Dataset Information

Using linked electronic health records to report healthcare-associated infections.

ABSTRACT:

Background

Reporting of strategic healthcare-associated infections (HCAIs) to Public Health England is mandatory for all acute hospital trusts in England, via a web-based HCAI Data Capture System (HCAI-DCS).

Aim

Investigate the feasibility of automating the current, manual, HCAI reporting using linked electronic health records (linked-EHR), and assess its level of accuracy.

Methods

All data previously submitted through the HCAI-DCS by the Oxford University Hospitals infection control (IC) team for methicillin-resistant and methicillin-susceptible Staphylococcus aureus (MRSA, MSSA), Clostridium difficile, and Escherichia coli, through March 2017 were downloaded and compared to outputs created from linked-EHR, with detailed comparisons between 2013-2017.

Findings

Total MRSA, MSSA, E. coli and C. difficile cases entered by the IC team vs linked-EHR were 428 vs 432, 795 vs 816, 2454 vs 2450 and 3365 vs 3393 respectively. From 2013-2017, most discrepancies (32/37 (86%)) were likely due to IC recording errors. Patient and specimen identifiers were completed for >98% of cases by both methods, with very high agreement (>97%). Fields relating to the patient at the time the specimen was taken were complete to a similarly high level (>99% IC, >97% linked-EHR), and agreement was fairly good (>80%) except for the main and treatment specialties (57% and 54% respectively) and the patient category (55%). Optional, organism-specific data-fields were less complete, by both methods. Where comparisons were possible, agreement was reasonably high (mostly 70-90%).

Conclusion

Basic factual information, such as demographic data, is almost-certainly better automated, and many other data fields can potentially be populated successfully from linked-EHR. Manual data collection is time-consuming and inefficient; automated electronic data collection would leave healthcare professionals free to focus on clinical rather than administrative work.

SUBMITTER: Quan TP

PROVIDER: S-EPMC6221334 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Publications

Using linked electronic health records to report healthcare-associated infections.

Quan T Phuong TP Hope Russell R Clarke Tiphanie T Moroney Ruth R Butcher Lisa L Knight Peter P Crook Derrick D Hopkins Susan S Peto Timothy E A TEA Johnson Alan P AP Walker A Sarah AS

PloS one 20181107 11

<h4>Background</h4>Reporting of strategic healthcare-associated infections (HCAIs) to Public Health England is mandatory for all acute hospital trusts in England, via a web-based HCAI Data Capture System (HCAI-DCS).<h4>Aim</h4>Investigate the feasibility of automating the current, manual, HCAI reporting using linked electronic health records (linked-EHR), and assess its level of accuracy.<h4>Methods</h4>All data previously submitted through the HCAI-DCS by the Oxford University Hospitals infecti ...[more]

PMID: 30403746

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Dataset Information

Using linked electronic health records to report healthcare-associated infections.

Background

Aim

Methods

Findings

Conclusion

Publications

Using linked electronic health records to report healthcare-associated infections.

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