he quantity of a medication supplied to a hospital ward should closely match the quantity administered to patients. 1 A discrepancy between the amounts supplied and used may reflect medication expiry, wastage, after-hours transfer to other wards, failure to document administration, or theft. 2 In emergency department (EDs), discrepancies have been reported for medications commonly used for self-treatment, and for oral alternatives to parenteral preparations. 1 Unlawful diversion of controlled medications is also a recognised problem. [3][4][5][6][7][8][9] Evaluating medication discrepancies was difficult when records were paper-based, as collating administrative data required a labour-intensive medical record audit. Electronic medication records, including medication supply and administration data, have facilitated the detection of medication discrepancies. 1 In this study, we analysed electronic medication supply and administration data for a variety of inpatient wards and EDs. Our aim was to describe the nature, extent, and cost of medication discrepancies. MethodsWe undertook a multicentre, retrospective observational study in the Austin, Box Hill, Footscray, and Frankston Hospitals in Melbourne, Victoria. The four hospitals are public metropolitan teaching centres with 560, 300, 425, and 401 beds respectively, and their EDs received 90 000, 43 200, 64 604, and 100 616 people in 2019 (according to hospital records).We assessed the quantities of selected medications supplied to two general medical wards, two surgical wards (one general, one orthopaedic) and the ED of each hospital, and the amounts administered to patients during the 2019 calendar year. Medication supply data were extracted from the pharmacy drug management system (MERLIN, PharmHos or iPharmacy, iSoft), and medication administration data from the electronic prescribing system (Millennium, Cerner). Data on doses that were lost, wasted, returned to the pharmacy, or destroyed were not available.For this study, an emergency physician and senior hospital pharmacists purposively sampled medications that are frequently prescribed (eg, for simple analgesia), useful for selftreatment (eg, anti-emetics), are associated with illegal diversion (eg, benzodiazepines), and oral and parenteral preparations of the same or similar medications (eg, oral and parenteral ondansetron). The selection was informed by the results of a pilot study, 1 and was not influenced by medication cost:• Antibiotics ► Phenoxymethylpenicillin (250 mg capsule), benzylpenicillin (1.2 g injection)► Cefalexin (500 mg capsule), ceftriaxone (1 g vial)

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Objective To determine the accuracy of discharge summary (DS) medication lists across a broad cross-section of hospital inpatients and to determine what factors may be associated with errors in this document. Methods A retrospective medical record audit was undertaken at five metropolitan hospitals that utilise an electronic medication management system (eMMS) at the point of discharge. Four hospitals utilised an eMMS for inpatient medication management, with the fifth utilising the paper-based National Inpatient Medication Chart (NIMC). Any inpatients discharged during the first week of February, May, August and November 2020 and February 2021 were included if they received both a DS and either a pharmacy-generated patient-friendly medication list or interim medication administration chart. Results Eight-hundred and one DSs were included, of which 525 (66%) had one or more medication errors and 220 (27%) had one or more high-risk medication errors. A higher proportion of patients with polypharmacy (five or more medications) had one or more errors compared to patients without polypharmacy (67% vs 54%, P < 0.01). DSs generated from the site with paper NIMCs were less likely to have one or more errors when compared to sites using an inpatient eMMS (58% vs 68%, P < 0.01). Age, sex, language spoken and preparing the DS post-discharge were not associated with differing rates of errors. Of the 2609 individual medication errors (390 high-risk errors), the most common types were ‘omitted drug or dose’ (34%) and ‘unnecessary drug’ (33%). Conclusion Medication errors in the DS are common and more likely to occur in patients with polypharmacy.

Clinical pharmacy services can be costly, and in resource-constrained healthcare services, should be prioritised towards patients with the greatest potential risks. At our health network, high-needs pharmacy criteria were developed to identify patients at greatest need of clinical pharmacy services. This retrospective study of 761 patients admitted to four hospitals in metropolitan Melbourne aimed to evaluate the ability of the high-needs pharmacy criteria to identify patients at increased risk of medication-related adverse clinical outcomes. Patients' clinical records were reviewed to determine if the patient met one or more elements of the high-needs criteria. Data on length of stay, 30-day readmission rate, medication-related problems, and medication-related incidents were obtained from the electronic records. Patients meeting one or more high-needs criteria had a longer length of stay (mean 6.7 days vs 3.1 days, p < 0.01), were more likely to be readmitted within 30 days (27% vs 16%, p < 0.01) and had a higher rate of medication-related problems (15% vs 7.6%, p < 0.01). The sensitivity of the high-needs criteria to identify patients with medication-related problems, medication-related incidents, or readmission within 30 days was above 80%. In conclusion, the high-needs pharmacy criteria identified older patients with longer length of stay who are at greater risk of 30-day readmission and medication-related problems.

Objective: The aims of this study were to evaluate the effectiveness of a new automated continuous temperature monitoring system in detecting temperature excursions and describe the challenges of implementing such a system. Design: This study is an observational before-and-after audit comparing temperature excursions detected in the three months before and three months after the implementation of the new monitoring system at Eastern Health. Inclusion criteria consisted of all medicine and vaccine storage facilities monitored by the new automated temperature monitoring system. Four sites not connected to the new monitoring system were excluded. Setting: Eastern Health is a large tertiary metropolitan health service in Melbourne, Australia. It operates from 21 locations including seven teaching hospitals, with medicines and vaccines stored in 124 refrigerators, 6 freezers and 101 ambient room temperature storage locations. Main outcome measures: An analysis of post-implementation data identified a potential association between refrigerator brands and temperature excursion rate. Results: There was a large increase in the number of temperature excursions detected post-implementation of the new automated monitoring system. 28746, 24 and 8966 temperature excursions were detected post-implementation compared to 344, 0 and 0 pre-implementation in refrigerators, freezers and ambient locations, respectively. The majority of temperature excursions detected in medicine and vaccine fridges were below +2°C (98.4%). One brand of refrigerators was linked to 27231 (94.7%) excursions (p<0.001). Conclusions: The new temperature monitoring system detects higher number of excursions which provides better visibility of performance, identifies areas of non-compliance, and guides and evaluates solutions. This study recommends that freezers and ambient storage locations are monitored as robustly as refrigerators, temperature monitoring devices are placed in close proximity to pharmaceuticals, and that healthcare organisations avoid purchasing unreliable medicine and vaccine refrigerators. Finally, this study suggests the development of a National Medicine Storage Guideline.