How To Use A Paper Questionnaire With A Computer Or Tablet (Or Both)

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1 Public Health Computing Dept. Epidemiology & Public Health Tablet computers and Open Data Kit for electronic data capture Nicolas Maire, Sven Meury Andreas Steiner

2 Outline Open Data Kit (ODK) ODK extensions 20 March

3 Electronic data capture as a replacement for paper questionnaires Guidance for interviewer Skip logic Input constraints Adequate data storage (1-N relationships) Potential cost savings Printing, copying, shipping, archiving paper Data entry, cleaning Requirement by some funders Near-time availability of data Secure and central storage 20 March

Potential cost savings Printing, copying, shipping, archiving paper Data entry,

4 Technology options A dynamic field Episurveyor (Palm, J2ME), openxdata (J2ME), EpiCollect (ios, Android), Open Data Kit (ODK) Open source software suite (Univ. Washington, Google.org) Large user community, active developer community (including Swiss TPH) Open standard compliant Android phones or tablets 20 March

5 Open Data Kit: Architecture and Workflow ODK Build/ XLSForm ODK Collect Publish form Download Form Upload Data ODK Aggregate Server

6 Questionnaire design Excel as a master form definition Intuitive and simple, but powerful through optional definitions Transformation to renderable XForm

7 Case study: FEVERKIN (2011) Cross sectional urban malaria survey in the city of Kinshasa, DRC Possession and use of bed nets 7 days training / 2 days pre-testing / 30 days data collection 8 teams (1 interviewer and 1 lab technician each) >2500 HH interviewed GPS coordinates of all HH 20 March

days pre-testing / 30 days data collection 8 teams (1 interviewer and 1

8 Data collection 20 March

9 Swiss TPH ODK projects 20 March

10 Feedback from project teams Challenges Requires infrastructure (mobile devices and server) Requires more careful planning Dependence on expert IT support Advantages Fast and efficient way to collect data Better quality data 20 March

careful planning Dependence on expert IT support Advantages

11 What s the evidence? Some: Studies comparing costs, time/delay, reliability of various electronic data capture methodologies indicate advantages or non-inferiority Shortcomings: Lack of good studies to compare data quality against traditional paper-based forms Study comparing tablets and paper (Giduthuri et al. 2014)

data capture methodologies indicate advantages or non-inferiority Shortcomings:

12 ODK validation study EMIC (Explanatory Model Interview Catalogue) interview for influenza vaccine acceptance 3 teams of 2 conducting 96 interviews with both paper and tablet devices Field work in Pune, India Debriefing assessment of interviewers experience in administering the interview with given device Tablet-paper discrepancy analysis with reference to authoritative voice recording

Field work in Pune, India Debriefing assessment of interviewers experience in administering the

13 Recurring roles for each of the field research assistants over the course of the study This cycle of respective roles in each interview repeats for the two field research assistants on each team using paper (P) or tablet (T) device, and functioning as interviewer (Lead, L) or follower (coder only, F).

the two field research assistants on each team using paper (P) or tablet

14 Results (Discoverable) error rates comparable for tablet and paper (2%) Interviewers indicate either no preference, or prefer tablet Tablets more cost-effective if sample size > 100 Additional objective: to acquire experience with qualitative data, using available features of hand writing recognition

cost-effective if sample size > 100 Additional objective: to acquire

15 ODK and qualitative research Workflow integration with analysis software possible (MAXQDA), with room for further improvements Data capture a challenge Strategies for direct digitization of notes (eliminating paper) Strategies for more efficient processing of audio recordings (e.g. timestamps, automated transcription) An interesting field for applied research

direct digitization of notes (eliminating paper) Strategies for more efficient processing

16 Beyond the paper-questionnaire analogy Additional data types (GPS, barcodes, diagnostic devices, time stamps ) Support for system-wide unique ids Near-time quality control (openhds & su2) Monitoring and planning (su2 & ODK_planner) An active field of development with a growing number of service providers

