Videoconferencing to reduce stress among hospitalized children
Child; Female; Hospitalization; Humans; Male; Parents; Prospective Studies; Videoconferencing; Stress; Psychological; Hospitalized; Propensity Score
OBJECTIVES: Family-Link is a videoconferencing program that allows hospitalized children and their parents to virtually visit family members and friends using laptops, webcams, and a secure Wi-Fi connection. We evaluated the association of Family-Link use on the reduction in stress experienced by children during hospitalization. METHODS: We offered Family-Link to pediatric patients who had an expected length of hospitalization equal to or greater than 4 days. We measured the stress levels of hospitalized children at admission and discharge using the previously published Parental Stress Survey. We used propensity score matching and multivariable linear regression methods to evaluate the relationship between the use of Family-Link and stress experienced by children during hospitalization. RESULTS: We included a total of 367 children in the study: 232 Family-Link users and 135 non-Family-Link users. Using the propensity score matching method, we found that the use of Family-Link was significantly associated with a greater reduction in overall mean stress compared with non-Family-Link users among the cohort of patients who lived closer to the hospital and had shorter lengths of hospitalization (β = 0.23; 95% confidence interval, 0.03 to 0.43; P < .05). In this cohort, the reduction in overall mean stress was 37% greater among Family-Link users than non-Family-Link users. CONCLUSIONS: The use of videoconferencing by some hospitalized children and families to conduct virtual visits with family and friends outside of the hospital was associated with a greater reduction in stress during hospitalization than those who did not use videoconferencing.
2014-07
Yang NH; Dharmar M; Hojman NM; Sadorra CK; Sundberg D; Wold GL; Parsapour K; Marcin JP
Pediatrics
2014
Article information provided for research and reference use only. PedPalASCNET does not hold any rights over the resource listed here. All rights are retained by the journal listed under publisher and/or the creator(s).
Journal Article
<a href="http://doi.org/10.1542/peds.2013-3912" target="_blank" rel="noreferrer">10.1542/peds.2013-3912</a>
Long-stay patients: are there any long-term solutions?
Child; Humans; infant; Intensive Care Units; Length of Stay; Risk Factors; Pediatric; Newborn; ICU Decision Making; Heart Defects; Cardiopulmonary Bypass; Congenital/surgery
2003
Slonim AD; Marcin JP; Pollack MM
Critical Care Medicine
2003
Article information provided for research and reference use only. PedPalASCNET does not hold any rights over the resource listed here. All rights are retained by the journal listed under publisher and/or the creator(s).
Journal Article
<a href="http://doi.org/10.1097/01.CCM.0000046066.19302.70" target="_blank" rel="noreferrer">10.1097/01.CCM.0000046066.19302.70</a>
Certainty and mortality prediction in critically ill children.
Child; Humans; Intensive Care Units; Medical Staff; Hospital Mortality; Prognosis; Prospective Studies; Clinical Competence; Longitudinal Studies; Risk Assessment; Pediatric; Empirical Approach; Professional Patient Relationship; Death and Euthanasia; Hospital; Health Care and Public Health; Critical Illness/mortality
OBJECTIVES: The objective of this study is to investigate the relationship between a physician's subjective mortality prediction and the level of confidence with which that mortality prediction is made. DESIGN AND PARTICIPANTS: The study is a prospective cohort of patients less than 18 years of age admitted to a tertiary Paediatric Intensive Care Unit (ICU) at a University Children's Hospital with a minimum length of ICU stay of 10 h. Paediatric ICU attending physicians and fellows provided mortality risk predictions and the level of confidence associated with these predictions on consecutive patients at the time of multidisciplinary rounds within 24 hours of admission to the paediatric ICU. Median confidence levels were compared across different ranges of mortality risk predictions. RESULTS: Data were collected on 642 of 713 eligible patients (36 deaths, 5.6%). Mortality predictions greater than 5% and less than 95% were made with significantly less confidence than those predictions 95%. Experience was associated with greater confidence in prognostication. CONCLUSIONS: We conclude that a physician's subjective mortality prediction may be dependent on the level of confidence in the prognosis; that is, a physician less confident in his or her prognosis is more likely to state an intermediate survival prediction. Measuring the level of confidence associated with mortality risk predictions (or any prognostic assessment) may therefore be important because different levels of confidence may translate into differences in a physician's therapeutic plans and their assessment of the patient's future.
