Quantifying Patient Expectations for Total Knee Arthroplasty: Expectations for Improvement are Greater than MCID.

INTRODUCTION: Achieving a minimal clinically important difference (MCID) in patient-reported outcomes (PROs) following total knee arthroplasty (TKA) is common, yet up to 20% patient dissatisfaction persists. Unmet expectations may explain post-TKA dissatisfaction. No prior studies have quantified patient expectations using the same PRO metric as used for MCID to allow direct comparison. METHODS: This was a prospective study of patients undergoing TKA with five fellowship-trained arthroplasty surgeons at one academic center. Baseline Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function (PF) and Pain Interference (PI) domains were assessed. Expected PROMIS scores were determined by asking patients to indicate the outcomes they were expecting at 12 months postoperatively. Predicted scores were generated from a predictive model validated in the Function and Outcomes Research for Comparative Effectiveness in Total Joint Replacement (FORCE-TJR) dataset. T-tests were used to compare baseline, expected, and predicted PROMIS scores. Expected scores were compared to PROMIS MCID values obtained from the literature. Regression models were used to identify patient characteristics associated with high expectations. RESULTS: There were 93 patients included. Mean age was 67 years (range, 30 to 85) and 55% were women. Mean baseline PROMIS PF and PI was 34.4+/-6.7 and 62.2+/-6.4, respectively. Patients expected significant improvement for PF of 1.9 times the MCID (MCID = 11.3; mean expected improvement = 21.6, 95% CI [confidence interval] 19.6 to 23.5, P < 0.001) and for PI of 2.3 times the MCID (MCID=8.9; mean expected improvement=20.6, 95%CI 19.1-22.2, P < 0.001). Predicted scores were significantly lower than expected scores (mean difference = 9.5, 95% CI 7.7 to 11.3, P < 0.001). No unique patient characteristics were associated with high expectations (P > 0.05). CONCLUSION: To our knowledge, this study is the first to quantify preoperative patient expectations using the same metric as MCID to allow for direct comparison. Patient expectations for improvement following TKA are ∼2x greater than MCID and are significantly greater than predicted outcome scores. This discrepancy challenges currently accepted standards of success after TKA and indicates a need for improved expectation setting prior to surgery.

A Novel Method for Tracking Neck Motions Using a Skin-Conformable Wireless Accelerometer: A Pilot Study.

Introduction: Cervical spine disease is a leading cause of pain and disability. Degenerative conditions of the spine can result in neurologic compression of the cervical spinal cord or nerve roots and may be surgically treated with an anterior cervical discectomy and fusion (ACDF) in up to 137,000 people per year in the United States. A common sequelae of ACDF is reduced cervical range of motion (CROM) with patient-based complaints of stiffness and neck pain. Currently, tools for assessment of CROM are manual, subjective, and only intermittently utilized during doctor or physical therapy visits. We propose a skin-mountable acousto-mechanic sensor (ADvanced Acousto-Mechanic sensor; ADAM) as a tool for continuous neck motion monitoring in postoperative ACDF patients. We have developed and validated a machine learning neck motion classification algorithm to differentiate between eight neck motions (right/left rotation, right/left lateral bending, flexion, extension, retraction, protraction) in healthy normal subjects and patients. Methods: Sensor data from 12 healthy normal subjects and 5 patients were used to develop and validate a Convolutional Neural Network (CNN). Results: An average algorithm accuracy of 80.0 ± 3.8% was obtained for healthy normal subjects (94% for right rotation, 98% for left rotation, 65% for right lateral bending, 87% for left lateral bending, 89% for flexion, 77% for extension, 50% for retraction, 84% for protraction). An average accuracy of 67.5 ± 5.8% was obtained for patients. Discussion: ADAM, with our algorithm, may serve as a rehabilitation tool for neck motion monitoring in postoperative ACDF patients. Sensor-captured vital signs and other events (extubation, vocalization, physical therapy, walking) are potential metrics to be incorporated into our algorithm to offer more holistic monitoring of patients after cervical spine surgery.

AOA Critical Issues Symposium: Shaping the Impact of Artificial Intelligence within Orthopaedic Surgery.

