(1) Objectives. Patients with heart failure (HF) who experience hospitalizations for worsening HF (HFH) are at high risk of subsequent events. We aimed to evaluate the impact of an outpatient care management program that includes a clinician-to-clinician e-consultation using an integrated electronic medical record in a healthcare area with a widely dispersed population on delay time in care, hospital admissions, and mortality in a high-risk group of patients with HF and previous episodes of HFH. (2) Methods. We selected 6,444 HF patients who visited the cardiology service at least once between 2010 and 2021. Of these, 4,851 were attended in e-consult, and 2,008 in one-time in-person consultations. In 2,230 HF patients, there was documentation of a previous episode of HFH. Using an interrupted time series regression model, we analysed the impact of incorporating e-consult into the health care model in the group of patients with HFH and evaluated the elapsed time to cardiology care, heart failure (HF), cardiovascular (CV), and all-cause hospital admissions and mortality, calculating the incidence relative risk (iRR). (3) Results. In the group of patients with previous HF hospitalizations, the introduction of e-consult substantially decreased waiting times to cardiology care. The time elapsed to care after e-consult implementation was significantly reduced compared with the previous in-person period (8.6 [8.7] vs 55.4 [79.9] days, p<0.001). In that group of patients, after e-consult implantation, hospital admissions for HF were reduced (iRR [CI95%]: 0,837 [0,840-0,833]), 0,900 [0,862-0,949] for CV and 0,699 [0,678-0,726] for all-cause hospitalizations. There was also lower mortality (iRR [CI95%]: 0.715 [0.657-0.798] due to HF, 0,737 [0.764-0.706] for CV and 0,687 [0.652-0,718] for all-cause). The improved outcomes after e-consultation implementation were significantly higher in the group of patients with previous HFH and were independent of the patient’s clinical characteristics managed during the in-person or e-consultation periods. (4) Conclusions. In HF patients with previous HFH, an outpatient care program that includes an e-consult significantly reduced waiting times to cardiology care and was safe, with a lower rate of hospital admissions and mortality in the first year.

Background: the primary care service in Catalonia has operated an asynchronous teleconsulting service between GPs and patients since 2015 (eConsulta), which has generated some 500,000 messages. New developments in big data analysis tools, particularly those involving natural language, can be used to accurately and systematically evaluate the impact of the service. Objective: the study was intended to examine the predictive potential of eConsulta messages through different combinations of vector representation of text and machine learning algorithms and to evaluate their performance. Methodology: 20 machine learning algorithms (based on 5 types of algorithms and 4 text representation techniques)were trained using a sample of 3,559 messages (169,102 words) corresponding to 2,268 teleconsultations (1.57 messages per teleconsultation) in order to predict the three variables of interest (avoiding the need for a face-to-face visit, increased demand and type of use of the teleconsultation). The performance of the various combinations was measured in terms of precision, sensitivity, F-value and the ROC curve. Results: the best-trained algorithms are generally effective, proving themselves to be more robust when approximating the two binary variables "avoiding the need of a face-to-face visit" and "increased demand" (precision = 0.98 and 0.97, respectively) rather than the variable "type of query"(precision = 0.48). Conclusion: to the best of our knowledge, this study is the first to investigate a machine learning strategy for text classification using primary care teleconsultation datasets. The study illustrates the possible capacities of text analysis using artificial intelligence. The development of a robust text classification tool could be feasible by validating it with more data, making it potentially more useful for decision support for health professionals.

