Causes of discrepancies between medications listed in the national electronic prescribing system and patients' actual use of medications.

Discrepancies between registered prescriptions and patients' actual use of medications are described as frequent and often resulting in adverse medication events. We aimed to assess the extent of and causes behind discrepancies between medications listed in the Danish national prescription system (Shared Medication Record) and patients' actual use of medications. We prospectively reconciled medication for 260 consecutively admitted polypharmacy patients (>50 years and ≥5 prescriptions) at two hospitals in the Capital Region of Denmark. The type of discrepancies were determined and the cause of the discrepancies were evaluated as primarily caused by (1) the patient (i.e., intentional or unintentional non-adherence) or (2) the health care system (i.e., lack of appropriate update of the SMR by physicians in primary or secondary care). There was a median of 12 [IQR 9-15] medications listed and 3 [IQR 1-5] medication discrepancies per patient (total n = 925). The majority (53%) of discrepancies were caused by the health care system, 32% were caused by the patients, of which 70% were intentional non-adherence, and 15% had an indeterminable cause. In conclusion, discrepancies between medications listed in the Shared Medication Record and actual use of medications were frequent and were most often caused by clinicians not updating the prescription information.

Important Aspects of Pharmacist-led Medication Reviews in an Acute Medical Ward.

In some hospitals, clinical pharmacists review the medication to find drug-related problems (DRPs) in acutely admitted patients. We aimed to identify the nature of identified DRPs and investigate factors of potential importance for the clinical implementation of pharmacist suggestions. In 100 randomly selected medication review (MR) notes, we retrospectively evaluated the clinical implementation and classified (1) timing and communication of the review; (2) DRPs and related suggestions for the physician; and (3) DRPs' potential clinical relevance to patients as 'beneficial', 'somewhat beneficial', 'no relevance' or 'other relevance'. Of 327 DRPs (0-13 DRPs per patient), 42% were implemented. The clinical implementation was higher if the MR note was made prior to (instead of after) the physician's admission, and even higher if the suggestions were communicated verbally (instead of only in writing) to the physicians (44% versus 79%, p < 0.05). The clinical relevance of the DRPs was either 'beneficial' (16%), 'somewhat beneficial' (43%), 'no relevance' (22%) or 'other relevance' (19%). The 'beneficial' DRPs had a higher clinical implementation (53%) than 'no relevance' (34%) (p < 0.05). The most frequently implemented suggestions were based on DRPs concerning 'indication for drug treatment not noticed', 'inappropriate drug form' and 'drug dose too low', with implementation rates of 83%, 67% and 63%, respectively. In our sample, the pharmacist's MR suggestions were only implemented by physicians in 42% of the cases, but review prior to physician contact and verbal communication of the suggestions, higher clinical relevance and specific types of DRPs were associated with a higher implementation rate.

Population pharmacokinetics of nalmefene in healthy subjects and its relation to µ-opioid receptor occupancy.

AIMS: The aims of this study were to develop a population pharmacokinetic (PK) model to describe the PK of nalmefene in healthy subjects and to relate the exposure of nalmefene to the µ-opioid receptor occupancy by simulations in the target population. METHODS: Data from nine phase I studies (243 subjects) with extensive blood sampling were pooled and used for the population PK model building. Data from four other phase I studies (85 subjects) were pooled and used as an external validation dataset. Eight subjects from an imaging study contributed occupancy data and the pharmacokinetic/pharmacodynamic (PK/PD) relationship was modelled. Combining the population PK model and the PK/PD relationship enabled simulations to predict µ-opioid occupancy. RESULTS: A two compartment model with first order absorption best described the nalmefene PK data. The typical subject in the population was estimated to have a systemic clearance of 60.4 l h(-1) and a central volume of distribution of 266 l. Absolute oral bioavailability was estimated to 41% without food intake and with food about 53%. Simulation of the µ-opioid receptor occupancy shows that the 95% confidence bound is within or above 60-90% occupancy for up to 22-24 h after a single dose of 20 mg nalmefene. CONCLUSIONS: A robust population PK model for nalmefene was developed. Based on the concentration-occupancy model the µ-opioid receptor occupancy after a single 20 mg dose of nalmefene is predicted to be above the target therapeutic occupancy for about 24 h in about 95% of the target population.