The pattern of the discovery of medication errors in a tertiary hospital in Hong Kong

Background The primary goal of reducing medication errors is to eliminate those that reach the patient. Objective We aimed to study the pattern of interceptions to tackle medication errors along the medication use processes. Setting Tertiary care hospital in Hong Kong. Method The ‘Swiss Cheese Model’ was used to explain the interceptions targeting medication error reporting over 5 years (2006–2010). Main outcome measures Proportions of prescribing, dispensing and drug administration errors intercepted by pharmacists and nurses; proportions of prescribing, dispensing and drug administration errors that reached the patient. Results Our analysis included 1,268 in-patient medication errors, of which 53.4 % were related to prescribing, 29.0 % to administration and 17.6 % to dispensing. 34.1 % of all medication errors (4.9 % prescribing, 26.8 % drug administration and 2.4 % dispensing) were not intercepted. Pharmacy staff intercepted 85.4 % of the prescribing errors. Nurses detected 83.0 % of dispensing and 5.0 % of prescribing errors. However, 92.4 % of all drug administration errors reached the patient. Conclusions Having a preventive measure at each stage of the medication use process helps to prevent most errors. Most drug administration errors reach the patient as there is no defense against these. Therefore, more interventions to prevent drug administration errors are warranted.     

我院门诊药房处方调剂内部差错的影响因素分析

目的分析我院门诊药房内部调剂差错发生率及类型,提高调剂工作质量。方法采用多因素回归分析我院门诊药房2010年4月～12月三个季度内发生的1 191例内部处方调剂差错。结果内部调剂差错分为5类,内容包括药品标签粘贴不规范、药品用法错误、药品错配、药品数量多配及药品数量少配,其中药品数量差错发生率占总内部调剂差错发生率的64.23%,第四季度的内部调剂差错发生率最低(P<0.01),各类型内部调剂差错发生率均较前两个季度有大幅下降(P<0.01)。结论药品数量错配是构成门诊处方内部调剂差错的主要因素,应采取相应的防范措施,保障患者用药安全。     

Electronic Inventory Systems and Barcode Technology: Impact on Pharmacy Technical Accuracy and Error Liability

Purpose:

To measure the effects associated with sequential implementation of electronic medication storage and inventory systems and product verification devices on pharmacy technical accuracy and rates of potential medication dispensing errors in an academic medical center.

Methods:

During four 28-day periods of observation, pharmacists recorded all technical errors identified at the final visual check of pharmaceuticals prior to dispensing. Technical filling errors involving deviations from order-specific selection of product, dosage form, strength, or quantity were documented when dispensing medications using (a) a conventional unit dose (UD) drug distribution system, (b) an electronic storage and inventory system utilizing automated dispensing cabinets (ADCs) within the pharmacy, (c) ADCs combined with barcode (BC) verification, and (d) ADCs and BC verification utilized with changes in product labeling and individualized personnel training in systems application.

Results:

Using a conventional UD system, the overall incidence of technical error was 0.157% (24/15,271). Following implementation of ADCs, the comparative overall incidence of technical error was 0.135% (10/7,379; P = .841). Following implementation of BC scanning, the comparative overall incidence of technical error was 0.137% (27/19,708; P = .729). Subsequent changes in product labeling and intensified staff training in the use of BC systems was associated with a decrease in the rate of technical error to 0.050% (13/26,200; P = .002).

Conclusions:

Pharmacy ADCs and BC systems provide complementary effects that improve technical accuracy and reduce the incidence of potential medication dispensing errors if this technology is used with comprehensive personnel training.     

