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Cited by 105Patient Safety and Medication ErrorsPharmaceutical Practices and Patient OutcomesPharmacovigilance and Adverse Drug Reactions

Reducing medication errors for adults in hospital settings

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Ciapponi, Agustín, Fernandez Nievas, Simon E, Seijo, Mariana, Rodríguez, María Belén, Vietto, Valeria, García-Perdomo, Herney A, Virgilio, Sacha, Fajreldines, Ana V +3 more·2021·Cochrane Database of Systematic Reviews
DOI 10.1002/14651858.cd009985.pub2PMC PMC8614640
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Abstract

BACKGROUND: 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. OBJECTIVES: To determine the effectiveness of interventions to reduce medication errors in adults in hospital settings. SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, five other databases and two trials registers on 16 January 2020. SELECTION CRITERIA: 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. DATA COLLECTION AND ANALYSIS: 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. MAIN RESULTS: 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

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  • A recent Cochrane meta-analysis concluded that compared to usual care, medication reconciliation, CPOE/CDSS, barcoding, feedback, and dispensing systems in surgical wards may reduce adverse drug events, medication errors, or both.

    “A recent Cochrane meta-analysis concluded that compared to usual care, medication reconciliation, computerized physician order entry (CPOE)/clinical decision support systems (CDSS), barcoding, feedback, and dispensing systems in surgical wards may reduce adverse drug events (ADEs), medication errors, or both (11).”

    From Application of zero trust model in preventing medical errors (2024) · cites this paper as [11]

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  • Application of zero trust model in preventing medical errors

    Sood, N., Parlapalli, R., Sharma, P., & Kashyap, R. (2024) · Frontiers in Health Services · doi:10.3389/frhs.2024.1453804 · Cited by 3 · see citing works

    “…meta-analysis concluded that compared to usual care, medication reconciliation, computerized physician order entry (CPOE)/ clinical decision support systems (CDSS), barcoding, feedback, and dispensing systems in surgical wards may reduce adverse drug events (ADEs), medication errors, or both (11).”
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Authors
Ciapponi, A., Fernandez Nievas, S. E., Seijo, M., Rodríguez, M. B., Vietto, V., García-Perdomo, H. A., Virgilio, S., Fajreldines, A. V., Tost, J., Rose, C. J., & Garcia-Elorrio, E.
Affiliations
  • Consejo Nacional de Investigaciones Científicas y Técnicas (AR)
  • Quality and Patient Safety; Institute for Clinical Effectiveness and Health Policy; Buenos Aires Argentina
  • Instituto de Efectividad Clínica y Sanitaria (AR)
  • Hospital Italiano de Buenos Aires (AR)
  • Department of Urology; Universidad del Valle; Cali Colombia
  • Austral University (AR)
  • Consorci Sanitari de Terrassa (ES)
  • Norwegian Institute of Public Health (NO)
  • Quality and Safety in Health Care; Institute for Clinical Effectiveness and Health Policy (IECS); Buenos Aires Argentina
ORCID
Venue
Cochrane Database of Systematic Reviews
Publisher
Wiley
Published
2021-11-25
Volume
2021
Issue
11
Pages
CD009985-CD009985
ISSN
  • 1361-6137 (ISSN-L)
  • 1465-1858
DOI
10.1002/14651858.cd009985.pub2
PMC
PMC8614640
OpenAlex
W3215522009
Cited by
105
References
144
Citations by year
2026: 15 · 2025: 36 · 2024: 22 · 2023: 19 · 2022: 13
FWCI
3.31
Type
journal article
Language
en
Open access
Locations
  • Cochrane Database of Systematic Reviews (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • CONICET Digital (CONICET) (submittedVersion, cc-by)
  • Greater South Information System
Topics
  • Health Sciences › Health Professions › Emergency Medical Services › Patient Safety and Medication Errors
  • Health Sciences › Medicine › Geriatrics and Gerontology › Pharmaceutical Practices and Patient Outcomes
  • Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Toxicology › Pharmacovigilance and Adverse Drug Reactions
Keywords
medication errors, hospitalized adults, medication reconciliation, adverse drug reactions, electronic prescribing, medication dispensing systems, organizational interventions, patient safety, length of hospital stay, mortality, quality of life, preventable adverse drug events, risk of bias, interrupted time series, risk of bias assessment
MeSH terms
Adult, Hospitalization, Hospitals, Humans, Medication Errors, Pharmacists, Medication Reconciliation

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