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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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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...

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Published: Swansea, Wales, UK 2023
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
first_indexed 2023-09-27T09:53:23Z
last_indexed 2024-11-25T14:14:23Z
id cronfa64624
recordtype RisThesis
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spelling 2023-09-29T09:22:49.3654139 v2 64624 2023-09-27 USING ROUTINELY COLLECTED DATA TO MAP THE ROLE OF RESPIRATORY PATHOGENS IN ACUTE EXACERBATIONS OF COPD 91bc5bebcbd279ab8883c90bbc10a0d7 SHANYA SIVAKUMARAN SHANYA SIVAKUMARAN true false 2023-09-27 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. E-Thesis Swansea, Wales, UK Respiratory Tract Infections, Pulmonary Disease, Chronic Obstructive, Electronic Health Records 27 9 2023 2023-09-27 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). COLLEGE NANME COLLEGE CODE Swansea University Davies, Gwyneth., Lyons, Ronan. and Quint, Jennifer. Master of Research MSc by Research 2023-09-29T09:22:49.3654139 2023-09-27T10:44:43.8408745 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Biomedical Science SHANYA SIVAKUMARAN 1 64624__28662__4694b637e6ae451caac2aa880ae6df86.pdf 2023_Sivakumaran_S.final.64624.pdf 2023-09-29T09:12:46.3117306 Output 2101383 application/pdf E-Thesis true 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). true eng https://creativecommons.org/licenses/by-nc/4.0/
title USING ROUTINELY COLLECTED DATA TO MAP THE ROLE OF RESPIRATORY PATHOGENS IN ACUTE EXACERBATIONS OF COPD
spellingShingle USING ROUTINELY COLLECTED DATA TO MAP THE ROLE OF RESPIRATORY PATHOGENS IN ACUTE EXACERBATIONS OF COPD
SHANYA SIVAKUMARAN
title_short USING ROUTINELY COLLECTED DATA TO MAP THE ROLE OF RESPIRATORY PATHOGENS IN ACUTE EXACERBATIONS OF COPD
title_full USING ROUTINELY COLLECTED DATA TO MAP THE ROLE OF RESPIRATORY PATHOGENS IN ACUTE EXACERBATIONS OF COPD
title_fullStr USING ROUTINELY COLLECTED DATA TO MAP THE ROLE OF RESPIRATORY PATHOGENS IN ACUTE EXACERBATIONS OF COPD
title_full_unstemmed USING ROUTINELY COLLECTED DATA TO MAP THE ROLE OF RESPIRATORY PATHOGENS IN ACUTE EXACERBATIONS OF COPD
title_sort USING ROUTINELY COLLECTED DATA TO MAP THE ROLE OF RESPIRATORY PATHOGENS IN ACUTE EXACERBATIONS OF COPD
author_id_str_mv 91bc5bebcbd279ab8883c90bbc10a0d7
author_id_fullname_str_mv 91bc5bebcbd279ab8883c90bbc10a0d7_***_SHANYA SIVAKUMARAN
author SHANYA SIVAKUMARAN
author2 SHANYA SIVAKUMARAN
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hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str Swansea University Medical School - Biomedical Science{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Biomedical Science
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description 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.
published_date 2023-09-27T20:38:16Z
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