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Estimating the frequency of automated dispensing cabinet discrepancy safety events using Markov models

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Abstract

Background

Medication errors are one of the most common types of adverse events in inpatient settings, accounting for nearly 5% of adverse events experienced by hospitalized patients. In this exploratory study, we modeled and estimated the frequency of automated dispensing cabinet (ADC) discrepancy safety events across three different data sources: ADC transaction logs, user ADC discrepancy reports, and user reports to a patient safety event (PSE) reporting system.

Methods

We collected data from the three sources over a 1-month time period from 5 January to 2 February 2021 and used a Markov model to categorize ADC transactions.

Results

A total of 1,989,443 ADC transactions were recorded. Of these, 18,943 (0.95%) had a discrepancy difference; of these, 1163 (6.1%) had a user report. In total, 17 (0.09% of 18,943) ADC discrepancy PSEs had discrepancy user reports and appeared in the transaction logs. However, 1146 of 1163 (98.5%) discrepancy user reports did not have an associated PSE report. In addition, 1914 of 3077 of the identified discrepancy events (62.2%) did not have a discrepancy user report or a PSE report.

Conclusion

The study findings illustrate how PSE reports are only the tip of the iceberg, capturing less than 0.6% of possible ADC discrepancy events. This work can be leveraged to better understand both safety hazards and the effectiveness of interventions.

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Acknowledgements

The authors thank our clinical pharmacist collaborator (LL) for his time, help, and clinical insights for this project. This work was funded in part by the Agency for Healthcare Research and Quality (grant # R01 HS025136).

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Authors and Affiliations

  1. National Center for Human Factors in Healthcare, MedStar Health, Washington, USA

    Allan Fong, Sadaf Kazi, Raj M. Ratwani & Aaron Z. Hettinger

  2. Center for Biostatistics, Informatics and Data Science, MedStar Health, Washington, USA

    Allan Fong, Raj M. Ratwani & Aaron Z. Hettinger

  3. Department of Emergency Medicine, Georgetown University School of Medicine, Washington, USA

    Aaron Z. Hettinger

  4. MedStar Health, Columbia, USA

    Marybeth Kazanas

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  1. Allan Fong
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  2. Sadaf Kazi
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  4. Raj M. Ratwani
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  5. Aaron Z. Hettinger
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Corresponding author

Correspondence to Allan Fong.

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Funding

R01 HS025136 from the Agency for Healthcare Research and Quality to Raj Ratwani.

Conflicts of interest/Competing interests:

AF, SK, MK, RMR, and AZH have no conflicts of interest that are directly relevant to the content of this article.

Ethics approval

MHRI protocol # 2018-144

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Author contributions

AF made substantial contributions to the conception and design of the work and the acquisition, analysis, and interpretation of the data. SK made substantial contributions to the conception and design of the work and the analysis and interpretation of the data. MK, RMR, and AZH made substantial contributions to the conception and design of the work and interpretation of data. MK was involved in the revising and final approval of the work. AF, SK, RMR, and AZH were involved in the drafting, revising, and final approval of the work.

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Fong, A., Kazi, S., Kazanas, M. et al. Estimating the frequency of automated dispensing cabinet discrepancy safety events using Markov models. Drugs Ther Perspect 38, 146–155 (2022). https://doi.org/10.1007/s40267-022-00900-2

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  • DOI: https://doi.org/10.1007/s40267-022-00900-2

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