United States

Background:
Deciding when a patient is a candidate for Total Hip (THA) or Knee (TKA) Arthroplasty to treat arthritis is complex. Accordingly, shared decision-making (SDM) between patient and surgeon regarding candidacy for THA/TKA is considered best practice. However, successful SDM requires clear communication of specific symptoms, their individualized functional impact, and a mutual understanding of expectations. Understanding a patient’s perspective and where communication gaps may occur can improve this conversation. The OPTION (Objective Performance Threshold Indicating Operative Need) Survey was developed to guide SDM regarding readiness for THA/TKA. Survey results provide critical insights into this conversation: specifically, surgeon perception of the patient’s experience, how individual patient priorities differ in arthritis management, and how radiographic data align with patients’ symptoms. 
Methods:
The OPTION survey was created in partnership with a panel of 10 active THA/TKA patients and 10 arthroplasty surgeons using a modified Delphi methodology that employed three sequential meetings with each group. It interrogates patient-reported pain VAS, activity limitation, duration of treatment, prior treatments, quality of life (QOL), treatment priorities, patient readiness for surgery, and xray changes. As an IRB- approved pilot, OPTION criteria surveys were completed during 643 patient-surgeon encounters discussing TKA/THA candidacy at 15 clinical sites in the US. Each OPTION survey was independently and anonymously completed by the patient before the encounter and verified by the surgeon after the encounter. 
Results:
Within each domain, there was disagreement in patient and surgeon response in less than 10% of cases. With questions of pain VAS, activity limitation, and QOL, where surgeon and patient responses differed, the surgeon most often understated the patient’s reported subjective experience. Higher patient prioritization of pain relief, minimizing activity limitation, and avoiding medications directly correlated with readiness for surgery. Avoiding high cost was consistently the lowest patient priority across groups; cost prioritization dropped most substantially once QOL was impacted. Surgeon-graded radiographic joint space narrowing correlated with patient-reported QOL impact and readiness for surgery. While early joint space loss was seen with mild activity limitation and pain, a ceiling effect was evident with respect to joint space narrowing as pain and activity limitation increased. 
Conclusion:
- When patient and surgeon disagree, surgeons tend to underestimate the patient- reported experience of arthritis. 
- Patient priorities in arthritis treatment vary depending upon the individualized functional impact of various factors on their personal experience. 
- Radiographic joint space narrowing does not reflect the full picture of the patient experience with arthritis. 


AMA Research Challenge 2023

Incorporating Patient Preferences into the Science of Shared Decision-Making for Discretionary Surgery: Understanding Surgeon and Patient Perspectives Regarding When it is Time for Elective Total Hip or Knee Replacement

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Background: The impact of socioeconomic status (SES) on health outcomes is an increasingly important topic. Identifying which patients are more likely to present with advanced musculoskeletal pathology is a top priority. The Area Deprivation Index (ADI) ranks neighborhoods across the United States based on socioeconomic disadvantage. The Childhood Opportunity Index 2.0 (COI 2.0) measures community resources and ranks neighborhoods according to the social determinants of health. Our study aimed to determine the relationship between scoliosis curve magnitude at presentation and SES as measured by the ADI and COI 2.0.

Methods: We retrospectively identified 1,649 patients presenting for adolescent idiopathic scoliosis at a single academic center between June 27, 2018 and June 6, 2023. The patients were divided into a non-surgical and surgical cohort with 1,510 and 139 patients, respectively. Curve magnitude at initial presentation (Cobb angle), BMI, and address were recorded using the electronic health record. Patients’ addresses were used to determine their ADI and COI 2.0 scores. The information was assessed using univariate analysis.

