Procalcitonin to guide antibiotic use during the first wave of COVID-19 in English and Welsh hospitals: integration and triangulation of findings from quantitative and qualitative sources
Aim To integrate the quantitative and qualitative data collected as part of the PEACH (Procalcitonin: Evaluation of Antibiotic use in COVID-19 Hospitalised patients) study, which evaluated whether procalcitonin (PCT) testing should be used to guide antibiotic prescribing and safely reduce antibiotic...
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BMJ Publishing Group
2025-08-01
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| Series: | BMJ Open |
| Online Access: | https://bmjopen.bmj.com/content/15/8/e093210.full |
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| author | Neil Powell Emma Thomas-Jones Paul Dark Tamas Szakmany Susan Hopkins Jonathan Sandoe Margaret Ogden Robert M West Enitan Carrol Lucy Brookes-Howell Philip Pallmann Bethany Shinkins Dominick Shaw Philip Howard Stacy Todd Thomas P Hellyer David G Partridge Mahableshwar Albur Martin Llewelyn Helena K Parsons Detelina Grozeva Joanne Euden Iain J McCullagh Josie Henley Wakunyambo Maboshe Stuart E Bond |
| author_facet | Neil Powell Emma Thomas-Jones Paul Dark Tamas Szakmany Susan Hopkins Jonathan Sandoe Margaret Ogden Robert M West Enitan Carrol Lucy Brookes-Howell Philip Pallmann Bethany Shinkins Dominick Shaw Philip Howard Stacy Todd Thomas P Hellyer David G Partridge Mahableshwar Albur Martin Llewelyn Helena K Parsons Detelina Grozeva Joanne Euden Iain J McCullagh Josie Henley Wakunyambo Maboshe Stuart E Bond |
| author_sort | Neil Powell |
| collection | DOAJ |
| description | Aim To integrate the quantitative and qualitative data collected as part of the PEACH (Procalcitonin: Evaluation of Antibiotic use in COVID-19 Hospitalised patients) study, which evaluated whether procalcitonin (PCT) testing should be used to guide antibiotic prescribing and safely reduce antibiotic use among patients admitted to acute UK National Health Service (NHS) hospitals.Design Triangulation to integrate quantitative and qualitative data.Setting and participants Four data sources in 148 NHS hospitals in England and Wales including data from 6089 patients.Method A triangulation protocol was used to integrate three quantitative data sources (survey, organisation-level data and patient-level data: data sources 1, 2 and 3) and one qualitative data source (clinician interviews: data source 4) collected as part of the PEACH study. Analysis of data sources initially took place independently, and then, key findings for each data source were added to a matrix. A series of interactive discussion meetings took place with quantitative, qualitative and clinical researchers, together with patient and public involvement (PPI) representatives, to group the key findings and produce seven statements relating to the study objectives. Each statement and the key findings related to that statement were considered alongside an assessment of whether there was agreement, partial agreement, dissonance or silence across all four data sources (convergence coding). The matrix was then interpreted to produce a narrative for each statement.Objective To explore whether PCT testing safely reduced antibiotic use during the first wave of the COVID-19 pandemic.Results Seven statements were produced relating to the PEACH study objective. There was agreement across all four data sources for our first key statement, ‘During the first wave of the pandemic (01/02/2020-30/06/2020), PCT testing reduced antibiotic prescribing’. The second statement was related to this key statement, ‘During the first wave of the pandemic (01/02/2020-30/06/2020), PCT testing safely reduced antibiotic prescribing’. Partial agreement was found between data sources 3 (quantitative patient-level data) and 4 (qualitative clinician interviews). There were no data regarding safety from data sources 1 or 2 (quantitative survey and organisational-level data) to contribute to this statement. For statements three and four, ‘PCT was not used as a central factor influencing antibiotic prescribing’, and ‘PCT testing reduced antibiotic prescribing in the emergency department (ED)/acute medical unit (AMU),’ there was agreement between data source 2 (organisational-level data) and data source 4 (interviews with clinicians). The remaining two data sources (survey and patient-level data) contributed no data on this statement. For statement five, ‘PCT testing reduced antibiotic prescribing in the intensive care unit (ICU)’, there was disagreement between data sources 2 and 3 (organisational-level data and patient-level data) and data source 4 (clinician interviews). Data source 1 (survey) did not provide data on this statement. We therefore assigned dissonance to this statement. For statement six, ‘There were many barriers to implementing PCT testing during the first wave of COVID-19’, there was partial agreement between data source 1 (survey) and data source 