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PS-103 Optimisation of the drug prescription process in patient admission
  1. I Plessala1,
  2. I Jolivet1,
  3. S Quintel2,
  4. B Granger3
  1. 1Pitié-Salpétrière University Hospital, Pharmacy, Paris, France
  2. 2Pitié-Salpétrière University Hospital, Sensorineural Surgery Pole, Paris, France
  3. 3Pitié-Salpétrière University Hospital, Biostatistic-Public Health and Medical Information, Paris, France


Background As pharmacists, medical prescription plays a major part of our daily activity. However, management of personal treatment is left behind. Our action plan of the quality management system (QMS) focused on several themes, including medication reconciliation and continuity of treatments.

Purpose Our objectives were to assess the following: conformity with the personal treatment procedure at admission; conformity of the initial medical prescription; and medication errors (ME).

Material and methods Our work involved a 2 month prospective study in 28 care units of our hospital. Adult patients over 18 years of age were included if they were hospitalised for at least 24 hours in our hospital and agreed to answer our questions. We assessed 5 patients per unit each day, 28 units in total. ME were identified as a result of missing information on patients’ records (such as who their general practitioner was, the management of the patient’s other treatments). Improvement measures were suggested in order to reduce ME.

Results 127 patients were included (sex ratio M/F: 0.6). Mean age was 60.5 years. Retired (A1) people represented 56% of the population. Only 15% of patients had no traceability of a general practitioner (GP) compared with 86% for a pharmacist, and 59% had no copy of their prescription in their medical file. Nurses transcribed medication prescriptions in 36.4% of cases (66.1% among nursing files with the patient’s own treatment traceability), which was the source of errors. The patient’s own treatment was not returned in 69% of cases. Therefore, it was stored in the patient room. These poor practices and/or standards could lead to ME. We found that 38.4% of unintentional discrepancies among patients’ prescriptions were mainly as a result of omission (40.5%), posology (35.7%) and timing errors (31%).

Conclusion Previous studies on medication reconciliation have already shown we should focus on high risk drugs and patients to reduce ME. Improving communication between different health professionals can also help reduce ME. We cannot currently implement medication reconciliation among all units in need in our hospital, but we can focus on patients with a high risk of discrepancies, using the HAS tools.

References and/or acknowledgements Arrêté du 6 avril2011.

HAS. Manuel de certification V2010.

No conflict of interest

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