BioMed Wizard - An Approach for Gathering Personal Risk Factor Data

Mohammad Shafahi, Hamideh Afsarmanesh, Stefan Paap

2016

Abstract

People can be at risk of developing some serious diseases without being aware of it. Such diseases either do not present symptoms in early stages or have simple symptoms that are ignored or not properly identified by patients, due to their lack of medical know-how. On the other hand, in order to provide patients with early indications of their risk level on developing such diseases, specially for chronic diseases such as diabetes type 2, it is necessary to collect substantial amount of personal data about risk factors related to the disease. A smart wizard software applying the approach developed in our study, which brings awareness about some socio-economical concerns of patients, can increase patients’ engagement in providing their personal data. The case study focuses on the diabetes type 2 and some socio-economical concerns of patients, including privacy invasion, time, and cost. In this research, the willingness of a sample group of more than 100 people is surveyed, in providing their personal data, for three different scenarios and related to nine main risk factors. The results collected in this survey is then applied to develop four user-specific data collection flow models, to be implemented in a smart wizard software.

References

  1. Abbasi, A., Peelen, L. M., Corpeleijn, E., van der Schouw, Y. T., Stolk, R. P., Spijkerman, A. M., Moons, K. G., Navis, G., Bakker, S. J., Beulens, J. W., et al. (2012). Prediction models for risk of developing type 2 diabetes: systematic literature search and independent external validation study. Bmj, 345:e5900.
  2. Adler-Milstein, J., DesRoches, C. M., Furukawa, M. F., Worzala, C., Charles, D., Kralovec, P., Stalley, S., and Jha, A. K. (2014). More than half of us hospitals have at least a basic ehr, but stage 2 criteria remain challenging for most. Health Affairs, pages 10-1377.
  3. Baan, C. A., Ruige, J. B., Stolk, R. P., Witteman, J., Dekker, J. M., Heine, R. J., and Feskens, E. (1999). Performance of a predictive model to identify undiagnosed diabetes in a health care setting. Diabetes care, 22(2):213-219.
  4. Beckjord, E. B., Rechis, R., Nutt, S., Shulman, L., and Hesse, B. W. (2011). What do people affected by cancer think about electronic health information exchange? results from the 2010 livestrong electronic health information exchange survey and the 2008 health information national trends survey. Journal of Oncology Practice, 7(4):237-241.
  5. Dörnyei, Z. and Taguchi, T. (2010). Questionnaires in second language research: Construction, administration, and processing. Routledge.
  6. Ferreira, A. M., Tziortzios, C., and Shafahi, M. (2011). Passwords awareness in the academic world. Technical report, University of Amsterdam.
  7. Fink, A. (2012). How to conduct surveys: A step-by-step guide. Sage Publications.
  8. Harris, M. I. (2001). Racial and ethnic differences in health care access and health outcomes for adults with type 2 diabetes. Diabetes care, 24(3):454-459.
  9. Hartemink, N., Boshuizen, H. C., Nagelkerke, N. J., Jacobs, M. A., and van Houwelingen, H. C. (2006). Combining risk estimates from observational studies with different exposure cutpoints: a meta-analysis on body mass index and diabetes type 2. American journal of epidemiology, 163(11):1042-1052.
  10. Hivert, M.-F., Grant, R. W., Shrader, P., and Meigs, J. B. (2009). Identifying primary care patients at risk for future diabetes and cardiovascular disease using electronic health records. BMC health services research, 9(1):170.
  11. Jha, A. K., DesRoches, C. M., Campbell, E. G., Donelan, K., Rao, S. R., Ferris, T. G., Shields, A., Rosenbaum, S., and Blumenthal, D. (2009). Use of electronic health records in us hospitals. New England Journal of Medicine, 360(16):1628-1638.
