Medication prescribing errors in a teaching hospital

A study of prescribing errors committed by physicians that occurred in a tertiary-care teaching hospital is reported. From a total of 289 411 medication orders written during the 1-year study period, 905 prescribing errors were detected and averted, of which 522 (57.7%) were rated as having potential for adverse consequences. The overall detected error rate was 3.13 errors for each 1000 orders written and a rate of 1.81 significant errors per 1000 orders. The error rate (4.01 per 1000 orders) was greatest between 12 pm and 3:59 pm. First-year postgraduate residents were found to have a higher error rate (4.25 per 1000 orders) than other prescriber classes, and obstetrics/gynecology services (3.54 per 1000 orders) and surgery/anesthesia services (3.42 per 1000 orders) had greater error rates than other services. The study results demonstrate the significant risk to patients from medication prescribing errors. Educational, operational, and risk-management activities should include efforts directed at reducing the risk to patients from prescribing errors.     

Medication Administration Discrepancies Persist Despite Electronic Ordering

Background

Up to 38% of inpatient medication errors occur at the administration stage. Although they reduce prescribing errors, computerized provider order entry (CPOE) systems do not prevent administration errors or timing discrepancies. This study determined the degree to which CPOE medication orders matched actual dose administration times.

Methods

At a 658-bed academic hospital with CPOE but lacking electronic medication administration charting, authors randomly selected adult patients with eligible medication orders from historical 1999–2003 CPOE log files. Retrospective manual chart audits compared expected (from CPOE) and actual timing of medication administrations. Outcomes included: dose omissions, median lag times between ordered and charted administrations, unauthorized doses, wrong dose errors, and the rate of nurses’ medication schedule shifting.

Results

Dose omissions occurred in 756 of 6019 (12.6%) audited administration opportunities; only 313 of the omissions (5.2% of opportunities) were unexplained. Wrong doses and unexpected doses occurred for 0.1% and 0.7% of opportunities, respectively. Median lag from expected first dose to actual charted administration time was 27 minutes (IQR 0-127). Nursing staff shifted from ordered to alternate administration schedules for 10.7% of regularly scheduled recurring medication orders. Chart review identified reasons for dose omissions, delays, and dose shifting.

Conclusion

Inpatient CPOE orders are legible and conveyed electronically to nurses and the pharmacy. Nonetheless, ward-based medication administrations do not consistently occur as ordered. Medication administration discrepancies are likely to persist even after implementing CPOE and bar-coded medication administration unless recommended interventions are made to address issues such as determining the true urgency of medication administration, avoiding overlapping duplicative medication orders, and developing a safe means for shifting dosing schedules.     

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

ObjectiveTo 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 MethodsWe 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.ResultsThere 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 ConclusionDespite 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.     

Medication Administration Errors in Nursing Homes Using an Automated Medication Dispensing System

Objective

To identify the frequency of medication administration errors as well as their potential risk factors in nursing homes using a distribution robot.

Design

The study was a prospective, observational study conducted within three nursing homes in the Netherlands caring for 180 individuals.

Measurements

Medication errors were measured using the disguised observation technique. Types of medication errors were described. The correlation between several potential risk factors and the occurrence of medication errors was studied to identify potential causes for the errors.

Results

In total 2,025 medication administrations to 127 clients were observed. In these administrations 428 errors were observed (21.2%). The most frequently occurring types of errors were use of wrong administration techniques (especially incorrect crushing of medication and not supervising the intake of medication) and wrong time errors (administering the medication at least 1 h early or late).The potential risk factors female gender (odds ratio (OR) 1.39; 95% confidence interval (CI) 1.05-1.83), ATC medication class antibiotics (OR 11.11; 95% CI 2.66-46.50), medication crushed (OR 7.83; 95% CI 5.40-11.36), number of dosages/day/client (OR 1.03; 95% CI 1.01-1.05), nursing home 2 (OR 3.97; 95% CI 2.86-5.50), medication not supplied by distribution robot (OR 2.92; 95% CI 2.04-4.18), time classes “7-10 am” (OR 2.28; 95% CI 1.50-3.47) and “10 am-2 pm” (OR 1.96; 1.18-3.27) and day of the week “Wednesday” (OR 1.46; 95% CI 1.03-2.07) are associated with a higher risk of administration errors.