Exploring the impact of feedback on prescribing error rates: a pilot study

Background Prescribing errors are prevalent in hospital settings with feedback identified as one potential error reduction strategy. Hospital pharmacists work alongside prescribers at ward level and are credible facilitators of prescribing error feedback. A formalised programme of pharmacist-led prescribing error feedback was designed and implemented Objective To determine the impact of the feedback intervention on prescribing error rates. Method Prospective prescribing audits were undertaken at baseline for control (n = 11) and intervention group (n = 10) prescribers. The intervention group received pharmacist-led, individualised constructive feedback on their prescribing, whilst the control group continued with existing practice. Prescribing was re-audited following 3-months of the intervention. Data were analysed using chi-squared and independent t-tests. Results Error frequency (123/641 intervention and 121/649 control) was comparable between groups at baseline (p = 0.819) with significant differences (90/1677 intervention and 236/984 control) post intervention (p = <0.005). Prescribing error rates were lower in the intervention group (mean change of ?11.5%) and higher in the control group (mean change of +5.9%) following the intervention, with a mean significant difference of 17.4% (SD 4.7, 95% CI, ?27.3 to ?7.6), t = ?3.694, p < 0.05, between groups. Conclusion Pharmacist-led prescribing error feedback positively influences prescribing. This intervention shows promise for wider application in hospital settings to optimise patient safety.     

Towards improving dose administration aid supply: a quality improvement intervention aimed at reducing dispensing errors

Background There is a risk that medicines can be dispensed into dose administration aids (DAAs), inaccurately or unsuitably. Quality improvement interventions (QIIs) may target this pharmacy medicine supply service and reduce the occurrence of these dispensing errors. In turn, medicine administration can improve in nursing homes (NHs) that use these devices. Objective To develop, introduce and evaluate the potential of a QII to improve DAA medicine supply. Setting Fourteen Victorian community pharmacies and 45 NHs. Methods A QII was developed using findings from three focus groups with 13 participants involved with DAAs at community pharmacies and NHs. The intervention was introduced to community pharmacies and NHs via a pharmacist-facilitated education session; attendees completed an evaluation questionnaire. Main outcome measure Potential usefulness and effectiveness of the QII at improving DAA supply and reducing dispensing errors. Results The QII was titled: ‘Be alert and work together for medicine safety, DAA incident awareness toolkit’. Four-hundred and thirty-five questionnaires were returned (85.0 % response rate). Respondents believed the intervention had the potential to improve pharmacy medicine supply or NH medicine administration involving DAAs ‘very’ (47.3 % of responses) or ‘extremely well’ (23.4 %). The intervention had the potential to reduce the occurrence of DAA dispensing errors ‘very’ (49.6 %) or ‘extremely well’ (20.5 %). Conclusion A stakeholder informed QII was perceived to have the potential to improve DAA medicine supply from community pharmacies to NHs and reduce the occurrence of dispensing errors found within them. Future quantitative evaluation of the intervention is required.     

The impact of an electronic prescribing and administration system on the safety and quality of medication administration

Objective To assess the effect of an electronic prescribing and administration system on the safety and quality of medication administration in a UK hospital. Setting Surgical ward in a teaching hospital. Method Data were collected before and after introducing a closed‐loop system comprising electronic prescribing, automated dispensing, barcode patient identification and electronic medication administration records (ServeRx, MDG Medical). We observed medication administration during drug rounds and assessed medication administration error (MAE) rates for ward‐stock and non‐ward‐stock drugs, accuracy of medication administration documentation, timeliness of administration, administration of medication from unlocked areas and supervision of patients taking oral medication by nursing staff. Key findings Pre‐ and post‐intervention MAE rates were 6.4 and 2.3% respectively for ward‐stock drugs (95% confidence interval for the difference (CI) ?5.8 to ?2.4%), and 14.6 and 13.7% for non‐ward‐stock drugs (CI ?6.5 to 4.7%). Excluding omissions due to unavailability, pre‐ and post‐intervention MAE rates were 6.2 and 2.2% respectively for ward‐stock drugs (CI ?5.7 to ?2.3%), and 9.2 and 3.5% for non‐ward‐stock drugs (CI ?9.3 to ?2.1%). Pre‐intervention, 2086 doses (96.3%) were documented correctly and 1557 (95.9%) post‐intervention (CI ?1.6 to 0.8%). There were five clinically significant documentation discrepancies pre‐intervention (0.2%), and 33 (2.0%) afterwards (CI 1.1 to 2.5%). Timeliness of administration improved post‐intervention (P < 0.001; Chi‐square test), as did administration of medication from unlocked areas (CI 4.7 to 7.3%) and supervision of patients taking oral medication (CI 17 to 23%). Conclusion Reductions in MAEs, excluding omissions due to unavailability, occurred for both ward‐stock and non‐ward‐stock drugs. The system also improved timeliness and security of drug administration. However, there was an increase in potentially significant documentation discrepancies.