Social determinants of health in prognostic machine learning models for orthopaedic outcomes: A systematic review.

RATIONAL: Social determinants of health (SDOH) are being considered more frequently when providing orthopaedic care due to their impact on treatment outcomes. Simultaneously, prognostic machine learning (ML) models that facilitate clinical decision making have become popular tools in the field of orthopaedic surgery. When ML-driven tools are developed, it is important that the perpetuation of potential disparities is minimized. One approach is to consider SDOH during model development. To date, it remains unclear whether and how existing prognostic ML models for orthopaedic outcomes consider SDOH variables. OBJECTIVE: To investigate whether prognostic ML models for orthopaedic surgery outcomes account for SDOH, and to what extent SDOH variables are included in the final models. METHODS: A systematic search was conducted in PubMed, Embase and Cochrane for studies published up to 17 November 2020. Two reviewers independently extracted SDOH features using the PROGRESS+ framework (place of residence, race/ethnicity, Occupation, gender/sex, religion, education, social capital, socioeconomic status, 'Plus+' age, disability, and sexual orientation). RESULTS: The search yielded 7138 studies, of which 59 met the inclusion criteria. Across all studies, 96% (57/59) considered at least one PROGRESS+ factor during development. The most common factors were age (95%; 56/59) and gender/sex (96%; 57/59). Differential effect analyses, such as subgroup analysis, covariate adjustment, and baseline comparison, were rarely reported (10%; 6/59). The majority of models included age (92%; 54/59) and gender/sex (69%; 41/59) as final input variables. However, factors such as insurance status (7%; 4/59), marital status (7%; 4/59) and income (3%; 2/59) were seldom included. CONCLUSION: The current level of reporting and consideration of SDOH during the development of prognostic ML models for orthopaedic outcomes is limited. Healthcare providers should be critical of the models they consider using and knowledgeable regarding the quality of model development, such as adherence to recognized methodological standards. Future efforts should aim to avoid bias and disparities when developing ML-driven applications for orthopaedics.

Discharge Disposition After Anterior Cervical Discectomy and Fusion.

OBJECTIVE: Age and comorbidity burden of patients going anterior cervical discectomy and fusion (ACDF) have increased significantly over the past 2 decades, resulting in increased expenditures. Non-home discharge after ACDF contributes to increased direct and indirect costs of postoperative care. The purpose of this study was to identify independent prognostic factors for discharge disposition in patients undergoing ACDF. METHODS: A retrospective review was conducted at 5 medical centers to identify patients undergoing ACDF for degenerative conditions. The primary outcome was non-home discharge. Additional outcomes considered included discharge to rehabilitation and home discharge with services. Bivariate and multivariable analyses were used to identify independent prognostic factors for non-home discharge. RESULTS: Of 2070 patients undergoing ACDF, 114 (5.5%) had non-home discharge and 63 (3.0%) had discharge to inpatient rehabilitation. Factors independently associated with non-home discharge included older age, marital status, Medicare insurance, Medicaid insurance, previous spine surgery, myelopathy, preoperative comorbidities (hemiplegia/paraplegia, congestive heart failure, cerebrovascular accident), anemia, and leukocytosis. C-statistic for the overall model was 0.85. Results were relatively similar for patients younger than the age of 65 years as well as for discharge to inpatient rehabilitation and discharge home with services. CONCLUSIONS: Numerous sociodemographic and clinical characteristics influence the risk of non-home discharge and discharge to inpatient rehabilitation in patients undergoing ACDF. Policy makers and payers should consider these factors when determining appropriate preoperative adjustment for risk-based reimbursements.

Practice Variation Among Surgeons Treating Lumbar Spinal Stenosis in a Single Institution.

