Background

‘Look-alike, sound-alike’ (LASA) medicines may be confused by prescribers, pharmacists, nurses and patients, with serious consequences for patient safety. The current research aimed to develop and trial software to proactively identify LASA medicines by computing medicine name similarity scores.

Methods

Literature review identified open-source software from the United States Food and Drug Administration for screening of proposed medicine names. We adapted and refined this software to compute similarity scores (0.0000-1.0000) for all possible pairs of medicines registered in Australia. Two-fold exploratory analysis compared:

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Computed similarity scores vs manually-calculated similarity scores that had used a different algorithm and underpinned development of Australia’s 2011 Tall Man Lettering List (‘the 2011 List’)

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Computed risk category vs expert-consensus risk category that underpinned the 2011 List.

Results

Screening of the Australian medicines register identified 7,750 medicine pairs with at least moderate (arbitrarily ≥0.6600) name similarity, including many oncology, immunomodulating and neuromuscular-blocking medicines. Computed similarity scores and resulting risk categories demonstrated a modest correlation with the manually-calculated similarity scores (r = 0.324, p < 0.002, 95% CI 0.119-0.529). However, agreement between the resulting risk categories was not significant (Cohen’s kappa = -0.162, standard error = 0.063.

Conclusions

The software (LASA v2) has potential to identify pairs of confusable medicines. It is recommended to supplement incident reports in risk-management programs, and to facilitate pre-screening of medicine names prior to brand/trade name approval and inclusion of medicines in formularies.

中文翻译：

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开发和探索分析软件，以检测外观相似，声音相似的药物名称。

背景

开处方者，药剂师，护士和患者可能会混淆“相似，声音相似”（LASA）药物，这对患者安全造成了严重后果。当前的研究旨在开发和试用软件，以通过计算药物名称相似性分数来主动识别LASA药物。

方法

文献综述确定了来自美国食品药品监督管理局的开源软件，用于筛选建议的药物名称。我们对该软件进行了改进和完善，以计算在澳大利亚注册的所有可能的成对药物的相似性评分（0.0000-1.0000）。两次探索性分析比较：

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计算的相似性得分与手动计算的相似性得分（使用了不同的算法，并支持了澳大利亚2011年《高个子》字母列表（“ 2011年列表”）的开发）

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支持2011年名单的计算风险类别与专家共识风险类别。

结果

对澳大利亚药品注册进行的筛选确定了7,750对具有至少中度（任意≥0.6600）名称相似性的药品，包括许多肿瘤学，免疫调节药和神经肌肉阻滞药。计算的相似性评分和所得的风险类别显示出与手动计算的相似性评分适度相关（r = 0.324，p <0.002，95％CI 0.119-0.529）。但是，由此产生的风险类别之间的一致性并不显着（Cohen的kappa = -0.162，标准误= 0.063。

结论

该软件（LASA v2）具有识别成对易混淆药物的潜力。建议在风险管理计划中补充事件报告，并在批准品牌/商标名称并将药物纳入配方之前，方便对药物名称进行预筛选。