scholarly journals Are administrative data valid when measuring patient safety in hospitals? A comparison of data collection methods using a chart review and administrative data

2015 ◽  
Vol 27 (4) ◽  
pp. 305-313 ◽  
Author(s):  
Christina Maass ◽  
Silke Kuske ◽  
Constanze Lessing ◽  
Matthias Schrappe
Author(s):  
Jamie West ◽  
Jennifer Atherton ◽  
Seán J Costelloe ◽  
Ghazaleh Pourmahram ◽  
Adam Stretton ◽  
...  

Preanalytical errors have previously been shown to contribute a significant proportion of errors in laboratory processes and contribute to a number of patient safety risks. Accreditation against ISO 15189:2012 requires that laboratory Quality Management Systems consider the impact of preanalytical processes in areas such as the identification and control of non-conformances, continual improvement, internal audit and quality indicators. Previous studies have shown that there is a wide variation in the definition, repertoire and collection methods for preanalytical quality indicators. The International Federation of Clinical Chemistry Working Group on Laboratory Errors and Patient Safety has defined a number of quality indicators for the preanalytical stage, and the adoption of harmonized definitions will support interlaboratory comparisons and continual improvement. There are a variety of data collection methods, including audit, manual recording processes, incident reporting mechanisms and laboratory information systems. Quality management processes such as benchmarking, statistical process control, Pareto analysis and failure mode and effect analysis can be used to review data and should be incorporated into clinical governance mechanisms. In this paper, The Association for Clinical Biochemistry and Laboratory Medicine PreAnalytical Specialist Interest Group review the various data collection methods available. Our recommendation is the use of the laboratory information management systems as a recording mechanism for preanalytical errors as this provides the easiest and most standardized mechanism of data capture.


2015 ◽  
Vol 06 (01) ◽  
pp. 96-109 ◽  
Author(s):  
K.-A. Bowles ◽  
E.H. Skinner ◽  
D. Mitchell ◽  
R. Haas ◽  
M. Ho ◽  
...  

Summary Background: Hospital length of stay and discharge destination are important outcome measures in evaluating effectiveness and efficiency of health services. Although hospital administrative data are readily used as a data collection source in health services research, no research has assessed this data collection method against other commonly used methods. Objective: Determine if administrative data from electronic patient management programs are an effective data collection method for key hospital outcome measures when compared with alternative hospital data collection methods. Method: Prospective observational study comparing the completeness of data capture and level of agreement between three data collection methods; manual data collection from ward-based sources, administrative data from an electronic patient management program (i.PM), and inpatient medical record review (gold standard) for hospital length of stay and discharge destination. Results: Manual data collection from ward-based sources captured only 376 (69%) of the 542 in-patient episodes captured from the hospital administrative electronic patient management program. Administrative data from the electronic patient management program had the highest levels of agreement with inpatient medical record review for both length of stay (93.4%) and discharge destination (91%) data. Conclusion: This is the first paper to demonstrate differences between data collection methods for hospital length of stay and discharge destination. Administrative data from an electronic patient management program showed the highest level of completeness of capture and level of agreement with the gold standard of inpatient medical record review for both length of stay and discharge destination, and therefore may be an acceptable data collection method for these measures. Citation: Sarkies MN, Bowles K-A, Skinner EH, Mitchell D, Haas R, Ho M, Salter K, May K, Markham D, O’Brien L, Plumb S, Haines T.P. Data collection methods in health services research – hospital length of stay and discharge destination. Appl Clin Inf 2015; 6: 96–109http://dx.doi.org/10.4338/ACI-2014-10-RA-0097


1998 ◽  
Author(s):  
J. L. Mitchell ◽  
Winston Bennett ◽  
J. J. Weissmuller ◽  
R. L. Gosc ◽  
Patricia Waldroop ◽  
...  

2011 ◽  
Author(s):  
Arne Weigold ◽  
Ingrid K. Weigold ◽  
Elizabeth J. Russell ◽  
John Shook ◽  
Sara N. Natera ◽  
...  

2021 ◽  
Vol 124 ◽  
pp. 103538
Author(s):  
Yantao Yu ◽  
Waleed Umer ◽  
Xincong Yang ◽  
Maxwell Fordjour Antwi-Afari

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