Results: Patients in the surgical cohort were more likely to have a higher ADI National Percentile, higher ADI State Decile, higher BMI, and greater Cobb angle at presentation compared to the non-surgical cohort (p = <0.05). Within the surgical cohort, patients with a higher BMI were more likely to have a greater Cobb angle at initial presentation (p = <0.05). Within the non-surgical cohort, patients with a Cobb angle >45 were more likely to have a higher ADI State Decile and live in neighborhoods with a higher poverty rate compared to patients with a curve <45 (p = <0.05). Within the non-surgical cohort, patients with a Cobb angle >45 were more likely to live near hazardous waste dump sites compared to patients with a curve <45 (p = <0.05).

Conclusion: There are significant associations between SES and scoliosis curve magnitude at presentation. Patients that have undergone surgery are more likely to be socioeconomically disadvantaged at a state and national level, according to the ADI. Non-surgical patients with a greater amount of socioeconomic disadvantage at the state level, those who live in neighborhoods with higher poverty rates, and those with greater environmental pollutant exposure are more likely to present with a Cobb angle that exceeds bracing indications (>45). More work must be done on a state and national level to identify, treat, and educate socioeconomically disadvantaged patients before their curve magnitude exceeds non-operative management.

The Impact of Socioeconomic Status on the Magnitude of Scoliosis Curve at Initial Presentation

Patient-reported outcomes (PROs) are increasingly recognized as a valuable data source that captures a patient’s experience of their disease, yet routine clinical PRO collection is still uncommon. We sought to understand the barriers and facilitators to sustainable PRO collection in an outpatient musculoskeletal practice. We performed a formal root-cause analysis and separated identified issues into three categories: technical, process, and human. We developed a multipronged intervention to target root causes. Qualitative feedback from patients and staff suggested that these changes resulted in more streamlined workflows and increased satisfaction.

Optimizing patient-reported outcome collection in a musculoskeletal outpatient clinic setting

Background

The Resource-Based Relative Value Scale (RBRVS) is utilized by the Centers for Medicare & Medicaid Services (CMS) and private payers alike to determine fee for service physician reimbursement. RVUs incorporate clinical and nonclinical resources, expertise required, and physician effort. Studies have demonstrated durable differences in RVUs for lumbar fusion instrumentation, but there has been no study on RVU reimbursement in cervical spine fusion. This study aims to compare mean work RVUs (wRVUs), mean operative time (OpTime), and wRVUs/min in single and multi-level anterior (ACDF) and posterior (PCDF) cervical decompression and fusions performed between 2011 and 2020.
Methods

The American College of Surgeons National Surgical Quality Improvement Program (NSQIP) was queried for Current Procedural Terminology (CPT) codes. CPT code 22551 reflects a primary ACDF level and subsequent 22552 codes correspond to additional levels while 22600 reflects a primary PCDF level and subsequent 22614 codes correspond to additional levels. The cohort was stratified into 5 groups: single-level, 2-level, 3-level, 4-level, and 5+ level anterior and posterior cervical fusions. Mean operative times, mean wRVUs, and wRVU/min were calculated and compared by the heteroscedastic student’s t-test.
Results



100,997 patients who underwent cervical fusion met the criteria for inclusion in this study in the following cohorts, with the vast majority receiving 1 and 2 level fusions. In single-, 3-level, 4- level, and 5+ level fusion, the anterior approach demonstrated significantly lower mean wRVU (p<0.001). Interestingly, an anterior approach demonstrated higher mean RVU for a 2-level fusion (67.76 ± 14.72 vs 65.98 ± 23.02, p<0.0001) over the study period. In single-, 2-, 3-, and 4-level fusion the anterior approach had significantly lower OpTime (all p<0.001). The anterior
approach also demonstrated significantly higher wRVU/min in single- and 2-levels (p<0.001) but lower wRVU/min in 3- and 4-level fusions ( p<0.001). No differences were seen in OpTime or wRVU/min between anterior and posterior approach for 5+ level fusions (p>0.05).
Conclusion

For single through 4 level fusions, anterior approach demonstrated lower OpTime and higher wRVU/min for single and 2-level fusions. As the number of fusion levels increased to 3- and 4- levels, wRVU/min was higher for posterior approaches. At 5+ levels, these returns became indistinguishable. These results may guide individual practices as spine surgeons aim to optimize surgical quality and outcomes as health services reimbursement shifts toward value based bundled reimbursements.

