Magnus Andersson Hagiwara, Lars Lundberg, Bengt Arne Sjöqvist, Hanna Maurin Söderholm
{"title":"The Effects of Integrated IT Support on the Prehospital Stroke Process: Results from a Realistic Experiment.","authors":"Magnus Andersson Hagiwara, Lars Lundberg, Bengt Arne Sjöqvist, Hanna Maurin Söderholm","doi":"10.1007/s41666-019-00053-4","DOIUrl":null,"url":null,"abstract":"<p><p>Stroke is a serious condition and the stroke chain of care is a complex. The present study aims to explore the impact of a computerised decision support system (CDSS) for the prehospital stroke process, with focus on work processes and performance. The study used an exploratory approach with a randomised controlled crossover design in a realistic contextualised simulation experiment. The study compared clinical performance among 11 emergency medical services (EMS) teams of 22 EMS clinicians using (1) a computerised decision support system (CDSS) and (2) their usual paper-based process support. Data collection consisted of video recordings, postquestionnaires and post-interviews, and data were analysed using a combination of qualitative and quantitative approaches. In this experiment, using a CDSS improved patient assessment, decision making and compliance to process recommendations. Minimal impact of the CDSS was found on EMS clinicians' self-efficacy, suggesting that even though the system was found to be cumbersome to use it did not have any negative effects on self-efficacy. Negative effects of the CDSS include increased on-scene time and a cognitive burden of using the system, affecting patient interaction and collaboration with team members. The CDSS's overall process advantage to the prehospital stroke process is assumed to lead to a prehospital care that is both safer and of higher quality. The key to user acceptance of a system such as this CDSS is the relative advantages of improved documentation process and the resulting patient journal. This could improve the overall prehospital stroke process.</p>","PeriodicalId":36444,"journal":{"name":"Journal of Healthcare Informatics Research","volume":"3 1","pages":"300-328"},"PeriodicalIF":5.9000,"publicationDate":"2019-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8982745/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Healthcare Informatics Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s41666-019-00053-4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2019/9/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 0
Abstract
Stroke is a serious condition and the stroke chain of care is a complex. The present study aims to explore the impact of a computerised decision support system (CDSS) for the prehospital stroke process, with focus on work processes and performance. The study used an exploratory approach with a randomised controlled crossover design in a realistic contextualised simulation experiment. The study compared clinical performance among 11 emergency medical services (EMS) teams of 22 EMS clinicians using (1) a computerised decision support system (CDSS) and (2) their usual paper-based process support. Data collection consisted of video recordings, postquestionnaires and post-interviews, and data were analysed using a combination of qualitative and quantitative approaches. In this experiment, using a CDSS improved patient assessment, decision making and compliance to process recommendations. Minimal impact of the CDSS was found on EMS clinicians' self-efficacy, suggesting that even though the system was found to be cumbersome to use it did not have any negative effects on self-efficacy. Negative effects of the CDSS include increased on-scene time and a cognitive burden of using the system, affecting patient interaction and collaboration with team members. The CDSS's overall process advantage to the prehospital stroke process is assumed to lead to a prehospital care that is both safer and of higher quality. The key to user acceptance of a system such as this CDSS is the relative advantages of improved documentation process and the resulting patient journal. This could improve the overall prehospital stroke process.
期刊介绍:
Journal of Healthcare Informatics Research serves as a publication venue for the innovative technical contributions highlighting analytics, systems, and human factors research in healthcare informatics.Journal of Healthcare Informatics Research is concerned with the application of computer science principles, information science principles, information technology, and communication technology to address problems in healthcare, and everyday wellness. Journal of Healthcare Informatics Research highlights the most cutting-edge technical contributions in computing-oriented healthcare informatics. The journal covers three major tracks: (1) analytics—focuses on data analytics, knowledge discovery, predictive modeling; (2) systems—focuses on building healthcare informatics systems (e.g., architecture, framework, design, engineering, and application); (3) human factors—focuses on understanding users or context, interface design, health behavior, and user studies of healthcare informatics applications. Topics include but are not limited to: · healthcare software architecture, framework, design, and engineering;· electronic health records· medical data mining· predictive modeling· medical information retrieval· medical natural language processing· healthcare information systems· smart health and connected health· social media analytics· mobile healthcare· medical signal processing· human factors in healthcare· usability studies in healthcare· user-interface design for medical devices and healthcare software· health service delivery· health games· security and privacy in healthcare· medical recommender system· healthcare workflow management· disease profiling and personalized treatment· visualization of medical data· intelligent medical devices and sensors· RFID solutions for healthcare· healthcare decision analytics and support systems· epidemiological surveillance systems and intervention modeling· consumer and clinician health information needs, seeking, sharing, and use· semantic Web, linked data, and ontology· collaboration technologies for healthcare· assistive and adaptive ubiquitous computing technologies· statistics and quality of medical data· healthcare delivery in developing countries· health systems modeling and simulation· computer-aided diagnosis