Introduction: The benefits of electronic data collection in healthcare can be defined by its application in both clinical and financial contexts. The benefits associated with the use of electronic data collection include the reduction in transcription errors, bias, medical errors, and paperwork1. Comparisons between electronic and manual data collection methods have shown the superiority of the electronic method with respect to the integrity of the data2, the quantity and type of data collected1, and the facilitation of data analysis3.
Quality assurance and quality control (QC) in health care delivery are recognized for the important roles that they play. Riley (JECT) promoted the importance of the perfusion profession in recognizing the importance of quality improvement and reporting in perfusion4. In our institution, quality assurance processes have been well developed, however we have not focused on the value and importance of QC processes. We recognized that additional enterprise advantages could be gained if we were able to utilize the information (data) we collected to improve our day to day perfusion practices – to develop a QC process.
The aim of initial work has been to develop an automated technique of data analysis, initiate a QC process and to assess the influence of continuous QC on both our perfusion practice, and on protocol development.
Process: Data management has been an integral component of the clinical pathway for Cardiac Surgery in our unit since inception. A detailed Cardiac Surgery Research (CSR) database is accessed via a Microsoft Access (Microsoft Corporation, Redmond, USA) user interface which is linked to the hospital SQL Server to provide a robust multi-user environment designed to communicate with other hospital based systems. This database includes clinical, biochemical, surgical, perfusion (manual data entry), outcome and outpatient data, thus providing a comprehensive patient data set. The incorporation of an electronic data management system into our practice (DMS; Stockert, Munich Germany) provided an additional source of detailed perfusion data, and facilitated the allowed integration of data from other devices.
We developed a process using visual basic programming, by which data from the perfusion software is analyzed and processed in a Microsoft Access database following a cardiopulmonary bypass (CPB) procedure. The queries are designed to transfer data from the perfusion software to our research database, and create a number of CPB quality indicator (QI) parameters5.
These QI parameters are designed to reflect our perfusion management protocols. Initially we looked at QI parameters relating to anticoagulation, flow, pressure, venous saturation, haematocrit, temperature and blood gas management.
In order to create a control process, standard practice was defined by unit perfusion protocols. In the event that practice deviated from protocol a quality control report is automatically generated.
The report is simultaneously emailed to the perfusionist performing the procedure and a second designated perfusionist.
Conclusion: The creation of CPB QI parameters allows monitoring of deviation from standard practice, and performance improvement initiatives to be implemented via data analysis and team discussion. Subsequent analysis of these initiatives creates a process of continuous quality improvement.
The Theory in Practice: The Flinders Medical CentreReferences1. Ottens J, Baker RA, Newland RF, Mazzone A. The future of the Perfusion Record, Automated Data collection vs Manual Recording. JECT 2005;37:355-92. Hollenburg JP, Pirraglia PA, et al. Computerised data collection in the operating room during coronary artery bypass surgery: a comparison to the hand – written record. J Cardiothorac Vasc Anesth 1997; 11(5): 545-51. 3. Brodaty D, Montgermont P, et al. Computerized management of the medical record in cardiac surgery. Experience at Foch Hospital; Arch Mal Coeur Vaiss. 1984 Nov;77(12):1344-50 4. Riley JB. Are Perfusion Technology and Perfusionists Ready for Quality Reporting Employing Six-Sigma Performance Measurement? JECT 2003;35:168-171. 5. Newland RF, Baker RA, Stanley RA. Electronic data management: The pathway to automated quality control of cardiopulmonary bypass. JECT 2006;38:139-143 |
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