Perfusion downunder collaboration database - Data quality assurance: Towards a high quality clinical database

Journal of Extra-Corporeal Technology

Volumn 43, Issue 1, 2011, Pages

  Tuble, Sigrid C ^a  

^a FLINDERS MEDICAL CENTRE   (Australia)

Author keywords

Audit; Cardiopulmonary bypass; Quality control

Indexed keywords

ACCURACY; AUSTRALIA; CONFERENCE PAPER; DATA BASE; DIALYSIS; FEEDBACK SYSTEM; HOSPITAL DISCHARGE; HUMAN; LENGTH OF STAY; MEDICAL AUDIT; MEDICAL INFORMATION; POSTOPERATIVE PERIOD; QUALITY CONTROL; RELIABILITY; SYSTEMATIC ERROR;

EID: 79952961477     PISSN: 00221058     EISSN: 29698960     Source Type: Journal    
DOI: None     Document Type: Conference Paper

References (16)

1. Arts DGT, De Keizer NF, Scheffer G-J. Defining and improving data quality in medical registries: A literature review, case study, and generic framework. J Am Med Inform Assoc. 2002;9:600-11. (Pubitemid 35231846)
2. Fortuna D, Vizioli M, Contini A, et al. Assessing clinical performance in cardiac surgery. Does a specialised clinical database make a difference? Interact Cardiovasc Thorac Surg. 2006;5:123-7.
3. Peterson ED, Coombs LP, Ferguson TB, et al. for the STS National Cardiac Database Investigators. Hospital variability in length of stay after coronary artery bypass surgery: Results from the society of thoracic surgeon's national cardiac database. Ann Thorac Surg. 2002;74:464-73.
4. Ferguson TB Jr, Hammill BG, Peterson ED, DeLong ER, Grover FL, for the STS National Database Committee. A decade of change - risk profiles and outcomes for isolated coronary artery bypass grafting procedures, 1990-1999: A report from the STS National Database Committee and the Duke Clinical Research Institute. Ann Thorac Surg. 2002;73:480-90.
5. Yan BP, Clark DJ, Buxton B, et al. on behalf of the Australasian Society of Cardiac and Thoracic Surgeons (ASCTS), the Melbourne Interventional Group (MIG). Clinical characteristics and early mortality of patients undergoing coronary artery bypass grafting compared to percutaneous coronary intervention: Insights from the Australasian Society of Cardiac and Thoracic Surgeons (ASCTS) and the Melbourne Interventional Group (MIG) Registries. Heart Lung Circ. 2009;18:184-90.
6. Black N, Payne M. Improving the use of clinical databases. BMJ. 2002;324:1194. (Pubitemid 34547923)
7. Black N. High-quality clinical databases: Breaking down barriers. Lancet. 1999;353:1205-6. (Pubitemid 29168456)
8. Sørensen HT, Sabroe S, Olsen J. A framework for evaluation of secondary data sources for epidemiological research. Int J Epidemiol. 1996;25:435-42. (Pubitemid 26137126)
9. Newland R, Baker RA, Stanley R, Place K, Willcox TW. The Perfusion Downunder Collaborative Database Project. J Extra Corpor Technol. 2008;40:159-65.
10. Reid C, Billah B, Dinh D, et al. An Australian risk prediction model for 30-day mortality after isolated coronary artery bypass: The AusSCORE. J Thorac Cardiovasc Surg. 2009;138:904-10.
11. Nashef SA, Roques F, Michel P, Gauducheau E, Lemeshow S, Salamon R. European system for cardiac operative risk evaluation (EuroSCORE). Eur J Cardiothorac Surg. 1999;16:9-13. (Pubitemid 29336425)
12. Shroyer AL, Coombs LP, Peterson ED, et al. The Society of Thoracic Surgeons: 30-day operative mortality and morbidity risk models. Ann Thorac Surg. 2003;75:1856-65. (Pubitemid 36677229)
13. Fine LG, Keogh BE, Cretin S, Orlando M, Gould MM. on behalf of the Nuffield-Rand Cardiac Surgery Demonstration Project Group. How to evaluate and improve the quality and credibility of an outcomes database: Validation and feedback study on the UK Cardiac Surgery Experience. BMJ. 2003;326:25-8.
14. Datta I, Findlay C, Kortbeek JB, Hameed SM. Evaluation of a regional trauma registry. Can J Surg. 2007;50:210-3.
15. Arts DGT, Bosman RB, de Jonge E, Joore JCA, de Keizer NF. Training in data definitions improves quality of intensive care data. Crit Care. 2003;7:179-84. (Pubitemid 36432677)
16. Gassman JJ, Owen WW, Kuntz TE, Martin JP, Amoroso WP. Data quality assurance, monitoring, and reporting. Control Clin Trials. 1995;16:104S-36S.