American Health Information Management Association (AHIMA) (2012). Data Quality Management Model (Updated). Journal of AHIMA(83)7: 62–67.
2.
DaveyM.SloanM.PalmaS.RileyM.KingJ. (2013). Methodological processes in validating and analysing the quality of population-based data: A case study using the Victorian Perinatal Data Collection. Health Information Management Journal42(3): 12–19.
3.
FreestoneD.WilliamsonD.WollersheimD. (2012). Geocoding coronial data: Tools and techniques to improve data quality. Health Information Management Journal41(3): 4–12.
4.
HaghighiM.H.H.DehghaniM.TeshiziS. H.MahmoodiH. (2013). Impact of documentation errors on accuracy of cause of death coding in an educational hospital in Southern Iran. Health Information Management Journal. DOI: 10.12826/18333575.2013.0015.Haghighi.
5.
HanafiS.HayatshahiA.TorkamandiH.JavadiM.R. (2012). Evaluation of treatment with Oseltamivir during the 2009 H1N1 (swine flu) pandemic: The problem of incomplete clinical information. Health Information Management Journal41(1): 31–34.
6.
PaulL.RobinsonK.M. (2012). Capture and documentation of coded data on Adverse Drug Reactions: An overview. Health Information Management Journal41(3): 27–36.
7.
RowlandsS.CallenJ.WestbrookJ. (2012). Are general practitioners getting the information they need from hospitals to manage their lung cancer patients? A qualitative exploration. Health Information Management Journal41(2):4–13.
8.
SchiffG.D.BatesD.W. (2010). Can electronic clinical documentation help prevent diagnostic errors?New England Journal of Medicine362(12): 1066–1069.
9.
WeiskopfN.WengC. (2013). Methods and dimensions of electronic health record data quality assessment: Enabling reuse for clinical research. Journal of the American Medical Informatics Association20: 144–151.