The Australian electoral commission: Balancing independence and accountability
In: Representation, Band 38, Heft 1, S. 25-30
ISSN: 1749-4001
8 Ergebnisse
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In: Representation, Band 38, Heft 1, S. 25-30
ISSN: 1749-4001
In: Electoral Studies, Band 4, Heft 1, S. 69-71
In: Journal of democracy, Band 30, Heft 3, S. 61-75
ISSN: 1086-3214
In: Conflict, security & development: CSD, Band 16, Heft 6, S. 653-671
ISSN: 1478-1174
In: Australian journal of political science: journal of the Australasian Political Studies Association, Band 26, Heft 1, S. 51-62
ISSN: 1363-030X
In: Electoral Studies, Band 7, Heft 1, S. 67-69
In: Australian journal of international affairs: journal of the Australian Institute of International Affairs, Band 52, Heft 3, S. 241-253
ISSN: 1465-332X
In: Health information management journal, Band 44, Heft 3, S. 7-12
ISSN: 1833-3575
Objective: Manual data-entry of handwritten laboratory test requests into electronic information systems has implications for data accuracy. This study sought to identify the types and number of errors occurring for handwritten serology test requests received from outpatient clinics. Methods: A 15-day audit at a serology laboratory in Sydney, Australia, compared the content of all transcribed serology outpatient test requests in the laboratory information system with the handwritten request form. Results: One or more errors were detected in 67/627 (10.7%) audited requests ( N=68 errors). Fifty-one of the errors (75.0%) were transcription errors: the wrong test was transcribed in 40/68 cases (58.8%) – ten of these occurred when the abbreviations 'HBsAb' and 'HBsAg' were confounded for one another – and transcribed requests were missing a test in 11/68 cases (16.2%). The remaining 17 non-transcription errors (25.0%) described request forms not signed by the ordering clinician, mislabelled specimens, and wrong tests due to computer algorithm errors. Conclusions: Manual data-entry of handwritten serology requests is an error-prone process. Electronic ordering has the potential to eliminate illegible handwriting and transcription errors, thus improving data accuracy in hospital information systems.