Comparison of Relative Value Unit (RVU) reimbursement anterior or posterior cervical spinal fusion

Introduction/purpose: 
Increased access to the internet and subsequent utilization of online health education materials by patients have established a demand for formal appraisal of such resources. The aim of this study was to evaluate the quality, credibility, and readability of web-based information related to turbinoplasty.

Methods: 
Search terms including “turbinoplasty nasal surgery”, “turbinate reduction”, “turbinate surgery”, and “nasal conchae surgery” were used to perform a search on Google.com, Bing.com, and Yahoo.com. Within each search term used, the top 30 results from Google.com were assessed, while the top 10 and top 5 results were assessed from Bing.com and Yahoo.com, respectively. The webpages were separated by authorship classification into six distinct groups: academic, commercial, governmental agency, health information platform, professional society, or other. To assess web page readability, the Flesch-Kincaid grade level, Gunning-Fog Index, SMOG Index, and Coleman-Liau Index were utilized. Webpage quality was computed through the DISCERN Instrument (DISCERN), the Journal of the American Medical Association benchmark criteria (JAMA), Novel Turbinoplasty Index (NTI) and presence of code certification by Health on The Net (HON).

Results: 
A final count of 71 unduplicated text-based web pages were appraised. Information quality was measured by an average DISCERN score of 47.4±7.40, indicating “fair” quality according to the scoring bands. The average readability was 9.7±1.57, notably higher than both grade level readability recommendations from either the American Medical Association (AMA) or National Institutes of Health (NIH). Of all web pages, only 11 (15.49%) proficiently met all four listed JAMA criteria. Significant correlations between web page classification and average DISCERN (p = 0. 0042) as well as JAMA score (p < 0.001) were discovered. The web pages that had HON code certification revealed significantly higher quality metrics with higher DISCERN scores (p < 0.001), JAMA scores (p < 0.001) and NTI scores (p = 0.038).

Conclusion:
Online health information associated with turbinoplasty has a considerably “fair” quality, while the average readability is several grade levels above the current AMA and NIH recommendations. Healthcare professionals should be encouraged to instruct their patients on proper search techniques for high-quality health resources on the web, as well as provide these materials in a physical written format when appropriate. We also recommend that health-based web pages amend their published information in a manner which can more effectively reach their intended consumers without sacrificing quality.

Quality and Readability Analysis of Turbinoplasty on the Web

Objective
To develop an evaluation clinic for toddlers suspected of having autism spectrum disorder (ASD) that improves the efficiency of the evaluation process and care coordination for those diagnosed with ASD. 

Purpose
While most children in the U.S. (85%) identified with ASD had documented caregiver concerns about their development by 3 years of age, less than half received an evaluation before their 3rd birthday.1 In addition, after receiving a diagnosis of ASD, many families struggle to connect with the recommended services and caregiver understanding of common features of ASD can be limited. MIND Institute staff recognized the need to develop a streamlined process to evaluate young children referred for ASD and assist families with navigating services. 

Methods
Children ages 15 to 42 months at time of referral for concern of ASD were triaged to the clinic. A licensed clinical social worker (LCSW) completed a telephone intake with families prior to the evaluation to explain the nature of the clinic and complete a structured interview inquiring about developmental milestones and behaviors concerning for ASD. The in-person evaluation consisted of an Autism Diagnostic Observation Schedule 2nd Edition, and the Bayley Scales of Infant and Toddler Development 4th Edition (BSID-4) cognitive subtest or the Differential Ability Scales 2nd Edition (DAS-II). The BSID-4 and DAS-II were not completed if either developmental assessment was recently completed and documented in the electronic health record. If the patient was diagnosed with ASD, caregivers met with a LCSW to discuss next steps in service coordination and were referred to the UC Davis MIND Institute Caregiver Coaching and Family Navigator programs.