Conclusions

Medication administration in nursing homes is prone to many errors. This study indicates that the handling of the medication after removing it from the robot packaging may contribute to this high error frequency, which may be reduced by training of nurse attendants, by automated clinical decision support and by measures to reduce workload.     

Risk factors associated with medication ordering errors

ObjectiveWe utilized a computerized order entry system–integrated function referred to as “void” to identify erroneous orders (ie, a “void” order). Using voided orders, we aimed to (1) identify the nature and characteristics of medication ordering errors, (2) investigate the risk factors associated with medication ordering errors, and (3) explore potential strategies to mitigate these risk factors.Materials and MethodsWe collected data on voided orders using clinician interviews and surveys within 24 hours of the voided order and using chart reviews. Interviews were informed by the human factors–based SEIPS (Systems Engineering Initiative for Patient Safety) model to characterize the work systems–based risk factors contributing to ordering errors; chart reviews were used to establish whether a voided order was a true medication ordering error and ascertain its impact on patient safety.ResultsDuring the 16-month study period (August 25, 2017, to December 31, 2018), 1074 medication orders were voided; 842 voided orders were true medication errors (positive predictive value = 78.3 ± 1.2%). A total of 22% (n = 190) of the medication ordering errors reached the patient, with at least a single administration, without causing patient harm. Interviews were conducted on 355 voided orders (33% response). Errors were not uniquely associated with a single risk factor, but the causal contributors of medication ordering errors were multifactorial, arising from a combination of technological-, cognitive-, environmental-, social-, and organizational-level factors.ConclusionsThe void function offers a practical, standardized method to create a rich database of medication ordering errors. We highlight implications for utilizing the void function for future research, practice and learning opportunities.     

The Utility of Adding Retrospective Medication Profiling to Computerized Provider Order Entry in an Ambulatory Care Population

Background

We assessed whether medication safety improved when a medication profiling program was added to a computerized provider order entry system.

Design

Between June 2001 and January 2002 we profiled outpatients with potential prescribing errors using computerized retrospective drug utilization software. We focused primarily on drug interactions. Patients were randomly assigned either to Provider Feedback or to Usual Care. Subsequent adverse drug event (ADE) incidence and other outcomes, including ADE preventability and severity, occurring up to 1 year following the last profiling date were evaluated retrospectively by a pharmacist blinded to patient assignment.

Measurements

Data were abstracted using a study-designed instrument. An ADE was defined by an Adverse Drug Reaction Probability scale score of 1 or more. Statistical analyses included negative binomial regression for comparing ADE incidence.

Results

Of 913 patients in the analytic sample, 371 patients (41%) had one or more ADEs. Incidence, by individual, was not significantly different between Usual Care and Provider Feedback groups (37% vs. 45%; p = 0.06; Coefficient, 0.19; 95% CI: −0.008, 0.390). ADE severity was also similar. For example, 51% of ADEs in the Usual Care and 58% in the Provider Feedback groups involved symptoms that were not serious (95% CI for the difference, −15%, 2%). Finally, ADE preventability did not differ. For example, 16% in the Usual Care group and 17% in the Provider Feedback group had an associated warning (95% CI for the difference, −7 to 5%; p = 0.79).

Conclusion

Medications safety did not improve with the addition of a medication profiling program to an electronic prescribing system.     

Computerized Clinical Decision Support During Medication Ordering for Long-term Care Residents with Renal Insufficiency

Objective

To determine whether a computerized clinical decision support system providing patient-specific recommendations in real-time improves the quality of prescribing for long-term care residents with renal insufficiency.

