Optimized Computerized Order Entry can Reduce Errors in Electronic Prescriptions and Associated Pharmacy Calls to Clarify (CTC)

Post-implementation optimization of medication alerts in hospital computerized provider order entry systems: a scoping review

OBJECTIVES

A scoping review identified interventions for optimizing hospital medication alerts post-implementation, and characterized the methods used, the populations studied, and any effects of optimization.

MATERIALS AND METHODS

A structured search was undertaken in the MEDLINE and Embase databases, from inception to August 2023. Articles providing sufficient information to determine whether an intervention was conducted to optimize alerts were included in the analysis. Snowball analysis was conducted to identify additional studies.

RESULTS

Sixteen studies were identified. Most were based in the United States and used a wide range of clinical software. Many studies used inpatient cohorts and conducted more than one intervention during the trial period. Alert types studied included drug-drug interactions, drug dosage alerts, and drug allergy alerts. Six types of interventions were identified: alert inactivation, alert severity reclassification, information provision, use of contextual information, threshold adjustment, and encounter suppression. The majority of interventions decreased alert quantity and enhanced alert acceptance. Alert quantity decreased with alert inactivation by 1%-25.3%, and with alert severity reclassification by 1%-16.5% in 6 of 7 studies. Alert severity reclassification increased alert acceptance by 4.2%-50.2% and was associated with a 100% acceptance rate for high-severity alerts when implemented. Clinical errors reported in 4 studies were seen to remain stable or decrease.

DISCUSSION

Post-implementation medication optimization interventions have positive effects for clinicians when applied in a variety of settings. Less well reported are the impacts of these interventions on the clinical care of patients, and how endpoints such as alert quantity contribute to changes in clinician and pharmacist perceptions of alert fatigue.

CONCLUSION

Well conducted alert optimization can reduce alert fatigue by reducing overall alert quantity, improving clinical acceptance, and enhancing clinical utility.

Benefits of electronic charts in intensive care and during a world health pandemic: advantages of the technology age

AIMS AND OBJECTIVES

This study sets out to describe benefits from the implementation of electronic observation charting in intensive care units (ICU). This was an extension to the existing hospital wide digital health system. We evaluated error reduction, time-savings and the costs associated with conversion from paper to digital records. The world health emergency of COVID-19 placed extraordinary strain on ICU and staff opinion was evaluated to test how well the electronic system performed.

METHODS

A clinically led project group working directly with programmers developed an electronic patient record for intensive care. Data error rates, time to add data and to make calculations were studied before and after the introduction of electronic charts. User feedback was sought pre and post go-live (during the COVID-19 pandemic) and financial implications were calculated by the hospital finance teams.

RESULTS

Error rates equating to 219 000/year were avoided by conversion to electronic charts. Time saved was the equivalent of a nursing shift each day. Recurrent cost savings per year were estimated to be £257k. Staff were overwhelmingly positive about electronic charts in ICU, even during a health pandemic and despite redeployment into intensive care where they were using the electronic charts for the first time.

DISCUSSION

Electronic ICU charts have been successfully introduced into our institution with benefits in terms of patient safety through error reduction and improved care through release of nursing time. Costs have been reduced. Staff feel supported by the digital system and report it to be helpful even during redeployment and in the unfamiliar environment of intensive care.

Comparing the variability of ingredient, strength, and dose form information from electronic prescriptions with RxNorm drug product descriptions

OBJECTIVE

To determine the variability of ingredient, strength, and dose form information from drug product descriptions in real-world electronic prescription (e-prescription) data.

MATERIALS AND METHODS

A sample of 10 399 324 e-prescriptions from 2019 to 2021 were obtained. Drug product descriptions were analyzed with a named entity extraction model and National Drug Codes (NDCs) were used to get RxNorm Concept Unique Identifiers (RxCUI) via RxNorm. The number of drug product description variants for each RxCUI was determined. Variants identified were compared to RxNorm to determine the extent of matching terminology used.

RESULTS

A total of 353 002 unique pairs of drug product descriptions and NDCs were analyzed. The median (1st-3rd quartile) number of variants extracted for each standardized expression in RxNorm, was 3 (2-7) for ingredients, 4 (2-8) for strength, and 41 (11-122) for dosage forms. Of the pairs, 42.35% of ingredients (n = 328 032), 51.23% of strengths (n = 321 706), and 10.60% of dose forms (n = 326 653) used matching terminology, while 16.31%, 24.85%, and 13.05% contained nonmatching terminology, respectively.

