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BACKGROUND: Comprehensive computerized gait analysis (CGA) alters orthopedic surgical plans and improves outcomes. Despite these documented benefits, CGA is not widely available to all patients who could be helped by it.
OBJECTIVE: Do social determinants of health impact access to CGA?
METHODS: Retrospective review of patients seen for CGA from 2021 to 2022. Dates of referral, insurance approval and completion of CGA, demographics and insurance type were extracted from patient records. Zip codes were used to determine the neighborhood socioeconomic status (SES). Data were analyzed using non-parametric statistics.
RESULTS: Insurance type affected time to authorization (private insurance/self-pay: median 9 days; HMO insurance: median 51.5 days; public insurance: median 27 days; p=0.0004). Once authorized, insurance type did not affect time to schedule and complete CGA (p=0.76). Lower neighborhood SES was associated with longer time to authorization but shorter time to complete CGA once authorized. Rescheduling was associated with longer time to complete CGA once authorized (median 29.5 vs. 16 days, p<0.0001). White, non-Hispanic families tended to reschedule more often than non-white or Hispanic families (35 % vs. 18 %, p=0.07).
CONCLUSIONS: Knowledge of barriers to CGA is necessary in order to design and implement effective strategies to widen its availability to all whom it could benefit. Social determinants of health and insurance type are associated with delays in authorization for CGA. Families with public insurance and HMO coverage experience delays in obtaining insurance authorization compared to PPO/self-pay patients, whose tests did not require prior authorization. However, there can also be delays in scheduling and completing CGA once authorized. This is a multi-faceted issue that requires further research.

The Philippines is a source of labor for many countries. Roughly 10 million overseas Filipinos are working and living outside of the Philippines. This paper examines the association between sociodemographic characteristics (sex, age, educational level, and income) and self-rated physical and mental health, access to healthcare, and health habits among immigrant Filipinos living in Santa Cruz de Tenerife, Spain. Through convenience sampling, Filipino migrants (n = 103) aged 18 years and above participated in the online survey between October 2022 and March 2023. The data were analyzed using descriptive statistical analysis and chi-square. Almost all respondents self-rated their health as excellent and very good. Female respondents are more affected by mental health. Most are enrolled in the Universal Health System of Spain (public insurance). There is more utilization of private health insurance among respondents aged 60 years and above and high-wage earners. Cigarette smoking and alcohol drinking are associated with males. More than half of the respondents perform weekly exercise occasionally or never. These findings suggest a potential need for targeted interventions with an emphasis on the practice of preventive health and the promotion of healthy lifestyles, especially among financially disadvantaged migrants with lesser health access.

The main aim of this research is to present an innovative method known as fuzzy network data envelopment analysis (FNDEA) in order to assess the performance of network decision-making units (DMUs) that possess a two-stage structure while taking into account the uncertainty of data. To attain this goal, we utilize various methodologies including the non-cooperative game (leader-follower) NDEA method, the concept of Z-number, credibility theory, and chance-constrained programming (CCP) to develop a model for the fuzzy NDEA approach. The FNDEA approach offers several advantages, such as the linearity of the presented FNDEA models, the ability to rank two-stage DMUs in situations of ambiguity, the provision of a unique efficiency decomposition method in an uncertain environment, and the capability to handle Z-information. To demonstrate the applicability and effectiveness of the proposed approach, we implement the Z-number network data envelopment analysis (ZNDEA) approach in assessing the performance of Iranian private insurance companies. The results of this implementation reveal that the proposed ZNDEA method is suitable and effective for measuring and ranking insurance companies in situations where data ambiguity is present.

BACKGROUND: Depression significantly impacts the quality of life and medical care in patients with coronary heart disease (CHD). This study assesses the burden of depression in adults aged 40 years and above with CHD and evaluates predictors of depression in this population. It has been reported that approximately 17-44% of persons with CHD have a major depression diagnosis and that nearly 27% of individuals undergoing coronary artery bypass graft operation suffer depression following the procedure.  Methods: Data from the 2022 National Health Interview Survey was used. The sample was made up of adults 40 years and above with CHD. A chi-square analysis was used to identify differences between those who were depressed and those who were not. Logistic and ordinal regression analyses were used to identify predictors of depression and severe depression, respectively.
RESULTS: The proportion of adults 40 years and above with CHD who reported having depression was 863/1700 (50.5%). Among those who were ≥65, the proportion of those who reported depression and those who did not were similar (49.3% vs. 50.7%). Most women reported having depression (57.4% vs. 42.6%), while fewer men reported having depression (46.3% vs. 53.7%). The positive predictors of depression include being insured (odds ratio (OR) 1.26 (1.05-1.53), p = 0.016), college degree (OR 1.09 (1.01-1.18), p = 0.040), diabetes mellitus (OR 1.28 (1.15-1.42), p < 0.001), and hypertension (OR 1.34 (1.24-1.44), p < 0.001). The negative predictors of being depressed were age ≥65 (OR 0.74 (0.69-0.80), p < 0.001), male sex (OR 0.54 (0.50-0.58), p < 0.001), and ratio of family income (RFI) ≥1 (OR 0.68 (0.61-0.77), p < 0.001). The positive predictors of severe depression include diabetes mellitus (OR 1.38 (1.06-1.81), p = 0.019) and current cigarette use (OR 2.10 (1.44-3.07), p < 0.001).
CONCLUSIONS: A significant proportion of adults 40 years and above with CHD have depression, and socioeconomic and cardiovascular risk factors are associated with a high likelihood of depression. Cardiovascular risk factors alone predict the likelihood of severe depression. Interventions to address depression in CHD should target specifically these high-risk individuals.