Design

Randomized trial within the long-stay units of a large long-term care facility. Randomization was within blocks by unit type. Alerts related to medication prescribing for residents with renal insufficiency were displayed to prescribers in the intervention units and hidden but tracked in control units.

Measurement

The proportions of final drug orders that were appropriate were compared between intervention and control units within alert categories: (1) recommended medication doses; (2) recommended administration frequencies; (3) recommendations to avoid the drug; (4) warnings of missing information.

Results

The rates of alerts were nearly equal in the intervention and control units: 2.5 per 1,000 resident days in the intervention units and 2.4 in the control units. The proportions of dose alerts for which the final drug orders were appropriate were similar between the intervention and control units (relative risk 0.95, 95% confidence interval 0.83, 1.1) for the remaining alert categories significantly higher proportions of final drug orders were appropriate in the intervention units: relative risk 2.4 for maximum frequency (1.4, 4.4); 2.6 for drugs that should be avoided (1.4, 5.0); and 1.8 for alerts to acquire missing information (1.1, 3.4). Overall, final drug orders were appropriate significantly more often in the intervention units—relative risk 1.2 (1.0, 1.4).

Conclusions

Clinical decision support for physicians prescribing medications for long-term care residents with renal insufficiency can improve the quality of prescribing decisions.Trial Registration: http://clinicaltrials.gov Identifier: NCT00599209     

The Influence that Electronic Prescribing Has on Medication Errors and Preventable Adverse Drug Events: an Interrupted Time-series Study

Objective

This study evaluated the effect of a Computerized Physician Order Entry system with basic Clinical Decision Support (CPOE/CDSS) on the incidence of medication errors (MEs) and preventable adverse drug events (pADEs).

Design

Interrupted time-series design.

Measurements

The primary outcome measurements comprised the percentage of medication orders with one or more MEs and the percentage of patients with one or more pADEs.

Results

Pre-implementation, the mean percentage of medication orders containing at least one ME was 55%, whereas this became 17% post-implementation. The introduction of CPOE/CDSS has led to a significant immediate absolute reduction of 40.3% (95% CI: −45.13%; −35.48%) in medication orders with one or more errors.Pre-implementation, the mean percentage of admitted patients experiencing at least one pADE was 15.5%, as opposed to 7.3% post-implementation. However, this decrease could not be attributed to the introduction of CPOE/CDSS: taking into consideration the interrupted time-series design, the immediate change was not significant (−0.42%, 95% CI: −15.52%; 14.68%) because of the observed underlying negative trend during the pre-CPOE period of −4.04% [95% CI: −7.70%; −0.38%] per month.

Conclusions

This study has shown that CPOE/CDSS reduces the incidence of medication errors. However, a direct effect on actual patient harm (pADEs) was not demonstrated.     

A Systematic Review of the Performance Characteristics of Clinical Event Monitor Signals Used to Detect Adverse Drug Events in the Hospital Setting

Objective

We conducted a systematic review of pharmacy and laboratory signals used by clinical event monitor systems to detect adverse drug events (ADEs) in adult hospitals.

Design and Measurements

We searched the MEDLINE, CINHAL, and EMBASE databases for the years 1985–2006, and found 12 studies describing 36 unique ADE signals (10 medication levels, 19 laboratory values, and 7 antidotes). We were able to calculate positive predictive values (PPVs) and 95% confidence intervals (CIs) for 15 signals.

Results

We found that PPVs ranged from 0.03 (95% CI, 0.03–0.03) for hypokalemia, to 0.50 (95% CI, 0.39–0.61) for supratherapeutic quinidine level. In general, antidotes (range = 0.09–0.11) had the lowest PPVs, followed by laboratory values (range = 0.03–0.27) and medication levels (range = 0.03–0.50).

Conclusion

Data from this study should help clinical information system and computerized decision support producers develop or improve existing clinical event monitor systems to detect ADEs in their own hospitals by prioritizing those signals with the highest PPVs.     

