{
  "abstract": "Introduction The transition from hospital to home can be challenging for parents of premature infants due to a lack of education on specific care. This may lead to both higher readmission rates and healthcare costs. Telehealth interventions can improve the quality of care specific to premature and critically ill newborns. This protocol outlines the WELCOME study and evaluates its feasibility and effectiveness of this approach.Methods and analysis This two-centre randomised control trial (RCT) will assign 240 families with premature and critically ill newborns to an intervention or control group. The study has a parallel group design and an exploratory framework. The control group will receive standard postdischarge care. The intervention group will additionally receive scheduled video consultations, digital assessments and 24/7 access to educational resources. Primary outcomes will focus on 30-day readmission and emergency care use. Secondary outcomes will include child development and parental health. The intervention is expected to be feasible, with high acceptance and minimal drop-out. It will aim to improve parents’ self-efficacy and health literacy. If successful, insights from this multimethod telehealth study will inform standard care.Ethics and dissemination Results will be published in anonymised and summarised form in international and national journals and symposia. The study received ethical approval from the Ethics Committee of the Ludwig-Maximilians-University Munich (No. 25-0028) and was registered in the German Clinical Trials Register on 6 March 2025 (DRKS00034422).Trial registration number DRKS00034422.",
  "authors": [
    {
      "affiliations": [
        "Clinical Nursing Research and Quality Management Unit, LMU Hospital, Munich, Germany",
        "Charité - Universitätsmedizin Berlin, Berlin, Germany"
      ],
      "name": "Laura Sehn"
    },
    {
      "affiliations": [
        "Institute of Clinical Nursing Science, Charité - Universitätsmedizin Berlin, Berlin, Germany"
      ],
      "name": "Melanie Otter"
    },
    {
      "affiliations": [
        "Institute of Clinical Nursing Science, Charité - Universitätsmedizin Berlin, Berlin, Germany"
      ],
      "name": "Julia Will"
    },
    {
      "affiliations": [
        "Institute for Medical Information Processing Biometry and Epidemiology, Chair of Public Health and Health Services Research, LMU Munich, Faculty of Medicine, Munich, Germany",
        "Pettenkofer School of Public Health, Munich, Germany"
      ],
      "name": "Rosa M S Visscher"
    },
    {
      "affiliations": [
        "Institute for Medical Information Processing Biometry and Epidemiology, Chair of Public Health and Health Services Research, LMU Munich, Faculty of Medicine, Munich, Germany",
        "Pettenkofer School of Public Health, Munich, Germany"
      ],
      "name": "Sandra Kus"
    },
    {
      "affiliations": [
        "Institute for Medical Information Processing Biometry and Epidemiology, Chair of Public Health and Health Services Research, LMU Munich, Faculty of Medicine, Munich, Germany",
        "Pettenkofer School of Public Health, Munich, Germany"
      ],
      "name": "Michaela Coenen"
    },
    {
      "affiliations": [
        "Dr. von Hauner Children’s Hospital, LMU Hospital, Munich, Germany"
      ],
      "name": "Andreas Walter Flemmer"
    },
    {
      "affiliations": [
        "Dr. von Hauner Children’s Hospital, LMU Hospital, Munich, Germany"
      ],
      "name": "Esther Schouten"
    },
    {
      "affiliations": [
        "Institute of Clinical Nursing Science, Charité - Universitätsmedizin Berlin, Berlin, Germany"
      ],
      "name": "Antje Tannen"
    },
    {
      "affiliations": [
        "Clinical Nursing Research and Quality Management Unit, LMU Hospital, Munich, Germany"
      ],
      "name": "Uli Fischer"
    }
  ],
  "title": "WELCOME: Digital transition of premature and newborn infants with special care needs to postdischarge care – study protocol for a randomised controlled duo-centred study",
  "uid": "26bb3a0f-40bc-576c-92de-debe6616d767"
}