Johnson, Danelle A

Home enteral nutrition (HEN) is essential for patients with a functioning gastrointestinal tract who cannot meet nutritional needs orally, yet outpatient management remains complex, resource-intensive, and supported by a limited evidence base. Artificial intelligence (AI) may augment HEN care by extending monitoring, education, risk assessment, documentation support, and operational coordination into the home environment. Consistent with the narrative review format, this article uses a pragmatic, transparent synthesis of influential HEN-specific literature, relevant clinical nutrition evidence, and background knowledge from adjacent fields, including home healthcare, chronic disease management, oncology nutrition, telehealth, and software regulation. Direct evidence in established HEN populations remains scarce; therefore, most AI applications should be considered hypotheses or early implementation opportunities rather than proven standards of care. The strongest near-term opportunities are clinician-supervised patient education, symptom triage, adherence support, remote monitoring, and workflow automation. Predictive analytics, smart pumps, and precision enteral prescription tools are promising but require prospective HEN-specific validation, interoperability with electronic health records and home-infusion systems, reimbursement pathways, and governance safeguards. Key barriers include dataset bias, limited external validation, alert fatigue, privacy and regulatory concerns, unclear accountability, digital equity, cost uncertainty, and the risk of dehumanizing care. AI should be viewed as a complement to multidisciplinary HEN expertise. Priorities for the near future include HEN registries, standardized outcomes, prospective validation, pragmatic implementation trials, health-economic evaluation, and transparent oversight that preserves clinician accountability and patient-centered care.

Background: Artificial intelligence (AI) is increasingly being integrated into healthcare, with applications ranging from predictive analytics to clinical decision support. In clinical nutrition, AI tools offer opportunities to improve workflow efficiency, enhance dietary assessment, and personalize nutrition care. Despite growing interest, little is known about registered dietitian nutritionists’ (RDNs) perceptions of AI in clinical practice. The aim of the present study was to assess RDNs’ attitudes toward AI use within a large healthcare system, along with their perceived barriers in this regard. Methods: A cross-sectional survey was developed through expert review and distributed electronically via REDCap to RDNs across Mayo Clinic’s academic campuses and affiliated health system sites. The 23-item survey included Likert-scale items addressing AI’s potential utilization within clinical care, perceived benefits and risks, and readiness for adoption. Responses were summarized using descriptive statistics. Factor analysis identified underlying constructs related to AI attitudes. Differences stratified by age and years of experience were evaluated using ANOVA. Results: Of the 185 RDNs invited, 64 (35%) responded. Two factors emerged: optimism regarding AI usage (Cronbach’s α = 0.94) and skepticism about implementation (α = 0.76). The overall mean ± SD score for optimism was 0.1 ± 0.6 (neutral), while skepticism averaged 1.0 ± 0.6 (moderate). Skepticism differed by years of experience (p = 0.012), with the lowest levels observed among RDNs with ≥21 years of practice. No significant differences were observed across age groups. Discussion: RDNs demonstrated neutral attitudes toward AI use but expressed concerns about accuracy, training, and implementation challenges. Addressing these concerns through education and structured implementation strategies may facilitate successful adoption of AI in dietetic practice.

Abstract Background With data demonstrating benefit, the prevalence of home enteral nutrition (HEN) has increased significantly over the last few decades. Despite this increase, there remains a paucity of data regarding real‐world use of HEN including clinical outcomes and complications. Methods Descriptive analysis of prospectively maintained database of our specialized HEN program was undertaken. Patients who received care in our program with HEN initiation date between January 1, 2018, and December 31, 2020, were included in the analysis. Data regarding demographic information, anthropometrics, enteral nutrition (EN) regimen, electrolytes, and nutrition therapy history were included and tracked until July 31, 2021. Results During the study period, 1600 patients initiated HEN treatment under our care. Majority of the study population needed EN therapy due to malignancy and its complications, including malignant dysphagia or mechanical obstruction (60.6%) followed by neurodegenerative diseases (7.5%). By the end of the study period, a majority of the patients (82%) stopped HEN treatment. Of these, 44.2% achieved EN goals and/or oral autonomy. Patients continued HEN treatment for a median of 100 (interquartile range, 32–301) days. Overall, 53.2% of patients experienced/reported at least one HEN‐related complication that was clinically managed by the HEN team. Complications included tube‐related, enteral feeding intolerance (EFI), and electrolyte shifts. Conclusion In our study population, HEN was most utilized to manage malignancy‐related complications, including dysphagia. Unfortunately, complications, including EFI and tube‐related complications, remained quite prevalent. Further evaluation regarding risk factors for complications and preventive mechanisms, such as increased education, is indicated.