ABSTRACT: Artificial intelligence (AI) is a broad term that is widely used but inconsistently understood. It refers to the ability of any machine to exhibit human-like intelligence by making decisions, solving problems, or learning from experience. With its ability to rapidly process large amounts of information, AI has already transformed many industries such as entertainment, transportation, and communications through consumer-facing products and business-to-business applications. Given its potential, AI is also anticipated to impact the practice of medicine and the delivery of health care. Interest in AI-based techniques has grown rapidly within the orthopaedic community, resulting in an increasing number of publications on this topic. Topics of interest have ranged from the use of AI for imaging interpretation to AI-based techniques for predicting postoperative outcomes.The highly technical and data-driven nature of orthopaedic surgery creates the potential for AI, and its subdisciplines machine learning (ML) and deep learning (DL), to fundamentally transform our understanding of musculoskeletal care. However, AI-based techniques are not well known to most orthopaedic surgeons, nor are they taught with the same level of insight and critical thinking as traditional statistical methodology. With a clear understanding of the science behind AI-based techniques, orthopaedic surgeons will be able to identify the potential pitfalls of the application of AI to musculoskeletal health. Additionally, with increased understanding of AI, surgeons and their patients may have more trust in the results of AI-based analytics, thereby expanding the potential use of AI in clinical care and amplifying the impact it could have in improving quality and value. The purpose of this American Orthopaedic Association (AOA) symposium was to facilitate understanding and development of AI and AI-based techniques within orthopaedic surgery by defining common terminology related to AI, demonstrating the existing clinical utility of AI, and presenting future applications of AI in surgical care.

Patient and Surgeon Perceptions Regarding Microdiscectomy Surgery: A Cross-Sectional Analysis of Social Media Posts.

BACKGROUND: Social media offers a powerful and expanding platform for sharing the patient experience with a large audience through an unsolicited perspective. The content may influence future perceptions around surgical care. OBJECTIVE: To analyze publicly available content on a major social media outlet related to microdiscectomy surgery based on perspective, location, timing, content, tone, and patient satisfaction. METHODS: A query of content was performed for the study period 1 January 2019 to 1 January 2021. Relevant content was identified by hashtag "#microdiscectomy." The initial query returned 10,050 publicly available posts, and the 1500 most "liked" posts were included for evaluation. Content was subsequently classified, characterized, and analyzed. RESULTS: Patients created 72.9% of microdiscectomy-related content, and spine surgeons created 23.5%. Regarding region, 77.0% of posts originated in the United States. The majority portrayed the patient experience in the postoperative phase of care (86.0%), with the primary reference to activities of daily living (56.9%). Only 1.7% of posts depicted the surgical incision site. The connotation of posts was deemed positive in 78.5% of cases. Of the posts referencing satisfaction, 98.3% depicted patient satisfaction with the surgical outcome. Patient posts in the postoperative phase of care (>1 week after surgery) were more than 2 times as likely to express positive tone (OR = 2.07, P ≤ 0.013) with their clinical course compared with patient posts outside the postoperative period. CONCLUSIONS AND CLINICAL RELEVANCE: Overall, social media posts are written in a positive tone, express satisfaction with surgical outcome, typically occur in the postoperative period of care, and depict activities of daily living. These popular mechanisms of communication, such as Instagram, offer spine surgeons unique insights into the true patient experience and may provide an opportunity for surgeons to assess patient feedback, influence patient perceptions, and enhance delivery of lumbar spine care.

Using Machine Learning and Deep Learning Algorithms to Predict Postoperative Outcomes Following Anterior Cervical Discectomy and Fusion.

STUDY DESIGN: A retrospective cohort study from a multisite academic medical center. OBJECTIVE: To construct, evaluate, and interpret a series of machine learning models to predict outcomes related to inpatient health care resource utilization for patients undergoing anterior cervical discectomy and fusion (ACDF). SUMMARY OF BACKGROUND DATA: Reducing postoperative health care utilization is an important goal for improving the delivery of surgical care and serves as a metric for quality assessment. Recent data has shown marked hospital resource utilization after ACDF surgery, including readmissions, and ED visits. The burden of postoperative health care use presents a potential application of machine learning techniques, which may be capable of accurately identifying at-risk patients using patient-specific predictors. METHODS: Patients 18-88 years old who underwent ACDF from 2011 to 2021 at a multisite academic center and had preoperative lab values within 3 months of surgery were included. Outcomes analyzed included 90-day readmissions, postoperative length of stay, and nonhome discharge. Four machine learning models-Extreme Gradient Boosted Trees, Balanced Random Forest, Elastic-Net Penalized Logistic Regression, and a Neural Network-were trained and evaluated through the Area Under the Curve estimates. Feature importance scores were computed for the highest-performing model per outcome through model-specific metrics. RESULTS: A total of 1026 cases were included in the analysis cohort. All machine learning models were predictive for outcomes of interest, with the Random Forest algorithm consistently demonstrating the strongest average area under the curve performance, with a peak performance of 0.84 for nonhome discharge. Important features varied per outcome, though age, body mass index, American Society of Anesthesiologists classification >2, and medical comorbidities were highly weighted in the studied outcomes. CONCLUSIONS: Machine learning models were successfully applied and predictive of postoperative health utilization after ACDF. Deployment of these tools can assist clinicians in determining high-risk patients. LEVEL OF EVIDENCE: III.

