Background to the question
An adverse drug event (ADE) is an injury resulting from a medical intervention related to a drug. ADEs are sometimes associated with medication errors. ADEs and medication errors may cause important harm, costs and even death.
Interventions for reducing medication errors include medication reconciliation, which is the process of comparing a patient's medication orders to the medications that the patient has been taking. Medication reconciliation can be performed jointly with other interventions, such as electronic prescribing systems, barcoding for a correct administering of medications, organisational changes, feedback on medication errors, education of professionals and improved medication dispensing systems.
Review question
What is the effectiveness of interventions to reduce medication errors for adults in hospital settings?
We included inpatient care settings (secondary or tertiary units, intensive care units, operating theatres), outpatient care settings, and accident and emergency departments.
Study characteristics
We searched databases of scientific studies. We included 65 studies, 51 of which were randomised trials, involving 23,182 adults in hospital settings. The remaining 14 studies were large interrupted time-series that concern long-term period before and after a point of intervention to assess the intervention's effects, involving more than 87,000 participants.
Certainty of the evidence
We assessed the included evidence to establish how certain we are that the effects are true and would not be altered with the addition of more evidence. In general, we judged the certainty of the evidence to be low to moderate, but it was very low for some outcomes.
Key results
Medication reconciliation compared with no medication reconciliation probably reduce ADEs and may reduce medication errors. It may have little to no effect on length of stay or quality of life. However, the effect of medication reconciliation on these latter outcomes is imprecise; it is not clear if the effects are beneficial or detrimental (low- to moderate-certainty evidence).
Compared to medication reconciliation by other professionals, medication reconciliation performed by pharmacists may increase ADEs (but this result is imprecise); may reduce medication errors; and may have little to no effect on length of stay, mortality during hospitalisation, and readmissions. However, these effects are imprecise (low-certainty evidence).
Compared to no assistance, database-assisted medication reconciliation conducted by pharmacists may reduce potential ADEs and may have no effect on length of stay, but the last effect is imprecise (low-certainty evidence).
Medication reconciliation performed by trained pharmacist technicians instead of pharmacists, may have no effect on length of stay, but this effect is imprecise (low-certainty evidence).
Medication reconciliation before admission, versus after admission, may increase identified discrepancies; however, the effect is imprecise (low-certainty evidence).
Compared to usual care, some interventions have different effects:
Multimodal interventions probably increase discrepancy resolutions (moderate-certainty evidence).
Electronic prescribing systems probably reduce medication errors and ADEs. Prioritised alerts may additionally prevent ADEs (low- to moderate-certainty evidence).
Barcode identification of participants or medications may reduce medication errors (low-certainty evidence).
Reduced working hours and feedback on medication errors may reduce serious medication errors; however, the effect is imprecise (low-certainty evidence).
Authors' conclusions
Compared to usual care, medication reconciliation, electronic prescribing systems, barcoding and feedback to professionals may reduce ADEs or medication errors, or both. Nonetheless, the best modalities to deliver these interventions, and the effect of other interventions, are less clear.
How up to date is this review?
The review authors searched for studies that had been published up to January 2020.
Low- to moderate-certainty evidence suggests that, compared to usual care, medication reconciliation, CPOE/CDSS, barcoding, feedback and dispensing systems in surgical wards may reduce medication errors and ADEs. However, the results are imprecise for some outcomes related to medication reconciliation and CPOE/CDSS. The evidence for other interventions is very uncertain. Powered and methodologically sound studies are needed to address the identified evidence gaps. Innovative, synergistic strategies –including those that involve patients– should also be evaluated.
Medication errors are preventable events that may cause or lead to inappropriate medication use or patient harm while the medication is in the control of the healthcare professional or patient. Medication errors in hospitalised adults may cause harm, additional costs, and even death.
To determine the effectiveness of interventions to reduce medication errors in adults in hospital settings.
We searched CENTRAL, MEDLINE, Embase, five other databases and two trials registers on 16 January 2020.
We included randomised controlled trials (RCTs) and interrupted time series (ITS) studies investigating interventions aimed at reducing medication errors in hospitalised adults, compared with usual care or other interventions. Outcome measures included adverse drug events (ADEs), potential ADEs, preventable ADEs, medication errors, mortality, morbidity, length of stay, quality of life and identified/solved discrepancies. We included any hospital setting, such as inpatient care units, outpatient care settings, and accident and emergency departments.
We followed the standard methodological procedures expected by Cochrane and the Effective Practice and Organisation of Care (EPOC) Group. Where necessary, we extracted and reanalysed ITS study data using piecewise linear regression, corrected for autocorrelation and seasonality, where possible.
