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Comparing GPs' antibiotic prescribing decisions to a clinical prediction rule: an online vignette study
Martine Nurek1, Alastair D Hay2, Olga Kostopoulou1
1Department of Surgery and Cancer, Imperial College London, London.
Insights
General practitioners (GPs) partially utilized the STARWAVe clinical prediction rule (CPR) for assessing children with cough. Discrepancies between rule factors and GP decisions highlight implementation challenges for CPRs in clinical practice.
Area of Science:
- Pediatric Medicine
- Clinical Decision Support
- General Practice
Background:
- The STARWAVe clinical prediction rule (CPR) aids risk assessment and antibiotic prescribing for pediatric cough.
- It comprises seven factors: Short illness duration, Temperature, Age, Recession, Wheeze, Asthma, and Vomiting.
Purpose of the Study:
- To evaluate how STARWAVe factors influence general practitioners' (GPs) unaided risk assessments and antibiotic prescribing decisions.
- To identify discrepancies between the CPR's intended use and actual clinical practice.
Main Methods:
- 188 UK GPs assessed clinical vignettes of children with cough online.
- Vignettes systematically varied the seven STARWAVe factors.
- GPs indicated risk assessment and antibiotic prescribing decisions; mixed-effects regressions analyzed influences.
Main Results:
- Six STARWAVe factors correctly influenced risk assessments, while one (short illness duration) incorrectly reduced them.
- Temperature increased antibiotic prescribing odds, whereas short illness duration, age, and recession reduced them.
- Parental concern elevated risk assessments but not prescribing decisions.
Conclusions:
- GPs selectively applied STARWAVe factors in risk assessment and antibiotic prescribing.
- Observed discrepancies necessitate careful consideration during CPR implementation in clinical settings.
Background:
The 'STARWAVe' clinical prediction rule (CPR) uses seven factors to guide risk assessment and antibiotic prescribing in children with cough (Short illness duration, Temperature, Age, Recession, Wheeze, Asthma, Vomiting).
Aim:
To assess the influence of STARWAVe factors on GPs' unaided risk assessments and prescribing decisions.
Design And Setting:
Clinical vignettes administered to 188 UK GPs online.
Method:
GPs were randomly assigned to view 32 (out of a possible 64) vignettes online depicting children with cough. The vignettes comprised the seven STARWAVe factors, which were varied systematically. For each vignette, GPs assessed risk of deterioration in one of two ways (sliding-scale versus risk-category selection) and indicated whether they would prescribe antibiotics. Finally, GPs saw an additional vignette, suggesting that the parent was concerned. Mixed-effects regressions were used to measure the influence of STARWAVe factors, risk-elicitation method, and parental concern on GPs' assessments and decisions.
Results:
Six STARWAVe risk factors correctly increased GPs' risk assessments (bssliding-scale≥0.66, odds ratios [ORs]category-selection≥1.75, Ps≤0.001), whereas one incorrectly reduced them (short illness duration: b sliding-scale -0.30, ORcategory-selection 0.80, P≤0.039). Conversely, one STARWAVe factor increased prescribing odds (temperature: OR 5.22, P<0.001), whereas the rest either reduced them (short illness duration, age, and recession: ORs≤0.70, Ps<0.001) or had no significant impact (wheeze, asthma, and vomiting: Ps≥0.065). Parental concern increased risk assessments (b sliding-scale 1.29, ORcategory-selection 2.82, P≤0.003) but not prescribing odds (P = 0.378).
Conclusion:
GPs use some, but not all, STARWAVe factors when making unaided risk assessments and prescribing decisions. Such discrepancies must be considered when introducing CPRs to clinical practice.
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