The Role of Preoperative Vitamin D in Spine Surgery.

PURPOSE OF REVIEW: Vitamin D is an essential micronutrient for human bone health and maintenance. Patients undergoing orthopaedic surgery with hypovitaminosis D may be at greater risk for worsened clinical outcomes. This narrative review aims to compile the current literature studying the effects of low preoperative vitamin D on spine surgery outcomes, creating a resource that clinicians can use to inform their practice. RECENT FINDINGS: Vitamin D deficiency predisposes to worse outcomes following spine surgery. Vitamin D supplementation may be beneficial in reducing the risk for adverse postoperative events; however, the literature is inconclusive regarding its efficacy in improving bone density and fracture risk. Spine clinicians should be aware of the increased risk for poor outcomes in patients with preoperative vitamin D deficiency. Future investigations are needed to better evaluate the benefits of preoperative vitamin D screening and supplementation on improving surgical outcomes in spine patients. These studies must also consider the effects on perioperative healthcare costs.

Impact of Social Determinants of Health in Spine Surgery.

PURPOSE OF REVIEW: Social determinants of health (SDH) are factors that affect patient health outcomes outside the hospital. SDH are "conditions in the environments where people are born, live, learn, work, play, worship, and age that affect a wide range of health, functioning, and quality-of-life outcomes and risks." Current literature has shown SDH affecting patient reported outcomes in various specialties; however, there is a dearth in research relating spine surgery with SDH. The aim of this review article is to identify connections between SDH and post-operative outcomes in spine surgery. These are important, yet understudied predictors that can impact health outcomes and affect health equity. RECENT FINDINGS: Few studies have shown associations between SDH pillars (environment, race, healthcare, economic, and education) and spine surgery outcomes. The most notable relationships demonstrate increased disability, return to work time, and pain with lower income, education, environmental locations, healthcare status and/or provider. Despite these findings, there remains a significant lack of understanding between SDH and spine surgery. Our manuscript reviews the available literature comparing SDH with various spine conditions and surgeries. We organized our findings into the following narrative themes: 1) education, 2) geography, 3) race, 4) healthcare access, and 5) economics.

The Effect of Diabetes and Metabolic Syndrome on Spine Surgery Outcomes.

PURPOSE OF REVIEW: Diabetes and metabolic syndrome are highly prevalent in patients undergoing spine surgery. This review aims to capture both the findings of recently published literature investigating the effects of diabetes and metabolic syndrome on spine surgery outcomes and the current best practices in patient management. RECENT FINDINGS: Diabetes and metabolic syndrome both contribute to worse outcomes in patients undergoing spine surgery. Although patients with diabetes are at greater risk of complications, those with uncontrolled diabetes experience increased healthcare costs and greater odds of postoperative complications. Furthermore, metabolic syndrome is repeatedly shown to have an adverse effect on spine surgery outcomes, including healthcare costs and medical complications. Spine surgeons should coordinate care with primary care physicians to optimize the preoperative profile of patients with comorbidities like diabetes and metabolic syndrome to minimize operative risk. With the shift to value-based care, understanding the patient factors that lead to complications is becoming increasingly important. Future studies should build upon the current literature and design preoperative interventions for at-risk patients. Additionally, further research is needed to analyze the modulatory effects of the social determinants of health in patients with diabetes and metabolic syndrome.

Hypothyroidism and Spine Surgery: a Review of Current Findings.

