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An integrative framework for sensor-based measurement of teamwork in healthcare.
Rosen, Michael A; Dietz, Aaron S; Yang, Ting; Priebe, Carey E; Pronovost, Peter J.
Affiliation
  • Rosen MA; The Armstrong Institute for Patient Safety and Quality, Baltimore, Maryland, USA Department of Anesthesiology and Critical Care Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
  • Dietz AS; The Armstrong Institute for Patient Safety and Quality, Baltimore, Maryland, USA.
  • Yang T; The Armstrong Institute for Patient Safety and Quality, Baltimore, Maryland, USA.
  • Priebe CE; The Whiting School of Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
  • Pronovost PJ; The Armstrong Institute for Patient Safety and Quality, Baltimore, Maryland, USA Department of Anesthesiology and Critical Care Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
J Am Med Inform Assoc ; 22(1): 11-8, 2015 Jan.
Article in En | MEDLINE | ID: mdl-25053579
ABSTRACT
There is a strong link between teamwork and patient safety. Emerging evidence supports the efficacy of teamwork improvement interventions. However, the availability of reliable, valid, and practical measurement tools and strategies is commonly cited as a barrier to long-term sustainment and spread of these teamwork interventions. This article describes the potential value of sensor-based technology as a methodology to measure and evaluate teamwork in healthcare. The article summarizes the teamwork literature within healthcare, including team improvement interventions and measurement. Current applications of sensor-based measurement of teamwork are reviewed to assess the feasibility of employing this approach in healthcare. The article concludes with a discussion highlighting current application needs and gaps and relevant analytical techniques to overcome the challenges to implementation. Compelling studies exist documenting the feasibility of capturing a broad array of team input, process, and output variables with sensor-based methods. Implications of this research are summarized in a framework for development of multi-method team performance measurement systems. Sensor-based measurement within healthcare can unobtrusively capture information related to social networks, conversational patterns, physical activity, and an array of other meaningful information without having to directly observe or periodically survey clinicians. However, trust and privacy concerns present challenges that need to be overcome through engagement of end users in healthcare. Initial evidence exists to support the feasibility of sensor-based measurement to drive feedback and learning across individual, team, unit, and organizational levels. Future research is needed to refine methods, technologies, theory, and analytical strategies.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Patient Care Team / Task Performance and Analysis Type of study: Prognostic_studies Limits: Humans Language: En Journal: J Am Med Inform Assoc Journal subject: INFORMATICA MEDICA Year: 2015 Document type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Patient Care Team / Task Performance and Analysis Type of study: Prognostic_studies Limits: Humans Language: En Journal: J Am Med Inform Assoc Journal subject: INFORMATICA MEDICA Year: 2015 Document type: Article Affiliation country: United States