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Data Quality: A Negotiator between Paper-Based and Digital Records in Pakistan’s TB Control Program

Author

Listed:
  • Syed Mustafa Ali

    (Mercy Corps, Islamabad 45550, Pakistan)

  • Farah Naureen

    (Mercy Corps, Islamabad 45550, Pakistan)

  • Arif Noor

    (Mercy Corps, Islamabad 45550, Pakistan)

  • Maged N. Kamel Boulos

    (Moray College, University of the Highlands and Islands, Elgin IV30 1JJ, Scotland, UK)

  • Javariya Aamir

    (Mercy Corps, Islamabad 45550, Pakistan)

  • Muhammad Ishaq

    (Mercy Corps, Islamabad 45550, Pakistan)

  • Naveed Anjum

    (Mercy Corps, Islamabad 45550, Pakistan)

  • John Ainsworth

    (Division of Informatics, Imaging & Data Sciences, University of Manchester, Manchester M13 9PT, UK)

  • Aamna Rashid

    (Mercy Corps, Islamabad 45550, Pakistan)

  • Arman Majidulla

    (Interactive Research and Development, Karachi 75300, Pakistan)

  • Irum Fatima

    (Mercy Corps, Islamabad 45550, Pakistan)

Abstract

Background: The cornerstone of the public health function is to identify healthcare needs, to influence policy development, and to inform change in practice. Current data management practices with paper-based recording systems are prone to data quality defects. Increasingly, healthcare organizations are using technology for the efficient management of data. The aim of this study was to compare the data quality of digital records with the quality of the corresponding paper-based records using a data quality assessment framework. Methodology: We conducted a desk review of paper-based and digital records over the study duration from April 2016 to July 2016 at six enrolled tuberculosis (TB) clinics. We input all data fields of the patient treatment (TB01) card into a spreadsheet-based template to undertake a field-to-field comparison of the shared fields between TB01 and digital data. Findings: A total of 117 TB01 cards were prepared at six enrolled sites, whereas just 50% of the records ( n = 59; 59 out of 117 TB01 cards) were digitized. There were 1239 comparable data fields, out of which 65% ( n = 803) were correctly matched between paper based and digital records. However, 35% of the data fields ( n = 436) had anomalies, either in paper-based records or in digital records. The calculated number of data quality issues per digital patient record was 1.9, whereas it was 2.1 issues per record for paper-based records. Based on the analysis of valid data quality issues, it was found that there were more data quality issues in paper-based records ( n = 123) than in digital records ( n = 110). Conclusion: There were fewer data quality issues in digital records as compared with the corresponding paper-based records of tuberculosis patients. Greater use of mobile data capture and continued data quality assessment can deliver more meaningful information for decision making.

Suggested Citation

  • Syed Mustafa Ali & Farah Naureen & Arif Noor & Maged N. Kamel Boulos & Javariya Aamir & Muhammad Ishaq & Naveed Anjum & John Ainsworth & Aamna Rashid & Arman Majidulla & Irum Fatima, 2018. "Data Quality: A Negotiator between Paper-Based and Digital Records in Pakistan’s TB Control Program," Data, MDPI, vol. 3(3), pages 1-16, July.
  • Handle: RePEc:gam:jdataj:v:3:y:2018:i:3:p:27-:d:158907
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    References listed on IDEAS

    as
    1. Hong Chen & David Hailey & Ning Wang & Ping Yu, 2014. "A Review of Data Quality Assessment Methods for Public Health Information Systems," IJERPH, MDPI, vol. 11(5), pages 1-38, May.
    2. Divorski, S. & Scheirer, M. A., 2001. "Improving data quality for performance measures: results from a GAO study of verification and validation," Evaluation and Program Planning, Elsevier, vol. 24(1), pages 83-94, February.
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