We included 65 studies: 51 RCTs and 14 ITS studies, involving 110,875 participants. About half of trials gave rise to 'some concerns' for risk of bias during the randomisation process and one-third lacked blinding of outcome assessment. Most ITS studies presented low risk of bias. Most studies came from high-income countries or high-resource settings. Medication reconciliation –the process of comparing a patient's medication orders to the medications that the patient has been taking– was the most common type of intervention studied. Electronic prescribing systems, barcoding for correct administering of medications, organisational changes, feedback on medication errors, education of professionals and improved medication dispensing systems were other interventions studied.
Medication reconciliation
Low-certainty evidence suggests that medication reconciliation (MR) versus no-MR may reduce medication errors (odds ratio [OR] 0.55, 95% confidence interval (CI) 0.17 to 1.74; 3 studies; n=379). Compared to no-MR, MR probably reduces ADEs (OR 0.38, 95%CI 0.18 to 0.80; 3 studies, n=1336 ; moderate-certainty evidence), but has little to no effect on length of stay (mean difference (MD) -0.30 days, 95%CI -1.93 to 1.33 days; 3 studies, n=527) and quality of life (MD -1.51, 95%CI -10.04 to 7.02; 1 study, n=131).
Low-certainty evidence suggests that, compared to MR by other professionals, MR by pharmacists may reduce medication errors (OR 0.21, 95%CI 0.09 to 0.48; 8 studies, n=2648) and may increase ADEs (OR 1.34, 95%CI 0.73 to 2.44; 3 studies, n=2873). Compared to MR by other professionals, MR by pharmacists may have little to no effect on length of stay (MD -0.25, 95%CI -1.05 to 0.56; 6 studies, 3983). Moderate-certainty evidence shows that this intervention probably has little to no effect on mortality during hospitalisation (risk ratio (RR) 0.99, 95%CI 0.57 to 1.7; 2 studies, n=1000), and on readmissions at one month (RR 0.93, 95%CI 0.76 to 1.14; 2 studies, n=997); and low-certainty evidence suggests that the intervention may have little to no effect on quality of life (MD 0.00, 95%CI -14.09 to 14.09; 1 study, n=724).
Low-certainty evidence suggests that database-assisted MR conducted by pharmacists, versus unassisted MR conducted by pharmacists, may reduce potential ADEs (OR 0.26, 95%CI 0.10 to 0.64; 2 studies, n=3326), and may have no effect on length of stay (MD 1.00, 95%CI -0.17 to 2.17; 1 study, n=311).
Low-certainty evidence suggests that MR performed by trained pharmacist technicians, versus pharmacists, may have little to no difference on length of stay (MD -0.30, 95%CI -2.12 to 1.52; 1 study, n=183). However, the CI is compatible with important beneficial and detrimental effects.
Low-certainty evidence suggests that MR before admission may increase the identification of discrepancies compared with MR after admission (MD 1.27, 95%CI 0.46 to 2.08; 1 study, n=307). However, the CI is compatible with important beneficial and detrimental effects.
Moderate-certainty evidence shows that multimodal interventions probably increase discrepancy resolutions compared to usual care (RR 2.14, 95%CI 1.81 to 2.53; 1 study, n=487).
Computerised physician order entry (CPOE)/clinical decision support systems (CDSS)
Moderate-certainty evidence shows that CPOE/CDSS probably reduce medication errors compared to paper-based systems (OR 0.74, 95%CI 0.31 to 1.79; 2 studies, n=88).
Moderate-certainty evidence shows that, compared with standard CPOE/CDSS, improved CPOE/CDSS probably reduce medication errors (OR 0.85, 95%CI 0.74 to 0.97; 2 studies, n=630).
Low-certainty evidence suggests that prioritised alerts provided by CPOE/CDSS may prevent ADEs compared to non-prioritised (inconsequential) alerts (MD 1.98, 95%CI 1.65 to 2.31; 1 study; participant numbers unavailable).
Barcode identification of participants/medications
Low-certainty evidence suggests that barcoding may reduce medication errors (OR 0.69, 95%CI 0.59 to 0.79; 2 studies, n=50,545).
Reduced working hours
Low-certainty evidence suggests that reduced working hours may reduce serious medication errors (RR 0.83, 95%CI 0.63 to 1.09; 1 study, n=634). However, the CI is compatible with important beneficial and detrimental effects.
Feedback on prescribing errors
Low-certainty evidence suggests that feedback on prescribing errors may reduce medication errors (OR 0.47, 95%CI 0.33 to 0.67; 4 studies, n=384).
Dispensing system
Low-certainty evidence suggests that dispensing systems in surgical wards may reduce medication errors (OR 0.61, 95%CI 0.47 to 0.79; 2 studies, n=1775).