Guideline Adherence

UnlabelledThe integration of artificial intelligence (AI) into clinical workflows is advancing even before full compliance with the European Union Cross-Border eHealth Network (MyHealth@EU) framework is achieved. While AI-based clinical decision support systems are automatically classified as high risk under the European Union's AI Act, cross-border health data exchange must also satisfy MyHealth@EU interoperability requirements. This creates a dual-compliance challenge: vertical safety and ethics controls mandated by the AI Act and horizontal semantic transport requirements enforced through Open National Contact Point (OpenNCP) gateways, many of which are still maturing toward production readiness. This paper provides a practical, phase-oriented tutorial that enables developers and providers to embed AI Act safeguards before approaching MyHealth@EU interoperability tests. The goal is to show how AI-specific metadata can be included in the Health Level Seven International Clinical Document Architecture and Fast Healthcare Interoperability Resources messages without disrupting standard structures, ensuring both compliance and trustworthiness in AI-assisted clinical decisions. We systematically analyzed Regulation (EU) 2024/1689 (AI Act) and the OpenNCP technical specifications, extracting a harmonized set of overlapping obligations. The AI Act provisions on transparency, provenance, and robustness are mapped directly onto MyHealth@EU workflows, identifying the points where outgoing messages must record AI involvement, log provenance, and trigger validation. To operationalize this mapping, we propose a minimal extension set, covering AI contribution status, rationale, risk classification, and Annex IV documentation links, together with a phase-based compliance checklist that aligns AI Act controls with MyHealth@EU conformance steps. A simulated International Patient Summary transmission demonstrates how Clinical Document Architecture/Fast Healthcare Interoperability Resources extensions can annotate AI involvement, how OpenNCP processes such enriched payloads, and how clinicians in another member state view the result with backward compatibility preserved. We expand on security considerations (eg, Open Worldwide Application Security Project generative AI risks such as prompt injection and adversarial inputs), continuous postmarket risk assessment, monitoring, and alignment with MyHealth@EU's incident aggregation system. Limitations reflect the immaturity of current infrastructures and regulations, with real-world validation pending the rollout of key dependencies. AI-enabled clinical software succeeds only when AI Act safeguards and MyHealth@EU interoperability rules are engineered together from day 0. This tutorial provides developers with a forward-looking blueprint that reduces duplication of effort, streamlines conformance testing, and embeds compliance early. While the concept is still in its early phases of practice, it represents a necessary and worthwhile direction for ensuring that future AI-enabled clinical systems can meet both European Union regulatory requirements from day 1., risks such as prompt injection and adversarial inputs), continuous postmarket risk assessment, monitoring, and alignment with MyHealth@EU's incident aggregation system. Limitations reflect the immaturity of current infrastructures and regulations, with real-world validation pending the rollout of key dependencies.

ImportanceLymph node dissection for early-stage lung adenocarcinoma is controversial. Histologic pattern subtyping reveals heterogeneity of lung adenocarcinoma, yet its association with lymph node involvement and dissection is understudied.ObjectiveTo assess the association between guideline-adherent lymph node dissection, histologic pattern subtyping, and overall survival in patients with clinical T1N0M0 lung adenocarcinoma.Design, setting, and participantsThis multicenter cohort study used data from the National Cancer Center LungReal database, a multicenter, electronic health records-based database for patients undergoing surgery for lung cancer, from January 2014 to December 2021, with the last follow-up in December 2022. Patients were categorized based on histologic pattern of adenocarcinoma into 2 groups: lepidic without high-grade pattern, and high-grade or no lepidic pattern. The data analysis was performed from April to November 2025.ExposureLymph node dissection adherence or nonadherence with the 3 + 1 standard (3 N2 plus 1 N1 station) and the 6-station standard (the subcarinal plus 2 other N2 stations and 3 N1 stations).Main outcome and measureOverall survival.ResultsOf 35 265 patients screened, 27 191 participants (mean [SD] age, 58.3 [11.7] years; 16 280 female [59.9%] and 10 911 male [40.1%] individuals) from 19 centers were included; among them, 15 593 (57.3%) received lymph node dissection adherent with the 3 + 1 standard and 4023 (14.8%) with the 6-station standard. Among the group of 13 369 patients (49.2%) with adenocarcinoma of lepidic without high-grade pattern, no association was observed between survival and adherence with the 3 + 1 standard (hazard ratio [HR], 0.81; 95% CI, 0.57-1.15) or the 6-station standard (HR, 0.54; 95% CI, 0.26-1.13). Whereas, among the group of 13 822 patients (50.8%) with adenocarcinoma of high-grade or no lepidic pattern, adherence with the 3 + 1 standard (HR, 0.81; 95% CI, 0.69-0.95; absolute risk difference at 3-year, 1.2%; 95% CI, 0.2%-2.2%; E-value, 1.78) or the 6-station standard (HR, 0.61; 95% CI, 0.45-0.83; absolute risk difference at 3 years, 1.0%; 95% CI, 0.1%-1.9%; E-value, 2.67) was associated with a significant but small absolute survival benefit.Conclusion and relevanceIn this cohort study, guideline-adherent nodal dissection was associated with small absolute survival benefit for patients with adenocarcinoma of high-grade or no lepidic pattern, but not for those with lepidic without high-grade pattern. These observational findings warrant prospective validation and should not be interpreted as causal.

BackgroundDespite the proven benefits of early breast cancer detection in reducing mortality, adherence to breast cancer screening guidelines in the United States is suboptimal. In this study, we assessed the prevalence and factors associated with adherence to breast cancer screening guidelines.MethodsUsing nationally representative data from the National Health Interview Survey 2021, we included breast cancer screening-eligible women (aged 50-74). Descriptive statistics and population-weighted multivariable logistic regression were employed to examine breast cancer screening adherence per the United States Preventive Services Task Force guidelines, and its determinants in this population.ResultsOf the 6814 screening-eligible women included in this study, 76.4% adhered to breast cancer screening guidelines. Asians (adjusted odds ratio [AOR]: 0.59 (95% confidence interval [95% CI]: 0.42-0.83), p = 0.003), current cigarette smokers (AOR: 0.62 (95% CI: 0.50-0.76), p ConclusionAdherence to breast cancer screening in the United States remained below the Healthy People 2030 goal, with important variations across sociodemographic, behavioral, and health-related factors. Public health actions such as integrating breast cancer awareness activities into smoking cessation programs, encouraging and equipping healthcare professionals to use culturally tailored interventions, and reinforcing community education about breast cancer and its prevention will help increase breast cancer screening adherence among US women.