A Pathophysiological Model-Driven Communication for Dynamic Distributed Medical Best Practice Guidance Systems.

There is a great divide between rural and urban areas, particularly in medical emergency care. Although medical best practice guidelines exist and are in hospital handbooks, they are often lengthy and difficult to apply clinically. The challenges are exaggerated for doctors in rural areas and emerge...

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Publicado en:Journal of Medical Systems Vol. 40; no. 11; pp. 1 - 18
Autores principales: Hosseini, Mohammad, Jiang, Yu, Wu, Poliang, Berlin, Richard, Ren, Shangping, Sha, Lui
Formato: pictorial tables/charts Journal Article
Publicado: Springer Nature Nov2016
Acceso en línea:Ver este registro en EBSCOhost
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s10916-016-0583-5
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        atl: A Pathophysiological Model-Driven Communication for Dynamic Distributed Medical Best Practice Guidance Systems.
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        au:
          Hosseini, Mohammad
          Jiang, Yu
          Wu, Poliang
          Berlin, Richard
          Ren, Shangping
          Sha, Lui
        affil: Department of Computer Science , University of Illinois at Urbana-Champaign , Urbana USA
      sug:
        subj:
          Hospitals, Rural
          Practice Guidelines
          Electronic Data Interchange
          Transportation of Patients
          Emergency Medical Technicians
          Stroke Patients
          Emergency Care
          Systems Design
          Communication Protocols
          Data Security
      ab: There is a great divide between rural and urban areas, particularly in medical emergency care. Although medical best practice guidelines exist and are in hospital handbooks, they are often lengthy and difficult to apply clinically. The challenges are exaggerated for doctors in rural areas and emergency medical technicians (EMT) during patient transport. In this paper, we propose the concept of distributed executable medical best practice guidance systems to assist adherence to best practice from the time that a patient first presents at a rural hospital, through diagnosis and ambulance transfer to arrival and treatment at a regional tertiary hospital center. We codify complex medical knowledge in the form of simplified distributed executable disease automata, from the thin automata at rural hospitals to the rich automata in the regional center hospitals. However, a main challenge is how to efficiently and safely synchronize distributed best practice models as the communication among medical facilities, devices, and professionals generates a large number of messages. This complex problem of patient diagnosis and transport from rural to center facility is also fraught with many uncertainties and changes resulting in a high degree of dynamism. A critically ill patient's medical conditions can change abruptly in addition to changes in the wireless bandwidth during the ambulance transfer. Such dynamics have yet to be addressed in existing literature on telemedicine. To address this situation, we propose a pathophysiological model-driven message exchange communication architecture that ensures the real-time and dynamic requirements of synchronization among distributed emergency best practice models are met in a reliable and safe manner. Taking the signs, symptoms, and progress of stroke patients transported across a geographically distributed healthcare network as the motivating use case, we implement our communication system and apply it to our developed best practice automata using laboratory simulations. Our proof-of-concept experiments shows there is potential for the use of our system in a wide variety of domains.
      pubtype: Academic Journal
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        pictorial
        tables/charts
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      ougenre: Article
    language: English
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