Skip to main content
Skip main navigation
No Access

A snapshot of data quality issues in Indonesian community health

Published Online:pp 280-297https://doi.org/10.1504/IJNVO.2014.065791

Healthcare services in Indonesia remain ‘poor’ by international standards. At the heart of the problem are systemic data quality issues. Little work has been done on health data quality in rural settings in this region. In this work, an exploratory study of data quality within a health centre (HC) in rural Indonesia is carried out with reference to two well-known sets of qualitative data quality measures AIMQ and PRISM. The research aims first to uncover data quality issues within a typical health facility in rural Indonesia, and second to discover whether these problems relate to operational issues. The research uses an inductive, qualitative case study approach using the following methodology. Key data quality issues are identified in the literature; these are used as a framework from which to develop seed questions for data collection via semi structured interviews. The full interview transcripts are analysed manually and using the text mining software Leximancer. Issues relating to data validation and integration are identified. Suggestions are put forward for development action both locally and nationally. This work provides a snapshot of the state of play in a typical rural health facility in Indonesia.

Keywords

health information systems, HIS, developing countries, PRISM, AIMQ, Leximancer, case study, data quality, Indonesia

References

  • 1. Aggelidis, V.P. , Chatzoglou, P.D. (2012). ‘Hospital information systems: measuring end user computing satisfaction (EUCS)’. J. Biomed. Inform.. 45, 3, 566-579 Google Scholar
  • 2. Aqil, A. , Lippeveld, T. , Hozumi, D. (2009). ‘PRISM framework: a paradigm shift for designing, strengthening and evaluating routine health information systems’. Health Policy and Planning. 24, 3, 217-228, %R 10.1093/heapol/czp010 Google Scholar
  • 3. Aung, E. , Whittaker, M. (2013). ‘Preparing routine health information systems for immediate health responses to disasters’. Health Policy and Planning. 28, 5, 495-507 Google Scholar
  • 4. Battulga, S. , Ajnai, L. , Purevbat, N. , Tsevelmaa, B. , Ochirbat, B. (2007). Establishment of Patients’ Information Database in Mongolia. Berlin, Heidelberg:Springer Google Scholar
  • 5. Dul, J. , Hak, T. (2008). Case Study Methodology in Business Research. Amsterdam:Elsevier, Butterworth-Heinemann Google Scholar
  • 6. E-Puskesmas (2011). e-Puskesmas Dalam Inaicta 2011. (accessed 10 May 2013), e-Puskesmas, [online] http://www.e-puskesmas.com/index.php?option=com_contentandamp;view=articleandamp;id=108:e-puskesmas-dalam-inaicta-2011andamp;catid=40:beritaandamp;Itemid=53 Google Scholar
  • 7. Hotchkiss, D.R. , Aqil, A. , Lippeveld, T. , Mukooyo, E. ‘Evaluation of the performance of routine information system management (PRISM) framework: evidence from Uganda’. BMC Health Services Research. 2010, 07, 10, 188, Google Scholar
  • 8. Husada, R. , Nguyen, L. (2012). ‘ICT alternative for primary care delivery in Indonesia: a proposal’. Proceedings of the 23rd Australasian Conference on Information Systems 2012, ACIS. Geelong, Vic., 1-7 Google Scholar
  • 9. Krishnan, A. , et al. ‘Evaluation of computerized health management information system for primary health care in rural India’. BMC Health Services Research. 2010, 11, 10, 310, Google Scholar
  • 10. Lee, Y.W. , Strong, D.M. , Beverley, K.K. , Richard, Y.W. (2002). ‘AIMQ: a methodology for information quality assessment’. Information and Management. 40, 2, 133-146 Google Scholar
  • 11. Liebscher, C. , Hui, K. (2007). SIMPUS Implementation Midterm Assessment: Findings Report. Aceh, Indonesia:IG Health Google Scholar
  • 12. Liu, C.F. , Hwang, H.G. , Chang, H.C. (2011). ‘E-healthcare maturity in Taiwan’. Telemedicine Journal and E-Health: The Official Journal of the American Telemedicine Association. 17, 7, 569-573 Google Scholar
  • 13. MEASURE Evaluation (2010a). Fourth International RHINO Workshop: Measuring and Improving RHIS Performance, 8–1 March, USAID Google Scholar
  • 14. MEASURE Evaluation (2010b). PRISM Tools for Assessing, Monitoring, and Evaluating RHIS Performance. USAID Google Scholar
  • 15. OECD (2010). Economic Surveys Indonesia. (accessed 16 April 2013), OECD Publishing, [online] http://dx.doi.org/10.1787/9789264000000-en Google Scholar
  • 16. Pipino, L. , Lee, Y.W. , Wang, R.Y. (2002). ‘Data quality assessment’. Communications of the ACM. 45, 4, 211-218 Google Scholar
  • 17. Smith, A.E. (2005). Leximancer Manual. Australia:The University of Queensland , Unpublished Manuscript Google Scholar
  • 18. The Ministry of Health (2012). Roadmap Sistem Informasi Kesehatan 2011–2014. Jakarta Google Scholar
  • 19. Wand, Y. , Wang, R.Y. (1996). ‘Anchoring data quality dimensions in ontological foundations’. Communications of the ACM. 39, 11, 86-95 Google Scholar
  • 20. Yin, R.K. (1989). Case Study Research: Design and Methods. Newbury Park, California:Sage Google Scholar
  • 21. Zumpe, S. , Ihme, D. (2006). ‘Information systems maturity in e-business organizations’. 14, European Conference on Information Systems, IT University of Gotteborg Google Scholar