Risk Management and Healthcare Policy最新文献

Objective: This study aimed to develop a novel homologous sequence analysis technique using high-throughput sequencing data to enhance CYP21A2 mutation detection. The approach leverages next-generation sequencing to overcome existing limitations and improve 21-hydroxylase deficiency diagnostic accuracy.

Methods: From April 21, 2022, to February 21, 2023, a total of 100 unrelated participants were enrolled at the Women and Children's Hospital of Ningbo University, selected based on clinical manifestations and genetic testing results. The study used next-generation sequencing combined with a homologous sequence alignment (HSA) algorithm, which calculated the sequencing read ratios from homologous regions to identify pathogenic or likely pathogenic variants in the CYP21A2 gene. All detected variants were further validated using long-range PCR or multiplex ligation-dependent probe amplification. The accuracy of the HSA algorithm was systematically assessed.

Results: Among the 100 participants, 84 were identified as carriers of CYP21A2 mutations, while 16 were diagnosed with 21-hydroxylase deficiency. A total of 107 pathogenic mutations were detected using the homologous sequence alignment algorithm, comprising of 99 single nucleotide variants or insertions/deletions, 6 copy number variants, and 8 fusion mutations. Additionally, eight cases of CYP21A2-CYP21A1P gene conversions were identified based on HSA scores and confirmed through long-range PCR or multiplex ligation-dependent probe amplification. The algorithm demonstrated a positive predictive value of 96.26% for identifying mutations in CYP21A2. The most frequently observed mutations included c.955C > T, c.844G > T, c.293-13C > G, c.518T > A, and exon-level deletions.

Conclusion: In genetic testing, particularly when addressing misalignment challenges associated with highly homologous genes such as CYP21A2, application of the HSA algorithm enables accurate mutation detection using commonly employed short-read sequencing methods. Through the characterization of homologous sequence features and optimization of the HSA algorithm, accurate mutation detection can be achieved in more homologous gene families (eg, HBA1/HBA2, SMN1/SMN2, GBA/GBAP1).

Objective: To analyze the risk factors for postpartum hemorrhage in non-primary women giving birth naturally and construct a predictive model.

Methods: Retrospective analysis of the clinical data of 436 second-time mothers who underwent natural childbirth in the Department of Obstetrics, Hefei Third People's Hospital. The cases were divided into a bleeding group (n=41) and a non-bleeding group (n=395) based on whether there was bleeding greater than 500 mL within 24 hours after delivery. Independent risk factors were established through univariate and multivariate analyses, a logistic regression model was established, and bootstrap resampling was used to internally verify and assess the calibration of the model.

Results: Among the 436 cases of maternal delivery included in the study, 41 (9.40%) were cases of postpartum hemorrhage. The results of the multifactor analysis indicated that in vitro fertilization, body mass index (BMI), episiotomy, placenta previa, newborn weight, and manual removal of the placenta were independent risk factors for postpartum hemorrhage (PPH) in non-primary mothers. Subsequently, a model was constructed, exhibiting an AUC value of 0.839 (95% CI: 0.758-0.919). The Hosmer-Lemeshow test of the calibration curve yielded a chi-squared value of 8.1013 and a P-value of 0.4236, indicating an excellent performance of the DCA curve.

Conclusion: In vitro fertilization, body mass index (BMI), episiotomy, placenta previa, newborn weight, and manual removal of the placenta are identified as independent risk factors for postpartum hemorrhage (PPH) in non-primary mothers. The constructed logistic regression model is capable of more accurately identifying high-risk PPH mothers and providing a reference basis for individualized interventions.

Patient falls are a major concern in healthcare due to their impact on patient safety, prolonged hospital stays, and increased costs. Traditional fall prevention methods often lack precision and adaptability, emphasizing the need for predictive approaches. This study reviews the current literature and explores the integration of human-centered artificial intelligence (AI)-based decision support systems to improve fall prevention through proactive risk assessment and prediction. This system enables early identification of fall risks, facilitating personalized interventions and real-time monitoring via advanced sensors and wearable devices. These technologies may provide timely alerts to caregivers and support administrators in optimizing resource allocation. Additionally, this study highlights the importance of systems thinking, recognizing patient falls as outcomes of interconnected system failures. By leveraging causal loop analysis and feedback mechanisms, healthcare stakeholders can develop dynamic, system-wide strategies to enhance fall prevention and operational efficiency.