2004
Marcin JP; Pretzlaff RK; Pollack MM; Patel KM; Ruttimann UE
Journal Of Medical Ethics
2004
Article information provided for research and reference use only. PedPalASCNET does not hold any rights over the resource listed here. All rights are retained by the journal listed under publisher and/or the creator(s).
Journal Article
<a href="http://doi.org/10.1136/jme.2002.001537" target="_blank" rel="noreferrer">10.1136/jme.2002.001537</a>
Long-stay patients in the pediatric intensive care unit
Child; Female; Humans; Male; Intensive Care Units; Hospital Mortality; Logistic Models; Treatment Outcome; Comorbidity; Health Services Research; Severity of Illness Index; Risk Factors; Quality of Health Care; Sensitivity and Specificity; Analysis of Variance; Predictive Value of Tests; Cost Savings; Preschool; infant; algorithms; Pediatric/utilization; ICU Decision Making; United States/epidemiology; Age Distribution; Discriminant Analysis; Patient Admission/statistics & numerical data; Length of Stay/statistics & numerical data; Emergencies; Decision Trees; Intensive Care/economics/standards
OBJECTIVE: Length of stay in the pediatric intensive care unit (PICU) is a reflection of patient severity of illness and health status, as well as PICU quality and performance. We determined the clinical profiles and relative resource use of long-stay patients (LSPs) and developed a prediction model to identify LSPs for early quality and cost saving interventions. DESIGN: Nonconcurrent cohort study. SETTING: A total of 16 randomly selected PICUs and 16 volunteer PICUs. PATIENTS: A total of 11,165 consecutive admissions to the 32 PICUs. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: LSPs were defined as patients having a length of stay greater than the 95th percentile (>12 days). Logistic regression analysis was used to determine which clinical characteristics, available within the first 24 hrs after admission, were associated with LSPs and to create a predictive algorithm. Overall, LSPs were 4.7% of the population but represented 36.1% of the days of care. Multivariate analysis indicated that the following factors are predictive of long stays: age <12 months, previous ICU admission, emergency admission, no CPR before admission, admission from another ICU or intermediate care unit, chronic care requirements (total parenteral nutrition and tracheostomy), specific diagnoses including acquired cardiac disease, pneumonia, and other respiratory disorders, having never been discharged from the hospital, need for ventilatory support or an intracranial catheter, and a Pediatric Risk of Mortality III score between 10 and 33. The performance of the prediction algorithm in both the training and validation samples for identifying LSPs was good for both discrimination (area under the receiver operating characteristics curve of 0.83 and 0.85, respectively), and calibration (goodness of fit, p = .33 and p = .16, respectively). LSPs comprised from 2.1% to 8.1% of individual ICU patients and occupied from 15.2% to 57.8% of individual ICU bed days. CONCLUSIONS: LSPs have less favorable outcomes and use more resources than non-LSPs. The clinical profile of LSPs includes those who are younger and those that require chronic care devices. A predictive algorithm could help identify patients at high risk of prolonged stays appropriate for specific interventions.
2001
Marcin JP; Slonim AD; Pollack MM; Ruttimann UE
Critical Care Medicine
2001
Article information provided for research and reference use only. PedPalASCNET does not hold any rights over the resource listed here. All rights are retained by the journal listed under publisher and/or the creator(s).
Journal Article
<a href="http://doi.org/10.1097/00003246-200103000-00035" target="_blank" rel="noreferrer">10.1097/00003246-200103000-00035</a>