Exploring the role of information
technology systems in
preventing and managing preanalytic laboratory errors
Karen Day, M...
Today’s presentation
•
•
•
•
•
•

Aim
Background
Methods
What we found
Discussion and conclusions
Recommendations
Aim
…to establish how
information technology
systems influence errors
in terms of preventing,
detecting and managing
the o...
Background

Population of Chile - 15,116,435
13,090,113 live in urban areas
Patients attending the lab - 159,100
(795,652 ...
Methods

Interviews covered
•Understanding of pre-analytical errors and relation to patient safety
•Reporting of pre-analy...
What we found
1. Organisational differences, constraints and
possibilities
• Different contexts
• Limited indirect influen...
2. Concern about reducing errors
•Unanimous
•Scope of concern and reach
•Patient experience
•Quality improvement
‘Although...
3. Differences in information systems and future
considerations
•Value of IT support
•….and it’s about the people and proc...
Discussion and conclusions
• Manual/electronic
• Influence of context
• Concern about nature and
consequences of errors
• ...
Future research recommendations
• Organisational influences on laboratory
processes
• What is the potential of e-orders?
•...
Thank you!
• Acknowledgements
– Laboratory staff from CCL in Chile
– The DHB laboratory in Auckland
k.day@auckland.ac.nz
KarenJDay
+64 27 820 1125
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Exploring the Role of Information Technology Systems in Preventing and Managing Pre-analytic Laboratory Errors

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Presented by Karen Day
Faculty of Medical and Health Sciences, University of Auckland

Published in: Technology, Business
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Exploring the Role of Information Technology Systems in Preventing and Managing Pre-analytic Laboratory Errors

  1. 1. Exploring the role of information technology systems in preventing and managing preanalytic laboratory errors Karen Day, Myriam Soto Lorca, Martin Orr k.day@auckland.ac.nz KarenJDay +64 27 820 1125
  2. 2. Today’s presentation • • • • • • Aim Background Methods What we found Discussion and conclusions Recommendations
  3. 3. Aim …to establish how information technology systems influence errors in terms of preventing, detecting and managing the occurrence and consequences of preanalytic laboratory errors
  4. 4. Background Population of Chile - 15,116,435 13,090,113 live in urban areas Patients attending the lab - 159,100 (795,652 laboratory tests p.a.) NZ population – 4,330,000 DHB population - 560,000 425,671 laboratory tests p.a.
  5. 5. Methods Interviews covered •Understanding of pre-analytical errors and relation to patient safety •Reporting of pre-analytical errors •Staff participation and costs involved in pre-analytical error prevention/management •Managerial reports •Future use of electronic systems
  6. 6. What we found 1. Organisational differences, constraints and possibilities • Different contexts • Limited indirect influence • IT systems vs manual processes ‘I think that the computer system has helped us to reduce our errors related to the accuracy of information about patients. To possess all the information in an accessible IT system allows us to more easily work on creating reports...’
  7. 7. 2. Concern about reducing errors •Unanimous •Scope of concern and reach •Patient experience •Quality improvement ‘Although the use of computerised support does not assure that there will be no error, it substantially decreases the gap that we have today with the standards of quality and patient safety...’
  8. 8. 3. Differences in information systems and future considerations •Value of IT support •….and it’s about the people and processes •Training ‘I consider this IT system 'friendly', it allowed us to track orders from their request, to analyse processing times, etc. I think the current system could be improved because, despite it being a technological support, still has significant manual elements...’
  9. 9. Discussion and conclusions • Manual/electronic • Influence of context • Concern about nature and consequences of errors • Limitations of the study Conclusions •Pre-analytical stage is critical in quality of analytical and post-analytical stages •IT systems can add value in reducing errors
  10. 10. Future research recommendations • Organisational influences on laboratory processes • What is the potential of e-orders? • Building IT systems where they don’t already exist • Extending the reach of the laboratory to improve quality of the whole process
  11. 11. Thank you! • Acknowledgements – Laboratory staff from CCL in Chile – The DHB laboratory in Auckland
  12. 12. k.day@auckland.ac.nz KarenJDay +64 27 820 1125

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