  12. Khan, A., Doucette, J. A., Cohen, R., and Lizotte, D. (2012). A hybrid design for medical decision support using data mining to impute missing data.
  13. Knowler, W. C., Barrett-Connor, E., Fowler, S. E., Hamman, R. F., Lachin, J. M., Walker, E. A., and Nathan, D. M. (2002). Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. The New England journal of medicine, 346(6):393.
  14. Lindström, J. and Tuomilehto, J. (2003). The diabetes risk score a practical tool to predict type 2 diabetes risk. Diabetes care, 26(3):725-731.
  15. Mayo Clinic (2015). Risk factors type 2 diabetes risk factors. http://www.mayoclinic.org/diseasesconditions/type-2-diabetes/basics/risk-factors/con20031902. Accessed: 2015, May 21.
  16. Montonen, J., Knekt, P., Järvinen, R., and Reunanen, A. (2004). Dietary antioxidant intake and risk of type 2 diabetes. Diabetes Care, 27(2):362-366.
  17. Pickard, K. T. and Swan, M. (2014). Big desire to share big health data: A shift in consumer attitudes toward personal health information. In 2014 AAAI Spring Symposium Series.
  18. Prince, S. A., Adamo, K. B., Hamel, M. E., Hardt, J., Gorber, S. C., and Tremblay, M. (2008). A comparison of direct versus self-report measures for assessing physical activity in adults: a systematic review. International Journal of Behavioral Nutrition and Physical Activity, 5(1):56.
  19. Rijksinstituut voor Volksgezondheid en Milieu (2013). Welke factoren beinvloeden de kans op diabetes mellitus? welke factoren benvloeden de kans op diabetes mellitus? - nationaal kompas volksgezondheid. http:// www.nationaalkompas.nl/gezondheid-en-ziekte/ ziekten-en-aandoeningen/endocriene-voedings-enstofwisselingsziekten-en-immuniteitsstoornissen/ diabetes-mellitus/welke-factoren-beinvloeden-dekans-op-diabetes-mellitus. Accessed: 2015, May 21.
  20. Shephard, R. J. (2003). Limits to the measurement of habitual physical activity by questionnaires. British journal of sports medicine, 37(3):197-206.
  21. Teixeira, P. A., Gordon, P., Camhi, E., and Bakken, S. (2011). Hiv patients willingness to share personal health information electronically. Patient education and counseling, 84(2):e9-e12.
  22. Tirosh, A., Shai, I., Afek, A., Dubnov-Raz, G., Ayalon, N., Gordon, B., Derazne, E., Tzur, D., Shamis, A., Vinker, S., et al. (2011). Adolescent bmi trajectory and risk of diabetes versus coronary disease. New England Journal of Medicine, 364(14):1315-1325.
  23. Wei, J.-N., Sung, F.-C., Lin, C.-C., Lin, R.-S., Chiang, C.-C., and Chuang, L.-M. (2003). National surveillance for type 2 diabetes mellitus in taiwanese children. Jama, 290(10):1345-1350.
  24. World Health Organization (2014). Global health estimates: Deaths by cause, age, sex and country, 2000-2012. Geneva, WHO.
  25. Xierali, I. M., Hsiao, C.-J., Puffer, J. C., Green, L. A., Rinaldo, J. C., Bazemore, A. W., Burke, M. T., and Phillips, R. L. (2013). The rise of electronic health record adoption among family physicians. The Annals of Family Medicine, 11(1):14-19.
  26. Zhang, J. and Zhao, Y. (2013). A user term visualization analysis based on a social question and answer log. Information Processing & Management, 49(5):1019- 1048.
Download


Paper Citation


in Harvard Style

Shafahi M., Afsarmanesh H. and Paap S. (2016). BioMed Wizard - An Approach for Gathering Personal Risk Factor Data . 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 298-305. DOI: 10.5220/0005701102980305


in Bibtex Style

@conference{healthinf16,
author={Mohammad Shafahi and Hamideh Afsarmanesh and Stefan Paap},
title={BioMed Wizard - An Approach for Gathering Personal Risk Factor Data},
booktitle={Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, (BIOSTEC 2016)},
year={2016},
pages={298-305},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005701102980305},
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 - BioMed Wizard - An Approach for Gathering Personal Risk Factor Data
SN - 978-989-758-170-0
AU - Shafahi M.
AU - Afsarmanesh H.
AU - Paap S.
PY - 2016
SP - 298
EP - 305
DO - 10.5220/0005701102980305