Category: Statistics

Leadersh Health Serv (Bradf Engl). 2025 Jun 26. doi: 10.1108/LHS-01-2025-0013. Online ahead of print.

ABSTRACT

PURPOSE: Middle managers play a crucial role in health care, as they are responsible for executing decisions made by upper management and supervising frontline staff. Enhancing their ability to implement these decisions is essential for effective health-care delivery. The purpose of this case study is to describe a leadership development program was designed to improve employee engagement scores among health-care middle managers. The program used employee engagement survey data, experiential learning, reflection and coaching.

DESIGN/METHODOLOGY/APPROACH: The authors analyzed annual employee engagement survey data to develop a series of leadership training sessions for health-care middle managers. Three leadership development series were conducted, each featuring diverse experiential learning methods facilitated by subject matter experts. Participants’ feedback was collected through open-ended surveys at the end of each series, focusing on key outcomes such as their understanding and application of leadership concepts. Descriptive statistics were used to summarize the results from the annual 2021 and 2022 engagement surveys.

FINDINGS: A total of 45 middle managers with various middle management roles and from different backgrounds (clinical and non-clinical) reported significant improvements in their engagement scores, with the overall score increasing from 80.02 to 81.98 (p = 0.045). Participants also reported improved team trust, valuing employee input and enhanced leadership effectiveness.

RESEARCH LIMITATIONS/IMPLICATIONS: This study’s limitations include that this study took place at a not-for-profit health-care system during the COVID-19 pandemic (2021-2022) and that not all participants’ demographic information was collected.

PRACTICAL IMPLICATIONS: Structured, data-driven leadership development programs can enhance middle managers’ skills, engagement and satisfaction in health-care organizations.

ORIGINALITY/VALUE: This case study used employee engagement survey data to design a leadership development program for middle managers in health care, a group often overlooked in traditional leadership development programs.

PMID:40553469 | DOI:10.1108/LHS-01-2025-0013

Med Decis Making. 2025 Jun 24:272989X251346844. doi: 10.1177/0272989X251346844. Online ahead of print.

ABSTRACT

IntroductionHospitals are interested in improving the quality of data disaggregation and collection to advance diversity, equity, and inclusion (DEI) goals. We evaluated the extent to which hospitals are adopting DEI disaggregated data to inform organizational decisions and the characteristics associated with this adoption.MethodsWe analyzed data from the 2022 American Hospital Association Annual Survey, which included the final iteration of a new survey item about hospital DEI disaggregated data adoption for decision making. Descriptive statistics, logistic regression, and negative binomial regression were used to evaluate this survey item.ResultsAmong hospitals adopting DEI disaggregated data (n = 2,596, 41.9%), two-thirds used these data to inform decisions about patient outcomes, half about training or professional development, and one-third about supply chain or procurement. Larger, tax-exempt, Veteran Affairs, or metropolitan hospitals are significantly more likely to adopt DEI disaggregated data for decision making.LimitationsOur work is limited by the reporting of 1-y cross-sectional results.ConclusionsMost hospitals adopt DEI disaggregated data to inform decisions about patient outcomes. Future research should explore whether hospital decisions or disaggregated data adoption have advanced DEI and health equity for underserved communities.ImplicationsAnalysis of disaggregated data adoption could reveal how hospitals make decisions and funding allocations to advance DEI goals and health equity.HighlightsThere is a limited understanding of the extent to which hospitals adopt diversity, equity, and inclusion (DEI) disaggregated data to inform organizational decision making, highlighting a knowledge gap at the intersection of data equity and health care management.Among hospitals that adopt DEI disaggregated data, two-thirds use them to inform organizational decisions about patient outcomes, and half about professional development.Larger, tax-exempt, Veteran Affairs, or metropolitan hospitals are more likely to adopt DEI disaggregated data for organizational decision making.Future research is needed to explore whether hospital adoption of DEI disaggregated data has advanced DEI organizational goals and health equity for underserved populations.

PMID:40553449 | DOI:10.1177/0272989X251346844

Inquiry. 2025 Jan-Dec;62:469580251349652. doi: 10.1177/00469580251349652. Epub 2025 Jun 24.

