Unlabelled: Intensive care units are hostile places, which must be conditioned to the needs of patients and families, and therefore the factors that influence their satisfaction must be known.
Objective: To update the knowledge on the satisfaction of the patients admitted to an adult intensive care unit and that of their family caregivers as described in the scientific literature.
Methodology: A systematized literature review was carried out in PubMed, Scopus, Cinahl and WOS databases.
Search Strategy: "Personal Satisfaction" and (patients or caregivers) and "Intensive Care Units".
Inclusion Criteria: studies published between 2013-2018, population aged between 19-64 years, English and Spanish language.
Results: 760 studies were located and 15 were selected. The factors that increased satisfaction are: good communication with professionals (n = 5), the quality of care (n = 4), and the cleanliness and environment of the units (n = 2). The factors that produced dissatisfaction are: the infrastructure of the waiting room (n = 5), inadequate communication (n = 4), and the involvement of families and patients in decision-making (n = 4). Training of professionals (n = 5), inclusion of the family during the process of hospitalization (n = 2) and redesigning the waiting room (n = 2) are some of the suggestions for improvement.
Conclusions: Factors related to professionals, environment and cleanliness of the units are satisfaction-generating factors. Factors generating dissatisfaction related to poor infrastructure, a lack of involvement in decision-making and poor professional communication. Strategies to improve patient and family satisfaction relate to the organization, professionals, family members, and infrastructure and environment.
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http://dx.doi.org/10.1016/j.enfie.2020.07.002 | DOI Listing |
JMIR Hum Factors
January 2025
Women's Health Research Institute, Vancouver, BC, Canada.
Background: Digital health innovations provide an opportunity to improve access to care, information, and quality of care during the perinatal period, a critical period of health for mothers and infants. However, research to develop perinatal digital health solutions needs to be informed by actual patient and health system needs in order to optimize implementation, adoption, and sustainability.
Objective: Our aim was to co-design a research agenda with defined research priorities that reflected health system realities and patient needs.
JMIR Res Protoc
January 2025
Institute for Health Care Management and Research, University of Duisburg-Essen, Essen, Germany.
Background: Artificial intelligence (AI)-based clinical decision support systems (CDSS) have been developed for several diseases. However, despite the potential to improve the quality of care and thereby positively impact patient-relevant outcomes, the majority of AI-based CDSS have not been adopted in standard care. Possible reasons for this include barriers in the implementation and a nonuser-oriented development approach, resulting in reduced user acceptance.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Radiation Oncology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Background: Primary intracranial germ cell tumors (iGCTs) are highly malignant brain tumors that predominantly occur in children and adolescents, with an incidence rate ranking third among primary brain tumors in East Asia (8%-15%). Due to their insidious onset and impact on critical functional areas of the brain, these tumors often result in irreversible abnormalities in growth and development, as well as cognitive and motor impairments in affected children. Therefore, early diagnosis through advanced screening techniques is vital for improving patient outcomes and quality of life.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Gastroenterology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China.
Background: Gastrointestinal bleeding (GIB) is a severe and potentially life-threatening complication in patients with acute myocardial infarction (AMI), significantly affecting prognosis during hospitalization. Early identification of high-risk patients is essential to reduce complications, improve outcomes, and guide clinical decision-making.
Objective: This study aimed to develop and validate a machine learning (ML)-based model for predicting in-hospital GIB in patients with AMI, identify key risk factors, and evaluate the clinical applicability of the model for risk stratification and decision support.
JMIR Res Protoc
January 2025
Department of Medicine and Optometry, eHealth Institue, Linnaeus University, Kalmar, Sweden.
Background: Health worker migration from Nigeria poses significant challenges to the Nigerian health care sector and has far-reaching implications for health care systems globally. Understanding the factors driving migration, its effects on health care delivery, and potential policy interventions is critical for addressing this complex issue.
Objective: This study aims to comprehensively examine the factors encouraging the emigration of Nigerian health workers, map out the effects of health worker migration on the Nigerian health system, document the loss of investment in health training and education resulting from migration, identify relevant policy initiatives addressing migration, determine the effects of Nigerian health worker migration on destination countries, and identify the benefits and demerits to Nigeria of health worker migration.
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