Risk of prescribing errors in acutely admitted patients: a pilot study

Abstract

Background Prescribing errors in emergency settings occur frequently. Knowing which patients have the highest risk of errors could improve patient outcomes. Objective The aim of this study was to test an algorithm designed to assess prescribing error risk in individual patients, and to test the feasibility of medication reviews in high-risk patients. Setting The study was performed at the Acute Admissions Unit at Aarhus University Hospital, Denmark. Methods The study was an interventional pilot study. Patients included were assessed according to risk of prescribing errors with the aid of an algorithm called 'Medication Risk Score' (MERIS). Based on the score, high-risk patients were offered a medication review. The clinical relevance of the medication reviews was assessed retrospectively. Main outcome measure The number and nature of prescribing errors during the patients' hospitalisation. Results The study included 103 patients, all of whom could be risk assessed with the algorithm MERIS. MERIS stratified 38 patients as high-risk patients and 65 as low-risk patients. The 103 patients were prescribed a total of 848 drugs in which 88 prescribing errors were found (10.4 %). Sixty-two of these were found in patients in the high-risk group. In general, the medication reviews were found to be clinically relevant and approximately 50 % of recommendations were implemented. Conclusion MERIS was found to be applicable in a clinical setting and stratified most patients with prescribing errors into the high-risk group. The medication reviews were feasible and found to be clinically relevant by most raters.

Screening Tools Used by Clinical Pharmacists to Identify Elderly Patients at Risk of Drug-Related Problems on Hospital Admission: A Systematic Review

“…Two studies [ 18 , 38 ] did not report the age demographics of the study participants (although participants were adults). The remaining studies were conducted in adult patients (including but not exclusively elderly patients) [ 3 , 20 , 34 , 35 , 36 , 37 , 39 , 40 , 42 ]. The majority of the studies presented either the mean or median age for participants, with the mean age of participants varying from 51.4 years [ 20 ] to 86.7 years [ 33 ], showing significant variations between the participants of the various studies.…”

“…One study involved the development and external validation of a tool [ 30 ], whilst another involved the development, internal and external validation of a tool [ 25 ]. One study [ 20 ] only described the development of an assessment tool (which was subsequently utilised in a further study; see below [ 35 ]); another study described the development and subsequent utilisation (rather than validation) of a tool [ 38 ], four studies described the utilisation or internal validation of a previously developed tool [ 35 , 36 , 37 , 39 ], and two studies provided external validation (only) of the previously developed GerontoNet ADR Risk Score [ 32 , 43 ].…”

“…The majority of the studies (74%) were conducted in European centres [ 3 , 18 , 25 , 30 , 31 , 32 , 33 , 34 , 36 , 37 , 41 , 42 , 43 , 44 ], and the remaining studies were conducted in New Zealand [ 38 , 39 ], Canada [ 20 , 35 ] and the US [ 40 ]. In two of the European-based studies [ 25 , 30 ], the development phase took place in Europe and the developed tools were then externally validated within centres in four European countries (and also internally validated in one of the studies [ 25 ]).…”

“…There were also subtle differences between studies with the same broad primary outcomes with respect to definitions/interpretations—for example, one study looked at the incidence of “non-trivial ADRs” [ 44 ] and another specified that their primary outcomes were ADEs that required a change in medical therapy, diagnostic testing, consultation, or hospital admission [ 20 ]. The primary outcomes for the remaining studies were more specific/individual to each study and included the incidence of medication errors per patient [ 42 ], prescribing errors (PEs) [ 36 ], medication discrepancies on medication reconciliation at admission and Pes [ 39 ], time to rehospitalisation or death during the year following discharge [ 33 ], the number of DRPs per admission [ 3 ], the rate of potentially avoidable hospital readmission at 30 days [ 40 ] and the rate of pharmacist interventions [ 34 ]. These variations in the primary outcomes (and even differences in the exact definitions included within these primary outcomes) made it difficult to compare or collate the results and findings of the different studies, as they were not measuring the same parameters.…”

Effects of stratified medication review in high-risk patients at admission to hospital: a randomised controlled trial

“…This corresponded to 119 patients when applying the mean number of drugs from a pilot study (8.2 drugs). 13 Physicians accepted approximately 50% of the recommendations and to minimise the risk of potential clustering a total of 375 patients was needed.…”