ABSTRACT

Emergency department (ED) re-attendance among older adults is an increasing global concern, often reflecting gaps in chronic disease management, discharge planning, and continuity of care. This study aimed to determine the frequency of ED re-attendance and identify associated patient- and system-level factors. A cross-sectional analytical study was conducted between July 2023 and August 2024 across general and community hospitals. A total of 740 participants were selected using multi-stage sampling, comprising 400 older adult patients and 340 healthcare professionals. Data were collected from medical records and structured questionnaires. Descriptive statistics and multiple logistic regression were applied to identify factors linked to ED re-attendance within 60 days. Among older adults, 35% revisited the ED within 60 days post-discharge. Key factors significantly associated with re-attendance included prior ED visits (OR = 3.92; 95% CI: 2.11-7.31), hospitalization within the previous year (OR = 1.97; 95% CI: 1.15-3.38), no follow-up with specialists (OR = 2.27; 95% CI: 1.35-3.83), and treatment at M2-level hospitals (OR = 7.28; 95% CI: 3.62-14.64). Targeted strategies to improve discharge processes, ensure specialist follow-up, and enhance primary care coordination are essential to reduce potentially avoidable ED re-attendance among older adults.

PMID:40553440 | DOI:10.1177/00469580251349652

Target Oncol. 2025 Jun 24. doi: 10.1007/s11523-025-01158-0. Online ahead of print.

ABSTRACT

BACKGROUND: In the real-world POLARIS study, patients with hormone receptor-positive (HR⁺)/human epidermal growth factor receptor 2-negative (HER2^–) advanced/metastatic breast cancer (ABC) who had received palbociclib + endocrine therapy (ET) had a median real-world progression-free survival (rwPFS) of 20.9 months in the first line of therapy (1LOT) and 13.5 months in second or later LOTs (≥ 2LOT).

OBJECTIVE: The aim of this study is to assess the relationship of prior anticancer treatments with clinical outcomes.

PATIENTS AND METHODS: Kaplan-Meier estimates of rwPFS and overall survival (OS) are described by prior anticancer treatments in patients with HR⁺/HER2^– ABC who received palbociclib + ET.

RESULTS: A total of 1250 patients received ≥ 1 palbociclib dose (1LOT: 901 [72.1%]; ≥ 2LOT: 349 [27.9%]). In the 1LOT group, 563 (62.5%) had received prior (neo)adjuvant treatments: 24.3% ET alone, 26.6% chemotherapy alone, 45.5% ET + chemotherapy, and 3.6% other treatments; both median rwPFS and OS were numerically longer in patients who had received ET alone (30.4 months and not reached, respectively) and had had no prior treatment (23.7 and 53.3 months, respectively) than in patients with prior chemotherapy alone (15.9 and 38.4 months, respectively). In the ≥ 2LOT group, patients with prior ET alone (21.5%; 19.8 months) or chemotherapy alone (16.6%; 15.5 months) in the (neo)adjuvant and/or metastatic setting had numerically longer median rwPFS than those with prior ET + chemotherapy (41.3%; 11.6 months); OS was comparable regardless of prior treatment.

CONCLUSIONS: Patients with HR⁺/HER2^– ABC who had received ET alone prior to palbociclib tended to have better clinical outcomes, while those with prior chemotherapy had less clinical benefit.

TRIAL REGISTRATION: ClinicalTrials.gov, NCT03280303.

PMID:40553419 | DOI:10.1007/s11523-025-01158-0

Dig Dis Sci. 2025 Jun 24. doi: 10.1007/s10620-025-09123-7. Online ahead of print.

ABSTRACT

PURPOSE: Prophylactic endoscopic submucosal dissection (ESD) defect closure has been suggested to reduce delayed adverse events (DAE) associated with ESD but the data are limited. We aim to study the effect of prophylactic rectal ESD defect closure on post-ESD outcomes.

METHODS: An international multicenter retrospective cohort study was performed between 2016 and 2023 involving patients who underwent rectal ESD without intraprocedural perforations and had follow-up data available for at least 2 weeks post-ESD. Delayed adverse events (DAE) defined as bleeding and perforation within 2 weeks of ESD and post-procedure hospitalization or observation rates were compared between the two groups – ESD defects closed (closure group) and ESD defects open (open group).

