Assessment of a novel semi-automated dataset for large scale surveillance of Central venous catheter-related mechanical complications
Ängeby, Emilia LU ; Adrian, Maria LU
; Lazarevic Lindblad, Mathias
LU
; Borgquist, Ola
LU
and Kander, Thomas
LU
(2026)
In International Journal for Quality in Health Care
- Abstract
BACKGROUND: The aim of this study was to examine whether a novel semi-automated dataset based on electronic health record documentation can be used for surveillance of central venous catheter-related mechanical complications (failed catheterisation, bleeding, cardiac arrhythmia, pneumothorax and nerve injury) within 24 hours of catheterisation.
METHODS: The semi-automated dataset comprised a fully automated extraction of clinical documentation from the electronic health record supplemented with a minor manual review aimed at identifying pneumothoraces as these rarely are diagnosed at the time of insertion but rather after a postprocedural chest X-ray. To assess surveillance performance, we compared the number of mechanical... (More)
BACKGROUND: The aim of this study was to examine whether a novel semi-automated dataset based on electronic health record documentation can be used for surveillance of central venous catheter-related mechanical complications (failed catheterisation, bleeding, cardiac arrhythmia, pneumothorax and nerve injury) within 24 hours of catheterisation.
METHODS: The semi-automated dataset comprised a fully automated extraction of clinical documentation from the electronic health record supplemented with a minor manual review aimed at identifying pneumothoraces as these rarely are diagnosed at the time of insertion but rather after a postprocedural chest X-ray. To assess surveillance performance, we compared the number of mechanical complications between the semi-automated and manually evaluated datasets for the same cohort and study period, focusing on agreement in aggregate counts. Comparisons were made at the group level only, without enforcing insertion-by-insertion matching.
RESULTS: A total of 12 667 insertions were included. Minor mechanical complications occurred in 615 (4.9%) of the insertions in the semi-automated dataset and in 645 (5.1%) of the insertions in the manually validated dataset. Major mechanical complications occurred in 44 (0.35%) of the insertions in the semi-automated dataset compared to 48 (0.38%) in the manually validated dataset.
CONCLUSION: A semi-automated dataset based on electronic health record documentation provides sufficiently accurate surveillance of central catheterisation related mechanical complications at the group level. Despite minor discrepancies, the semi-automated method enhances efficiency, scalability, and supports continuous real-time quality assurance. The potential underestimation of complication rates is offset by the possibility of robust real-time quality assurance in registries and a substantial analytical power in scientific studies.
(Less)
- author
- Ängeby, Emilia
LU
; Adrian, Maria
LU
; Lazarevic Lindblad, Mathias
LU
; Borgquist, Ola
LU
and Kander, Thomas
LU
- organization
- publishing date
- 2026-06-05
- type
- Contribution to journal
- publication status
- epub
- subject
- in
- International Journal for Quality in Health Care
- article number
- mzag080
- publisher
- Oxford University Press
- external identifiers
-
- pmid:42249702
- scopus:105042319254
- ISSN
- 1464-3677
- DOI
- 10.1093/intqhc/mzag080
- language
- English
- LU publication?
- yes
- additional info
- © The Author(s) 2026. Published by Oxford University Press on behalf of International Society for Quality in Health Care.
- id
- b21c7e3e-3dfc-41ea-ab62-0107adbeefe2
- date added to LUP
- 2026-06-08 07:52:31
- date last changed
- 2026-08-23 08:01:13
@article{b21c7e3e-3dfc-41ea-ab62-0107adbeefe2,
abstract = {{<p>BACKGROUND: The aim of this study was to examine whether a novel semi-automated dataset based on electronic health record documentation can be used for surveillance of central venous catheter-related mechanical complications (failed catheterisation, bleeding, cardiac arrhythmia, pneumothorax and nerve injury) within 24 hours of catheterisation.</p><p>METHODS: The semi-automated dataset comprised a fully automated extraction of clinical documentation from the electronic health record supplemented with a minor manual review aimed at identifying pneumothoraces as these rarely are diagnosed at the time of insertion but rather after a postprocedural chest X-ray. To assess surveillance performance, we compared the number of mechanical complications between the semi-automated and manually evaluated datasets for the same cohort and study period, focusing on agreement in aggregate counts. Comparisons were made at the group level only, without enforcing insertion-by-insertion matching.</p><p>RESULTS: A total of 12 667 insertions were included. Minor mechanical complications occurred in 615 (4.9%) of the insertions in the semi-automated dataset and in 645 (5.1%) of the insertions in the manually validated dataset. Major mechanical complications occurred in 44 (0.35%) of the insertions in the semi-automated dataset compared to 48 (0.38%) in the manually validated dataset.</p><p>CONCLUSION: A semi-automated dataset based on electronic health record documentation provides sufficiently accurate surveillance of central catheterisation related mechanical complications at the group level. Despite minor discrepancies, the semi-automated method enhances efficiency, scalability, and supports continuous real-time quality assurance. The potential underestimation of complication rates is offset by the possibility of robust real-time quality assurance in registries and a substantial analytical power in scientific studies.</p>}},
author = {{Ängeby, Emilia and Adrian, Maria and Lazarevic Lindblad, Mathias and Borgquist, Ola and Kander, Thomas}},
issn = {{1464-3677}},
language = {{eng}},
month = {{06}},
publisher = {{Oxford University Press}},
series = {{International Journal for Quality in Health Care}},
title = {{Assessment of a novel semi-automated dataset for large scale surveillance of Central venous catheter-related mechanical complications}},
url = {{http://dx.doi.org/10.1093/intqhc/mzag080}},
doi = {{10.1093/intqhc/mzag080}},
year = {{2026}},
}