Dataset Information

How effective are electronic medication systems in reducing medication error rates and associated harm among hospital inpatients? A systematic review and meta-analysis.

ABSTRACT:

Objective

To conduct a systematic review and meta-analysis to assess: 1) changes in medication error rates and associated patient harm following electronic medication system (EMS) implementation; and 2) evidence of system-related medication errors facilitated by the use of an EMS.

Materials and methods

We searched Medline, Scopus, Embase, and CINAHL for studies published between January 2005 and March 2019, comparing medication errors rates with or without assessments of related harm (actual or potential) before and after EMS implementation. EMS was defined as a computer-based system enabling the prescribing, supply, and/or administration of medicines. Study quality was assessed.

Results

There was substantial heterogeneity in outcomes of the 18 included studies. Only 2 were strong quality. Meta-analysis of 5 studies reporting change in actual harm post-EMS showed no reduced risk (RR: 1.22, 95% CI: 0.18-8.38, P?=?.8) and meta-analysis of 3 studies reporting change in administration errors found a significant reduction in error rates (RR: 0.77, 95% CI: 0.72-0.83, P?=?.004). Of 10 studies of prescribing error rates, 9 reported a reduction but variable denominators precluded meta-analysis. Twelve studies provided specific examples of system-related medication errors; 5 quantified their occurrence.

Discussion and conclusion

Despite the wide-scale adoption of EMS in hospitals around the world, the quality of evidence about their effectiveness in medication error and associated harm reduction is variable. Some confidence can be placed in the ability of systems to reduce prescribing error rates. However, much is still unknown about mechanisms which may be most effective in improving medication safety and design features which facilitate new error risks.

SUBMITTER: Gates PJ

PROVIDER: S-EPMC7810459 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Publications

How effective are electronic medication systems in reducing medication error rates and associated harm among hospital inpatients? A systematic review and meta-analysis.

Gates Peter J PJ Hardie Rae-Anne RA Raban Magdalena Z MZ Li Ling L Westbrook Johanna I JI

Journal of the American Medical Informatics Association : JAMIA 20210101 1

<h4>Objective</h4>To conduct a systematic review and meta-analysis to assess: 1) changes in medication error rates and associated patient harm following electronic medication system (EMS) implementation; and 2) evidence of system-related medication errors facilitated by the use of an EMS.<h4>Materials and methods</h4>We searched Medline, Scopus, Embase, and CINAHL for studies published between January 2005 and March 2019, comparing medication errors rates with or without assessments of related h ...[more]

PMID: 33164058

Similar Datasets

Project description:BACKGROUND:Computerized physician order entry and clinical decision support systems are electronic prescribing strategies that are increasingly used to improve patient safety. Previous reviews show limited effect on patient outcomes. Our objective was to assess the impact of electronic prescribing strategies on medication errors and patient harm in hospitalized patients. METHODS:MEDLINE, EMBASE, CENTRAL, and CINAHL were searched from January 2007 to January 2018. We included prospective studies that compared hospital-based electronic prescribing strategies with control, and reported on medication error or patient harm. Data were abstracted by two reviewers and pooled using random effects model. Study quality was assessed using the Effective Practice and Organisation of Care and evidence quality was assessed using Grading of Recommendations Assessment, Development, and Evaluation. RESULTS:Thirty-eight studies were included; comprised of 11 randomized control trials and 27 non-randomized interventional studies. Electronic prescribing strategies reduced medication errors (RR 0.24 (95% CI 0.13, 0.46), I2 98%, n?=?11) and dosing errors (RR 0.17 (95% CI 0.08, 0.38), I2 96%, n?=?9), with both risk ratios significantly affected by advancing year of publication. There was a significant effect of electronic prescribing strategies on adverse drug events (ADEs) (RR 0.52 (95% CI 0.40, 0.68), I2 0%, n?=?2), but not on preventable ADEs (RR 0.55 (95% CI 0.30, 1.01), I2 78%, n?=?3), hypoglycemia (RR 1.03 (95% CI 0.62-1.70), I2 28%, n?=?7), length of stay (MD -?0.18 (95% -?1.42, 1.05), I2 94%, n?=?7), or mortality (RR 0.97 (95% CI 0.79, 1.19), I2 74%, n?=?9). The quality of evidence was rated very low. DISCUSSION:Electronic prescribing strategies decrease medication errors and adverse drug events, but had no effect on other patient outcomes. Conservative interpretations of these findings are supported by significant heterogeneity and the preponderance of low-quality studies.

