2017
DOI: 10.1111/jep.12754
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Indicators of inappropriate tumour marker use through the mining of electronic health records

Abstract: The developed indicators resulted suitable to monitor TM overordering in outpatients through the mining of EHRs. The present study is a first approach towards the use of big-data mining for TM appropriateness evaluation purposes.

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Cited by 8 publications
(14 citation statements)
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“…In contrast, Zhi et al reported that inappropriateness of laboratory tests ordering did not show significant variations over a similar time period (5). Published data on tumour markers confirm that no significant improvement of test ordering appropriateness occurred over the last years (15,17,19,20,(23)(24)(25)(26)(27). These findings support the hypothesis that recommendation of CPGs on tumour markers are largely disregarded and the process of knowledge translation presents on the whole significant margins for improvement.…”
Section: Discussionmentioning
confidence: 89%
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“…In contrast, Zhi et al reported that inappropriateness of laboratory tests ordering did not show significant variations over a similar time period (5). Published data on tumour markers confirm that no significant improvement of test ordering appropriateness occurred over the last years (15,17,19,20,(23)(24)(25)(26)(27). These findings support the hypothesis that recommendation of CPGs on tumour markers are largely disregarded and the process of knowledge translation presents on the whole significant margins for improvement.…”
Section: Discussionmentioning
confidence: 89%
“…However, the developed epidemiological-based model does not provide a direct measure of appropriateness, since it reveals areas of overutilization probably related to inappropriate use, in which it is necessary to confirm the inappropriateness through a deeper analysis. Our group developed a complementary methodological approach to deeply examine the inappropriateness of tumour markers ordering in outpatients (20). The method was based on the formulation of performance indicators which were tested by mining cohort-wide structured information in the electronic health records (EHRs) of the Italian National Health Service, which include demographic data as well as disease-associated codes registered to manage costs and reimbursement.…”
Section: Developing Indicators To Monitor Appropriateness Of Tumor Mamentioning
confidence: 99%
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