PURPOSE OF REVIEW: Hypothyroidism is a common medical comorbidity and has been linked to adverse surgical outcomes. However, its effect on spine surgery outcomes is less clear. The aim of this review is to compile current literature to serve as a guide for spine surgeons when treating patients with hypothyroidism. RECENT FINDINGS: In both the cervical and lumbar spine, patients with hypothyroidism are at increased risk of postoperative medical complications. Consequently, patients with hypothyroidism experience increased healthcare costs and readmission rates. However, there are some contradictory findings with some studies suggesting that hypothyroidism may have a protective effect in patients undergoing lumbar fusion, specifically against postoperative myocardial infraction and decreased inpatient mortality. When examining spine surgery outcomes, there are mixed results when considering the effect of hypothyroidism. Some studies have shown increased medical complications, hardware failure, and increased expenditure; however, other recent findings suggest possible protective effects. Future studies are needed to help create concrete guidelines for treating patients with hypothyroidism.

Spine Surgery and Ankylosing Spondylitis: Optimizing Perioperative Management.

Ankylosing spondylitis (AS) is a common form of axial spondyloarthritis, characterized by inflammatory back pain, radiographic sacroiliitis, excess spinal bone formation, and a high prevalence of HLA-B27. Commonly, AS patients require spinal surgery for kyphotic deformities, spinal trauma, and spinal infections. For preoperative management, proper interruption considering each specific half-lives of disease-modifying antirheumatic drugs are necessary to avoid complications, such as infections. When feasible, bone quality assessment before surgery is mandatory. For intraoperative measurements, airway management should be carefully evaluated, especially in patients with severe cervical deformities. Cardiac, renal, and pulmonary assessment should be made considering specific pathologic characteristics involved in AS patients, such as pulmonary restrictive disease and chronic anti-inflammatory drugs use. Multimodal neurophysiological intraoperative monitoring is recommended once these patients had a high risk for neurological deterioration. At the postoperative period, early oral intake, early mobilization, and aggressive pain control may decrease complications and enhance recovery. AS presents several unique challenges that require specific attention around spine surgery. This includes handling preoperative and postoperative pharmacotherapeutics, intraoperative airway management, and the mitigation of postoperative complications. In this paper, we provide a literature review of optimal strategies for the perioperative management for patients with AS.

Social Media Posts Pertaining to Anterior Cervical Discectomy and Fusion (ACDF) Surgery: A Cross-sectional Analysis of Patient and Surgeon Perceptions.

STUDY DESIGN: Cross-sectional study. OBJECTIVE: To analyze publicly available content on a major social media outlet related to anterior cervical discectomy and fusion (ACDF) surgery based on perspective, location, timing, content, tone, and patient satisfaction. SUMMARY OF BACKGROUND DATA: Social media offers a powerful platform for sharing the patient experience with the public through an unfiltered perspective. Social media content may influence future perceptions around surgical care and postings around ACDF have not been previously reported. METHODS: A query of content from a major social media outlet was performed for the study period January 1, 2018, to January 1, 2020, and returned 6500 publicly available posts. Content was identified by the hashtags "#acdf" or "#acdfsurgery." Content was ranked by number of "likes." Of the 1500 most popular posts, 1136 related to ACDF surgery and were included. Post content was characterized and classified. RESULTS: Patients created 85% of ACDF-related content and spine surgeons created 11.8%. Most posts portrayed the patient experience in the postoperative period and depicted patients performing activities of daily living, participating in sports, or completing work activities (54.4%). The connotation of posts was deemed to be positive in 79.2% of cases. In regard to their care or state of health as it related to ACDF surgery, 59.8% of patients expressed satisfaction, whereas 14.1% expressed dissatisfaction. Female patients were >4 times as likely to express dissatisfaction (odds ratio=4.16, P =<0.0001), with their clinical course compared with their male counterparts. CONCLUSIONS: Patients were the source of most posts on a major social media outlet that pertained to ACDF surgery with a majority reporting positive tone and satisfaction. These mechanisms of communication offer surgeons unique insights into patient experience and may provide an opportunity for surgeons to assess patient feedback, influence patient perceptions, and enhance delivery of cervical spine care.

Predictive Analysis of Healthcare Resource Utilization after Elective Spine Surgery.

