Reducing medical device alarms by an order of magnitude: A human factors approach

The intensive care unit (ICU) is one of the most technically advanced environments in healthcare, using a multitude of medical devices for drug administration, mechanical ventilation and patient monitoring. However, these technologies currently come with disadvantages, namely noise pollution, information overload and alarm fatigue—all caused by too many alarms. Individual medical devices currently generate alarms independently, without any coordination or prioritisation with other devices, leading to a cacophony where important alarms can be lost amongst trivial ones, occasionally with serious or even fatal consequences for patients. We have called this approach to the design of medical devices the single-device paradigm, and believe it is obsolete in modern hospitals where patients are typically connected to several devices simultaneously. Alarm rates of one alarm every four minutes for only the physiological monitors (as recorded in the ICUs of two hospitals contributing to this paper) degrades the quality of the patient’s healing environment and threatens patient safety by constantly distracting healthcare professionals. We outline a new approach to medical device design involving the application of human factors principles which have been successful in eliminating alarm fatigue in commercial aviation. Our approach comprises the networked-device paradigm, comprehensive alarms and humaniform information displays. Instead of each medical device alarming separately at the patient’s bedside, our proposed approach will integrate, prioritise and optimise alarms across all devices attached to each patient, display information more intuitively and hence increase alarm quality while reducing the number of alarms by an order of magnitude below current levels

Intravenous morphine versus intravenous paracetamol after cardiac surgery in neonates and infants

Background: Morphine is worldwide the analgesic of first choice after cardiac surgery in children. Morphine has unwanted hemodynamic and respiratory side effects. Therefore, post-cardiac surgery patients may potentially benefit from a non-opioid drug for pain relief. A previous study has shown that intravenous (IV) paracetamol is effective and opioid-sparing in children after major non-cardiac surgery. The aim of the study is to test the hypothesis that intermittent IV paracetamol administration in children after cardiac surgery will result in a reduction of at least 30% of the cumulative morphine requirement. Methods: This is a prospective, multi-center, randomized controlled trial at four level-3 pediatric intensive care units (ICUs) in the Netherlands and Belgium. Children who are 0-36months old will be randomly assigned to receive either intermittent IV paracetamol or continuous IV morphine up to 48h post-operatively. Morphine will be available as rescue medication for both groups. Validated pain and sedation assessment tools will be used to monitor patients. The sample size (n=208, 104 per arm) was calculated in order to detect a 30% reduction in morphine dose; two-sided significance level was 5% and power was 95%. Discussion: This study will focus on the reduction, or replacement, of morphine by IV paracetamol in children (0-36months old) after cardiac surgery. The results of this study will form the basis of a new pain management algorithm and will be implemented at the participating ICUs, resulting in an evidence-based guideline on post-operative pain after cardiac surgery in infants who are 0-36months old

Identifying the critically ill paediatric oncology patient: a study protocol for a prospective observational cohort study for validation of a modified Bedside Paediatric Early Warning System score in hospitalised paediatric oncology patients

Introduction Hospitalised paediatric oncology patients are at risk to develop acute complications. Early identification of clinical deterioration enabling adequate escalation of care remains challenging. Various Paediatric Early Warning Systems (PEWSs) have been evaluated, also in paediatric oncology patients but mostly in retrospective or case–control study designs. This study protocol encompasses the first prospective cohort with the aim of evaluating the predictive performance of a modified Bedside PEWS score for non-elective paediatric intensive care unit (PICU) admission or cardiopulmonary resuscitation in hospitalised paediatric oncology patients.Methods and analysis A prospective cohort study will be conducted at the 80-bed Dutch paediatric oncology hospital, where all national paediatric oncology care has been centralised, directly connected to a shared 22-bed PICU. All patients between 1 February 2019 and 1 February 2021 admitted to the inpatient nursing wards, aged 0–18 years, with an International Classification of Diseases for Oncology (ICD-O) diagnosis of paediatric malignancy will be eligible. A Cox proportional hazard regression model will be used to estimate the association between the modified Bedside PEWS and time to non-elective PICU transfer or cardiopulmonary arrest. Predictive performance (discrimination and calibration) will be assessed internally using resampling validation. To account for multiple occurrences of the event of interest within each patient, the unit of study is a single uninterrupted ward admission (a clinical episode).Ethics and dissemination The study protocol has been approved by the institutional ethical review board of our hospital (MEC protocol number 16-572/C). We adapted our enrolment procedure to General Data Protection Regulation compliance. Results will be disseminated at scientific conferences, regional educational sessions and publication in peer-reviewed journals.Trial registration number Netherlands Trial Registry (NL8957)