Research and applications: The safety of electronic prescribing: manifestations,mechanisms, and rates of system-related errors associated with two commercial systems in hospitals

Objectives

To compare the manifestations, mechanisms, and rates of system-related errors associated with two electronic prescribing systems (e-PS). To determine if the rate of system-related prescribing errors is greater than the rate of errors prevented.

Methods

Audit of 629 inpatient admissions at two hospitals in Sydney, Australia using the CSC MedChart and Cerner Millennium e-PS. System related errors were classified by manifestation (eg, wrong dose), mechanism, and severity. A mechanism typology comprised errors made: selecting items from drop-down menus; constructing orders; editing orders; or failing to complete new e-PS tasks. Proportions and rates of errors by manifestation, mechanism, and e-PS were calculated.

Results

42.4% (n=493) of 1164 prescribing errors were system-related (78/100 admissions). This result did not differ by e-PS (MedChart 42.6% (95% CI 39.1 to 46.1); Cerner 41.9% (37.1 to 46.8)). For 13.4% (n=66) of system-related errors there was evidence that the error was detected prior to study audit. 27.4% (n=135) of system-related errors manifested as timing errors and 22.5% (n=111) wrong drug strength errors. Selection errors accounted for 43.4% (34.2/100 admissions), editing errors 21.1% (16.5/100 admissions), and failure to complete new e-PS tasks 32.0% (32.0/100 admissions). MedChart generated more selection errors (OR=4.17; p=0.00002) but fewer new task failures (OR=0.37; p=0.003) relative to the Cerner e-PS. The two systems prevented significantly more errors than they generated (220/100 admissions (95% CI 180 to 261) vs 78 (95% CI 66 to 91)).

Conclusions

System-related errors are frequent, yet few are detected. e-PS require new tasks of prescribers, creating additional cognitive load and error opportunities. Dual classification, by manifestation and mechanism, allowed identification of design features which increase risk and potential solutions. e-PS designs with fewer drop-down menu selections may reduce error risk.     

Pharmacist participation on physician rounds and adverse drug events in the intensive care unit.

CONTEXT: Pharmacist review of medication orders in the intensive care unit (ICU) has been shown to prevent errors, and pharmacist consultation has reduced drug costs. However, whether pharmacist participation in the ICU at the time of drug prescribing reduces adverse events has not been studied. OBJECTIVE: To measure the effect of pharmacist participation on medical rounds in the ICU on the rate of preventable adverse drug events (ADEs) caused by ordering errors. DESIGN: Before-after comparison between phase 1 (baseline) and phase 2 (after intervention implemented) and phase 2 comparison with a control unit that did not receive the intervention. SETTING: A medical ICU (study unit) and a coronary care unit (control unit) in a large urban teaching hospital. PATIENTS: Seventy-five patients randomly selected from each of 3 groups: all admissions to the study unit from February 1, 1993, through July 31, 1993 (baseline) and all admissions to the study unit (postintervention) and control unit from October 1, 1994, through July 7, 1995. In addition, 50 patients were selected at random from the control unit during the baseline period. INTERVENTION: A senior pharmacist made rounds with the ICU team and remained in the ICU for consultation in the morning, and was available on call throughout the day. MAIN OUTCOME MEASURES: Preventable ADEs due to ordering (prescribing) errors and the number, type, and acceptance of interventions made by the pharmacist. Preventable ADEs were identified by review of medical records of the randomly selected patients during both preintervention and postintervention phases. Pharmacists recorded all recommendations, which were then analyzed by type and acceptance. RESULTS: The rate of preventable ordering ADEs decreased by 66% from 10.4 per 1000 patient-days (95% confidence interval [CI], 7-14) before the intervention to 3.5 (95% CI, 1-5; P<.001) after the intervention. In the control unit, the rate was essentially unchanged during the same time periods: 10.9 (95% CI, 6-16) and 12.4 (95% CI, 8-17) per 1000 patient-days. The pharmacist made 366 recommendations related to drug ordering, of which 362 (99%) were accepted by physicians. CONCLUSIONS: The presence of a pharmacist on rounds as a full member of the patient care team in a medical ICU was associated with a substantially lower rate of ADEs caused by prescribing errors. Nearly all the changes were readily accepted by physicians.     

