Risk Management and Healthcare Policy最新文献

Purpose: The hydrocephalus patient community has reported difficulties accessing medical care. The Hydrocephalus Association Patient Powered Interactive Engagement Registry (HAPPIER), a self-reported patient registry, provides a unique opportunity to examine the current landscape of healthcare access and barriers. This study aimed to identify and describe patterns in reported access to care among individuals with hydrocephalus in the United States.

Methods: HAPPIER participants completed a survey which captured information about physician access and insurance information. Analyses focused on US-based respondents and included measures of insurance coverage, access to neurosurgeons and neurologists, frequency of specialist visits, first point of contact in non-emergency situations, and reported barriers due to cost.

Results: HAPPIER included 606 US-based respondents. Half reported private health insurance, while 23.6% had Medicare and 20.1% Medicaid. A total of 17.2% reported lacking access to a neurosurgeon and 43.2% lacked access to a neurologist. Adults were significantly more likely than pediatric participants to lack access to specialists (23.0% vs 1.8% for neurosurgeons; 45.9% vs 36.1% for neurologists). Adults also reported less frequent visits to both neurosurgeons (p < 0.0001) and neurologists (p = 0.0013). In non-emergency situations, 50.5% of respondents identified a neurosurgeon as their first point of contact. 33.3% of participants reported financial barriers, particularly for medications (10.4%), medical specialists (9.9%), and rehabilitation services (8.4%). Adults more frequently reported difficulty accessing medications, specialists, and procedures, while pediatric patients reported more difficulty with rehabilitation services and genetic testing. Household income levels did not influence difficulty accessing care, other than for medications (p = 0.0075).

Conclusion: Findings from HAPPIER highlight substantial barriers to accessing specialized care for individuals with hydrocephalus, with disparities by age and insurance type. These results underscore the need for standardized long-term care guidelines and healthcare policies that ensure equitable access to specialized providers and services for all hydrocephalus patients.

Background: Cancer-related pain is a common and debilitating symptom that reduces quality of life and increases healthcare utilization. While prior studies have examined pain in specific cancer populations, its national economic impact remains understudied.

Objective: To estimate pain prevalence among US adults with cancer, evaluate differences in healthcare expenditures by pain status, and identify drivers of these disparities, with the aim of informing value-based cancer care and pain management policies.

Methods: We analyzed 4368 adults with cancer from the 2019-2022 Medical Expenditure Panel Survey (MEPS). Pain defined as self-reported interference with normal activities in the past four weeks. Total healthcare expenditures including: inpatient, outpatient, prescription, emergency, and other costs were examined using generalized linear models, adjusting for demographic, socioeconomic, and clinical factors. Blinder-Oaxaca decomposition quantified contributions of observed and unobserved factors to expenditure differences.

Results: Pain was reported by 55% of adults with cancer. Unadjusted mean expenditures were higher for patients with pain ($22,072) versus those without ($13,366; p < 0.0001). Adjusted analyses indicated pain was associated with an incremental total cost of $4473 (p = 0.001), mainly driven by inpatient ($2002; p = 0.001), prescription ($1711; p = 0.045), and outpatient costs ($1347; p = 0.003). Decomposition analysis showed 64% of the expenditure difference was explained by observed factors particularly self-reported health and comorbidities, while 36% remained unexplained, suggesting gaps in pain assessment, care quality, or access to effective management strategies. Pain prevalence and associated costs were higher among older adults, socioeconomically disadvantaged individuals, and those with multiple chronic conditions.

Conclusion: Pain places a substantial economic burden on adults with cancer, with disparities influenced by both clinical and socioeconomic factors. Implementing systematic pain assessment and management, including patient-reported outcomes and multimodal interventions, may support cost containment, improve outcomes, and advance value-based oncology care. Policy efforts should prioritize equitable access to comprehensive pain management and integration of pain metrics into cancer care quality frameworks and reimbursement models.

Background: Tongue cancer remains a significant public health concern due to its persistently high mortality. However, population-level evidence on long-term trends and geographic inequities, particularly urban-rural disparities, remains limited. This observational ecological study examined national temporal trends and demographic and geographic heterogeneity in tongue cancer mortality.