Project description:BACKGROUND: Considerable investments are being made in commercial electronic prescribing systems (e-prescribing) in many countries. Few studies have measured or evaluated their effectiveness at reducing prescribing error rates, and interactions between system design and errors are not well understood, despite increasing concerns regarding new errors associated with system use. This study evaluated the effectiveness of two commercial e-prescribing systems in reducing prescribing error rates and their propensities for introducing new types of error. METHODS AND RESULTS: We conducted a before and after study involving medication chart audit of 3,291 admissions (1,923 at baseline and 1,368 post e-prescribing system) at two Australian teaching hospitals. In Hospital A, the Cerner Millennium e-prescribing system was implemented on one ward, and three wards, which did not receive the e-prescribing system, acted as controls. In Hospital B, the iSoft MedChart system was implemented on two wards and we compared before and after error rates. Procedural (e.g., unclear and incomplete prescribing orders) and clinical (e.g., wrong dose, wrong drug) errors were identified. Prescribing error rates per admission and per 100 patient days; rates of serious errors (5-point severity scale, those ?3 were categorised as serious) by hospital and study period; and rates and categories of postintervention "system-related" errors (where system functionality or design contributed to the error) were calculated. Use of an e-prescribing system was associated with a statistically significant reduction in error rates in all three intervention wards (respectively reductions of 66.1% [95% CI 53.9%-78.3%]; 57.5% [33.8%-81.2%]; and 60.5% [48.5%-72.4%]). The use of the system resulted in a decline in errors at Hospital A from 6.25 per admission (95% CI 5.23-7.28) to 2.12 (95% CI 1.71-2.54; p<0.0001) and at Hospital B from 3.62 (95% CI 3.30-3.93) to 1.46 (95% CI 1.20-1.73; p<0.0001). This decrease was driven by a large reduction in unclear, illegal, and incomplete orders. The Hospital A control wards experienced no significant change (respectively -12.8% [95% CI -41.1% to 15.5%]; -11.3% [-40.1% to 17.5%]; -20.1% [-52.2% to 12.4%]). There was limited change in clinical error rates, but serious errors decreased by 44% (0.25 per admission to 0.14; p?=?0.0002) across the intervention wards compared to the control wards (17% reduction; 0.30-0.25; p?=?0.40). Both hospitals experienced system-related errors (0.73 and 0.51 per admission), which accounted for 35% of postsystem errors in the intervention wards; each system was associated with different types of system-related errors. CONCLUSIONS: Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates. Reductions in clinical errors were limited in the absence of substantial decision support, but a statistically significant decline in serious errors was observed. System-related errors require close attention as they are frequent, but are potentially remediable by system redesign and user training. Limitations included a lack of control wards at Hospital B and an inability to randomize wards to the intervention.

Project description:IntroductionThe benchmarking for medication incidents rate is not regarded as a recognized key performance measure or indicator in national or international organizations. The absence of benchmarking the medication incidents results in the loss of a self-governing perception of how well we performed compared to other peers.Methodology and settingsThis 600-bed tertiary, Joint Commission International (JCI) accredited hospital retrospective analysis looked at all medication management-related events from January-2018 to December-2021. The study design follows descriptive, cross-sectional, retrospective prevalence research.ResultsThe rate of medication incidents that resulted in harm declined from Q3-2019 to Q4-2021. A significant increase in Pharmacy interventions/clarifications was recorded. Additionally, a significant increase in incidents reported with no-harm coupled with a significant reduction in incidences of serious events from 2019 to 2020. Finally, no-harm events were significantly reduced from 2020 to 2021.DiscussionThe Pharmacy's study analyzed every medication incident documented from 2019 to 2021. 99.7% of reported incidents were classified as no-harm (near misses). There was an exponential decrease from Q1-2020 to Q1-202. A significant increase in incidents fell in the category of (near misses) with no-harm and a significant reduction in serious events. Pharmacy interventions/clarifications saw a massive increase and impact from Q3-2018 to Q2-2019, compared to the same period in 2018. By preventing medical incidents, benchmarking, and analyzing incidents and the reporting system, the use of information technology could dramatically reduce the rate of drug incidents.ConclusionThis study found that benchmarking medication incidents is valuable, as it can help identify areas where improvements can be made, implement strategies to improve safety, and track progress over time. The benchmark was recommended to be below 100 incidents for every 10,000 prescriptions/orders processed, and for E-I categories, below one incident for every 10,000 prescriptions/orders processed. This will help develop a worldwide standard with an absolved culture with non-punitive consequences.