Does Computerized Provider Order Entry Reduce Prescribing Errors for Hospital Inpatients? A Systematic Review

Previous reviews have examined evidence of the impact of CPOE on medication errors, but have used highly variable definitions of “error”. We attempted to answer a very focused question, namely, what evidence exists that CPOE systems reduce prescribing errors among hospital inpatients? We identified 13 papers (reporting 12 studies) published between 1998 and 2007. Nine demonstrated a significant reduction in prescribing error rates for all or some drug types. Few studies examined changes in error severity, but minor errors were most often reported as decreasing. Several studies reported increases in the rate of duplicate orders and failures to discontinue drugs, often attributed to inappropriate selection from a dropdown menu or to an inability to view all active medication orders concurrently. The evidence-base reporting the effectiveness of CPOE to reduce prescribing errors is not compelling and is limited by modest study sample sizes and designs. Future studies should include larger samples including multiple sites, controlled study designs, and standardized error and severity reporting. The role of decision support in minimizing severe prescribing error rates also requires investigation.     

The Effect of Electronic Prescribing on Medication Errors and Adverse Drug Events: A Systematic Review

The objective of this systematic review is to analyse the relative risk reduction on medication error and adverse drug events (ADE) by computerized physician order entry systems (CPOE). We included controlled field studies and pretest-posttest studies, evaluating all types of CPOE systems, drugs and clinical settings. We present the results in evidence tables, calculate the risk ratio with 95% confidence interval and perform subgroup analyses for categorical factors, such as the level of care, patient group, type of drug, type of system, functionality of the system, comparison group type, study design, and the method for detecting errors. Of the 25 studies that analysed the effects on the medication error rate, 23 showed a significant relative risk reduction of 13% to 99%. Six of the nine studies that analysed the effects on potential ADEs showed a significant relative risk reduction of 35% to 98%. Four of the seven studies that analysed the effect on ADEs showed a significant relative risk reduction of 30% to 84%. Reporting quality and study quality was often insufficient to exclude major sources of bias. Studies on home-grown systems, studies comparing electronic prescribing to handwriting prescribing, and studies using manual chart review to detect errors seem to show a higher relative risk reduction than other studies. Concluding, it seems that electronic prescribing can reduce the risk for medication errors and ADE. However, studies differ substantially in their setting, design, quality, and results. To further improve the evidence-base of health informatics, more randomized controlled trials (RCTs) are needed, especially to cover a wider range of clinical and geographic settings. In addition, reporting quality of health informatics evaluation studies has to be substantially improved.     

Medication errors—an enduring problem for children and elderly patients

Objective

To analyze the types and reasons of medication errors, committed by health care professionals, which led to toxicological consultations at the Czech Toxicological Information Centre (TIC).

Methods

Inquiries arising from medication errors for 2000–2010 were extracted and evaluated from the database of the TIC, recording the consultations of poisonings due to drugs, household products, plants, and mushrooms.

Results

From a total of 44,344 calls concerning pharmaceuticals, 215 (0.5%) were denoted by the caller as medication errors; 130 involved children (90 below 5 years of age) and 85 involved adults (30–60 years of age). The most common errors were: improper dosage (60.9%), wrong medication (19.3%), or erroneous route of administration (12.9%). The most frequent medication errors appeared using drugs affecting the nervous system (psycholeptics and antiepileptics), antibiotics, and drugs affecting the respiratory system. Nurses administering the drugs were responsible for 43.0%, physicians prescribing the drugs for 36.8%, and pharmacists dispensing the drugs for 20.2% of the errors. Of 25 patients with severe drug intoxications, 60.0% were children under 5 years of age treated with pharmaceuticals affecting the CNS, and 28.0% patients over 60 years of age with chronic application of theophylline, digoxin, or lithium.