Methods: We analyzed mortality data from 1999-2020 obtained from the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER). Deaths were identified using ICD-10 codes C01-C02 as the underlying cause. Age-adjusted mortality rates (AAMRs) and estimated annual percent change (EAPC) were used to quantify trends. Analyses were stratified by sex, race or ethnicity, age group, US Census region, urbanization level, and state. Frontier analysis assessed the association between state-level mortality rates and the socio-demographic index (SDI).

Results: A total of 47,943 tongue cancer deaths were recorded, with an overall AAMR of 0.660 per 100,000 population. Mortality increased modestly from 0.617 to 0.683 per 100,000 (EAPC, 0.262%). Urban-rural disparities were pronounced: urban rates remained stable (EAPC, 0.039%), whereas rural rates increased significantly (EAPC, 1.103%), reversing from lower than urban in 1999 to higher by 2020 (0.742 vs 0.662). Men experienced approximately threefold higher mortality than women, with increases confined to men. Mortality rose among White individuals but declined among Black individuals, and deaths were concentrated in older adults. Regionally, mortality increased in the Midwest and declined in the Northeast. Frontier analysis demonstrated an inverse association between SDI and AAMR.

Conclusion: Tongue cancer mortality in the US has remained relatively stable overall but exhibits widening rural disadvantages, persistent male predominance, divergent racial trends, regional heterogeneity, and a concentration among older adults. These findings underscore the need for equity-focused, geography-based interventions, particularly in rural communities.

Animal-derived ingredients (ADIs) account for up to 75% of prescription drugs, triggering clinical risks such as alpha-gal syndrome (AGS), ethical-religious conflicts, and supply transparency issues. This calls for a systematic evaluation of ADIs and accelerated development of animal-free alternatives (AFAs). This critical review synthesizes evidence from the biomedical, regulatory, and ethical literature to analyze the persistence of ADIs, map their risk stratification (biological and religious), and evaluate progress in AFAs. ADIs persist due to their functional, regulatory, and biocompatibility advantages in various medical products. Methodologically, the proposed dual risk stratification framework integrates immunological risk profiles, specifically targeting the galactose-α-1,3-galactose epitope, with Halal jurisprudential criteria for categorizing pharmaceutical ingredients. Although various AFAs (plant-based, recombinant, and synthetic) have been developed and supported by global regulatory initiatives, significant challenges in scalability, cost, and bioequivalence remain. The transition to AFAs is crucial and increasingly technically feasible. A unified framework that integrates scientific, ethical, and religious analysis is needed to accelerate the adoption of safe and inclusive AFAs, while ensuring patient autonomy and safety.

Objective: We aimed to develop and evaluate inflammatory bowel disease (IBD)-specific risk-adjustment models using an actuarial approach.

Methods: This retrospective, cross-sectional study was conducted using Optum administrative claims data from patients with Crohn's disease and/or ulcerative colitis between January 1, 2020, and December 31, 2022. Clinical-risk groupers with three severity levels were developed for Crohn's disease and ulcerative colitis based on IBD medical costs associated with diagnosis codes. Linear regression models assessed the relationship between clinical-risk groupers and concurrent or prospective costs. Separate models were developed for commercially and Medicare Advantage-insured patients, and for users and nonusers of targeted IBD therapies. Additional predictors that improved explanatory power (R²) were included.

Results: In commercially and Medicare Advantage-insured patients, the clinical-risk grouper explained 20.99% and 20.72% of the variance in concurrent costs incurred by targeted therapy users, and 2.07% and 2.01% of the variance for nonusers, respectively. Including IBD-related hospitalizations (number and duration of stay) increased R² to 41.56% and 22.71% for targeted IBD therapy users and to 29.20% and 16.56% for nonusers who were commercially and Medicare Advantage-insured, respectively. In prospective models, the clinical-risk grouper explained 12.04% and 31.68% of the variance in costs of commercially and Medicare Advantage-insured targeted IBD therapy users and 6.73% and 4.65% of the variance in nonusers, respectively. No evaluated predictors improved prospective model performance.

