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Computerised interventions designed to reduce potentially inappropriate prescribing in hospitalised older adults: a
Kieran Dalton1, Gary O'Brien1, Denis O'Mahony2,3
1Pharmaceutical Care Research Group, School of Pharmacy, University College Cork, Cork, Ireland.
Background:
computerised interventions have been suggested as an effective strategy to reduce potentially inappropriate prescribing (PIP) for hospitalised older adults. This systematic review and meta-analysis examined the evidence for efficacy of computerised interventions designed to reduce PIP in this patient group.
Methods:
an electronic literature search was conducted using eight databases up to October 2017. Included studies were controlled trials of computerised interventions aiming to reduce PIP in hospitalised older adults (≥65 years). Risk of bias was assessed using Cochrane's Effective Practice and Organisation of Care criteria.
Results:
of 653 records identified, eight studies were included-two randomised controlled trials, two interrupted time series analysis studies and four controlled before-after studies. Included studies were mostly at a low risk of bias. Overall, seven studies showed either a statistically significant reduction in the proportion of patients prescribed a potentially inappropriate medicine (PIM) (absolute risk reduction {ARR} 1.3-30.1%), or in PIMs ordered (ARR 2-5.9%). However, there is insufficient evidence thus far to suggest that these interventions can routinely improve patient-related outcomes. It was only possible to include three studies in the meta-analysis-which demonstrated that intervention patients were less likely to be prescribed a PIM (odds ratio 0.6; 95% CI 0.38, 0.93). No computerised intervention targeting potential prescribing omissions (PPOs) was identified.
Conclusions:
this systematic review concludes that computerised interventions are capable of statistically significantly reducing PIMs in hospitalised older adults. Future interventions should strive to target both PIMs and PPOs, ideally demonstrating both cost-effectiveness data and clinically significant improvements in patient-related outcomes.
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