Toward robust information: data quality in healthcare systems

Yıl 2024, Cilt: 1 Sayı: 1, 24 - 30, 30.05.2024

Sultan Nezihe Turhan

Öz

In healthcare, data moves with the patients they reference, creating interdependencies between healthcare organizations. This means that poor data management in one organization can negatively and cascading affect other organizations and the quality of care a patient receives. The large number of different data sources in healthcare leads to significant complexity in their management. As a result, there is currently a reactive approach to data quality management, which contributes to a lack of trust in data, as users only become aware of data quality issues when they first try to use the data. This paper examines the issues that define and control data quality and the mechanisms that can be developed to achieve and maintain good data quality in the light of the literature.

Anahtar Kelimeler

Healthcare Data, Data Quality, Data Governance

Kaynakça

• Provost, LP, Murray, SK, (2022). The health care data guide: learning from data for improvement. John Wiley & Sons. Howie, L, Hirsch, B, Locklear, T, Abernethy, A, (2014). Assessing the value of patient-generated data to comparative effectiveness research. Health affairs 33 7, 1220-8. https://doi.org/10.1377/hlthaff.2014.0225.
• D'Amore, J, McCrary, L, Denson, J, Li, Vitale, C, Tokachichu, P, Sittig, D, McCoy, A, Wright, A, (2021). Clinical data sharing improves quality measurement and patient safety. Journal of the American Medical Informatics Association: JAMIA. 28, 1534-1542. https://doi.org/10.1093/jamia/ocab039.
• Strasberg, H, Rhodes, B, Fiol, G, Jenders, R, Haug, P, Kawamoto, K, (2021). Contemporary clinical decision support standards using health level seven international fast healthcare interoperability resources. Journal of the American Medical Informatics Association. 28.8: 1796-1806.
• Lu, C, (2014). Uncertainties in real‐world decisions on medical technologies. International Journal of Clinical Practice. 68. https://doi.org/10.1111/ijcp.12434.
• Rodriguez-Lainz, A, McDonald, M, Fonseca-Ford, M, Penman-Aguilar, A, Waterman, S, Truman, B, Cetron, M., & Richards, C, (2018). Collection of Data on Race, Ethnicity, Language, and Nativity by US Public Health Surveillance and Monitoring Systems: Gaps and Opportunities. Public Health Reports. 133, 45 - 54. https://doi.org/10.1177/0033354917745503.
• Bali, A, & Ramesh, M, (2017). Designing effective healthcare: Matching policy tools to problems in China. Public Administration and Development. 37.1: 40-50.
• Mavrogiorgou, A, Kiourtis, ., Perakis, K, Miltiadou, D, Pitsios, S, Kyriazis, D, (2019). Analyzing data and data sources towards a unified approach for ensuring end-to-end data and data sources quality in healthcare 4.0. Computer methods and programs in biomedicine, 181, 104967.
• De Lusignan, S, Stephens, PN, Adal, N, Majeed, A, (2002). Does feedback improve the quality of computerized medical records in primary care?. Journal of the American Medical Informatics Association, 9(4), 395-401. Were, V, Moturi, C, (2017). Toward a data governance model for the Kenya health professional regulatory authorities. The TQM Journal, 29(4), 579-589.
• Johnson, SG, Speedie, S, Simon, G, Kumar, V, Westra, BL, (2017). Quantifying the effect of data quality on the validity of an eMeasure. Applied clinical informatics, 8(04), 1012-1021.
• Taylor, JA. Crowe, S, Pujol, FE, Franklin, RC, Feltbower, RG, Norman, LJ, Pagel, C, (2021). The road to hell is paved with good intentions: the experience of applying for national data for linkage and suggestions for improvement. Bmj Open, 11(8), e047575.
• Oktaviana, S, Handayani, PW, & Hidayanto, AN, (2022). Health Data Governance Issues in Healthcare Facilities: Perspective of Hospital Management. In 2022 10th International Conference on Information and Communication Technology (ICoICT) (pp. 1-5). IEEE.
• Zhang, Y., & Koru, G. (2020). Understanding and detecting defects in healthcare administration data: Toward higher data quality to better support healthcare operations and decisions. Journal of the American Medical Informatics Association, 27(3), 386-395.
• Hickey, D., O'Connor, R., McCormack, P., Kearney, P., Rosti, R., & Brennan, R. (2021, April). The data quality index: improving data quality in Irish healthcare records. ICEIS.
• Shiloach, M., Frencher Jr, S. K., Steeger, J. E., Rowell, K. S., Bartzokis, K., Tomeh, M. G., ... & Hall, B. L. (2010). Toward robust information: data quality and inter-rater reliability in the American College of Surgeons National Surgical Quality Improvement Program. Journal of the American College of Surgeons, 210(1), 6-16.
• Botha, M., Botha, A., & Herselman, M. (2014). Data quality challenges: A content analysis in the e-health domain. 2014 4th World Congress on Information and Communication Technologies (WICT 2014), 107-112. https://doi.org/10.1109/WICT.2014.7077311.
• Elkin-Koren, N, Gal, M, (2019). The Chilling Effect of Governance-by-Data on Data Markets. University of Chicago Law Review, 86, 6.
• Petersen, I, Rensburg, A, Kigozi, F, Semrau, M, Hanlon, C, Abdulmalik, J, Kola, L, Fekadu, A, Gureje, O, Gurung, D, Jordans, M, Mntambo, N, Mugisha, J, Muke, S, Petrus, R, Shidhaye, R, Ssebunnya, J, Tekola, ., Upadhaya, N, Patel, Lund, C, Thornicroft, G, (2019). Scaling up integrated primary mental health in six low- and middle-income countries: obstacles, synergies and implications for systems reform. BJPsych Open, 5. https://doi.org/10.1192/bjo.2019.7.
• Noyes, K, Myneni, A, Schwaitzberg, S, & Hoffman, A, (2019). Quality of MBSAQIP data: bad luck, or lack of QA plan?. Surgical Endoscopy, 34, 973-980. https://doi.org/10.1007/s00464-019-06884-x.
• Scheibner, J, Sleigh, J, Ienca, M, Vayena, E, (2021). Benefits, challenges, and contributors to success for national eHealth systems implementation: a scoping review. Journal of the American Medical Informatics Association, 28(9), 2039-2049.
• Dungey, S, Beloff, N, Williams, R, Williams, T, Puri, S, Tate, AR, (2015). Characterisation of Data Quality in Electronic Healthcare Records. Health Monitoring and Personalized Feedback Using Multimedia Data, 115–135. doi:10.1007/978-3-319-17963-6.