STUDY DESIGN: A retrospective study. OBJECTIVE: The aim of this study was to examine practice variation in the treatment of lumbar spinal stenosis and identify targets for reducing variation. SUMMARY OF BACKGROUND DATA: Lumbar spinal stenosis is a degenerative condition susceptible to practice variation. Reducing variation aims to improve quality, increase safety, and lower costs. Establishing differences in surgeons' practices from a single institution can help identify personalized variation. METHODS: We identified adult patients first diagnosed with lumbar spinal stenosis between 2003 and 2015 in three hospitals of the same institution with ICD-9 codes.We extracted number of office visits, imaging procedures, injections, electromyographies (EMGs), and surgery within the first year after diagnosis; physical therapy within the first 3 months after diagnosis. Multivariable logistic regression was used to identify factors associated with surgery. The coefficient of variation (CV) was calculated to compare the variation in practice. RESULTS: The 10,858 patients we included had an average of 2.5 visits (±1.9), 1.5 imaging procedures (±2.0), 0.03 EMGs (±0.22), and 0.16 injections (±0.53); 36% had at least one surgical procedure and 32% had physical therapy as part of their care. The CV was smallest for number of visits (19%) and largest for EMG (140%).Male sex [odds ratio (OR): 1.23, P < 0.001], seeing an additional surgeon (OR: 2.82, P < 0.001), and having an additional spine diagnosis (OR: 3.71, P < 0.001) were independently associated with surgery. Visiting an orthopedic clinic (OR: 0.46, P < 0.001) was independently associated with less surgical interventions than visiting a neurosurgical clinic. CONCLUSION: There is widespread variation in the entire spectrum of diagnosis and therapy for lumbar spinal stenosis among surgeons in the same institution. Male gender, seeing an additional surgeon, having an additional spine diagnosis, and visiting a neurosurgery clinic were independently associated with increased surgical intervention. The main target we identified for decreasing variability was the use of diagnostic EMG. LEVEL OF EVIDENCE: 3.

Variation in costs among surgeons for lumbar spinal stenosis.

BACKGROUND CONTEXT: Lumbar spinal stenosis is a common condition in the elderly for which costs vary substantially by region. Comparing differences between surgeons from a single institution, thereby omitting regional variation, could aid in identifying factors associated with higher costs and individual drivers of costs. The use of decision aids (DAs) has been suggested as one of the possible tools for diminishing costs and cost variation. PURPOSE: (1) To determine factors associated with higher costs for treatment of spinal stenosis in the first year after diagnosis in a single institution; (2) to find individual drivers of costs for providers with higher costs; and (3) to determine if the use of DAs can decrease costs and cost variability. STUDY DESIGN: Retrospective cohort study. PATIENT SAMPLE: A total of 10,858 patients in 18 different practices diagnosed with lumbar spinal stenosis between January 2003 and July 2015 in three associated hospitals of a single institution. OUTCOME MEASURES: Mean cost for a patient per provider in US dollars within 1 year after diagnosis of lumbar spinal stenosis. METHODS: We collected all diagnostic testing, office visits, injections, surgery, and occupational or physical therapy related to lumbar spinal stenosis within 1 year after initial diagnosis. We used multivariable linear regression to determine independent predictors for costs. Providers were grouped in tiers based on mean total costs per patient to find drivers of costs. To assess the DAs effect on costs and cost variability, we matched DA patients one-to-one with non-DA patients. RESULTS: Male gender (ß 0.10, 95% confidence interval [CI] 0.05-0.15, p<.001), seeing an additional provider (ß 0.77, 95% CI 0.69-0.86, p<.001), and having an additional spine diagnosis (ß 0.79, 95% CI 0.74-0.84, p<.001) were associated with higher costs. Providers in the high cost tier had more office visits (p<.001), more imaging procedures (p<.001), less occupational or physical therapy (p=.002), and less surgery (p=.001) compared with the middle tier. Eighty-two patients (0.76%) received a DA as part of their care; there was no statistically significant difference between the DA group and the matched group in costs (p=.975). CONCLUSIONS: Male gender, seeing an additional provider, and having an additional spine diagnosis were independently associated with higher costs. The main targets for cost reduction we found are imaging procedures and number of office visits. Decision aids were not found to affect cost.