Purpose: Colpocleisis is a surgical option for elderly women with advanced pelvic organ prolapse (POP), often complicated by comorbidities that heighten postoperative deep venous thrombosis (DVT) risk. Effective tools for predicting postoperative DVT in these patients are lacking. This study aimed to develop a predictive model for the risk of DVT following colpocleisis and to validate its performance.

Patients and methods: This retrospective study included elderly patients who underwent colpocleisis for advanced POP between August 2019 and December 2024. Demographics, obstetric history, comorbidities, preoperative tests, and surgical details were analyzed. The primary endpoint was postoperative DVT, confirmed by ultrasound examination. Univariate and multivariable logistic regression analyses identified risk factors, which informed the development of a predictive nomogram-a graphical tool that translates statistical risk into a user-friendly format for individual prediction. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA), which evaluates the net clinical benefit across threshold probabilities.

Results: Of 307 patients, 8.8% (27/307) developed postoperative DVT. Multivariable analysis identified insulin-dependent diabetes, elevated preoperative cholesterol, and D-dimer levels as independent risk factors. The nomogram demonstrated strong discriminatory ability, with AUCs of 0.809 (95% confidence interval [CI]: 0.760-0.857) in the training set and 0.802 (95% CI: 0.752-0.852) in the validation set. At the optimal threshold (0.494), sensitivity was 0.725, specificity 0.848, positive predictive value (PPV) 0.805, and negative predictive value (NPV) 0.728. Calibration curves showed alignment between predicted and observed outcomes, while DCA demonstrated significant net benefit.

Conclusion: This nomogram is a valuable tool for early DVT risk stratification in elderly colpocleisis patients. External validation in prospective multicenter studies is warranted.

Background: Patient participation in safety behaviors has been recognized as a critical component of reducing medical errors and improving healthcare outcomes in hospitalized settings. However, there is currently a lack of research to understand the decision-making processes that drive these behaviors.

Purpose: This study aimed to identify and construct the different types of decision-making personas adopted by inpatients when thinking about participating in patient safety.

Methods: A qualitative phenomenological study was conducted at a tertiary hospital in Chongqing from October to December 2024. Inpatients meeting the inclusion and exclusion criteria were selected via purposive sampling, and semi-structured interviews were performed to explore their motivation, willingness, decision-making factors, decision-making balance, and effect evaluation during their participation in patient safety decision-making. Data were analyzed using Colaizzi's seven-step method, facilitating the process from raw data to factual labeling and ultimately to the construction of personas dimensions. Patient characteristics were extracted and personas were constructed by artificial intelligence (AI), with the visualization of these personas achieved through a combination of character images and labels.

Results: This study developed four distinct personas that reflect the decision-making types of inpatients' participation in patient safety, with the personas classifications as follows: self-driven decision-makers, passive collaborators, resource-limited decision avoiders, and self-assertive decision-makers.

Conclusion: The diversity of patients' decision-making types necessitates targeted interventions, such as shared decision-making tools, simplified communication, community support provision, and trust reconstruction. Future research should also include longitudinal studies and cross-cultural validation.

Objective: This study aims to investigate the clinical characteristics and identify risk factors associated with progressive pulmonary fibrosis (PPF) in individuals diagnosed with primary Sjögren's syndrome (pSS).

Methods: A retrospective case-control study was conducted from individuals with pSS-associated interstitial lung disease (pSS-ILD) registered in the Chinese Rheumatism Data Center between June 2010 and October 2023. Participants were categorized into two groups: those with PPF (pSS-PPF) and those without PPF (pSS-non-PPF). Comparative analyses were performed on clinical manifestations, laboratory parameters, pulmonary function, and treatment history between the two groups.

