSQIP Risk Calculator

Patients from Socioeconomically Distressed Communities Experience Similar Clinical Improvements Following Anterior Cervical Discectomy and Fusion

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