Sound psychometric properties of a short new screening tool for patient safety climate: applying a Rasch model analysis.

Background: WHO recommends repeated measurement of patient safety climate in health care and to support monitoring an 11 item questionnaire on sustainable safety engagement (HSE) has been developed by the Swedish Association of Local Authorities and Regions. This study aimed to validate the psychometric properties of the HSE.

Methods: Survey responses (n = 761) from a specialist care provider organization in Sweden was used to evaluate psychometric properties of the HSE 11-item questionnaire.

Emergency department crowding and hospital transformation during COVID-19, a retrospective, descriptive study of a university hospital in Stockholm, Sweden.

Objectives: COVID-19 presents challenges to the emergency care system that could lead to emergency department (ED) crowding. The Huddinge site at the Karolinska university hospital (KH) responded through a rapid transformation of inpatient care capacity together with changing working methods in the ED. The aim is to describe the KH response to the COVID-19 crisis, and how ED crowding, and important input, throughput and output factors for ED crowding developed at KH during a 30-day baseline period followed by the first 60 days of the COVID-19 outbreak in Stockholm Region.

Data Quality Governance at the Emergency Department: A Qualitative Study Influenced by Grounded Theory in Nine Swedish Emergency Departments.

Vital Sign Data Quality is essential for successful implementation of clinical decision support systems in emergency care. Studies have shown that data quality is inadequate and needs improvement. This study shows that data quality is dependent on both technical and human factors and provides a conceptual model of data quality governance and improvement in the emergency department.

Is it possible to quickly identify acutely unwell patients who can be safely managed as outpatients? The need for a "Universal Safe to Discharge Score".

If scores or algorithms were developed that quickly identified patients who are bound to have 100% survival, if even only for a few days, more patients could be safely discharged from emergency department, this eliminating the risks of hospitalization for many patients. This hypothesis proposes that it is possible to develop a "Universal Safe to Discharge Score", and suggests how it might be developed and validated.

Man vs machine in emergency medicine - a study on the effects of manual and automatic vital sign documentation on data quality and perceived workload, using observational paired sample data and questionnaires.

Background: Emergency medicine is characterized by a high patient flow where timely decisions are essential. Clinical decision support systems have the potential to assist in such decisions but will be dependent on the data quality in electronic health records which often is inadequate. This study explores the effect of automated documentation of vital signs on data quality and workload.

Exploring Vital Sign Data Quality in Electronic Health Records with Focus on Emergency Care Warning Scores.

Background: Computerized clinical decision support and automation of warnings have been advocated to assist clinicians in detecting patients at risk of physiological instability. To provide reliable support such systems are dependent on high-quality vital sign data. Data quality depends on how, when and why the data is captured and/or documented.

How to improve vital sign data quality for use in clinical decision support systems? A qualitative study in nine Swedish emergency departments.

Background: Vital sign data are important for clinical decision making in emergency care. Clinical Decision Support Systems (CDSS) have been advocated to increase patient safety and quality of care. However, the efficiency of CDSS depends on the quality of the underlying vital sign data.