BACKGROUND: Insurance companies often mandate six weeks of physical therapy (PT) prior to approving MRIs for patients with atraumatic rotator cuff (RTC) tears. While this is designed to limit unnecessary imaging orders, it can increase healthcare costs and delay diagnosis and surgery. This study investigated the incidence of full- and partial-thickness tears when an MRI was ordered at the time of initial consultation for shoulder pain by an orthopedic provider.
METHODS: A retrospective review of patients who had an MRI ordered upon initial orthopedic consultation for chronic shoulder pain was conducted. The primary outcome measured was the presence of RTC tears as determined by the MRI report. The cost of six weeks of PT versus the cost of immediate MRI in these patients was collected from our institution\'s financial database. ANOVA, independent T-test, and chi-square test were used to analyze the differences between groups.
RESULTS: A total of 365 patients were included. There were no significant differences in demographics between patients with full, partial, or no tears, with the exception that patients with full-thickness tears were older. Specifically, 43.0% had a full-thickness tear, 24.7% had a partial-thickness tear, and 32.2% had no tear on MRI. A total of 56.1% of the full-thickness tears proceeded to surgery. The cost of an upper extremity MRI without contrast averages $2,268, while two sessions of PT per week for six weeks totals $2,328.
CONCLUSIONS: Over 67% of MRI orders yielded a positive finding of an RTC tear and remained at 67.2% in the absence of a history of conservative treatment, validating a specialist\'s clinical suspicion for an RTC tear and indication for MRI. Pre-MRI PT to satisfy insurance requirements may therefore delay intervention and increase healthcare costs when an orthopedic provider believes an MRI is warranted for clinical decision-making.

UNASSIGNED: The use of point-of-care (POC) tests prior to the COVID-19 pandemic was relatively infrequent outside of the health care context. Little is known about how public opinions regarding POC tests have changed during the pandemic.
UNASSIGNED: We redeployed a validated survey to uncompensated volunteers to assess preferences for point-of-care testing (POCT) benefits and concerns between June and September 2022. We received a total of 292 completed surveys. Linear regression analysis was used to compare differences in survey average response scores (ARSs) from 2020 to 2022.
UNASSIGNED: Respondent ARSs indicated agreement for all 16 POCT benefits in 2022. Of 14 POCT concerns, there were only 2 statements that respondents agreed with most frequently, which were that \"Insurance might not cover the costs of the POC test\" (ARS 0.9, ± 1.0) and \"POC tests might not provide a definitive result\" (ARS 0.1, ± 1.0). Additionally, when comparing survey responses from 2020 to 2022, we observed 8 significant trends for POCT harms and benefits.
UNASSIGNED: The public\'s opinion on POC tests has become more favorable over time. However, concerns regarding the affordability and reliability of POCT results persist. We suggest that stakeholders address these concerns by developing accurate POC tests that continue to improve care and facilitate access to health care for all.

Fraudulent activities especially in auto insurance and credit card transactions impose significant financial losses on businesses and individuals. To overcome this issue, we propose a novel approach for fraud detection, combining convolutional neural networks (CNNs) with support vector machine (SVM), k nearest neighbor (KNN), naive Bayes (NB), and decision tree (DT) algorithms. The core of this methodology lies in utilizing the deep features extracted from the CNNs as inputs to various machine learning models, thus significantly contributing to the enhancement of fraud detection accuracy and efficiency. Our results demonstrate superior performance compared to previous studies, highlighting our model\'s potential for widespread adoption in combating fraudulent activities.

OBJECTIVE:  This study aims to investigate the association between malnutrition using the global consensus criteria and food texture levels in residents of Integrated Facilities for Medical and Long-Term Care (IFMLCs), which are new long-term care insurance facilities in Japan.
METHODS: This single-center study had a retrospective cross-sectional design. The study was conducted from November 1 to 30, 2021, and the study participants were residents admitted to an IFMLC during the study period. Malnutrition was diagnosed according to the Global Leadership Initiative on Malnutrition (GLIM) criteria. Food texture levels consumed by patients at admission were categorized based on the International Dysphagia Diet Standardization Initiative (IDDSI) framework. Multivariate logistic regression models were used to determine the association between the food texture levels consumed and malnutrition.
RESULTS: A total of 98 older residents were analyzed in this study. The median age of the participants was 88 years, and 68 (69%) female participants were included. The IDDSI framework levels were 24% in levels 7 and 6 and 26% in levels 5 and 4. A significant difference in the prevalence of low BMI, reduced muscle mass, and reduced food intake or assimilation was noted between IDDSI framework levels 4 and 7. Multivariate logistic regression analysis was performed for malnutrition, adjusting simultaneously for potential confounders. IDDSI level 4 (odds ratio, 5.074; 95% confidence interval, 1.059-28.092; p=0.042) consumption was independently associated with malnutrition.
CONCLUSIONS: The consumption of lower food texture levels categorized using the IDDSI framework was associated with a higher malnutrition prevalence in IFMLC residents.

The authors provide a brief overview for thoracic surgeons in topics essential to achieving financial well-being as a student, trainee, practicing surgeon, and beyond. While broad in nature, the authors\' article is comprehensive, and they cover topics including student loans, asset and wealth management, investment opportunities, financial and estate planning, and insurances. It is hoped that the information provided will allow thoracic surgeons to become more familiar with the financial topics that pertain to thoracic surgeons and provide an introduction to explore financial wellness and literacy more thoroughly.