A Development Methodology for a Stroke Rehabilitation Monitoring Application

Pilar Mata, Craig Kuziemsky, Liam Peyton

2016

Abstract

The capabilities of mobile devices (e.g. flexibility, portability, and the ability to retrieve information quickly) have been leveraged for the development of clinical performance monitoring applications. In this paper we assess the suitability of a methodology for development of clinical performance monitoring applications to support stroke rehabilitation. We use a case study, with two use cases of patients recovering from stroke events, to design a monitoring application at a conceptual level and compare it to other clinical performance monitoring applications.

References

  1. Avison, D., & Young, T. (2007). Time to rethink health care and ICT? Commun.ACM, 50(6), 69-74.
  2. Baarah, A., Mouttham, A., & Peyton, L. (2012). Architecture of an event processing application for monitoring cardiac patient wait times. International Journal of Information Technology and Web Engineering (IJITWE), 7(1), 1-16.
  3. Brown, A. W., Therneau, T. M., Schultz, B. A., Niewczyk, P. M., & Granger, C. V. (2015). Measure of functional independence dominates discharge outcome prediction after inpatient rehabilitation for stroke. Stroke; a Journal of Cerebral Circulation, 46(4), 1038-1044.
  4. Chamney, A., Mata, P., Viner, G., Archibald, D., & Peyton, L. (2014). Development of a resident practice profile in a business intelligence application framework. ICTH-2014, Halifax, Canada.
  5. Chukmaitov, A., Harless, D. W., Bazzoli, G. J., Carretta, H. J., & Siangphoe, U. (2014). Delivery system characteristics and their association with quality and costs of care. Health Care Management Review, 40(2), 92-103.
  6. Cifu, D. X., & Stewart, D. G. (1999). Factors affecting functional outcome after stroke. Archives of physical medicine and rehabilitation, 80(5), S35-S39.
  7. Duncan, P. W., Zorowitz, R., Bates, B., Choi, J. Y., Glasberg, J. J., . . . Reker, D. (2005). Management of adult stroke rehabilitation care. Stroke; a Journal of Cerebral Circulation, 36(9), e100.
  8. Ferenchick, G. S., Foreback, J., Towfiq, B., Kavanaugh, K., Solomon, D., & Mohmand, A. (2010). The implementation of a mobile problem-specific electronic CEX for assessing directly observed student-patient encounters. Medical Education Online, 15.
  9. Ferenchick, G. S., & Solomon, D. (2013). Using cloudbased mobile technology for assessment of competencies among medical students. PeerJ, 1, e164.
  10. Gresham, G. E., Duncan, P. W., & Stason, W. B. (1997). Post-stroke rehabilitation DIANE Publishing.
  11. IOM (Institute of Medicine). (2012). Health IT patient safety: Building safer systems for better care. Washington DC: The National Academic Press.
  12. Kimball, R. (2013). The data warehouse toolkit,(3rd ed.). Indianapolis, Ind. Wiley.
  13. Kushniruk, A., Nohr, C., Jensen, S., & Borycki, E. M. (2013). From usability testing to clinical simulations. Yearbook of Medical Informatics, 8, 78-85.
  14. Kuziemsky, C. E. (2015). A model of tradeoffs for understanding health information technology implementation. Studies in Health Technology and Informatics, 215:116-28.
  15. Mata, P., Chamney, A., Viner, G., Archibald, D., & Peyton, L. (2015). A development framework for mobile healthcare monitoring apps. Personal and Ubiquitous Computing, 19(3-4), 623-633.
  16. Novak, L., Brooks, J., Gadd, C., Anders, S., & Lorenzi, N. (2012). Mediating the intersections of organizational routines during the introduction of a health IT system. European Journal of Information Systems, 21(5), 552- 569.
  17. Vincent, C., Burnett, S., & Carthey, J. (2014). Safety measurement and monitoring in healthcare: A framework to guide clinical teams and healthcare organisations in maintaining safety. BMJ Quality & Safety, 23(8), 670-677.
  18. Vredenburg, K., Mao, J., Smith, P. W., & Carey, T. (2002). A survey of user-centered design practice. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 471-478.
  19. Xu, B., Xu, L., Cai, H., Jiang, L., Luo, Y., & Gu, Y. (2015). The design of an m-health monitoring system based on a cloud computing platform. Enterprise Information Systems, 1-20.
Download


Paper Citation


in Harvard Style

Mata P., Kuziemsky C. and Peyton L. (2016). A Development Methodology for a Stroke Rehabilitation Monitoring Application . In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, (BIOSTEC 2016) ISBN 978-989-758-170-0, pages 400-405. DOI: 10.5220/0005785104000405


in Bibtex Style

@conference{healthinf16,
author={Pilar Mata and Craig Kuziemsky and Liam Peyton},
title={A Development Methodology for a Stroke Rehabilitation Monitoring Application},
booktitle={Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, (BIOSTEC 2016)},
year={2016},
pages={400-405},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005785104000405},
isbn={978-989-758-170-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, (BIOSTEC 2016)
TI - A Development Methodology for a Stroke Rehabilitation Monitoring Application
SN - 978-989-758-170-0
AU - Mata P.
AU - Kuziemsky C.
AU - Peyton L.
PY - 2016
SP - 400
EP - 405
DO - 10.5220/0005785104000405