Conclusions

The trend in medication errors has remained relatively stable over the past 11 years. The analysis of medication errors shows two high-risk categories: children of less than 5 years of age, in whom the dose was not correctly adjusted, and elderly people with chronic medication and insufficient control of their medication level. Therefore, the measures for risk reduction should focus primarily on them.     

Cost-effectiveness analysis of a hospital electronic medication management system

Objective To conduct a cost–effectiveness analysis of a hospital electronic medication management system (eMMS).Methods We compared costs and benefits of paper-based prescribing with a commercial eMMS (CSC MedChart) on one cardiology ward in a major 326-bed teaching hospital, assuming a 15-year time horizon and a health system perspective. The eMMS implementation and operating costs were obtained from the study site. We used data on eMMS effectiveness in reducing potential adverse drug events (ADEs), and potential ADEs intercepted, based on review of 1 202 patient charts before (n = 801) and after (n = 401) eMMS. These were combined with published estimates of actual ADEs and their costs.Results The rate of potential ADEs following eMMS fell from 0.17 per admission to 0.05; a reduction of 71%. The annualized eMMS implementation, maintenance, and operating costs for the cardiology ward were A$61 741 (US$55 296). The estimated reduction in ADEs post eMMS was approximately 80 actual ADEs per year. The reduced costs associated with these ADEs were more than sufficient to offset the costs of the eMMS. Estimated savings resulting from eMMS implementation were A$63–66 (US$56–59) per admission (A$97 740–$102 000 per annum for this ward). Sensitivity analyses demonstrated results were robust when both eMMS effectiveness and costs of actual ADEs were varied substantially.Conclusion The eMMS within this setting was more effective and less expensive than paper-based prescribing. Comparison with the few previous full economic evaluations available suggests a marked improvement in the cost–effectiveness of eMMS, largely driven by increased effectiveness of contemporary eMMs in reducing medication errors.     

Errors and electronic prescribing: a controlled laboratory study to examine task complexity and interruption effects

Objective

To examine the effect of interruptions and task complexity on error rates when prescribing with computerized provider order entry (CPOE) systems, and to categorize the types of prescribing errors.

Design

Two within-subject factors: task complexity (complex vs simple) and interruption (interruption vs no interruption). Thirty-two hospital doctors used a CPOE system in a computer laboratory to complete four prescribing tasks, half of which were interrupted using a counterbalanced design.

Measurements

Types of prescribing errors, error rate, resumption lag, and task completion time.

Results

Errors in creating and updating electronic medication charts that were measured included failure to enter allergy information; selection of incorrect medication, dose, route, formulation, or frequency of administration from lists and drop-down menus presented by the CPOE system; incorrect entry or omission in entering administration times, start date, and free-text qualifiers; and omissions in prescribing and ceasing medications. When errors occurred, the error rates across the four prescribing tasks ranged from 0.5% (1 incorrect medication selected out of 192 chances for selecting a medication or error opportunities) to 16% (5 failures to enter allergy information out of 32 error opportunities). Any impact of interruptions on prescribing error rates and task completion times was not detected in our experiment. However, complex tasks took significantly longer to complete (F(1, 27)=137.9; p<0.001) and when execution was interrupted they required almost three times longer to resume compared to simple tasks (resumption lag complex=9.6 seconds, SD=5.6; resumption lag simple=3.4 seconds, SD=1.7; t(28)=6.186; p<0.001).

Conclusion

Most electronic prescribing errors found in this study could be described as slips in using the CPOE system to create and update electronic medication charts. Cues available within the user interface may have aided resumption of interrupted tasks making CPOE systems robust to some interruption effects. Further experiments are required to rule out any effect interruption might have on CPOE error rates.