Adopting electronic health records (EHRs) offers improved communication and information sharing and reduces medical staff errors. Despite these potential benefits, EHR adoption often introduces new challenges for healthcare staff, including increased administrative burdens and workplace stress. This study examines the impact of EHR systems on the well-being and workplace stress of healthcare staff in a hospital setting. Using a qualitative multi-perspective research approach, 16 guideline-based interviews were conducted to explore experiences, insight, and perceptions surrounding the anticipated introduction of EHRs. Data analysis reveals a complex interplay between the perceived advantages of EHRs, such as improved data accessibility and patient safety, and the challenges related to increased workload. Based on interviewers’ perceptions, emerging themes were categorized as technostress creators or inhibitors. The findings highlight a dual impact of EHRs: while participants acknowledged improvements in patient safety and information access, they also expressed concerns about increased workload, technostress, and potential disruptions to team dynamics. This study identified two major themes: “EHR Adoption as a Double-Edged Sword” and “EHRs’ Influence on Professional Dynamics”. These findings underscore the need for organizational readiness and staff support to mitigate the negative impacts of EHRs on healthcare workers’ well-being and job satisfaction.

Background/Objectives: The advent of large language models (LLMs), like platforms such as ChatGPT, capable of generating quick and interactive answers to complex questions, opens the way for new approaches to training healthcare professionals, enabling them to acquire up-to-date and specialised information easily. In nursing, they have proven to support clinical decision making, continuing education, the development of care plans and the management of complex clinical cases, as well as the writing of academic reports and scientific articles. Furthermore, the ability to provide rapid access to up-to-date scientific information can improve the quality of care and promote evidence-based practice. However, their applicability in clinical practice requires thorough evaluation. This study evaluated the accuracy, completeness and safety of the responses generated by ChatGPT-4 on pressure injuries (PIs) in infants. Methods: In January 2025, we analysed the responses generated by ChatGPT-4 to 60 queries, subdivided into 12 main topics, on PIs in infants. The questions were developed, through consultation of authoritative documents, based on their relevance to nursing care and clinical potential. A panel of five experts, using a 5-point Likert scale, assessed the accuracy, completeness and safety of the answers generated by ChatGPT. Results: Overall, over 90% of the responses generated by ChatGPT-4o received relatively high ratings for the three criteria assessed with the most frequent value of 4. However, when analysing the 12 topics individually, we observed that Medical Device Management and Technological Innovation were the topics with the lowest accuracy scores. At the same time, Scientific Evidence and Technological Innovation had the lowest completeness scores. No answers for the three criteria analysed were rated as completely incorrect. Conclusions: ChatGPT-4 has shown a good level of accuracy, completeness and safety in addressing questions about pressure injuries in infants. However, ongoing updates and integration of high-quality scientific sources are essential for ensuring its reliability as a clinical decision-support tool.

Improving patient activation may be an effective way to reduce healthcare costs and improve patient outcomes after surgery. To determine whether preoperative patient activation is associated with delayed discharge (i.e., length of stay >24 h) after elective laparoscopic cholecystectomy. Postoperative symptoms, unscheduled access to healthcare facilities within seven days of surgery, unplanned hospital readmissions, and postoperative complications were analyzed as secondary outcomes. This cohort study was a secondary analysis of the DeDiLaCo study (Delayed Discharge after day-surgery Laparoscopic Cholecystectomy) collecting data of patients undergoing elective laparoscopic cholecystectomy during 2021 in Italy. Data was analyzed from June 2022 to April 2023. 90 Italian surgical centers participating in the study. 4708 adult patients with an instrumental diagnosis of gallbladder disease and undergoing laparoscopic cholecystectomy. Patient activation was assessed using the Italian translation of Patient Activation Measure in the preoperative setting. Of 4532 cases analyzed the median (IQR) Patient Activation Measure score was 80.3 (71.2-92.3). Participants were on average 55.5 years of age and 58.1 % were female. Two groups based on the activation level were created: 270 (6 %) had low activation, and 4262 had high activation. The low activation level was associated with the likelihood of delayed discharge (odds ratio [OR] 1.47, 95 % CI, 1.11-1.95; P = .008), higher symptom burden (OR 1.99, 95 % CI 1.49-2.66, P < .0001), and unplanned healthcare utilization within seven days after hospital discharge (OR 1.85, 95 % CI, 1.29-2.63; P = .001). There was no difference between the high and low activation groups in the incidence of postoperative complications (OR 1.28, 95 % CI, 0.95-1.73; P = .10) and hospital readmission after discharge (OR 0.95, 95 % CI, 0.30-3.05; P = .93). Our results suggest that patients with low activation have 1.47 times the risk of delayed discharge compared with patients with higher activation, almost twice the risk of the onset of postoperative symptoms, and 1.85 times the risk of unscheduled use of hospital services. Screening for patient activation in the preoperative setting could not only identify patients not suitable for early discharge, but more importantly, help physicians and nurses develop tailored interventions.

Background: The concept of early discharge ≤24 hours after Laparoscopic Cholecystectomy (LC) is still doubted in Italy. This prospective multicentre study aims to analyze the prevalence of patients undergoing elective LC who experienced a delayed discharge >24 hours in an extensive Italian national database and identify potential limiting factors of early discharge after LC. Methods: This is a prospective observational multicentre study performed from January 1, 2021 to December 31, 2021 by 90 Italian surgical units. Results: A total of 4664 patients were included in the study. Clinical reasons were found only for 850 patients (37.7%) discharged >24 hours after LC. After excluding patients with nonclinical reasons for delayed discharge >24 hours, 2 groups based on the length of hospitalization were created: the Early group (≤24 h; 2414 patients, 73.9%) and the Delayed group (>24 h; 850 patients, 26.1%). At the multivariate analysis, ASA III class (P<0.0001), Charlson’s Comorbidity Index (P=0.001), history of choledocholithiasis (P=0.03), presence of peritoneal adhesions (P60 min (P<0.0001), drain placement (P<0.0001), pain (P=0.001), postoperative vomiting (P=0.001) and complications (P24 hours. Conclusions: The majority of delayed discharges >24 hours after LC in our study were unrelated to the surgery itself. ASA class >II, advanced comorbidity, the presence of peritoneal adhesions, prolonged operative time, and placement of abdominal drainage were intraoperative variables independently associated with failure of early discharge.