Near-time quality control (openhds & su2) Monitoring and planning (su2 &

17 ODK: beyond cross-sectional surveys Longitudinal follow-up requires extension of the ODK system (at present) In particular, system-wide, referencable ids are a key requirement Our (and others) approach is integration of ODK with other software components

particular, system-wide, referencable ids are a key requirement

18 Health and Demographic Surveillance Systems (HDSS) openhds A set of field and computing operations to handle the longitudinal follow-up of well-defined entities or primary subjects (individuals, households, and residential units) and all related demographic and health outcomes within a clearly circumscribed geographic area 46 HDSS sites for INDEPTH over 46 years Primary goal can be routine surveillance in the absence of a vital registration system Platform to provide essential denominator data for epidemiological and demographic research In 24 countries Each with unique health systems An operational challenge, in particular the data management A functional data collection and management platform is a key requirement: OpenHDS

19 Open Data Kit: Architecture and Workflow ODK Build/ XLSForm ODK Collect Publish form Download Form Upload Data ODK Aggregate Server

20 openhds/odk integration ODK Build XLSForm OpenHDS Mobile Download Form ODK Aggregate Server Publish form Sync Data Upload Data Download/ Update Location Information openhds

21 SOLARMAL HDSS experience Rusinga Island First update completed 2 days before 2nd annual SOLARMAL workshop Data presented at workshop BUT: Suspected issues with data quality

22 Su2: the surveillance surveillant Demo

23 odk_planner History Bagamoyo, Tanzania : paper-based forms Long delays for data capture, difficult overview Started using ODK for all data entry Missing parts: implemented odk_planner Outline 1. Overview ODK/odk_planner 2. TB-Dar study 3. TB-Pharm study 4. Availability 5. Live demo

24 odk_planner : Overview Study planning Data review Build forms ODK Collect Data Upload Aggregate MySQL Database odk_planner SMS reminder

25 odk_planner : Why? Planning! TB-Dar study Tuberculosis cohort 500 cases per year, + controls 21 forms, complicated flow Doctors, field workers, secretaries, X-rays, CRFs, lab results, ODK Aggregate odk_planner: Study planning

26 odk_planner : Why? Automation! Pharmacy TB Clinic Patient referral Study center Data Data no show : automatic SMS reminder

27 odk_planner : How? 1) Find it odk_planner 2) Read Open source code Extensive documentation 3) Apply TPH : Experimental add-on service for ODK instances, just ask Use it, extend it!

28 odk_planner : Live demo Username: demo Password: ODKTPH Non-admin features Colored overview See some data Download/upload forms Help

29 Swiss TPH: requesting ODK hosting and support Order by mail to Meaningful subject (e.g. Application for ODK server) Order as early as possible Required information Project name Project name abbreviation (up to 12 alphanumeric characters) Cost center Starting date of the project Expected end date of project

30 What is included in the service An URL to send your data to A trusted SSL certificate to keep the data transfer securely Unlimited server space Daily backup of your server based ODK data Setup and maintenance of your ODK instance Costs for setup maintenance per year Setup + maintenance for the first year

31 Process Ticket is reviewed (check for completeness) Approval request to cost center owner Database setup by IT ODK instance setup by Public Health Computing group Default 2 users: Form Manager + Data collector Invoice Tablets Separate order by mail to helpdesk-tph@unibas.ch Requirements of the tablets (display size, mobile broadband module 3G/4G) Specific model (normally only available for short time)

32 Advisory capacity Depending on needs and capacity - Advisory support for form design and field processes - Support for data manipulation/export for data analysis Coming soon: odk_tph@unibas.ch Budget!

33 Acknowlegdements A. Di Pasquale, R. Mitra, J. Giduthuri, M. Weiss, L. Fenner, J. Hella ODK core developers ODK Swiss TPH, in particular early adopters

MOBILE MEETS THE CLOUD

An Exploration of the Open Data Kit MOBILE MEETS THE CLOUD CalGIS 19 th Annual California GIS Conference April 15 th 17 th, 2013 Joseph Doherty Software Engineer Microdesk jdoherty@microdesk.com ABSTRACT