Conclusion: Our novel concurrent and prospective risk-adjustment models for patients with IBD explain and predict IBD-related costs using administrative claims data, which may offer real-world utility in multiple settings.

Objective: This study aimed to develop and internally validate an early warning predictive model to identify the risk of critical illness among patients presenting to the emergency department (ED).

Methods: A retrospective analysis was conducted using clinical data from 3859 patients admitted between November 1, 2021 and December 31, 2021. Patients were randomly assigned to a training cohort (n = 2,703) and a validation cohort (n = 1,156) in a 7:3 ratio. Fourteen readily accessible physiological indicators obtained during the early stage of emergency department presentation were adopted as predictive parameters. Independent predictors of early critical risk were identified in the training cohort using generalized additive models, stepwise multivariate logistic regression and clinical practical considerations. The resulting model was used to stratify risk levels.

Results: No statistically significant differences were observed in in baseline characteristics between the training and validation cohorts (p>0.05). Sex, age, heart rate, respiratory rate, systolic blood pressure, pulse oximetry saturation, level of consciousness, pupil status, mental status, and pain score were identified as independent predictors of critical risk (all p<0.05). Risk stratification using conditional inference trees categorized patients into low-risk (p≤0.129), medium-risk (0.129<p≤0.867), and high-risk (p>0.867) groups. The model demonstrated strong discriminatory ability, with area under the curve values of 0.926 (95% CI: 0.913-0.940) in the training cohort and 0.914 (95% CI: 0.889-0.938) in the validation cohort. Calibration was satisfactory, as indicated by Hosmer-Lemeshow test p-values of 0.318 and 0.654, respectively.

Conclusion: The developed predictive model demonstrated good discrimination, calibration, and clinical utility for the early identification of patients at critical risk in the ED setting. All predictors can be obtained during the initial clinical assessment, which facilitates real-time application in triage. This practical accessibility supports the model's potential integration into routine emergency workflows and primary healthcare settings.

Background: This study aims to identify and reduce risks that could negatively impact patient safety and organizational aspects related to the different phases of anticancer drug therapy for lung cancer patients in the Day Hospital (DH) care.

Methods: From April 2023 until February 2024, a team of multi-disciplinary healthcare professionals of the National Cancer Institute of Naples, Italy, used a modified Delphi approach to identify the care process, the main activities and related risk factors. The severity of these harms and the probability of their occurrence were assessed by applying a 5×5 semi-quantitative ISO 31000:2018 (ISO 31000) risk matrix. Multiple improvement actions were identified and adopted by the team to reduce the risks to acceptable levels.

Results: Nine main activities, 19 correlated potential risks (10 risks for patient safety domain; 53.0%) (9 risks for organizational area; 47.0%) and 19 mitigation measures were identified. The highest risk levels were recognized in the organizational area for: (i) DH Outpatient Visits, due to delays in patients check-in or lab test results or problems with the prescription software; (ii) anticancer drugs administration, for the unavailability of chemotherapy chairs or lack of dedicated nursing staff. Conversely, risk levels for patient safety area were low overall, because several control measures were already in place. Once the mitigation measures were implemented, a new semi-quantitative risk analysis was performed. Risk levels for organizational area changed from a 44.4% to 0.0% in high level, from 44.4% to 67.0% in moderate level, and from 11.2% to 33.0% in minor level. Risk levels for safety areas did not modify for high level (10.0%), but changed from 50.0% to 10.0% in moderate level and increased from 40.0% to 80.0% in minor level.

Conclusion: ISO 31000 risk management framework applied to lung cancer DH care could improve both organizational and safety objectives in oncology.

