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. 2018 Nov 7;13(11):e0206860.
doi: 10.1371/journal.pone.0206860. eCollection 2018.

Using linked electronic health records to report healthcare-associated infections

T Phuong Quan  1   2 , Russell Hope  3 , Tiphanie Clarke  4 , Ruth Moroney  4 , Lisa Butcher  4 , Peter Knight  2   4   5 , Derrick Crook  1   2   3   5 , Susan Hopkins  3 , Timothy E A Peto  1   2   5 , Alan P Johnson  1   3 , A Sarah Walker  1   2   5
Affiliations

Using linked electronic health records to report healthcare-associated infections

T Phuong Quan et al. PLoS One. .

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.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Total numbers of individual cases recorded each month by the infection control (IC) team versus the number found in the linked-EHR.
The lower section of each graph shows the total number of cases entered by the IC team. The upper section shows the difference compared to linked-EHR: a positive number indicates more cases found by linked-EHR, a negative number indicates more cases found by IC.
Fig 2
Fig 2. Quarterly-aggregated numbers of infections identified.
This compares the quarterly-aggregated numbers reported by the infection control (IC) team versus the number of individual cases entered in that quarter, versus the number found in the linked-her.
See this image and copyright information in PMC

References

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