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4CPS-369 PharmaCheck as a screening tool to intercept high risk situations in internal medicine that could lead to adverse drug events
  1. C Skalafouris1,
  2. JL Reny2,
  3. J Stirnemann2,
  4. O Grosgurin2,
  5. F Eggimann3,
  6. D Grauser3,
  7. M Jermini1,
  8. C Bruggmann1,
  9. P Bonnabry1,
  10. B Guignard1
  1. 1Geneva University Hospital, Pharmacy Department, Geneva, Switzerland
  2. 2Geneva University Hospital, General Internal Medicine Division, Geneva, Switzerland
  3. 3Geneva University Hospital, Information Systems Department, Geneva, Switzerland


Background and importance In the internal medicine department of our hospital, medication review provided by pharmacists during medical rounds is offered to only a fraction of the 200 inpatients, due to limited resources. In order to detect high risk situations potentially leading to adverse drug events, we developed PharmaCheck, an electronic tool that screens all patient electronic health records (EHR) in real time, by aggregating drug prescriptions, laboratory values, vital signs and medical problems.

Aim and objectives To determine the impact of PharmaCheck in the identification of high risk situations and on the clinical pharmacist’s interventions.

Material and methods PharmaCheck was set to screen 20 situations distributed into four risk classes: a drug prescription with an abnormal laboratory value, a contraindication, a drug–drug interaction (DDI) and an inadequate administration mode. For 150 days (February to August 2020), PharmaCheck performed a daily screen of patients’ EHR, admitted to the internal medicine department. As soon as an alert was triggered, the clinical pharmacist analysed the patient’s clinical context to suggest a treatment adjustment when needed. An observational prospective study was performed to assess the distribution of each risk class, the predictive positive value of each alert (PPV: proportion of situations associated with an intervention) as well as the acceptance rate by the prescribers.

Results 430 alerts were triggered for 387 patients (3.3±1.9 alerts/day) with a global PPVof 19.3% (n=83/430). Regarding risk classes, PPVs were 25.6% (n=58/226) for abnormal laboratory value, 3.10% (4/127) for contraindications, 28.2% (20/71) for DDIs and 16.7% (1/6) for inadequate administration mode. The approval rate of treatment adjustment suggestions was 71.1% (n=59/83); rejections were related to an acceptable risk–benefit balance (n=20) or an unknown cause (n=4).

Conclusion and relevance PharmaCheck identified a significant number of high risk situations. By contextualising these alerts the clinical pharmacist selected the most relevant ones to suggest treatment adjustment, mostly accepted by physicians. Beyond the clinical context, the relevance of alerts depends on the informative quality of the triggering elements, explaining a low PPV for some risk classes (eg, contraindication, depending on unstructured textual medical problems). PharmaCheck expands the coverage of the clinical pharmacist for selected situations and we plan to transpose this strategy to other, more fragile, patient populations (eg, geriatrics, paediatrics, oncology).

Conflict of interest No conflict of interest

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