Legislative Documents

Also, variously referred to as: House bills; House documents; House legislative documents; legislative documents; General Court documents

Neighbourhood characteristics and prevalence and severity of depression: pooled analysis of eight Dutch cohort studies

BACKGROUND: Studies on neighbourhood characteristics and depression show equivocal results.AimsThis large-scale pooled analysis examines whether urbanisation, socioeconomic, physical and social neighbourhood characteristics are associated with the prevalence and severity of depression. METHOD: Cross-sectional design including data are from eight Dutch cohort studies (n = 32 487). Prevalence of depression, either DSM-IV diagnosis of depressive disorder or scoring for moderately severe depression on symptom scales, and continuous depression severity scores were analysed. Neighbourhood characteristics were linked using postal codes and included (a) urbanisation grade, (b) socioeconomic characteristics: socioeconomic status, home value, social security beneficiaries and non-Dutch ancestry, (c) physical characteristics: air pollution, traffic noise and availability of green space and water, and (d) social characteristics: social cohesion and safety. Multilevel regression analyses were adjusted for the individual's age, gender, educational level and income. Cohort-specific estimates were pooled using random-effects analysis. RESULTS: The pooled analysis showed that higher urbanisation grade (odds ratio (OR) = 1.05, 95% CI 1.01-1.10), lower socioeconomic status (OR = 0.90, 95% CI 0.87-0.95), higher number of social security beneficiaries (OR = 1.12, 95% CI 1.06-1.19), higher percentage of non-Dutch residents (OR = 1.08, 95% CI 1.02-1.14), higher levels of air pollution (OR = 1.07, 95% CI 1.01-1.12), less green space (OR = 0.94, 95% CI 0.88-0.99) and less social safety (OR = 0.92, 95% CI 0.88-0.97) were associated with higher prevalence of depression. All four socioeconomic neighbourhood characteristics and social safety were also consistently associated with continuous depression severity scores. CONCLUSIONS: This large-scale pooled analysis across eight Dutch cohort studies shows that urbanisation and various socioeconomic, physical and social neighbourhood characteristics are associated with depression, indicating that a wide range of environmental aspects may relate to poor mental health.Declaration of interestNone

Neighbourhood characteristics and prevalence and severity of depression: pooled analysis of eight Dutch cohort studies

BACKGROUND: Studies on neighbourhood characteristics and depression show equivocal results.AimsThis large-scale pooled analysis examines whether urbanisation, socioeconomic, physical and social neighbourhood characteristics are associated with the prevalence and severity of depression. METHOD: Cross-sectional design including data are from eight Dutch cohort studies (n = 32 487). Prevalence of depression, either DSM-IV diagnosis of depressive disorder or scoring for moderately severe depression on symptom scales, and continuous depression severity scores were analysed. Neighbourhood characteristics were linked using postal codes and included (a) urbanisation grade, (b) socioeconomic characteristics: socioeconomic status, home value, social security beneficiaries and non-Dutch ancestry, (c) physical characteristics: air pollution, traffic noise and availability of green space and water, and (d) social characteristics: social cohesion and safety. Multilevel regression analyses were adjusted for the individual's age, gender, educational level and income. Cohort-specific estimates were pooled using random-effects analysis. RESULTS: The pooled analysis showed that higher urbanisation grade (odds ratio (OR) = 1.05, 95% CI 1.01-1.10), lower socioeconomic status (OR = 0.90, 95% CI 0.87-0.95), higher number of social security beneficiaries (OR = 1.12, 95% CI 1.06-1.19), higher percentage of non-Dutch residents (OR = 1.08, 95% CI 1.02-1.14), higher levels of air pollution (OR = 1.07, 95% CI 1.01-1.12), less green space (OR = 0.94, 95% CI 0.88-0.99) and less social safety (OR = 0.92, 95% CI 0.88-0.97) were associated with higher prevalence of depression. All four socioeconomic neighbourhood characteristics and social safety were also consistently associated with continuous depression severity scores. CONCLUSIONS: This large-scale pooled analysis across eight Dutch cohort studies shows that urbanisation and various socioeconomic, physical and social neighbourhood characteristics are associated with depression, indicating that a wide range of environmental aspects may relate to poor mental health.Declaration of interestNone

Analysis of Outcomes in Ischemic vs Nonischemic Cardiomyopathy in Patients With Atrial Fibrillation A Report From the GARFIELD-AF Registry

IMPORTANCE Congestive heart failure (CHF) is commonly associated with nonvalvular atrial fibrillation (AF), and their combination may affect treatment strategies and outcomes