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.

Triangulation to integrate quantitative and qualitative data.

Four data sources in 148 NHS hospitals in England and Wales including data from 6089 patients.

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.

To explore whether PCT testing safely reduced antibiotic use during the first wave of the COVID-19 pandemic.

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.

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.

ISRCTN66682918.

To explore patient and healthcare professional perceptions about the acceptability and impact of a large-scale system for automated, real-time monitoring and feedback of shared decision-making (SDM) that has been integrated into surgical care pathways.

Qualitative, semistructured interviews were conducted with patients and healthcare professionals between June and November 2021. Data were analysed using deductive and inductive approaches.

Large-scale monitoring of SDM has been integrated in NHS surgical care across two large UK National Health Service Trusts.

Adult surgical patients (N=18, 56% female), following use of an SDM real-time monitoring and feedback system, and healthcare professionals (N=14, 36% female) involved in their surgical care. Patient recruitment was conducted through hospital research nurses and professionals by direct approach from the study team to sample individuals purposively from seven surgical specialties (general, vascular, urology, orthopaedics, breast, gynaecology and urgent cardiac).

10 themes were identified within three areas of exploration that described factors underpinning: (1) the acceptability of large-scale automated, real-time monitoring of SDM experiences, (2) the acceptability of real-time feedback and addressing SDM deficiencies and (3) the impact of real-time monitoring and feedback. There was general support for real-time monitoring and feedback because of its perceived ability to efficiently address deficiencies in surgical patients’ SDM experience at scale, and its perceived benefits to patients, surgeons and the wider organisation. Factors potentially influencing acceptability of large-scale automated, real-time monitoring and feedback were identified for both stakeholder groups, for example, influence of survey timing on patient-reported SDM scores, disease-specific risks, patients’ dissatisfaction with hospital processes. Factors particularly important for patients included concerns over digital exclusion exacerbated by electronic real-time monitoring. Factors unique to professionals included the need for detailed, qualitative feedback of SDM to contextualise patient-reported SDM scores.

This study explored factors influencing the acceptability of automated, real-time monitoring and feedback of patients’ experiences of SDM integrated into surgical practice, at scale among key stakeholders. Findings will be used to guide refinement and implementation of SDM monitoring and feedback prior to formal development, evaluation and implementation of an SDM intervention in the NHS.

ISRCTN17951423.

doi: 10.1136/bmjopen-2023-079155.