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

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.

Medication Review and Patient Outcomes in an Orthopedic Department: A Randomized Controlled Study.

OBJECTIVE: We investigated the health-related effect of systematic medication review performed by a clinical pharmacist and a clinical pharmacologist on nonelective elderly orthopedic patients. METHODS: This is a nonblinded randomized controlled study of 108 patients 65 years or older treated with at least 4 drugs. For the intervention, the clinical pharmacist reviewed the participants' medication after completion of the usual medication routine. Information was collected from medical charts, interviews with participants, and database registrations of drug purchase. Results were conferred with the clinical pharmacologist, and recommendations were delivered directly to the ward physicians. The control was usual medication routine, that is, physicians prescribing admitting orders. The primary outcome was time to the first unplanned contact to a physician after discharge (i.e., general practitioner, emergency department visit, or readmission) during 3-month follow-up. Secondary outcomes included other health-related outcomes, for example, length of in-hospital stay, mortality, and quality of life. RESULTS: Time to the first unplanned contact to a physician was 14.9 days (95% confidence interval, 8.9-21.0) in the intervention group compared with 27.3 days (95% confidence interval, 18.9-35.7) in the controls (P = 0.05). Overall, no statistically significant differences were seen in the secondary outcomes apart from "number of" and "time to first" emergency department visits, which were in favor of the intervention group. A marked hesitation of the ward physicians to comply with recommendations was noted (18%). CONCLUSIONS: The study showed that the patients receiving usual care had a significantly longer time to the first unplanned contact to a physician after discharge; however, the fact that less than 1 of 5 recommendations was adopted by the physicians raises concerns as to whether this finding could be attributable to the intervention.

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

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.

Detection of Patients at High Risk of Medication Errors: Development and Validation of an Algorithm.

Medication errors (MEs) are preventable and can result in patient harm and increased expenses in the healthcare system in terms of hospitalization, prolonged hospitalizations and even death. We aimed to develop a screening tool to detect acutely admitted patients at low or high risk of MEs comprised by items found by literature search and the use of theoretical weighting. Predictive variables used for the development of the risk score were found by the literature search. Three retrospective patient populations and one prospective pilot population were used for modelling. The final risk score was evaluated for precision by the use of sensitivity, specificity and area under the ROC (receiver operating characteristic) curves. The variables used in the final risk score were reduced renal function, the total number of drugs and the risk of individual drugs to cause harm and drug-drug interactions. We found a risk score in the prospective population with an area under the ROC curve of 0.76. The final risk score was found to be quite robust as it showed an area under the ROC curve of 0.87 in a recent patient population, 0.74 in a population of internal medicine and 0.66 in an orthopaedic population. We developed a simple and robust score, MERIS, with the ability to detect patients and divide them according to low and high risk of MEs in a general population admitted at acute admissions unit. The accuracy of the risk score was at least as good as other models reported using multiple regression analysis.

Classification of drugs with different risk profiles.

INTRODUCTION: A risk stratification approach is needed to identify patients at high risk of medication errors and a resulting high need of medication review. The aim of this study was to perform risk stratification (distinguishing between low-risk, medium-risk and high-risk drugs) for drugs found to cause serious adverse reactions due to medication errors. The study employed a modified Delphi technique. METHODS: Drugs from a systematic literature search were included into two rounds of a Delphi process. A panel of experts was asked to evaluate each identified drug's potential for harm and for clinically relevant drug-drug interactions on a scale from 1 (low risk) to 9 (high risk). RESULTS: A total of 36 experts were appointed to serve on the panel. Consensus was reached for 29/57 (51%) drugs or drug classes that cause harm, and for 32/57 (56%) of the drugs or drug classes that cause interactions. For the remaining drugs, a decision was made based on the median score. Two lists, one stating the drugs' potential for causing harm and the other stating clinically relevant drug-drug interactions, were stratified into low-risk, medium-risk and high-risk drugs. CONCLUSION: Based on a modified Delphi technique, we created two lists of drugs stratified into a low-risk, a medium-risk and a high-risk group of clinically relevant interactions or risk of harm to patients. The lists could be incorporated into a risk-scoring tool that stratifies the performance of medication reviews according to patients' risk of experiencing adverse reactions. FUNDING: none. TRIAL REGISTRATION: not relevant.

Medication counselling: physicians' perspective.

Medication reviews have the potential to lower the incidence of prescribing errors. To benefit from a medication review, the prescriber must adhere to medication counselling. Adherence rates vary from 39 to 100%. The aim of this study was to examine counselling-naive hospital physicians' perspectives and demands to medication counselling as well as study factors that might increase adherence to the counselling. The study was conducted as a questionnaire survey among physicians at Aarhus University Hospital, Denmark. The questionnaire was developed based on focus group interviews and literature search, and was pilot-tested among 30 physicians before being sent to 669 physicians. The questionnaire consisted of 35 items divided into four categories: attitudes (19 items), behaviours (3 items), assessment (8 items) and demographics (5 items). The response rate was 60% (400/669). Respondents were employed at psychiatric, medical or surgical departments. Eighty-five per cent of respondents agreed that patients would benefit of an extra medication review, and 72% agreed that there was a need for external medication counselling. The most important factor that could increase adherence was the clinical relevance of the counselling as 78% rated it of major importance. The most favoured method for receiving counselling was via the electronic patient record.