Results: Sixty-six individuals with pSS-ILD were included, of whom 29 met the criteria for PPF. Compared to pSS-non-PPF group, the pSS-PPF group demonstrated a higher rate of expectoration (48.3% vs 16.2%, p = 0.005) and crackles on auscultation (41.4% vs 13.5%, p = 0.01), but lower rates of parotid gland enlargement (3.4% vs 32.4%, p = 0.003), and arthritis (6.9% vs 27%, p = 0.035). Additionally, the incidence rate of the subjects suffering xerophthalmia and xerostomia in the PPF group was lower (24.1% vs 2.7%, p = 0.023). Pulmonary function testing showed significantly reduced forced vital capacity percentage predicted (83.6±15.6 vs 91.3±14.6, p = 0.042) and diffusing capacity of the lung for carbon monoxide percentage predicted (DLCO%, 54.2±21.5 vs 68.5±13.6, p = 0.003) in the PPF group. Multivariate logistic regression identified a baseline DLCO% < 60% as an independent risk factor for PPF. Parotid gland enlargement and arthritis were potentially protective. The predictive model demonstrated good performance, with an area under the curve of 0.821 (95% CI: 0.716~0.925, p < 0.001). The sensitivity was 58.6% and the specificity was 91.7%.

Conclusion: A baseline DLCO% < 60% is an independent predictor of PPF in individuals with pSS. The developed predictive model shows strong discriminatory ability, while further validation in larger cohorts is warranted.

Background: China introduced the outpatient pooling fund model into Urban Employee Basic Medical Insurance (UEBMI) to increase the compensation level for outpatient costs, but the empirical evidence is extremely limited. As an early adopter of China's healthcare reform, Sanming City increased the reimbursement rate of general outpatient visits for UEBMI enrollee in August 2016. The reimbursement rate for UEBMI enrollees seeking general outpatient care at primary hospitals increased from 40% to 90%, and for secondary and above hospitals from 30% to 70%. This study aimed to assess the changes in medical service utilization, medical costs, and medical insurance fund expenditures among UEBMI enrollees after the improvement of outpatient pooling level for employees.

Methods: A retrospective analysis was conducted using monthly monitoring data on public hospitals from August 2015 to August 2017 in Sanming City, China. An interrupted time-series analysis was performed to evaluate the level and trend changes in medical services utilization, medical costs, and UEBMI fund expenditures before and after the improvement of outpatient pooling level.

Results: After the intervention, the number of monthly outpatient visits per capita for UEBMI enrollees increased by 0.047 immediately (P<0.05), while the change in inpatient demand was insignificant (P>0.05). The medical cost per outpatient visit increased by 0.6% per month (P<0.001). The out-of-pocket (OOP) cost per outpatient visit decreased by 23.66% immediately (P<0.001), with a monthly increase of 1.61% afterward (P<0.001). The outpatient fund expenditures increased by 151.68% immediately (P<0.001), but decreased by 2.37% per month in the long term (P<0.01). The total and inpatient fund expenditures varied insignificantly (P>0.05).

Conclusion: The improvement of outpatient pooling level for urban employees had positive effects on stimulating the demand for outpatient medical services, reducing OOP costs, and maintaining the sustainability of UEBMI funds, while the long-term effect was weakened, and the substitution effect between inpatient and outpatient healthcare was insignificant. There is an urgent need to improve the outpatient benefits, establish a value-based outpatient payment method and an intelligent medical insurance fund monitoring system.

Objective: This study aimed to analyze the participation and results of the interlaboratory quality assessment for serological biomarkers of infectious diseases, including a five-panel test for hepatitis B, hepatitis C antibodies, and syphilis spirochete antibodies in Kaifeng City, China.

Methods: The assessment conducted by the Center for Clinical Laboratories in Kaifeng City from 2021 to 2022 was retrospectively analyzed. Laboratories participating in the interlaboratory quality assessment activities received two batches of independent clinical laboratory quality control material. These samples were tested in accordance with the provided test instruction manual. The reported results were statistically compared and assessed against those obtained by the clinical testing center.

