Abstract
Introduction: Clostridium difficile (C.diff) has become a major healthcare burden from the beginning of the 2000s leading to an increase in hospital costs, length of hospitalization and mortality. The major risk factor associated with the infection is the consumption of broad-spectrum antibiotics 4C, (e.g. co-amoxiclav, clindamycin…), consequently, health boards scrutinised the prescribing of 4C antibiotics. However, GPs are unable to avoid the prescription of 4C antibiotics with particular patients, due to allergies or interaction with other medication.
Therefore a tool that support GPs to identify High-risk patient’s to contract C.diff has to be created
Method: a risk predictive mathematical model for C.diff has been created using patient’s demographics and clinical characteristics to predicate patients’ risk of C.diff infection. Three GP champions were interviewed, and shadowed to understand their perceptions of C.diff burden, needs for the tool and their general perceptions of using technology during consultations. Furthermore, barriers and facilitators that influence the implementation of this risk predictive tool was identified using the Consolidated Framework for Implementation Research (CIFR). This was followed by a co-design workshop to create a low fidelity prototype taking into consideration their needs, limitations of the model and the technology.
Result: Facilitators that emerged from the analysis were, a) GPs prefer the C.diff tool to be integrated into their prescribing system, b) clinicians have a positive attitude to adopt computer decision support tools when a definite requirement of the tool and ease of their workload was demonstrated and c) clinicians are aware they need help. While a couple of barriers that emerged was a) GPs low demand for C.diff risk predictive tool, b) C.diff is not perceived as an issue in primary care, c) patient data is not always up to date and d) they would prefer a tool that would guide them with the choice of antibiotic instead of just a risk score.
Nonetheless, these are the key findings, from the interview of only 3 GPs, therefore opinions from a broader panel of clinicians is required.
Future work: Further evaluation of the created prototype in terms of layout, format, usability and usefulness is required before testing the tool in clinical practice. This to be done with GPs as well as additional potential prescribers such as nurses, and pharmacists.
Therefore a tool that support GPs to identify High-risk patient’s to contract C.diff has to be created
Method: a risk predictive mathematical model for C.diff has been created using patient’s demographics and clinical characteristics to predicate patients’ risk of C.diff infection. Three GP champions were interviewed, and shadowed to understand their perceptions of C.diff burden, needs for the tool and their general perceptions of using technology during consultations. Furthermore, barriers and facilitators that influence the implementation of this risk predictive tool was identified using the Consolidated Framework for Implementation Research (CIFR). This was followed by a co-design workshop to create a low fidelity prototype taking into consideration their needs, limitations of the model and the technology.
Result: Facilitators that emerged from the analysis were, a) GPs prefer the C.diff tool to be integrated into their prescribing system, b) clinicians have a positive attitude to adopt computer decision support tools when a definite requirement of the tool and ease of their workload was demonstrated and c) clinicians are aware they need help. While a couple of barriers that emerged was a) GPs low demand for C.diff risk predictive tool, b) C.diff is not perceived as an issue in primary care, c) patient data is not always up to date and d) they would prefer a tool that would guide them with the choice of antibiotic instead of just a risk score.
Nonetheless, these are the key findings, from the interview of only 3 GPs, therefore opinions from a broader panel of clinicians is required.
Future work: Further evaluation of the created prototype in terms of layout, format, usability and usefulness is required before testing the tool in clinical practice. This to be done with GPs as well as additional potential prescribers such as nurses, and pharmacists.
Original language | English |
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Publication status | Published - 28 May 2019 |
Event | Global Implementation Conference - Scottish Event Campus, Glasgow, United Kingdom Duration: 15 Sept 2019 → 17 Dec 2019 |
Conference
Conference | Global Implementation Conference |
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Abbreviated title | GIC |
Country/Territory | United Kingdom |
City | Glasgow |
Period | 15/09/19 → 17/12/19 |
Keywords
- clostridium difficile
- risk prediction
- risk factors