RESULTS: A total of 385 patients were included. Complete closure of ESD defects was performed in 166 (43%) patients. DAE were observed in 21 (5.5%) patients. On logistic regression analysis, anticoagulant use, NICE3 lesions and incomplete resections had significantly higher rate of DAE. In these high-risk groups, defect closure had a numerically lower rate of DAE without statistical significance. While defect closure did not significantly reduce the rate of overall DAE (p = 0.16), there were no delayed perforations in the closure group compared to 3 (1.3%) in the open group. A significantly lower number of patients were kept for post-ESD overnight hospital observation in the closure group compared to the open group (17% v 37%, p < 0.01).

CONCLUSIONS: Prophylactic closure of rectal ESD defects leads to significantly less overnight hospital observation. Anticoagulant use, NICE 3 lesions and incomplete resections had significantly higher DAE within 2 weeks. While defect closure did not significantly reduce the overall DAE, selective prophylactic defect closure in high-risk groups will need to be studied in larger samples.

PMID:40553399 | DOI:10.1007/s10620-025-09123-7

Acta Neurol Belg. 2025 Jun 24. doi: 10.1007/s13760-025-02826-8. Online ahead of print.

ABSTRACT

BACKGROUND: Stigmatization in MS patients is an important problem that affects social interaction, work life and daily life. In this study, we investigated the prevalence, severity and especially the effects of stigmatization on work life in MS patients.

METHODS: A cross-sectional study of 420 people living with MS (PwMS) assessed stigma using the NeuroQoL Stigma Short Form and a direct stigma survey. Demographic, clinical, workplace, and social data were collected through an online survey. Statistical analyses were performed.

RESULTS: Stigma was prevalent, with 77% reporting stigma in direct surveys and 67.6% scoring > 8 on the NeuroQoL Stigma Short Form. Stigma was more severe in patients with progressive MS and higher EDSS scores. The most disturbing symptoms were fatigue (73.3%), imbalance (46.7%) and attention deficit 50.5%). The most prominent complaint affecting work life was fatigue (41.2%). Only 7.3% of the patients had sought psychological support for this issue. 57.4% of patients had disclosed their illness to their employer and 68.1% to their coworkers.

CONCLUSIONS: Stigma in MS is pervasive, linked to clinical severity, workplace challenges, and social withdrawal. Interventions targeting stigma’s psychological and social dimensions, along with workplace education and support are essential.

PMID:40553376 | DOI:10.1007/s13760-025-02826-8

Methods Mol Biol. 2025;2952:411-428. doi: 10.1007/978-1-0716-4690-8_22.

ABSTRACT

The integration of Artificial Intelligence (AI) with conventional biostatistics represents a pivotal advancement in healthcare research. The synergistic relationship between traditional biostatistical approaches and modern AI techniques highlights their complementary roles in advancing medical research and clinical practice. While conventional biostatistics provides robust frameworks for hypothesis testing, parameter estimation, and statistical inference, AI offers enhanced capabilities in pattern recognition, predictive modeling, and the analysis of complex, high-dimensional datasets. This chapter explores the fundamental concepts and the complementary strengths of these two paradigms, discussing their foundational principles, practical applications, critical challenges, and ethical considerations in clinical practice. Furthermore, we present emerging trends and future directions, focusing on explainable AI, hybrid modeling approaches, real-time data integration, and advances in precision medicine. The comprehensive analysis illuminates the convergence of AI and biostatistics is revolutionizing healthcare research while maintaining scientific rigor and statistical validity, ultimately paving the way for more sophisticated, efficient, and personalized healthcare solutions.

PMID:40553345 | DOI:10.1007/978-1-0716-4690-8_22

Methods Mol Biol. 2025;2952:283-295. doi: 10.1007/978-1-0716-4690-8_17.

ABSTRACT

The synergistic integration of Artificial Intelligence (AI) techniques with bioinformatics, statistics, and biotechnology has ushered in a transformative era in the realms of cell and genetic engineering. This convergence represents a powerful alliance, combining the computational prowess of AI with the wealth of biological information harnessed through bioinformatics and statistical methodologies. The collaborative impact of these disciplines has redefined our approach to understanding, manipulating, and optimizing complex biological systems. By leveraging advanced algorithms, machine learning models, and data analytics, researchers can navigate the intricate molecular landscapes with unprecedented precision. This chapter aims to dissect the multifaceted applications of AI within cell and genetic engineering, shedding light on its role in enhancing precision, efficiency, and innovation. The intricate dance between AI and biological data comes to life, showcasing how algorithms unravel genomic intricacies or predict protein structures. Formulas, grounded in statistical methodologies, underline the quantitative rigor AI brings to these fields. Accompanied by images, this exploration seeks to elucidate the tangible impact of AI on the biological sciences, offering readers a visual journey into the world where computational intelligence meets the intricacies of life at the molecular level.

