Data Quality Associated with Handwritten Laboratory Test Requests: Classification and Frequency of Data-Entry Errors for Outpatient Serology Tests
| Autor: | George Toouli, Johanna I. Westbrook, Elia Vecellio, Andrew Georgiou, Michael Maley |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Clinical audit
Handwriting Leadership and Management computer.software_genre Medical Order Entry Systems Patient safety Ambulatory care Outpatients Ambulatory Care Humans Medicine Outpatient clinic Serologic Tests Clinical Audit Medical Errors business.industry Health Policy Australia Data Accuracy Test (assessment) Data quality Hospital Information Systems Data mining Artificial intelligence business computer Quality assurance Natural language processing |
| Zdroj: | Health Information Management Journal. 44:7-12 |
| ISSN: | 1833-3575 1833-3583 |
| DOI: | 10.1177/183335831504400302 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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