Preprint Article Version 1 NOT YET PEER-REVIEWED

ODK Scan: Digitizing Data Collection and Impacting Data Management Processes in the Tuberculosis Control Program of Pakistan

  1. Monitoring Evaluation and Learning Unit, Mercy Corps, Pak Palace, Murree Road, Rawal Chowk, Islamabad 44000, Pakistan
  2. Information Systems, Village Reach, Seattle, WA 98102, USA
  3. Computer Science and Engineering, University of Washington, Seattle, WA 98105, USA
Version 1 : Received: 30 August 2016 / Approved: 31 August 2016 / Online: 31 August 2016 (08:59:49 CEST)
Version 2 : Received: 1 September 2016 / Approved: 2 September 2016 / Online: 2 September 2016 (03:17:38 CEST)

A peer-reviewed article of this Preprint also exists.

Ali, S.M.; Powers, R.; Beorse, J.; Noor, A.; Naureen, F.; Anjum, N.; Ishaq, M.; Aamir, J.; Anderson, R. ODK Scan: Digitizing Data Collection and Impacting Data ManagementProcesses in Pakistan’s Tuberculosis Control Program. Future Internet 2016, 8, 51. Ali, S.M.; Powers, R.; Beorse, J.; Noor, A.; Naureen, F.; Anjum, N.; Ishaq, M.; Aamir, J.; Anderson, R. ODK Scan: Digitizing Data Collection and Impacting Data ManagementProcesses in Pakistan’s Tuberculosis Control Program. Future Internet 2016, 8, 51.

Journal reference: Future Internet 2016, 8, 51
DOI: 10.3390/fi8040051

Abstract

The present grievous situation of the tuberculosis disease can be improved by efficient case management and timely follow-up evaluations. With the advent of digital technology this can be achieved by quick summarization of the patient-centric data. The aim of our study was to assess the effectiveness of the ODK Scan paper-to-digital system during testing period of three months. A sequential, explanatory mixed-method research approach was employed to elucidate technology use. Training, smartphones, application and 3G enabled SIMs were provided to the four field workers. At the beginning, baseline measures of the data management aspects were recorded and compared with endline measures to see the impact of ODK Scan. Additionally, at the end, users’ feedback was collected regarding app usability, user interface design and workflow changes. 122 patients’ records were retrieved from the server and analysed for quality. It was found that ODK Scan recognized 99.2% of multiple choice bubble responses and 79.4% of numerical digit responses correctly. However, the overall quality of the digital data was decreased in comparison to manually entered data. Using ODK Scan, a significant time reduction is observed in data aggregation and data transfer activities, however, data verification and form filling activities took more time. Interviews revealed that field workers saw value in using ODK Scan, however, they were more concerned about the time consuming aspects of the use of ODK Scan. Therefore, it is concluded that minimal disturbance in the existing workflow, continuous feedback and value additions are the important considerations for the implementing organization to ensure technology adoption and workflow improvements.

Subject Areas

mHealth; ODK scan; mobile health application; digitizing data collection; data management processes; paper-to-digital system; technology-assisted data management; treatment adherence

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