Introduction: The management of degenerative spine pathology continues to be a significant source of costs to the US healthcare system. Besides surgery, utilization of healthcare resources after spine surgery drives costs. The responsibility of managing costs is gradually shifting to patients and providers. Patient-centered predictors of healthcare utilization after elective spine surgery may identify targets for cost reduction and value creation. Therefore, our study aims to quantify patterns of healthcare utilization and identify risk factors that predict high healthcare utilization after elective spine surgery. Methods: A total of 623 patients who underwent elective spine surgery at a tertiary academic medical center by one of three fellowship-trained orthopedic spine surgeons between 2013 and 2018 were identified in this retrospective cohort study. Healthcare utilization was quantified including advanced spine imaging, emergency and urgent care visits, hospital readmission, reoperation, PT/OT referrals, opioid prescriptions, epidural steroid injections, and pain management referrals. Patient variables, namely, the Charlson comorbidity index (CCI) and the American Society of Anesthesiologists (ASA) classification system, were assessed as potential predictors for healthcare utilization. Results: Among all patients, a wide range of health utilization was identified. Age, body mass index, Charlson Comorbidity Index, and American Society of Anesthesiology class were identified as positive predictors of postoperative healthcare utilization including emergency department visits, spine imaging studies, opioid and nerve blocker prescriptions, inpatient rehabilitation, any referrals, and pain management referrals. Conclusions: Markers of patient health-such as CCI and ASA class-may be used to predict healthcare utilization following elective spine surgery. Identifying at-risk patients and addressing these challenges prior to surgery is an important step to deliver efficient postoperative care. Level of Evidence: 3.

Measuring Value in Elective Spine Surgery.

Objective: To summarize the main findings from research on measuring the value in spine surgery. Summary of Background Data: Determining the value of surgical interventions, which is defined by the quality and efficacy of care received divided by the cost to deliver healthcare, is inherently complex. The two most fundamental components of value-quality and total cost-are multifactorial and difficult to quantify. Methods: A narrative review of all the relevant papers known to the author was conducted. Results: It is straightforward to calculate the aggregate hospital cost following a surgical procedure, but it is not simple to estimate the total cost of a procedure-including the direct and indirect costs. These individual metrics can help providers make more educated decisions with regards to improving patient quality of life and minimizing unnecessary costs. A consensus of the appropriate cost-per-quality-adjusted life-year threshold of different spine surgeries needs to be established. As these metrics become more commonplace in spine surgery, the potential for personalized health care will continue to be developed. Conclusions: As the healthcare system shifts toward value-based care, there is a substantial need for research assessing the value as defined by the quality and efficacy of care received divided by the cost to deliver healthcare of specific spine surgery procedures. Studies on different predictors-both patient-specific and surgical-that may influence outcomes, cost, and value are required.

The Drivers of Persistent Opioid Use and Its Impact on Healthcare Utilization After Elective Spine Surgery.

STUDY DESIGN: Retrospective cohort study. OBJECTIVE: The aim of this study was to determine the incidence of and risk factors for persistent opioid use after elective cervical and lumbar spine procedures and to quantify postoperative healthcare utilization in this patient population. METHODS: Patients were retrospectively identified who underwent elective spine surgery for either cervical or lumbar degenerative pathology between November 1, 2013, and September 30, 2018, at a single academic center. Patients were split into 2 cohorts, including patients with and without opioid use at 180-days postoperatively. Baseline patient demographics, underlying comorbidities, surgical variables, and preoperative/postoperative opioid use were assessed. Health resource utilization metrics within 1 year postoperatively (ie, imaging studies, emergency and urgent care visits, hospital readmissions, opioid prescriptions, etc.) were compared between these 2 groups. RESULTS: 583 patients met inclusion criteria, of which 16.6% had opioid persistence after surgery. Opioid persistence was associated with ASA score ≥3 (P = .004), diabetes (P = .019), class I obesity (P = .012), and an opioid prescription in the 60 days prior to surgery (P = .006). Independent risk factors for opioid persistence assessed via multivariate regression included multi-level lumbar fusion (RR = 2.957), cervical central stenosis (RR = 2.761), and pre-operative opioid use (RR = 2.668). Opioid persistence was associated with higher rates of health care utilization, including more radiographs (P < .001), computed tomography (CT) scans (.007), magnetic resonance imaging (MRI) studies (P = .014), emergency department (ED) visits (.009), pain medicine referrals (P < .001), and spinal injections (P = .003). CONCLUSIONS: Opioid persistence is associated with higher rates of health care utilization within 1 year after elective spine surgery.