Project description:Adverse drug reactions, poor patient adherence and errors, here collectively referred to as medication-related harm (MRH), cause around 2.7-8.0% of UK hospital admissions. Communication gaps between successive healthcare providers exist, but little is known about how MRH is recorded in inpatients' medical records. We describe the presence and quality of MRH documentation for patients admitted to a London teaching hospital due to MRH. Additionally, the international classification of disease 10th revision (ICD-10) codes attributed to confirmed MRH-related admissions were studied to explore appropriateness of their use to identify these patients.Clinical pharmacists working on an admissions ward in a UK hospital identified patients admitted due to suspected MRH. Six different data sources in each patient's medical record, including the discharge summary, were subsequently examined for MRH-related information. Each data source was examined for statements describing the MRH: symptom and diagnosis, identification of the causative agent, and a statement of the action taken or considered. Statements were categorised as 'explicit' if unambiguous or 'implicit' if open to interpretation. ICD-10 codes attributed to confirmed MRH cases were recorded.Eighty-four patients were identified over 141 data collection days; 75 met our inclusion criteria. MRH documentation was generally present (855 of 1307 statements were identified; 65%), and usually explicit (705 of 855; 82%). The causative agent had the lowest proportion of explicit statements (139 of 201 statements were explicit; 69%). For two (3%) discharged patients, the causal agent was documented in their paper medical record but not on the discharge summary. Of 64 patients with a confirmed MRH diagnosis at discharge, only six (9%) had a MRH-related ICD-10 code.Availability of information in the paper medical record needs improving and communication of MRH-related information could be enhanced by using explicit statements and documenting reasons for changing medications. ICD-10 codes underestimate the true occurrence of MRH.

Project description:People who smoke make up a significant number of those admitted to hospital (NICE 2014). Being admitted to hospital can present a unique opportunity to attempt to stop smoking. Many smokers find quitting very difficult (Rigotti et al 2007), in large part due to them living and working in environments that contain many cues and triggers associated with nicotine consumption and smoking behaviours. Hospitals generally do not contain such environmental prompts to smoke. In the community, smokers have access to numerous types of support including GP's, pharmacies and Stop Smoking Services (SSS). Once admitted to hospital access to such support is significantly diminished. Given that many patients may be highly motivated to attempt to stop smoking due to heightened concerns about their health and being in an environment not associated with their smoking habits, it seems prudent to ensure there is access to all the levels of smoking cessation support available outside of the hospital. Not providing such support neglects implementing an evidence based, cost-effective health intervention in a major health setting (NICE 2014). A SSS pathway was designed that enabled existing hospital healthcare staff to be trained to identify patients that smoke, ask if the patient is considering quitting or abstaining whilst in hospital. If motivated to quit or abstain, to complete an assessment. This being based around dependence to nicotine and motivation to quit. Access to all available stop smoking medications should be included. Medication should only be provided alongside some level of motivational support up to discharge. Training core staff was felt to be the best option. They are available outside of office hours and access hospital systems such as pharmacy more readily than satellite staff. On discharge the patient is 'handed over' to SSS for continued contact and support once at home. Over 200 staff are trained to complete the assessment and support inpatients to stop or abstain. Approximately 30-35 referrals are made to the local SSS each month, the quit rate at 4 weeks averaging around 40-45%. Most referrals are seen from cardiology and respiratory. All hospital departments should identify staff to be trained to offer cessation support to their patients .

Dataset Information

How effective are electronic medication systems in reducing medication error rates and associated harm among hospital inpatients? A systematic review and meta-analysis.

Objective

Materials and methods

Results

Discussion and conclusion

Publications

How effective are electronic medication systems in reducing medication error rates and associated harm among hospital inpatients? A systematic review and meta-analysis.

Similar Datasets

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