Results
Since the clinic started in August 2022, 29 children ages 19 to 49 months (23 M, 6 F) have received an ASD evaluation. One appointment was rescheduled, and none were canceled. The average time from referral to evaluation was 5 months. Twenty-five children (86%) were diagnosed with ASD; 16 (64%) of these families were referred to the Family Navigator program. Twenty-one of the 29 families were insurance eligible for the Caregiver Coaching program; of those, 4 (19%) have been enrolled and 12 (57%) are pending enrollment. 

Conclusion 
Preliminary data suggests that structured intakes completed by a LCSW prior to and service coordination after an initial ASD evaluation can improve clinic show rates and engagement in services. 


A Clinic Model for Evaluation and Care Coordination for Toddlers Suspected of Having Autism

Background: To assess school-aged children’s wellbeing and to characterize changes in school-related needs from 2021 to 2022.
Methods: We surveyed a nationally representative sample of parents of children enrolled in grades K-12 in the 2021-2022 academic year in June 2021 and again one year later (June 2022). Parents completed the Strengths and Difficulties Questionnaire (SDQ) and reported their child’s general health and needs for school-related services. Weighted regressions examined associations among wellbeing, needs, and socio-demographic characteristics.
Results: 1,504 participants completed baseline and 1,199 completed follow up surveys. The percentage of children with deficits in total difficulties, hyperactivity, and prosocial behavior decreased from baseline to follow up, but a high percentage of children continued to have peer problems. Parents reported receiving support from their school for 45.3% of needs during the 2021-2022 school-year but 72.5% of parents continued to have at least one school-related need. Highest priority needs were academic enrichment, socialization, physical activity, tutoring, and coping with stress.
Implications for School Health Policy, Practice, and Equity: While many children with school-related needs received school support, a large percentage continue to have unmet needs and experience peer-related problems.
Conclusions: Continued investment in school-based services is necessary to support child health.

Changes in School-Age Children’s Wellbeing and School-Related Needs during the COVID-19 Pandemic

Background: The Adverse Childhood Experiences (ACEs) questionnaire is a widely used screener for pediatric trauma exposure and general household dysfunction. On a population level, ACEs are cumulative risk factors for a range of mental health and physical conditions. ACEs research has been largely based on self-reported ACEs exposures and health conditions, anthropometric measures, and biomarkers. In contrast, data mined directly from the electronic health record (EHR) allows for more objective analysis and reduces potential harms and limitations of self-report. The objectives of this pilot were to generate and test an algorithm for deriving Proxy ACEs values from existing EHR data, and to study the population-level association between derived Proxy ACEs, medical morbidity, and healthcare utilization. 

Methods: Proxy ACE scores were derived from structured EHR data including diagnoses, chief complaints, and social and family history sections. Medical morbidity was operationalized using the total number of medical diagnoses and prescribed medications, while healthcare utilization was represented by the number of emergency room visits, number of hospitalizations, and total hospital length of stay. We generated a dataset of 142,719 patients <18 years old who received care at Yale, spot-checked the derivation algorithm, and iterated modifications to obtain their final Proxy ACE scores. 

Results: Proxy ACE scores were positively correlated with all medical morbidity and healthcare utilization outcome variables at a significance level of P<0.01, with the strongest associations for number of medical diagnoses (r=0.30), number of prescribed medications (r=0.19), and number of emergency room visits (r=0.17). After accounting for outliers using Cook’s d and applying hierarchical multiple regression, Proxy ACE scores predicted an additional 9.2% of the variability in number of medical diagnoses after controlling for age, sex, race, and ethnicity (β=.31). 

