11th EAI International Conference on Pervasive Computing Technologies for Healthcare

Research Article

Application of I-COMO Device towards Geographic Disease Enrichment Pattern Revealed from Electronic Medical Record at A Large Urban Academic Medical Center

  • @INPROCEEDINGS{10.1145/3154862.3154913,
        author={Matteo Danieletto and Li Li and Joel Dudley},
        title={Application of I-COMO Device towards Geographic Disease Enrichment Pattern Revealed from Electronic Medical Record at A Large Urban Academic Medical Center},
        proceedings={11th EAI International Conference on Pervasive Computing Technologies for Healthcare},
        publisher={ACM},
        proceedings_a={PERVASIVEHEALTH},
        year={2018},
        month={1},
        keywords={environmental diseases electronic medical records iot lorawan network air pollution},
        doi={10.1145/3154862.3154913}
    }
    
  • Matteo Danieletto
    Li Li
    Joel Dudley
    Year: 2018
    Application of I-COMO Device towards Geographic Disease Enrichment Pattern Revealed from Electronic Medical Record at A Large Urban Academic Medical Center
    PERVASIVEHEALTH
    ACM
    DOI: 10.1145/3154862.3154913
Matteo Danieletto1, Li Li1,*, Joel Dudley1
  • 1: Institute for Next Generation Healthcare
*Contact email: li.li@mssm.edu

Abstract

For decades, the air pollution has been studied as key driver factor for uncountable number of diseases ranging from respiratory diseases to neoplasms. However, in each city, the effort to control the air quality is low. Plenty of studies report the importance of quality of air, but majority of them is based on outdoors air quality that do not consider or track people outside or inside a building. In this study, we have analyzed the largest electronic medical records (EMR) in New York City and air pollution data collected from environmental protection agency (EPA) to identify environmental diseases impacted by air pollution. We have identified that the different environmental diseases are significantly enriched to certain geographic areas influenced by surrounding environment. Therefore, using this data-driven approach, we are here to present a new Internet of Things network concept. The new architecture based on LoRaWAN has the objective to bypass most of the issues encountered in these years to collect patient data as well as to improve the telemedicine. At the same time, the network can open new scenario of crowdsourcing to improve the granularity of data collection. Third-party companies can use IoT infrastructure to test new devices and to integrate the existing data sets.