Background During the last decade, healthcare shifted from a disease-focused approach towards a more patient-focused approach. Hospital pharmacy services experienced a similar development. Traditional drug-oriented services expanded towards patient-oriented services by imbedding computerised clinical decision support systems (CDSSs) in the prescribing process and implementing bedside clinical pharmacy services. However, due to limited resources, clinical pharmacy services are not implemented on a hospital-wide basis in Belgian hospitals.
Purpose To guarantee patient safety, a central check of medication appropriateness (COMA) was developed and implemented since March 2016 in the University Hospitals Leuven.
Materials and Methods Based on a risk analysis, high-risk prescriptions are checked by a hospital pharmacist for appropriateness. A daily check (0.5 FTE) of automatically generated queries is performed using standardised algorithms. The queries are a result of the screening of all new prescriptions in the electronic prescribing system of the last 24 hours. Interventions are performed via electronic warnings in the patient’s file or phone calls to the treating physician.
Results Twelve hospital pharmacists are now involved in the COMA and 79 specific algorithms were developed, covering five pharmacotherapeutic areas of interest: drugs with restrictive indication; overruled interventions raised by CDSS; medication-related biochemical changes; sequential therapy for bio-equivalent drugs; and reimbursement of drugs.
During a 18 month period, 92 050 prescriptions were checked for which 24 943 (27%) electronic warnings were sent and 637 (1%) phone calls were carried out. When analysed without automatic warnings for sequential therapy, 39 481 prescriptions were checked for which 2568 (7%) electronic warnings were sent and 637 (2%) phone calls were carried out.
Conclusion For the future we obtain the next goals:
Evaluation of the acceptance of the current COMA process.
Fine–tuning the screening queries with an emphasis on improving specificity.
Determining inter–rater validity.
Development of new algorithms, also expanding to other areas of interest.
Development of an easy access training tool for hospital pharmacists to perform COMA.
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