A Surgeon's Guide to Understanding Artificial Intelligence and Machine Learning Studies in Orthopaedic Surgery.

PURPOSE OF REVIEW: In recent years, machine learning techniques have been increasingly utilized across medicine, impacting the practice and delivery of healthcare. The data-driven nature of orthopaedic surgery presents many targets for improvement through the use of artificial intelligence, which is reflected in the increasing number of publications in the medical literature. However, the unique methodologies utilized in AI studies can present a barrier to its widespread acceptance and use in orthopaedics. The purpose of our review is to provide a tool that can be used by practitioners to better understand and ultimately leverage AI studies. RECENT FINDINGS: The increasing interest in machine learning across medicine is reflected in a greater utilization of AI in recent medical literature. The process of designing machine learning studies includes study design, model choice, data collection/handling, model development, training, testing, and interpretation. Recent studies leveraging ML in orthopaedics provide useful examples for future research endeavors. This manuscript intends to create a guide discussing the use of machine learning and artificial intelligence in orthopaedic surgery research. Our review outlines the process of creating a machine learning algorithm and discusses the different model types, utilizing examples from recent orthopaedic literature to illustrate the techniques involved.

Predictors of Dysphagia After Anterior Cervical Discectomy and Fusion: A Prospective Multicenter Study.

STUDY DESIGN: Multicenter prospective study. OBJECTIVE: Our aim was to evaluate the incidence and predictors of postoperative dysphagia in patients undergoing anterior cervical discectomy and fusion (ACDF). SUMMARY OF BACKGROUND DATA: Dysphagia is a common complication after ACDF that can have significant effect on patients' quality of life, but the frequency of occurrence and potential risk factors are not known. METHODS: A multicenter prospective study was undertaken at three academic sites to evaluate patients undergoing ACDF between September 2018 and September 2020. Included patients were aged 18 to 80 years and were undergoing primary or revision ACDF for a degenerative condition. Dysphagia was assessed using the validated Eating Assessment Tool (EAT-10) questionnaire, with dysphagia defined as EAT-10 ≥ 3. RESULTS: A total of 170 patients (53.5% female; mean age at surgery 55.0 yr) were included. At preoperative baseline, 23 patients (13.5%) had dysphagia. Rates of dysphagia increased to 45.3% at 2 weeks postoperatively but gradually decreased to 15.3% at 24weeks. On univariate analysis, patients with dysphagia at 2weeks had longer operations (113.1 ±â€Š58.4 vs. 89.0 ±â€Š39.8 minutes, P   =  0.003) and higher baseline dysphagia rates (18.2% vs. 6.2%, P   =  0.018) and were more likely to be female (66.2% vs. 45.7%, P   =  0.009). Patients with prolonged dysphagia had more levels fused (2.1 ±â€Š1.0 vs. 1.7 ±â€Š0.7, P   =  0.020), longer operations (131.8 ±â€Š63.1 vs. 89.3 ±â€Š44.3 min-minutes, P   <  0.001), and higher baseline dysphagia rates (32% vs. 7.1%, P   <  0.001) and were more likely to be smokers (24% vs. 8%, P   =  0.021). On multivariate analysis to determine associations with prolonged dysphagia, only smoking status (OR 6.2, 95% CI 1.57-24.5, P   =  0.009) and baseline dysphagia (OR 5.1, 95% CI 1.47-17.6, P   =  0.01) remained significant. CONCLUSION: Dysphagia is common immediately after ACDF, but rates of prolonged dysphagia are similar to preoperative baseline rates. We identified dysphagia rates over time and several patient factors associated with development of short- and long-term postoperative dysphagia.Level of Evidence: 3.

Preoperative PROMIS Scores Predict Postoperative Outcomes in Lumbar Spine Surgery Patients.