DISCUSSION

A wide variety of drug product descriptions makes it difficult to determine whether 2 drug product descriptions describe the same drug product (eg, using abbreviations to describe an active ingredient or using different units to represent a concentration). This results in patient safety risks that lead to incorrect drug products being ordered, dispensed, and used by patients. Implementation and use of standardized terminology may reduce these risks.

CONCLUSION

Drug product descriptions on real-world e-prescriptions exhibit large variation resulting in unnecessary ambiguity and potential patient safety risks.

The use of narrative electronic prescribing instructions in pharmacoepidemiology: A scoping review for the International Society for Pharmacoepidemiology

Narrative electronic prescribing instructions (NEPIs) are text that convey information on the administration or co‐administration of a drug as directed by a prescriber. For researchers, NEPIs have the potential to advance our understanding of the risks and benefits of medications in populations; however, due to their unstructured nature, they are not often utilized. The goal of this scoping review was to evaluate how NEPIs are currently employed in research, identify opportunities and challenges for their broader application, and provide recommendations on their future use. The scoping review comprised a comprehensive literature review and a survey of key stakeholders. From the literature review, we identified 33 primary articles that described the use of NEPIs. The majority of articles (n = 19) identified issues with the quality of information in NEPIs compared with structured prescribing information; nine articles described the development of novel algorithms that performed well in extracting information from NEPIs, and five described the used of manual or simpler algorithms to extract prescribing information from NEPIs. A survey of 19 stakeholders indicated concerns for the quality of information in NEPIs and called for standardization of NEPIs to reduce data variability/errors. Nevertheless, stakeholders believed NEPIs present an opportunity to identify prescriber's intent for the prescription and to study temporal treatment patterns. In summary, NEPIs hold much promise for advancing the field of pharmacoepidemiology. Researchers should take advantage of addressing important questions that can be uniquely answered with NEPIs, but exercise caution when using this information and carefully consider the quality of the data.

Longitudinal impact of a pre-populated default quantity on emergency department opioid prescriptions

OBJECTIVE

Previously published studies indicate that a pre-populated default quantity may decrease opioid amounts on discharge prescriptions from the emergency department (ED). However, the longitudinal effect of defaulted quantities has not been described in the literature.

METHODS

A retrospective review of electronic health record data from visits to 4 hospital EDs in a community health system examined opioid prescription dispense quantities 3.5 years pre- and 6.5 years post-implementation of a defaulted dispense quantity of seventeen. The primary purpose was to determine the percentage of ED discharge opioid prescriptions containing the prepopulated default dispense quantity after implementation. The longitudinal effect of a default quantity implementation on the average quantity prescribed (normalized per 1000 visits) was examined by comparing the pre-implementation period (January 1, 2009-July 31, 2012) to the post-implementation period (August 1, 2012-June 30, 2018).

RESULTS

After implementation in 2012, the acceptance rate of the default dispense quantity increased each year, up to 48% in 2016 and maintained through 2018. A significant decrease in prescribed opioid quantities post-default quantity implementation was sustained, with the average quantity prescribed from 2015-2018 maintained at 17 or lower.

CONCLUSION

A pre-populated default quantity impacts discharge opioid prescribing as evidenced by a high sustained rate of prescriber utilization over years and reduction in the per prescription average pill quantity. The acceptance of a pre-populated default quantity may allow for selection of even a lower quantity to influence prescribing patterns of opioid analgesics.

Administration of gamma-hydroxybutyrate instead of beta-hydroxybutyrate to a liver transplant recipient suffering from propionic acidemia and cardiomyopathy: A case report on a medication prescribing error

Beta‐hydroxybutyrate (BHB) is a synthetic ketone body used as an adjuvant energy substrate in the treatment of patients with metabolic cardiomyopathy. A medication prescribing error led to the administration of the general anesthetic sodium gamma‐hydroxybutyrate (GHB) instead of sodium BHB in a liver transplant recipient with propionic acidemia and cardiomyopathy, causing acute coma. A 15‐year‐old boy suffering from neonatal propionic acidemia underwent liver transplantation (LT) for metabolic decompensation and cardiomyopathy (treated with cardiotropic drugs and BHB) diagnosed a year previously. The patient had been rapidly extubated after LT, and was recovering well. Eight days after LT, the patient suddenly became comatose. No metabolic, immunological, hypertensive, or infectious complications were apparent. The brain magnetic resonance imaging and electroencephalography results were normal. The coma was soon attributed to a medication prescribing error: administration of GHB instead of BHB on day 8 post‐LT. The patient recovered fully within a few hours of GHB withdrawal. The computerized prescription system had automatically suggested the referenced anesthetic GHB (administered intravenously) instead of the non‐referenced ketone body BHB, triggering coma in our patient. A computerized prescription system generated a medication prescribing error for a rare disease, in which the general anesthetic GHB was mistaken for the nonreferenced energy substrate BHB.

