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PS-028 Consolidation of drug data sheets to decrease electronic prescription errors
  1. L Damery,
  2. M Bourdoncle,
  3. R Stehle,
  4. B Juillard-Condat,
  5. J Tourel
  1. Toulouse Teaching Hospital, Pharmacy, Toulouse, France


Background The development of electronic prescriptions secures patient medication care in hospital. However, software can also lead to medication errors, for example when the drug data sheet is misconfigured.1

Purpose To correct configuration errors related to prescription and distribution parameters in prescription software, in order to obtain a more accurate drug database, improve drug information and decrease the number of prescription errors.

Material and methods 3 pharmacists and 2 pharmacy residents developed a monthly checklist to consolidate the key data regarding drugs which were available in our hospital. Between June and October 2016, all of the data sheets corresponding to these drugs were extracted monthly and then analysed. Configuration errors were identified, quantified and corrected in prescription software (Orbisv8.4, AGFA).

Results During the initial set up, 25 checkboxes and 15 path fields were available on 7 tabs. Using data mining, the main parameters of prescription (5 path fields) and distribution (5 path fields) were first studied. On average, 2073 data sheets per month were extracted. Regarding prescription parameters, 1641 of 2125 data sheets (77.2%) included at least 1 error in June. This rate decreased to 13.4% in October (270/2021). The rates of data sheets with at least 1 errors were, respectively, in June and October: 72.3% (1536/2125) and 9.6% (194/2021) for the pharmacotherapeutic groups, 8.4% (179/2125) and 3.4% (69/2021) for the pharmaceutical forms, 4.8% (102/2125) and 0.89% (18/2021) for administration routes, and 3.8% (80/2125) and 0.15% (3/2021) for prescription units. In June and October, 84.1% (1787/2125) and 2.28% (46/2021) of data sheets, respectively, included at least 1 error of distribution: respectively, 74.4% (1581/2125) and 0.30% (6/2021) for the minimum unit of distribution, 18.7% (397/2125) and 0.0% for the global order mode, 4.1% (87/2125) and 2.1% (42/2021) for the packaging, 3.8% (80/2125) and 0.15% (3/2021) for the distribution unit, and 2.4%(50/2125) and 0.0% for the restocking.

Conclusion Updating data have led to a more accurate drug database for prescription software. Enlargement of the method to other criteria (drug status, colour of the wording according to the class, etc) will improve drug information. This work should also decrease the number of medication errors in our hospital.

References and/or acknowledgements 1. Charpiat B, et al. Opportunities for medication errors and pharmacist’s interventions in the context of computerised prescription order entry. Ann Pharm Fr2012.

No conflict of interest

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