Conclusion: Our findings are proof of concept that Proxy ACEs scores can be meaningfully derived from the EHR. Future directions include incorporating natural language processing methodology to account for unstructured data stored in the EHR and creating and validating an individual-level multivariable predictive model using our Proxy ACEs dataset.

Harnessing electronic health record data to examine the association between adverse childhood experiences, medical morbidity, and healthcare utilization

Background: Depression is a public health concern affecting the well-being and development of adolescents. Despite evidence-based guidelines promoting routine depression screening, many youths remain unidentified and untreated. Quality improvement (QI) initiatives may enhance depression screening practices. This retrospective chart review assesses a QI initiative's impact on depression screening rates among 12 to 18-year-old patients at four pediatric clinics in urban Nebraska from 2018 to 2022. The study evaluates trends in positive depression screens and the effectiveness of targeted interventions to increase adolescent depression screening. 
Methods: Electronic health record data was used to calculate adolescent depression screening rates and the percentage of positive depression screens. The screening rate equaled the total number of completed adolescent depression screens divided by the total number of well child exams for 12 through 18-year-old patients. The percentage of positive depression screens was the percentage of all adolescents who were screened and were positive on the Patient Health Questionnaire-4 (PHQ-4). The QI initiative comprised a “Lunch and Learn" session to raise provider awareness about the importance of depression screening. Additional interventions involved creating supportive materials for managing positive screenings, integrating depression screening into well-child exam rooming, and posting educational materials in the clinic's computer system for easy access by patients and providers. The impact of the initiative on depression screening rates was analyzed annually over five years. 
Results: The data revealed variations in depression screening rates and stability in the percentage of positive depression screens over the five-year study period. In 2018, the screening rate at well- child exams was 25.9%, with 8.1% of patients positive for depression. In 2019, the screening rate decreased to 21.6%, while the percentage of positive screenings increased to 13.1%. Following the initiation and continuation of the QI initiative in 2019, screening rates notably increased, reaching 37.2% with 11.7% positive patients in 2020. Screening rates further improved to 48.4% and 88.6% in 2021 and 2022, respectively, while the percentage of positive screenings remained relatively stable at 11.2% and 10.1%. 
Conclusion: The QI initiative positively impacted depression screening rates among adolescent patients at the four pediatric clinics, empowering healthcare providers to recognize and support adolescents facing depression. Continuous screening practice improvement efforts are crucial for early identification and intervention. The initiative offers a promising approach to enhance adolescent mental health care. 


Impact of Targeted Interventions on Depression Screening Rates among Adolescent Patients: A Retrospective Chart Review

Background
Pediatric hypertension is underrecognized, affecting 4% of adolescents in the USA with an additional 10% having elevated BP. Disparities exist among racial/ethnic groups. The global aim of this initiative is to improve recognition of elevated BP and hypertension and eliminate disparities in adolescents at the three NYU Langone Hospital Long Island primary care ambulatory sites.

Methods
Data between 2019-2021 was analyzed to determine prevalence and distribution of elevated BP and hypertension in patients >13 years by sex, race/ethnicity, and preferred language. Continuous variables were compared using Wilcoxon rank-sum test, and Chi-square/Fisher’s exact tests utilized for categorical variables. SAS v9.4 was used with statistical significance if p-value <0.05.

An interprofessional QI team was chartered to standardize BP measurement and improve recognition/management of adolescent hypertension. QI measures included percentage of appropriate documentation of elevated BP and hypertension in the care plan, timely primary care follow-up, and appropriate nephrology referral. Random sampling of 10-15 adolescents/month per site with elevated BP were reviewed. Data for 6 months was utilized for baseline QI measures. Our SMART aim is to increase recognition and appropriate follow-up by 25% from baseline across all sites in twelve months. Key driver diagram was constructed, and change ideas implemented using PDSA cycles. Interventions included multi-modal education and site visits to standardize BP measurement. BP reference and management algorithm handouts were distributed. Data were analyzed quarterly and plotted using run charts.

