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Victorian Emergency Minimum Dataset: Factors that impact upon the data quality
Author(s) -
Marson Rebecca,
Taylor David McD,
Ashby Karen,
Cassell Erin
Publication year - 2005
Publication title -
emergency medicine australasia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.602
H-Index - 52
eISSN - 1742-6723
pISSN - 1742-6731
DOI - 10.1111/j.1742-6723.2005.00700.x
Subject(s) - medicine , data collection , data quality , psychological intervention , quality (philosophy) , quality assurance , data entry , minimum data set , medical emergency , emergency department , family medicine , nursing , operations management , database , metric (unit) , statistics , philosophy , external quality assessment , mathematics , epistemology , pathology , computer science , nursing homes , economics
Objective: The Victorian Emergency Minimum Dataset (VEMD) records details of approximately 80% of Victoria's ED presentations. Its usefulness for quality assurance and research relies on the data being both complete and accurate. We aimed to determine the factors that impact adversely on the collection of high‐quality VEMD data. Methods: The study was a voluntary, anonymous, cross‐sectional survey of a range of ED staff (medical, nursing, clerical) who collect and enter data into the VEMD. Nine of the 28 hospitals that contribute to the VEMD were surveyed. The questionnaire was purpose‐designed and self‐administered. Results: A total of 218 staff participated (response rate 95%). Six different software types were used, with 40% of respondents using the Pickware (MCAT) system. There was no consistency of ED personnel for the completion of specific data fields. One hundred and twenty‐six (56%) respondents had heard of the VEMD, 67 (29%) had had its structure and purpose explained and 65 (30%) had been trained to enter data. Ninety‐seven (45%) respondents knew what the VEMD data was used for, 38 (17%) knew they could request VEMD data for their own use and 17 (7.8%) had done so. Time constraints, software problems and lack of formal orientation and training in data entry were reported as the most important factors impacting adversely upon quality data entry. Conclusion: Staff knowledge of the VEMD system and its uses are poor. Numerous factors impact on the quality of data entered and interventions aimed at improving staff education, training and feedback and software are indicated.