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

Abstract

Background: Patients at high risk of medication errors will potentially benefit most from medication reviews. An algorithm, MERIS, can identify the patients who are at highest risk of medication errors. The aim of this study was to examine the effects of performing stratified medication reviews on patients who according to MERIS were at highest risk of medication errors. Methods: A randomised controlled trial was performed at the Acute Admissions Unit, Aarhus University Hospital, Denmark. Patients were included at admission to the hospital and were randomised to control or intervention. The intervention consisted of stratified medication review at admission on patients with a high MERIS score. Clinical pharmacists and clinical pharmacologists performed the medication reviews; the clinical pharmacologists performed the reviews on patients with the highest MERIS score. The primary outcome measure was the number of prescribing errors during the hospitalisation. Secondary outcomes included self-experienced quality of life, health-care utilisation and mortality measured at follow-up 90 days after discharge. Results: A total of 375 patients were included, of which medication reviews were performed in 64 patients. The medication reviews addressed 63 prescribing errors in 37 patients and 60 other drug-related problems. No difference in the number of prescribing errors during hospitalisation between the intervention group ( n = 165) and control group ( n = 153) was found, corresponding to 0.11 prescribing errors per drug (95% confidence interval (CI): 0.08–0.14) versus 0.13 per drug (95% CI: 0.09–0.16), respectively. No differences in secondary outcomes were observed. Conclusion: A stratified medication review approach based on the individual patient’s risk of medication errors did not show impact on the chosen outcomes. Plain language summary How does a medication review at admission affect patients who are in high risk of medication errors? Patients are at risk of medication errors at admission to hospital. Medication reviews aim to detect and solve these. Yet, due to limited resources in healthcare, it would be beneficial to detect the patients who are most at risk of medication errors and perform medication reviews on those patients. In this study we investigated whether an algorithm, MERIS, could detect patients who are at highest risk of medication errors; we also studied whether performing medication reviews on patients at highest risk of medication errors would have an effect on, for example, the number of medication errors during hospitalisation, qualify of life and number of readmissions. We included 375 patients in a Danish acute admission unit and they were divided into control group and intervention group. Patients in the intervention group received a medication review at admission if they were considered at high risk of medication errors, assessed with the aid of MERIS. In summary, 64 patients in the intervention group were most at risk of medication errors and therefore received a medication review. We conclude in the study that MERIS was useful in identifying relevant patients for medication reviews. Yet, the medication reviews performed at admission did not impact on the chosen outcomes.

Using soluble urokinase plasminogen activator receptor to stratify patients for medication review in the emergency department

“…Procedures for medication review have been implemented in many countries to improve rational medication use 58 . Number of prescribed medications is often used as a selection criteria for medication reviews, 59 and many strategies, screening tools and prescribing algorithms have been developed to prevent inappropriate prescribing and optimize medication use in the ED 32–35,60–62 . A recent systematic review identified 42 potential tools for assessing appropriateness of prescribed medications 26 .…”

“…58 Number of prescribed medications is often used as a selection criteria for medication reviews, 59 and many strategies, screening tools and prescribing algorithms have been developed to prevent inappropriate prescribing and optimize medication use in the ED. [32][33][34][35][60][61][62] A recent systematic review identified 42 potential tools for assessing appropriateness of prescribed medications. 26 However, disease burden was not included as a tool in this study.…”

“…22 However, randomized controlled trial in Denmark found no explanatory effect of the MERIS algorithm on medication errors, hospitalization or mortality among ED patients. 33 Rofu and colleagues from Australia validated a risk-assessment tool to identify patients at low and high risk of readmission. The variables with the highest impact were living alone with self-management of own medication, history of noncompliance, cognitive impairment, recent medication changes, recent hospital admission, cardiovascular disease, respiratory disease, diabetes and high-risk medications and the total area under the receiver operating characteristic curve was 0.64.…”

“…[30][31][32] In daily practice, patients are often stratified for medication review based on number or types of medications taken without accounting for the patient's disease burden or disease severity. 22,[33][34][35][36] It can be difficult and time-consuming in an acute setting to assess each patient's overall disease burden, and there are currently no simple and easily obtainable clinical tools to identify which patients will benefit most from a medication review. Soluble urokinase plasminogen activator receptor (suPAR) is a nonspecific systemic inflammatory biomarker associated with a range of diseases, including cardiovascular disease, 37 diabetes, 38 chronic obstructive pulmonary disease, 39 kidney disease 40,41 and cognitive decline.…”

External validation of the Medication Risk Score in polypharmacy patients in general practice: A tool for prioritizing patients at greatest risk of potential drug‐related problems

“…A recent randomized controlled trial, including 375 patients with similar mean age and number of drugs as our population, used the MERIS to perform stratified CMRs in patients at the highest risk of DRPs. 39 The trial was conducted at an acute admissions unit, where intervention patients with a MERIS score ≥14 received a CMR by either a clinical pharmacist (score 14 to 26) or a clinical pharmacologist (score ≥26). In total, 34% of the patients in the intervention group were identified as high-risk patients according to the MERIS.…”