Results
Retrospective data from 2019-2021 (n=6158) showed 32% prevalence of elevated BP and hypertension in our cohort, 66.3% of which were male. Race/ethnicity distribution of adolescents with elevated BP and hypertension were 37.1% Black, 31.9% Hispanic, 31.7% White, and 27.7% Asian. Distribution by preferred language revealed 33.1% Spanish and 32.1% English (remainder other).

Appropriate documentation of elevated BP and hypertension in the care plan improved by 4.5 % (from 2% to 6.5%). Inter-site comparison revealed site-site variations, with the largest improvement of 11% at our Patient-Centered Medical Home. Twelve-month baseline for timely primary care follow-up and appropriate nephrology referral were 7% and 13%, respectively. 

Conclusion
The prevalence of elevated BP was higher in our cohort, potentially due to variations in BP measurement, and was targeted by our interventions. We achieved our SMART aim of increased recognition and documentation of adolescents with elevated BP and hypertension through standardization of BP measurement and provider education. Our next step is to target timely primary care follow-up and appropriate nephrology referral. An additional goal is to identify and reduce disparities across race, ethnicity, and preferred language for recognition and management of adolescent hypertension.

Measurement of Ambulatory Blood Pressure (BP) Standardization (MAPS) in Adolescents: A Quality Improvement (QI) Initiative

Background: Predicting the discharge destination, otherwise known as discharge disposition, can offer several advantages for the inpatient rehabilitation patient, including treatment and discharge planning. Machine learning (ML) models have demonstrated a strong predictive capacity for discharge disposition, particularly for patients with specific diagnoses such as traumatic brain injuries, or in specific settings such as acute neurologic care, or among specific populations. 



Objective: Explore various ML models’ ability to predict inpatient rehabilitation discharge disposition to home versus non-home using patient encounter data. 



Methods: Patient data included demographics, diagnoses, lab values, length of stay, and insurance status from all inpatient rehabilitation encounters at a large midwestern health system occurring between 2015 and 2022 (N=4919). We compared two commonly used ML approaches: a random forest (RF) classifier and a decision tree (DT) classifier. Two bagging classifiers, which aggregate the results of multiple RF or DT classifiers to improve predictions, were also tested. Because the imbalance in number between home (N=3687) and non-home discharges (N=1232) can impair predictions, balancing techniques were used prior to training the ML classifiers. The ML classifiers were then optimized with grid search and cross validation. Performance of the ML classifiers was determined by the receiver operating characteristic area under the curve (AUC) – a measure of the ability to discriminate the true discharge disposition, accuracy (computed using the Jaccard Index), and macro f1-score (indicative of classification ability across classes). 



Results: 

A bagging classifier using RF showed highest predictive performance in terms of AUC (0.68) and accuracy (0.75), however it struggled to predict non-home discharges (macro f1-score = 0.54). A bagging DT classifier improved prediction of non-home discharges (macro f1-score = 0.59), however AUC (0.65) and accuracy (0.69) were lower. Generally, bagging classifiers combining the predictions from multiple RF or DT classifiers improved predictive performance compared to single RF or DT classifiers. 



Conclusions: As artificial intelligence and ML continue to grow in healthcare applications, this study showcased the effectiveness of ML approaches to predict discharge disposition from inpatient rehabilitation. Our findings complement previous studies in other diagnoses and settings, due to our diversity of available variables and differences in our patient population and treatment paradigms. Of note, utilization of bagging classifiers proved valuable in enhancing the performance of the tested base classifiers. Our results may help guide optimization of ML approaches to predict discharge disposition, in hopes of improving patients' hospital courses and post-hospital planning and treatment.

Next from AMA Research Challenge 2023

The Impact of Socioeconomic Status on the Magnitude of Scoliosis Curve at Initial Presentation