Dispensing errors, often driven by look-alike/sound-alike medicine names, similar packaging, and complex workflows, pose a persistent threat to patient safety and care quality. Artificial intelligence (AI) offers new opportunities to detect discrepancies and support decision-making in near real time, yet its impact depends on how it is embedded within the wider healthcare system. In this perspective, we use a systems approach to synthesize current AI-enabled strategies for reducing dispensing errors and to outline a roadmap for their safe and effective implementation. We focus in particular on an AI-based natural language processing (NLP) decision-support application as an exemplar, examining how it can be integrated into dispensing workflows to flag high-risk prescriptions and labelling discrepancies before medications reach patients. Using systems thinking, we organise our analysis around four interrelated perspectives: people (training, human-AI teaming, trust), system (interoperability, data pipelines, monitoring), design (human-centred interfaces, uncertainty displays, workflow fit), and risk (ethical oversight, bias assessment, safety assurance, and governance). Across these perspectives, we identify priorities such as multimodal data use, external validation across sites and populations, prospective evaluation with safety and equity metrics, and continuous model monitoring with clear rollback mechanisms. AI can enhance safety, timeliness, and efficiency in dispensing; however, its value depends on disciplined sociotechnical integration and feedback within learning healthcare systems, rather than on standalone algorithmic performance.

Purpose: GLP-1 receptor agonists have attracted increasing attention due to their dual efficacy in glycemic control and weight reduction. Although several GLP-1 receptor agonists have been included in China's National Reimbursement Drug List, their actual adoption at the hospital level still faces multiple challenges. A well-structured evaluation framework is urgently needed to facilitate their integration into hospital formularies. This study aims to develop a clinically comprehensive evaluation system for GLP-1 receptor agonists in public hospital drug selection, based on multicriteria decision analysis (MCDA). The goal is to provide a systematic and quantifiable tool to support the rational selection and implementation of GLP-1RAs in public hospitals, thereby enhancing the scientific basis of hospital formulary decisions.

Patients and methods: The study integrates the Delphi method and multi-criteria decision analysis (MCDA), utilizing literature review, expert consultations, and questionnaire surveys to select and assign weights to evaluation indicators.

Results: A three-tier evaluation system was established, comprising four primary indicators, eight secondary indicators, and seventeen tertiary indicators. Among them, "Clinical Value" had the highest weight (0.5373), followed by "Hospital Admission Demand" (0.1924) and "Hospital Management" (0.1379), while "Economic Value" had the lowest weight (0.1324). At the tertiary level, "Cost-Effectiveness Advantage", "Glycosylated Hemoglobin", "Cardiovascular, Hepatic, and Renal Benefits", "Addressing Unmet Clinical Needs", and "Hypoglycemia Incidence" contributed most to decision-making.

Conclusion: This study fills the gap in clinical evaluation research on GLP-1RA drugs in China. The proposed evaluation system provides scientific support for hospital pharmaceutical management, medical insurance inclusion, and drug procurement, promoting value-based hospital drug selection strategies.

Purpose: To explore nurses' stress experiences, sources of stress, and support needs during patient safety incidents, and to propose tailored management strategies.

Methods: Guided by Perceived Organizational Support Theory and the Dynamic Model of Work Stress, a phenomenological qualitative design was used in this study. Using purposive sampling, we recruited nurses who had directly experienced patient safety incidents (as second victims) from a tertiary hospital in Jiangsu Province, China, between June 10 and July 15, 2025. Data were collected through semi-structured interviews and analyzed with Colaizzi's seven-step method.

Results: Four core themes and twelve subthemes were identified: (1) multidimensional experiences triggered by incidents; (2) multiple sources of stress; (3) diverse pathways of support; and (4) reflections and suggestions for organizational mechanisms. Nurses described a substantial emotional and bodily burden as second victims. Stressors arose from the interplay of individual psychological conflict, interpersonal pressures, and organizational burdens. Perceived organizational support-such as managers' protective communication, colleagues' empathy, and interprofessional collaboration-buffered distress and facilitated recovery; when support was absent or unsystematic, nurses often relied on self-regulation and time to cope.

Conclusion: Nurses' experiences during patient safety incidents were multidimensional, involving psychological, physiological, and occupational stress shaped by individual, organizational, and social factors. Findings emphasize the need for support interventions tailored to stress sources and nurses' actual needs to reduce stress and enhance care quality and patient safety.