Mood and anxiety disorders affect pregnant people and their families at increased rates throughout the perinatal period. Geographic, financial, and social barriers persist in identification and access to care that preclude adequate diagnosis and treatment of anxiety and mood disorders. These challenges have been exacerbated by the COVID-19 pandemic, particularly for Black and Indigenous People and People of Color (BIPOC) who already experience increased risk for adverse mental health outcomes and faced structural barriers to accessing perinatal mental health care at baseline. The literature shows that integrated care can improve mental health outcomes and save billions of dollars in annual healthcare costs. This study evaluated a novel statewide integrated care effort designed to facilitate access to perinatal mental health care for OB/GYN patients. In addition to enrollment data, variables studied were maternal program satisfaction, retention rates, and preliminary maternal mental health outcomes. 285 patients were ever referred for care. Of this, we contacted 259 patients (91%) and enrolled 209 (72%). Of the 209, 48 were lost to follow up, while 107 remained enrolled at the time of data analysis. 54 patients met their treatment goals. 97% of individuals asserted they were satisfied with the services they received. Black race and public insurance predicted faster attrition from treatment; risk for interpersonal violence exposure and substance use were not related to attrition. Preliminary mental health outcomes showed significant decreases in anxiety and depression, with the most dramatic decreases in the first month of treatment. The MC3 Perinatal care program is a viable, patient-endorsed collaborative care model that increases access to perinatal mental health and facilitate access to outside resources.

The introduction of ChatGPT in academia has raised significant concerns, particularly regarding issues like plagiarism and the ethical use of generative text for academic purposes. Existing literature has predominantly focused on ChatGPT adoption, leaving a notable gap in addressing the strategies users employ to mitigate these emerging challenges. To bridge this gap, this research utilizes the Uncertainty Reduction Theory (URT) to formulate user strategies for reducing uncertainty. These strategies include both interactive and passive approaches. Concurrently, the study identifies key sources of uncertainty, which include concerns related to transparency, information accuracy, and privacy. Additionally, it introduces the concepts of seeking clarification and consulting peer feedback as mediating roles to facilitate reduced uncertainty. We tested these hypotheses with a sample of Indonesian users (N = 566) using structural equation modeling via Smart-PLS 4.0 software. The results confirm that interactive Uncertainty Reduction Strategies (URS) are more effective in reducing uncertainty when using ChatGPT compared to passive URS. Transparency concerns, information accuracy, and privacy concerns are identified as factors that increase the level of uncertainty. In contrast, consulting peer feedback is the most effective strategy for reducing uncertainty compared to seeking clarification at the individual-system level. Insights from the mediating effects confirm that consulting peer feedback significantly mediates uncertainty sources to reduce uncertainty. The study discusses various strategies for the ethical use of ChatGPT by users in the educational context and contributes significantly to theoretical development.

With the outbreak of coronavirus disease 2019 (COVID-19), there is a need for efficient management of patients with mild or no symptoms, which account for the majority. The aim of this study is to introduce the structure and operation protocol of a living and treatment support centre (LTSC) operated by Seoul National University Hospital in South Korea. The existing accommodation facility was converted into a 'patient centre' where patients was isolated. A few Medical staff here performed medical tests and responded to emergencies. Another part of the LTSC was 'remote monitoring centre'. In this center, patients’ self-measured vital signs and symptoms were monitored twice a day, and the medical staff staying here provided video-consultation via a smartphone. During the 3 weeks from March 5 to March 26, 2020, 113 patients were admitted and treated. LTSC could be an efficient alternative to hospital admission in pandemic situation like COVID-19.

In chronic hepatitis C (CHC) patients, interferon-based treatments showed toxicity, limited efficacy, and psychiatric manifestations. Direct-acting antiviral (DAA) agents appeared safer, though it remains unclear if they may exacerbate or foster mood symptoms in drug-naïve CHC patients. We evaluated 62 CHC patients’ mental status, before and 12 weeks after DAA therapy, by assessment scales and psychometric instruments. We subdivided patients into two groups, CHC patients with (Group A) or without (Group B) a current and/or past psychiatric history. After DAA treatment, Group A patients showed low anxiety and improved depression, no variation in self-report distress, but worse general health perceptions. No significant difference emerged from coping strategies. Depression and anxiety improved in Group B, and no change emerged from total self-reported distress, except for somatization. Moreover, Group B increased problem-focused strategies for suppression of competing activities, and decreased strategies of instrumental social support. Contrarily, Group B reduced significantly emotion-focused strategies, such as acceptance and mental disengagement, and improved vitality, physical and social role functioning. DAA therapy is safe and free of hepatological and psychiatric side effects in CHC patients, regardless of current and/or past psychiatric history. In particular, patients without a psychiatric history also remarkably improved their quality of life.

