2010
DOI: 10.14236/jhi.v18i3.773
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Clinical data extraction and feedback in general practice: a case study from Australian primary care

Abstract: Background Quality improvement in general practice has increasingly focused on the analysis of its clinical databases to guide its improvement strategies. However, general practitioners (GPs) need to be motivated to extract and review their clinical data, and they need skills to do so. This study examines the initial experience of 15 practices in undertaking clinical data extraction and management and the support they were given by their local division of general practice. Objectives To explore the uptake of d… Show more

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Cited by 15 publications
(15 citation statements)
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“…Schattner et al 12 suggest that there is a need to improve eHealth data transmission to increase accessibility of clinical data by DETs for Pap smear results, in addition to improving the functionality of DETs themselves.…”
Section: Discussionmentioning
confidence: 99%
“…Schattner et al 12 suggest that there is a need to improve eHealth data transmission to increase accessibility of clinical data by DETs for Pap smear results, in addition to improving the functionality of DETs themselves.…”
Section: Discussionmentioning
confidence: 99%
“…Some of the physicians who received the intervention and software training to query their EMR did not think the results of their personalised feedback on 10 the utility of data extraction tools for quality improvement activities was also found to be dependent on the accuracy and completeness of computerised clinical data, where it is necessary to have results recorded in specific structured fields to be detected by data extraction tools.…”
Section: Limitations Of the Methodsmentioning
confidence: 99%
“…14,16,19,20,35 Other studies have found that the use of data extraction was possible; similar to our study, practices required external support for this. 36 Studies on data improvement in primary care EMRs have relied on audit, feedback and training, with moderate effects. [37][38][39][40][41] In this study, we report larger changes through the involvement of non-clinicians in data management and data re-entry in EMRs.…”
Section: Comparison With the Literaturementioning
confidence: 99%