Results: Data analysis revealed no significant differences in report rates and passing rates among medical institutions of varying levels. However, a significant statistical difference was observed between primary and tertiary hospitals (X ² = 341.1, P < 0.05). Additionally, a similar significant difference was noted in the results obtained using different methodologies (X ² = 0.997, P < 0.05).

Conclusion: The retrospective analysis of interlaboratory quality assessment activities, along with the statistical assessment of test results, assists clinical laboratories in identifying potential systematic and random errors, as well as other factors contributing to control loss. This process facilitates the timely development of effective improvement measures, enhancing test quality and ensuring the provision of accurate and reliable laboratory data for clinical use.

Purpose: To explore the application of Lean Six Sigma (LSS) combined with pre-prescription review system in reducing the irrational rate of emergency prescriptions.

Methods: The emergency prescriptions of our hospital in May 2022 to May 2023 and June 2023 to December 2024 were selected as the research objects. Based on the pre-prescription review system and LSS, a comparative analysis was carried out regarding the irrational rate of emergency prescriptions, the changing trend of the irrational rate, the types of irrational prescriptions and their departmental distribution, patients' satisfaction, and the proportion of doctors' returning and modifying irrational prescriptions before and after the implementation of intervention measures.

Results: After the adoption of LSS and Review system, the irrational rate of emergency prescriptions was significantly reduced (P<0.001); The irrational prescription rate decreased by 0.07% (P<0.001, 95% CI=[-0.06, 0.20]) month by month; The main types of irrational prescriptions remained unchanged, but except for combination medication, incompatibility and repeated medication, all types of irrational prescriptions were significantly lower than those before the intervention (P<0.05); Before and after the intervention, the irrational prescriptions were mainly issued by emergency internal medicine and urology emergency department, and the pediatric emergency department increased after the intervention; Patients' satisfaction was significantly improved after intervention (P<0.05); The proportion of physicians returning to correct irrational prescriptions increased significantly after the intervention (P<0.001).

Conclusion: LSS combined with pre-prescription review system can effectively reduce the irrational rate of emergency prescriptions, optimize emergency medication management, and ensure patient medication safety.

Background: Pressure injury (PI) is a major concern in ICUs, where multiple risk factors contribute to its development. ICU nurses are vital in PI prevention, a key element of patient safety and care quality.

Aim: Explore ICU nurses' perceptions of PI prevention in prone-positioned patients across nine major hospitals in Shanghai, China, and to evaluate their knowledge and attitudes toward PI prevention.

Design: A multicenter cross-sectional study.

Methods: Convenience sampling recruited 252 ICU nurses from nine hospitals in Shanghai between July 31 and August 25, 2024. Participants completed a questionnaire assessing their perceptions of PI prevention in prone-positioned patients. Their knowledge and attitudes were evaluated using the Pressure Ulcer Knowledge Assessment Tool version 2.0 (PUKAT 2.0) and the Attitudes toward Pressure Ulcer Prevention instrument (APuP). Statistical analyses included Pearson correlation, t-tests, ANOVA, and multivariate regression.

Results: ICU nurses showed a positive perception of PI prevention in prone-positioned patients. The mean knowledge score was 8.45 ± 2.55 (40.24%, ≥60% satisfactory), while the mean attitude score was 39.39 ± 4.88 (75.75%, ≥75% satisfactory). Knowledge and attitudes were significantly positively correlated (r = 0.215; p < 0.05). Demographic factors such as gender, age, and ICU experience significantly influenced knowledge and attitudes (all p < 0.05). Nurses with a master's degree and those who had been primary nurses for prone-ventilated patients had higher knowledge scores. Additionally, nurses with 6-15 years of experience showed more favorable attitudes toward PI prevention.

Conclusion: Although ICU nurses had a positive perception of PI prevention in prone-positioned patients, their knowledge was insufficient, and their attitudes were moderate. To address these gaps, healthcare administrators should implement targeted strategies and update evidence-based protocols for PI prevention in prone-ventilated patients. Improving nurses' knowledge and fostering a proactive attitude can enhance clinical practices and patient outcomes.