Introduction: The reduced implementation of surveillance programs and limited bedside infectious diseases consultations due to the pressure of COVID-19 pandemic in healthcare systems led to increased rates of irrational use of antimicrobials and incidence of infections by multidrug-resistant microorganisms. The aim of the present study is to evaluate the incidence of antimicrobial resistance and the management of bloodstream infections before and during COVID-19 pandemic at the University General Hospital of Alexandroupolis (Greece). Material-Methods: This is a retrospective study conducted from January 2018 to December 2022. Data were collected from the University Microbiology Laboratory per semester regarding the isolated strains of Gram positive and negative bacteria in blood cultures and respiratory samples in hospitalized patients in medical and surgical wards and in the Intensive Care Unit (ICU). Additionally, bloodstream infections with requested infectious diseases consultation were reported (n=400), determining whether these were carried out via telephone contact or at the patient's bedside. Demographic data, comorbidities, focus of infection, antimicrobial regimen, duration of treatment, length of hospitalization and clinical outcome were analysed. Results: A total of 4569 strains of Gram positive and negative bacteria were isolated. An increasing trend was reported compared to the pre-pandemic period in the incidence of resistant Gram-negative bacteria, particularly in ICUs. Prior antimicrobial use and the rate of hospital-acquired infections were increased significantly during the pandemic. In the pre-pandemic period 2018-2019, a total of 246 infectious diseases consultations were carried out, while during the period 2020-2022 154, with the percentage of telephone consultations 15% and 76% respectively. Detection of the source of infection and timely administration of appropriate antimicrobial agents were more frequently recorded before the pandemic and 28-day mortality was significantly reduced in cases with bedside consultations. Conclusion: Empowering of infectious diseases surveillance programs and committees, rational use of antimicrobials agents and bedside infectious diseases consultations are vital in order to reduce the impact of infections caused by multidrug-resistant strains.

Background: Handover is a critical process for ensuring quality and safety in healthcare. Considerable research suggests that poor handover results in significant morbidity, mortality, dissatisfaction, and excess financial costs. Despite this, little formal attention, education, and evaluation has been given to handover. There is also paucity of data on the opinions of practitioners on the safety of handover.Objectives: The aim of this study was to measure the perceived risk, degree of patient harm and the systems used to support handover, and to understand how this varied by care setting, type of clinical practice, location, or level of experience. Methods: An open, anonymous and confidential online questionnaire covering: (a) respondent characteristics; (b) peer-to-peer handover; (c) internal referrals; (d) discharges and transfers between organisations; and (e) leading and improving handover was conducted with healthcare practitioners and managers from various settings. Results: We gathered a total of 432 completed responses from 26 countries. The average reported performance of handover was rated as 3.9 out of 5.For each type of handover, 12 - 14% reported errors occurring more than weekly. Of those that knew the outcome of such errors, between 29% and 34% reported that they had witnessed moderate or severe harm. 12% and 17% of respondents believed that handover was high or very high risk (See table 4). These respondents were more likely to have witnessed moderate or severe harm, or to be more senior.A wide combination of handover systems was utilised by respondents. 28% - 32% relied exclusively on EPRs (with or without face-to-face contact). 21% used Office documents such as Word and Excel for peer-to-peer handover, and over 30% used hand-written or manual systems. Conclusions: This study suggests the need to do more — and go further — to improve communication and reduce risk during all types of handovers. Clinical leaders should find ways to train and support handover with effective systems, with less experienced staff being the primary focus. More research is needed to demonstrate the interventions that improve the safety of handover.