Dietitians can improve accuracy of prescribing by interacting with electronic prescribing systems

Background

Dietitians increasingly interact with electronic health records (EHRs) and use them to alert prescribers to medication inaccuracies.

Objective

To understand renal dietitians’ use of electronic prescribing systems and influence on medication accuracy in inpatients. In outpatients to determine whether renal dietitians’ use of the electronic medication recording might improve accuracy.

Methods

In inpatients we studied the impact of dietetic advice on medical prescribing before and after moving from paper recommendations to ePrescribing. In outpatients, when dietitians recommended changes in dialysis units, we assessed the time to patients receiving the new medications. We trained dietitians to use the ePrescribing system and assessed accuracy of medication lists at the start and end of the study period.

Results

Inpatients: before the use of EHRs, 25% of proposals were carried out and took an average of 20 days. This rose to 38% using an EHR and took an average of 4 days.

Outpatients: in dialysis units dietitians recommend initiating and stopping medications and advise on repeat medications. Most recommendations were during multidisciplinary team (MDT) meetings; the average time to receive medications was 10 days. Drug histories updated by dietitians increased after the start of the study and accuracy of medication lists improved from 2.4 discrepancies/patient to 0.4.

Conclusion

Dietitians can make medication suggestions directly using EHR, delivering more timely change to patient care and improving accuracy of patients’ medication lists. Allowing the whole of the MDT to contribute to the EHR improves data completeness and therefore patient care is likely to be enhanced.

By Default: The Effect of Prepopulated Prescription Quantities on Opioid Prescribing in the Emergency Department

Introduction

Opioid prescribing patterns have come under increasing scrutiny with the recent rise in opioid prescriptions, opioid misuse and abuse, and opioid-related adverse events. To date, there have been limited studies on the effect of default tablet quantities as part of emergency department (ED) electronic order entry. Our goal was to evaluate opioid prescribing patterns before and after the removal of a default quantity of 20 tablets from ED electronic order entry.

Methods

We performed a retrospective observational study at a single academic, urban ED with 58,000 annual visits. We identified all adult patients (18 years or older) seen in the ED and discharged home with prescriptions for tablet forms of hydrocodone and oxycodone (including mixed formulations with acetaminophen). We compared the quantity of tablets prescribed per opioid prescription 12 months before and 10 months after the electronic order-entry prescription default quantity of 20 tablets was removed and replaced with no default quantity. No specific messaging was given to providers, to avoid influencing prescribing patterns. We used two-sample Wilcoxon rank-sum test, two-sample test of proportions, and Pearson's chi-squared tests where appropriate for statistical analysis.

Results

A total of 4,104 adult patients received discharge prescriptions for opioids in the pre-intervention period (151.6 prescriptions per 1,000 discharged adult patients), and 2,464 post-intervention (106.69 prescriptions per 1,000 discharged adult patients). The median quantity of opioid tablets prescribed decreased from 20 (interquartile ration [IQR] 10-20) to 15 (IQR 10-20) (p<0.0001) after removal of the default quantity. While the most frequent quantity of tablets received in both groups was 20 tablets, the proportion of patients who received prescriptions on discharge that contained 20 tablets decreased from 0.5 (95% confidence interval [CI] [0.48-0.52]) to 0.23 (95% CI [0.21-0.24]) (p<0.001) after default quantity removal.

Conclusion

Although the median number of tablets differed significantly before and after the intervention, the clinical significance of this is unclear. An observed wider distribution of the quantity of tablets prescribed after removal of the default quantity of 20 may reflect more appropriate prescribing patterns (i.e., less severe indications receiving fewer tabs and more severe indications receiving more). A default value of 20 tablets for opioid prescriptions may be an example of the electronic medical record's ability to reduce practice variability in medication orders actually counteracting optimal patient care.