STUDY DESIGN: Retrospective case series. OBJECTIVE: Our objective was to examine the ability of preoperative Patient-reported Outcomes Measurement Information System (PROMIS) scores to predict postoperative achievement of a minimum clinically important difference (MCID) in outcome scores following lumbar spine surgery. SUMMARY OF BACKGROUND DATA: PROMIS is a computer adaptive testing system that has been validated in spine surgery patients. PROMIS allows for more efficient and personalized data collection compared to legacy assessment tools. METHODS: A total of 138 patients who underwent lumbar spine surgery at a single institution completed PROMIS Physical Function (PF) and Pain Interference (PI) scores preoperatively and at 3, 12, and 24 months postoperatively. Univariate and multivariate analyses of PROMIS scores and clinical factors were performed. Receiver-operating characteristic curves were calculated to determine the ability of preoperative scores to predict postoperative achievement of an MCID of 8. PF and PI t score MCID achievement threshold values with 90% specificity were calculated. RESULTS: Preoperative PROMIS PF and PI scores were significantly correlated to achievement of postoperative MCID after multivariate analysis. Patients with worse preoperative scores were more likely to achieve MCID. Preoperative PF and PI scores showed strong predictive value in determining ability to achieve postoperative MCID with respective area under the curve of 0.85 and 0.82. A preoperative PF threshold T-score of 31.6 had a 64% chance of achieving postoperative MCID, while a preoperative PI threshold t score of 67.8 had an 86% chance of achieving postoperative MCID. CONCLUSION: Preoperative PROMIS PF and PI scores predicted improvement in postoperative PROMIS scores in lumbar spine surgery patients as worse preoperative scores correlated to improved PROMIS scores postoperatively. The calculated threshold t scores showed the ability to predict improvement in postoperative PROMIS scores. Preoperative PROMIS data may be useful in surgical decision-making and improved patient education regarding postoperative outcomes.Level of Evidence: 4.

Private Equity and Its Emergence in Orthopaedics.

Private equity (PE) is increasing its role in healthcare financing and may be a source of strategic funding for orthopaedic practice groups. With acquisitions in other medical specialties such as dermatology and ophthalmology, PE works to increase operating efficiency and cut costs. Orthopaedic practices' access to revenue through ancillary services and ambulatory surgery centers, coupled with a growing, aging cohort, make them an attractive candidate for PE acquisition. However, careful consideration is warranted before surgeons enter these partnerships to ensure patient safety, and the quality of care is not compromised because PE works to increase the return on their investment.

The content and accessibility of spine surgery fellowship websites and the North American Spine Surgery (NASS) fellowship directory.

BACKGROUND CONTEXT: The North American Spine Society (NASS) spine fellowship directory is an established resource that provides applicants with access to important information about different fellowship programs. Additionally, some programs have created websites to provide information about their fellowship program. There has been limited research on the amount and breadth of information provided by these different resources. PURPOSE: To assess and compare the scope of information provided by the North American Spine Society (NASS) fellowship directory and individual fellowship program websites. STUDY DESIGN/SETTING: Web Content Accessibility Study. PATIENT SAMPLE: There were no patient data used in this study. All reported data were accessed from public websites and the NASS fellowship directory (August 2022 fellowships). OUTCOME MEASURES: Outcome measures were reported as the presence or lack thereof of 22 topics pertaining to the specifics of each individual spine fellowship program on both the NASS fellowship directory and individual fellowship program websites. METHODS: The NASS fellowship directory (August 2022 fellowships) and individual program websites were evaluated by two independent reviewers. Program websites were identified via Google search with a systematic protocol. Within each platform, the availability of various data were recorded. Twenty-four different data points were assessed for each program and were categorized into four main categories-general program information, fellow profiles, clinical roles, and nonclinical roles of the fellow. Chi-squared tests were used to compare differences in the availability of specific data provided by the NASS fellowship directory and individual program websites. RESULTS: Seventy-four fellowship programs were identified. The NASS fellowship directory was more likely to provide information about the application process, a description of the program, fellow salary, faculty members, case descriptions, and research requirements (p<.05). The program websites were more likely to provide information about current and previous fellows-including a list of current fellow(s), their education/training, and a list of the previous fellows and their job choice (p<.05). Program websites were also more likely to discuss rotation schedules, clinic expectations, research opportunities, journal club, institutional meetings, sponsored national meetings, and current/previous research (p<.05). However, certain information, including specific clinical responsibilities (eg, rotation schedule, call expectations, clinic expectations) and the profiles of current and previous fellows, were not well represented on either platform. CONCLUSIONS: There were significant differences in the type of information provided by the NASS fellowship directory and program websites. Furthermore, there were key pieces of information that were not well represented on either platform.