How to improve vital sign data quality for use in clinical decision support systems? A qualitative study in nine Swedish emergency departments.
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. Therefore, possible factors affecting vital sign data quality need to be understood. This study aims to explore the factors affecting vital sign data quality in Swedish emergency departments and to determine in how far clinicians perceive vital sign data to be fit for use in clinical decision support systems. A further aim of the study is to provide recommendations on how to improve vital sign data quality in emergency departments.



Semi-structured interviews were conducted with sixteen physicians and nurses from nine hospitals and vital sign documentation templates were collected and analysed. Follow-up interviews and process observations were done at three of the hospitals to verify the results. Content analysis with constant comparison of the data was used to analyse and categorize the collected data.



Factors related to care process and information technology were perceived to affect vital sign data quality. Despite electronic health records (EHRs) being available in all hospitals, these were not always used for vital sign documentation. Only four out of nine sites had a completely digitalized vital sign documentation flow and paper-based triage records were perceived to provide a better mobile workflow support than EHRs. Observed documentation practices resulted in low currency, completeness, and interoperability of the vital signs. To improve vital sign data quality, we propose to standardize the care process, improve the digital documentation support, provide workflow support, ensure interoperability and perform quality control.



Vital sign data quality in Swedish emergency departments is currently not fit for use by CDSS. To address both technical and organisational challenges, we propose five steps for vital sign data quality improvement to be implemented in emergency care settings.
Capio St Görans Hospital, 112 81, Stockholm, Sweden. Niclas.skyttberg@ki.se.|Health Informatics Centre, Department of Learning, Informatics, Management, and Ethics, Karolinska Institutet, 171 77, Stockholm, Sweden. Niclas.skyttberg@ki.se.
Niclas
N
Skyttberg
Health Informatics Centre, Department of Learning, Informatics, Management, and Ethics, Karolinska Institutet, 171 77, Stockholm, Sweden.|Cambio Healthcare Systems, Stockholm, Sweden.
Joana
J
Vicente
Health Informatics Centre, Department of Learning, Informatics, Management, and Ethics, Karolinska Institutet, 171 77, Stockholm, Sweden.
Rong
R
Chen
Department of Anaesthesia and Intensive Care, Karolinska University Hospital, 171 76, Stockholm, Sweden.
Hans
H
Blomqvist
Health Informatics Centre, Department of Learning, Informatics, Management, and Ethics, Karolinska Institutet, 171 77, Stockholm, Sweden.
Sabine
S
Koch
D020000:Decision Support Systems, Clinical / Q000592:standards*; D057286:Electronic Health Records / Q000592:standards*; D004636:Emergency Service, Hospital / Q000592:standards*; D006801:Humans; D036301:Qualitative Research; D058996:Quality Improvement / Q000592:standards*; D013548:Sweden; D055986:Vital Signs
Computer-assisted decision making; Data quality; Electronic health records; Emergency care; Medical informatics; Vital signs