PMID:40553340 | DOI:10.1007/978-1-0716-4690-8_17

Int Urol Nephrol. 2025 Jun 24. doi: 10.1007/s11255-025-04627-7. Online ahead of print.

ABSTRACT

PURPOSE: Holmium laser enucleation of the prostate (HoLEP) is an effective treatment for benign prostatic hyperplasia (BPH). This study aimed to assess the impact of catheterization duration on postoperative outcomes, focusing on re-catheterization rates and associated risk factors.

METHODS: A retrospective analysis was conducted on patients who underwent HoLEP at our institution (June 2022-August 2024). Starting in November 2023, we decided to attempt catheter removal the morning after the procedure unless contraindicated. Patients were categorized into two groups based on catheterization duration: > 1 day (Group A) and ≤ 1 day (Group B). Perioperative variables, functional outcomes, and re-catheterization rates were compared between the groups. Multivariable logistic regression models were used to identify independent predictors of re-catheterization.

RESULTS: 258 patients were analyzed. Baseline characteristics, including age, BMI, IPSS, Q_max, and PSA, were comparable between groups. Median prostate volume was larger in Group A (85 vs. 70.5 mL, p = 0.06) -though the difference bordered on statistical significance. Enucleation time was significantly longer in Group A (80 vs. 55 min, p < 0.001). Patients in Group A experienced higher re-catheterization rates (21.9 vs. 1.5%, p < 0.001) and longer hospitalization (2 vs. 1 day, p < 0.001). Multivariable analysis confirmed catheterization duration as the sole independent predictor of re-catheterization (p < 0.001). Factors such as prostate volume, post-void residual volume, and enucleation time were insignificant. Most re-catheterizations were due to urinary tract infections (16/30, 53%).

CONCLUSION: Early catheter removal after HoLEP is safe and effective, reducing re-catheterization risk without compromising outcomes. Early removal may also enhance postoperative recovery by minimizing infections.

PMID:40553309 | DOI:10.1007/s11255-025-04627-7

J Racial Ethn Health Disparities. 2025 Jun 24. doi: 10.1007/s40615-025-02463-0. Online ahead of print.

ABSTRACT

BACKGROUND: The built environment and food environment have been well documented as correlated factors of obesity, but literature has paid less attention to how these environments interact with racial and ethnic composition to affect obesity. This study examines the racial-ethnic context of obesity concerning the built environment and food environment in a racially segregated city, Chicago.

METHODS: The obesity data was sourced from the Healthy Chicago Survey, which gathered information through landline and cell phone interviews with adults aged 18 years or older. The built environment was measured by density, diversity, and design: the density was measured in 1000 residents per square mile within a community; the design of the built environment was measured by the intersection density; and the diversity was measured by the entropy index for land use mix. Spatial statistics were used to identify local clusters and outliers of built environments. We used the North American Industry Classification System codes to distinguish different types of food stores. We used ordinary least squares regression models to examine the effects of the built environment on the obesity rate and included interaction terms to investigate how the built environment interacts with racial composition to impact the obesity rate.

RESULTS: Our results show that population density had a positive association with obesity rates when the African American population percentage increased. Both intersection density and the land use mix were negatively associated with obesity rates. However, as the percentage of the African American population increased, the magnitude of the negative association between the intersection density and obesity rate decreased, while the magnitude of the negative association between the land use entropy index and obesity rate increased. Besides, built environments are more important than food environments in reducing the obesity rate, although grocery stores showed negative effects on obesity while restaurant establishments showed positive effects on obesity.

CONCLUSIONS: We provide suggestive evidence that improving urban planning and design to increase the intersection density and land use diversity might significantly reduce the obesity rate, although race was significant in the obesity rate, and the magnitudes of effects of intersection density and land use diversity on the obesity rate differed in African American communities. This evidence highlights the importance of considering demographic factors in designing and planning urban environments to promote public health. Race significantly influenced the obesity rate, with varying effects observed in African American communities. Our findings suggest that tailored urban planning strategies might be necessary to effectively address obesity in different populations.

PMID:40553299 | DOI:10.1007/s40615-025-02463-0