4 (clinician interviews) and no data provided by the two remaining data sources (organisational-level data and patient-level data). For statement seven, ‘Local PCT guidelines/protocols were perceived to be valuable’, only data source 4 (clinician interviews) provided data. The clinicians expressed that guidelines were valuable, but as there was no data from the other three data sources, we assigned silence to this statement.Conclusion There was agreement between all four data sources on our key finding ‘during the first wave of the pandemic (01/02/2020-30/06/2020), PCT testing reduced antibiotic prescribing’. Data, methodological and investigator triangulation, and a transparent triangulation protocol give validity to this finding.Trial registration number ISRCTN66682918. |
| format | Article |
| id | doaj-art-2de9048ca07942bc84c223050b10a2b7 |
| institution | Kabale University |
| issn | 2044-6055 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Open |
| spelling | doaj-art-2de9048ca07942bc84c223050b10a2b72025-08-20T03:36:19ZengBMJ Publishing GroupBMJ Open2044-60552025-08-0115810.1136/bmjopen-2024-093210Procalcitonin to guide antibiotic use during the first wave of COVID-19 in English and Welsh hospitals: integration and triangulation of findings from quantitative and qualitative sourcesNeil Powell0Emma Thomas-Jones1Paul Dark2Tamas Szakmany3Susan Hopkins4Jonathan Sandoe5Margaret Ogden6Robert M West7Enitan Carrol8Lucy Brookes-Howell9Philip Pallmann10Bethany Shinkins11Dominick Shaw12Philip Howard13Stacy Todd14Thomas P Hellyer15David G Partridge16Mahableshwar Albur17Martin Llewelyn18Helena K Parsons19Detelina Grozeva20Joanne Euden21Iain J McCullagh22Josie Henley23Wakunyambo Maboshe24Stuart E Bond25Royal Cornwall Hospitals NHS Trust, Truro, UKCollege of Biomedical and Life Sciences, Cardiff University Centre for Trials Research, Cardiff, Wales, UKDivision of Immunology, Immunity to Infection and Respiratory Medicine, The University of Manchester, Manchester, England, UKDepartment of Anaesthesia, Intensive Care and Pain Medicine, Division of Population Medicine, Cardiff University, Cardiff, UKUK Health Security Agency, London, England, UKDepartment of Microbiology, Leeds General Infirmary, Leeds, England, UKCollege of Biomedical and Life Sciences, Cardiff University Centre for Trials Research, Cardiff, Wales, UKUniversity of Leeds Leeds Institute of Health Sciences, Leeds, West Yorkshire, UKDepartment of Clinical Infection, Microbiology and Immunology, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UKCollege of Biomedical and Life Sciences, Cardiff University Centre for Trials Research, Cardiff, Wales, UKCollege of Biomedical and Life Sciences, Cardiff University Centre for Trials Research, Cardiff, Wales, UKUniversity of Leeds Leeds Institute of Health Sciences, Leeds, West Yorkshire, UKNIHR Leicester Biomedical Research Centre Respiratory Diseases, Leicester, East Midlands, UKSchool of Healthcare, University of Leeds, Leeds, UKLiverpool University Hospitals NHS Foundation Trust, Liverpool, England, UKTranslational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UKSheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UKMicrobiology, NHS North Bristol NHS Trust, Bristol, England, UKGlobal Health and Infectious Diseases, University of Sussex, Brighton, UKSheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UKCollege of Biomedical and Life Sciences, Cardiff University Centre for Trials Research, Cardiff, Wales, UKCollege of Biomedical and Life Sciences, Cardiff University Centre for Trials Research, Cardiff, Wales, UKCritical Care Department, Royal Victoria Infirmary, Newcastle upon Tyne, England, UKSchool of Social Sciences, Cardiff University, Cardiff, UKCollege of Biomedical and Life Sciences, Cardiff University Centre for Trials Research, Cardiff, Wales, UKMid Yorkshire Hospitals NHS Trust, Wakefield, UKAim To integrate the quantitative and qualitative data collected as part of the PEACH (Procalcitonin: Evaluation of Antibiotic use in COVID-19 Hospitalised patients) study, which evaluated whether procalcitonin (PCT) testing should be used to guide antibiotic prescribing and safely reduce antibiotic use among patients admitted to acute UK National Health Service (NHS) hospitals.Design Triangulation to integrate quantitative and qualitative data.Setting and participants Four data sources in 148 NHS hospitals in England and Wales including data from 6089 patients.Method A triangulation protocol was used to integrate three quantitative data sources (survey, organisation-level data and patient-level data: data sources 1, 2 and 3) and one qualitative data source (clinician interviews: data source 4) collected as part of the PEACH study. Analysis of data sources initially took place independently, and then, key findings for each data source were added to a matrix. A series of interactive discussion meetings took place with quantitative, qualitative and clinical researchers, together with patient and public involvement (PPI) representatives, to group the key findings and produce seven statements relating to the study objectives. Each statement and the key findings related to that statement were considered alongside an assessment of whether there was agreement, partial agreement, dissonance or silence across all four data sources (convergence coding). The matrix was then interpreted to produce a narrative for each statement.Objective To explore whether PCT testing safely reduced antibiotic use during the first wave of the COVID-19 pandemic.Results Seven statements were produced relating to the PEACH study objective. There was agreement across all four data sources for our first key statement, ‘During the first wave of the pandemic (01/02/2020-30/06/2020), PCT testing reduced antibiotic prescribing’. The second statement was related to this key statement, ‘During the first wave of the pandemic (01/02/2020-30/06/2020), PCT testing safely reduced antibiotic prescribing’. Partial agreement was found between data sources 3 (quantitative patient-level data) and 4 (qualitative clinician interviews). There were no data regarding safety from data sources 1 or 2 (quantitative survey and organisational-level data) to contribute to this statement. For statements three and four, ‘PCT was not used as a central factor influencing antibiotic prescribing’, and ‘PCT testing reduced antibiotic prescribing in the emergency department (ED)/acute medical unit (AMU),’ there was agreement between data source 2 (organisational-level data) and data source 4 (interviews with clinicians). The remaining two data sources (survey and patient-level data) contributed no data on this statement. For statement five, ‘PCT testing reduced antibiotic prescribing in the intensive care unit (ICU)’, there was disagreement between data sources 2 and 3 (organisational-level data and patient-level data) and data source 4 (clinician interviews). Data source 1 (survey) did not provide data on this statement. We therefore assigned dissonance to this statement. For statement six, ‘There were many barriers to implementing PCT testing during the first wave of COVID-19’, there was partial agreement between data source 1 (survey) and data source 4 (clinician interviews) and no data provided by the two remaining data sources (organisational-level data and patient-level data). For statement seven, ‘Local PCT guidelines/protocols were perceived to be valuable’, only data source 4 (clinician interviews) provided data. The clinicians expressed that guidelines were valuable, but as there was no data from the other three data sources, we assigned silence to this statement.Conclusion There was agreement between all four data sources on our key finding ‘during the first wave of the pandemic (01/02/2020-30/06/2020), PCT testing reduced antibiotic prescribing’. Data, methodological and investigator triangulation, and a transparent triangulation protocol give validity to this finding.Trial registration number ISRCTN66682918.https://bmjopen.bmj.com/content/15/8/e093210.full |
| spellingShingle | Neil Powell Emma Thomas-Jones Paul Dark Tamas Szakmany Susan Hopkins Jonathan Sandoe Margaret Ogden Robert M West Enitan Carrol Lucy Brookes-Howell Philip Pallmann Bethany Shinkins Dominick Shaw Philip Howard Stacy Todd Thomas P Hellyer David G Partridge Mahableshwar Albur Martin Llewelyn Helena K Parsons Detelina Grozeva Joanne Euden Iain J McCullagh Josie Henley Wakunyambo Maboshe Stuart E Bond Procalcitonin to guide antibiotic use during the first wave of COVID-19 in English and Welsh hospitals: integration and triangulation of findings from quantitative and qualitative sources BMJ Open |
| title | Procalcitonin to guide antibiotic use during the first wave of COVID-19 in English and Welsh hospitals: integration and triangulation of findings from quantitative and qualitative sources |
| title_full | Procalcitonin to guide antibiotic use during the first wave of COVID-19 in English and Welsh hospitals: integration and triangulation of findings from quantitative and qualitative sources |
| title_fullStr | Procalcitonin to guide antibiotic use during the first wave of COVID-19 in English and Welsh hospitals: integration and triangulation of findings from quantitative and qualitative sources |
| title_full_unstemmed | Procalcitonin to guide antibiotic use during the first wave of COVID-19 in English and Welsh hospitals: integration and triangulation of findings from quantitative and qualitative sources |
| title_short | Procalcitonin to guide antibiotic use during the first wave of COVID-19 in English and Welsh hospitals: integration and triangulation of findings from quantitative and qualitative sources |
| title_sort | procalcitonin to guide antibiotic use during the first wave of covid 19 in english and welsh hospitals integration and triangulation of findings from quantitative and qualitative sources |
| url | https://bmjopen.bmj.com/content/15/8/e093210.full |
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