E-Thesis 143 views 29 downloads
USING ROUTINELY COLLECTED DATA TO MAP THE ROLE OF RESPIRATORY PATHOGENS IN ACUTE EXACERBATIONS OF COPD / SHANYA SIVAKUMARAN
Swansea University Author: SHANYA SIVAKUMARAN
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Copyright: The Author, Shanya Sivakumaran, 2023. Distributed under the terms of a Creative Commons Attribution Non Commercial 4.0 License (CC BY-NC 4.0).
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Abstract
Linkage of routinely collected microbiology data with other electronic health records (EHRs) could provide important insights into a variety of infection syndromes. In a demonstration of utility, over the course of the thesis, I outline the steps taken in order to retrospectively identify laboratory...
| Published: |
Swansea, Wales, UK
2023
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| Institution: | Swansea University |
| Degree level: | Master of Research |
| Degree name: | MSc by Research |
| Supervisor: | Davies, Gwyneth., Lyons, Ronan. and Quint, Jennifer. |
| URI: | https://cronfa.swan.ac.uk/Record/cronfa64624 |
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| Abstract: |
Linkage of routinely collected microbiology data with other electronic health records (EHRs) could provide important insights into a variety of infection syndromes. In a demonstration of utility, over the course of the thesis, I outline the steps taken in order to retrospectively identify laboratory-confirmed respiratory pathogens associated with hospital admission for acute exacerbations of chronic obstructive pulmonary disease (COPD) in Wales, over a two-year period. I firstly performed a systematic, scoping review to explore how individuals with COPD were identified in EHRs in the recent literature. Next, using the Secure Anonymised Information Linkage (SAIL) databank, which contains deidentified health and administrative data covering the entire population of Wales, I created a dataset of individuals admitted to hospitals in Wales with acute exacerbations of COPD over a two-year period, and linked these records to laboratory tests for respiratory pathogensassociated with the admission. Using this dataset, I could then identify what proportion of these emergency admissions were associated with testing for, and detection of, a respiratory pathogen. Additionally, I was able to examine the accuracy of using diagnosis codes (specifically, International Statistical Classification of Diseases and Related Health Problems (ICD) codes) to identify laboratory-confirmed respiratory pathogens associated with COPD exacerbations. My analysis revealed that respiratory viruses were detected in 46.7% of hospital admissions for COPD exacerbation where testing was undertaken, however diagnostic testing appears to be underutilised (respiratory virus testing carried out in only 4.7% of emergency admissions for COPD). Increasing respiratory viral testing in this population therefore has the potential to enable more effective antimicrobial stewardship. When comparing ICD codes to microbiology data, the analysis showed that ICD codes have low sensitivity in identifying laboratory-confirmed respiratory pathogens. Large-scale linkage with microbiology data is thus key in order to be able to delineate the burden of specific pathogens with greater accuracy. |
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| Item Description: |
A selection of content is redacted or is partially redacted from this thesis to protect sensitive and/or personal information. Chapter 2: Distributed under the terms of a Creative Commons Attribution Non Commercial 4.0 License (CC BY-NC 4.0). Chapter 4: Distributed under the terms of a Creative Commons Attribution 4.0 License (CC BY 4.0). |
| Keywords: |
Respiratory Tract Infections, Pulmonary Disease, Chronic Obstructive, Electronic Health Records |
| College: |
Faculty of Medicine, Health and Life Sciences |