Analysis of National Drug Code Identifiers in Ambulatory E-Prescribing

Assessing automated product selection success rates in transmissions between electronic prescribing and community pharmacy platforms

OBJECTIVE

Wrong drug product errors occurring in community pharmacies often originate at the transcription stage. Electronic prescribing and automated product selection are strategies to reduce product selection errors. However, it is unclear how often automated product selection succeeds in outpatient pharmacy platforms.

MATERIALS AND METHODS

The intake of over 800 e-prescriptions was observed at baseline and after intervention to assess the rate of automated product selection success. A dispensing accuracy audit was performed at baseline and postintervention to determine whether enhanced automated product selection would result in greater accuracy; data for both analyses were compared by 2x2 Chi square tests. In addition, an anonymous survey was sent to a convenience sample of 60 area community pharmacy managers.

RESULTS

At baseline, 79.8% of 888 e-prescriptions achieved automated product selection. After the intervention period, 84.5% of 903 e-prescriptions achieved automated product selection (P = .008). Analysis of dispensing accuracy audits detected a slight but not statistically significant improvement in accuracy rate (99.3% versus 98.9%, P = .359). Fourteen surveys were returned, revealing that other community pharmacies experience similar automated product selection failure rates.

DISCUSSION

Our results suggest that manual product selection by pharmacy personnel is required for a higher than anticipated proportion of e-prescriptions received and filled by community pharmacies, which may pose risks to both medication safety and efficiency.

CONCLUSION

The question of how to increase automated product selection rates and enhance interoperability between prescriber and community pharmacy platforms warrants further investigation.

Twice-daily versus once-daily lisinopril and losartan for hypertension: Real-world effectiveness and safety

BACKGROUND

Lisinopril and losartan manufacturer labels recommend twice-daily dosing (BID) if once-daily (QDay) is insufficient to lower blood pressure (BP).

METHODS AND RESULTS

Retrospective cohort study of patients taking QDay lisinopril and losartan who experienced a dose-doubling (index date). A text-processing tool categorized BID and QDay groups at the index date based on administration instructions. We excluded: pregnant/hospice, regimens other than BID/QDay, and without BP measurements -6 months/+12 months of the index date. The most proximal BP measurements -6 months and +2 weeks to 12 months of the index date were used to evaluate BP differences. Propensity scores were generated, and differences in BP and adverse events (angioedema, acute kidney injury, hyperkalemia) between BID/QDay groups were analyzed within dosing cohorts using inverse propensity of treatment-weighted regression models. Of 11,210 and 6,051 patients who met all criteria for lisinopril and losartan, 784 (7.0%) and 453 (7.5%) were taking BID, respectively. BID patients were older and had higher comorbidity and medication burdens. There were no differences in systolic/diastolic BP between BID and QDay, with absolute differences in mean systolic BP ranging from -1.8 to 0.7 mmHg and diastolic BP ranging from -1.1 to 0.1 mmHg (all 95% confidence intervals [CI] cross 0). Lisinopril 10mg BID was associated with an increased odds of angioedema compared to lisinopril 20mg QDay (odds ratio 2.27, 95%CI 1.13-4.58).

CONCLUSIONS

Adjusted models do not support improved effectiveness or safety of BID lisinopril and losartan.

Sound-Alike Look-Alike Confusion and Matching Medication Product Attributes: Simulated Case-Control Studies

Background: Sound-alike look-alike (SALA) medication confusions harm as many as 250 000 Americans annually. Most preventive strategies focus on medication name similarities. Objectives: To evaluate the association between matching medication product attributes and SALA confusion. Methods: We simulated 20 000 case-control studies using the Institute for Safe Medication Practices' List of Confused Drug Names as case pairs and 4 randomly selected control pairs per case pair from the First DataBank MedKnowledge (FDBM) database. We extracted 7 product attributes for each medication from the FDBM database. We used logistic regression models to estimate the associations between matching product attributes and SALA confusion. The models included a series of univariate (unadjusted) models, a model that adjusted for all product attributes, and a model that further adjusted for medication name similarity measures. Results: Medications with a matching product attribute had increased odds of SALA confusion in the univariate analyses (odds ratio [OR] = 4.2 to 55.5). When we simultaneously adjusted for all attributes, the associations of matching package unit, package unit size, formulation, strength, therapeutic class, and manufacturer with SALA confusion were attenuated but remained elevated (OR = 1.5 to 26.5), whereas the direction of association between matching route and SALA confusion reversed (OR = 0.8). These associations persisted on adjustment for medication name similarity measures. Conclusions and Relevance: This study is the first to evaluate the association between matching medication product attributes and SALA confusion with a control group. Having matching product attributes increased the odds of SALA confusion. SALA risk reduction strategies should consider product attributes.