The feasibility of using remote data collection tools in field surveys
DOI:
https://doi.org/10.18203/2394-6040.ijcmph20175514Keywords:
Data Collection, Internet, Medical records systems, Software, Mobile phonesAbstract
Background: The objectives of the study were to conduct a field survey to measure the prevalence of chronic diseases by taking history, to assess the feasibility of using remote data collection tools in field surveys and to create the map of the survey area using global positioning system (GPS).
Methods: A community survey was carried out in two urban municipal wards by trainees with medical sociology back ground among those aged 35 years and above. There were a total of 563 participants from whom history of chronic diseases were collected and from those aged 60 years and above the presence of frailty was assessed using Canadian Study of Health and Ageing (CSHA) Clinical Frailty Scale. The data was collected using a remote data collection application named KoBo Toolbox, downloaded in their smart phones, which was sent directly to the main computer in the Clinical Epidemiological Unit, using mobile data or Wi-Fi hotspots. The co-ordinates of the households were marked using GPS which was also sent through the KoBo Toolbox to the main computer. At the centre the data was converted into excel sheets and various percentages were calculated.
Results: In the survey the proportion affected with diabetes, hypertension, coronary artery disease and cerebrovascular accidents were 24%, 20.6%, 10.5% and 3.5% respectively. Among the older population 2.2% were found to be severely frail or worse requiring special care. The field map of the area surveyed was also generated using the co-ordinates marked using the GPS enabled phones.
Conclusions: The remote data collection tool enabled us to conduct a survey on chronic diseases, effectively, within a limited period of time, creating a map of the area surveyed.
References
Suchman L, Jordan B. Interactional Troubles in Face-to-Face Survey Interviews. J Am Stat Assoc. 1990;85(409):232–41.
Rockwood K, Song X, MacKnight C, Bergman H, Hogan DB, McDowell I, et al. A global clinical measure of fitness and frailty in elderly people. CMAJ Can Med Assoc J. 2005;173(5):489–95.
Gregorevic KJ, Hubbard RE, Katz B, Lim WK. The clinical frailty scale predicts functional decline and mortality when used by junior medical staff: a prospective cohort study. BMC Geriatr. 2016;16:117.
Harvard Humanitarian Initiative. KoBoToolbox: Data Collection Tools for Challenging Environments. KoBo Toolbox. Available at: http://www.kobotoolbox.org/. Accessed on 4 August 2017.
Deniau C, Gaillard T, Mbagogo A, Réounodji F, Le Bel S. Using the KoBoCollect tool to analyze the socio-economic and socio-cultural aspects of commercial hunting and consumption of migratory waterbirds in the Lakes Chad and Fitri (Chad). In: Conference proceedings of 2017 EFITA WCCA congress: European conference dedicated to the future use of ICT in the agri-food sector, bioresource and biomass sector. Available at: http://www.efita2017.org/proceedings/. Accessed on 4 August 2017.
Hamer MJM, Reed PL, Greulich JD, Charles W. Beadling MD. Liberia national disaster preparedness coordination exercise: Implementing lessons learned from the West African disaster preparedness initiative. Am J Disaster Med. 2017;12(1):35–41.
Rajan SI. Aging in Kerala: one more population problem? POPLINE.org. Asia-Pac Popul J. 1989;4(2):19–48.
Gulati L, Rajan SI. The Added Years: Elderly in India and Kerala. Econ Polit Wkly. 1999;34(44): 46-51.
Thomas MB, James KS. Changes in mortality and human longevity in Kerala: are they leading to the advanced stage? Glob Health Action. 2014.
Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Lond Engl. 2017;390(10100):1084–150.
Pushpangadan K. Remittances, consumption and economic growth in Kerala : 1800-2000. 2003; Available at: https://opendocs.ids.ac.uk/opendocs/ handle/123456789/3038. Accessed on 4 August 2017.
Rajan SI. From Kerala to the Gulf: Impacts of Labor Migration. Asian Pac Migr J. 2004;13(4):497–509.
Ministry of Consumer Affairs, Food and Public Distribution. Press Information Bureau, Government of India. 2017. Available at: http://pib.nic.in/newsite/mbErel.aspx?relid=158329
Cyriac S, Sam V, Jacob N. The PDS system in Kerala: A review. CCS Working Paper; 2008.
Ministry of Health & Family Welfare. Rashtriya Swasthya Bima Yojana. 2017. Available at: http://www.rsby.gov.in/Statewise.aspx?state=27. Accessed on 4 August 2017.
National Informatics Centre, Pathanamthitta. Pathanamthitta - Statistics. Pathanamthitta District Official Website. Available at: http://pathanamthitta. nic.in/statistics/statistics.html
Sathish T, Oldenburg B, Tapp RJ, Shaw JE, Wolfe R, Sajitha B, et al. Baseline characteristics of participants in the Kerala Diabetes Prevention Program: a cluster randomized controlled trial of lifestyle intervention in Asian Indians. Diabet Med. 2017;34(5):647–53.
Kutty VR, Joseph A, Soman CR. High Prevalence of Type 2 Diabetes in an Urban Settlement in Kerala, India. Ethn Health. 1999;4(4):231–9.
Menon VU, Kumar KV, Gilchrist A, Sugathan TN, Sundaram KR, Nair V, et al. Prevalence of known and undetected diabetes and associated risk factors in central Kerala—ADEPS. Diabetes Res Clin Pract. 2006;74(3):289–94.
Kutty VR, Soman RC, Joseph A, Pisharody R, Vijayakumar K. Type 2 diabetes in southern Kerala: Variation in prevalence among geographic divisions within a region. Natl Med J India. 2000;13(6):287-92.
McBean AM, Li S, Gilbertson DT, Collins AJ. Differences in Diabetes Prevalence, Incidence, and Mortality Among the Elderly of Four Racial/Ethnic Groups: Whites, Blacks, Hispanics, and Asians. Diabetes Care. 2004;27(10):2317–24.
King H, Aubert RE, Herman WH. Global Burden of Diabetes, 1995–2025: Prevalence, numerical estimates, and projections. Diabetes Care. 1998;21(9):1414–31.
Indian Council of Medical Research, Public Health Foundation of India, Institute for Health Metrics and Evaluation. India: Health of the Nation’s States The India State-Level Disease Burden Initiative. New Delhi, India: ICMR, PHFI, IHME; 2017. Available at: http://icmr.nic.in/publications/India_Health_ of_the_Nation%27s_States_Report_2017.pdf. Accessed on 4 August 2017.
Thankappan KR, Sivasankaran S, Sarma PS, Mini G, Khader SA, Padmanabhan P, et al. Prevalence-correlates-awareness-treatment and control of hypertension in kumarakom, kerala: baseline results of a community-based intervention program. Indian Heart J. 2006;58(1):28–33.
G Zachariah M, Thankappan KR, C Alex S, Sarma P, S Vasan R. Prevalence, correlates, awareness, treatment, and control of hypertension in a middle-aged urban population in Kerala. Indian Heart J. 2003;55:245–51.
Vimala A, Ranji SA, Jyosna MT, Chandran V, Mathews SR, Pappachan JM. The prevalence, risk factors and awareness of hypertension in an urban population of Kerala (South India). Saudi J Kidney Dis Transplant. 2009;20(4):685.