User-Centered Design of Pervasive Healthcare Applications

Research Article

Optimizing Long-Term Treatment of Rheumatoid Arthritis with Systematic Documentation

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  • @INPROCEEDINGS{10.4108/icst.pervasivehealth.2011.246087,
        author={Klaus Simonic and Andreas Holzinger and Marcus Bloice and Josef Hermann},
        title={Optimizing Long-Term Treatment of Rheumatoid Arthritis with Systematic Documentation},
        proceedings={User-Centered Design of Pervasive Healthcare Applications},
        publisher={IEEE},
        proceedings_a={U-CDPHA},
        year={2012},
        month={4},
        keywords={Clinical Information Systems Decision Support Patient Empowerment Longitudinal Data Analysis},
        doi={10.4108/icst.pervasivehealth.2011.246087}
    }
    
  • Klaus Simonic
    Andreas Holzinger
    Marcus Bloice
    Josef Hermann
    Year: 2012
    Optimizing Long-Term Treatment of Rheumatoid Arthritis with Systematic Documentation
    U-CDPHA
    IEEE
    DOI: 10.4108/icst.pervasivehealth.2011.246087
Klaus Simonic1,*, Andreas Holzinger1, Marcus Bloice1, Josef Hermann1
  • 1: Medical University Graz
*Contact email: klaus.simonic@medunigraz.at

Abstract

About 1% of the population suffers from rheumatoid arthritis. They not only experience pain, but during the course of the disease their mobility is reduced due to a deterioration of their joints. To retard this destructive process an assortment of drugs are available today, however, for optimal results both medication and dosage have to be tailored for each individual patient. RCQM is a clinical information system that moderates this process: within the confines of the examination routine, physicians gather more than 100 clinical and functional parameters (time needed < 10 minutes). The amassed data are morphed into more useable information by applying scoring algorithms (e.g. Disease Activity Score (DAS), Health Assessment Questionnaire (HAQ)), which is subsequently interpreted as a function of time. The resulting DAS trends and patterns are ultimately used for treatment optimization and as a measure for the quality of patient outcome. Graphical data acquisition and information visualization support the entire interaction between doctor and patient. Both are equally informed of the course of the disease and, in practice, treatment decisions are made jointly. The task of documentation becomes an integral part of the dialog with the patient. This yields an increased level of decision quality, higher compliance, and verifiable patient empowerment.