For the estimation of the weighted MAI scores at admission and discharge, the medical records documented in the patient charts at the time of the pharmaceutical medication review shortly after admission and shortly before discharge were used. To assess the follow-up value of the MAI score, the patients in both groups were contacted three months after discharge by telephone, and their medication plan was assessed by the two pharmacists.
The patient MAI score was calculated via the summation of the weighted MAI scores for each noted drug the patient received at admission, discharge and follow-up, respectively. The subtraction of the patient MAI score at discharge and follow-up from admission resulted in the assessment of the change in patient MAI score. The MAI scoring was verified independently by a senior psychiatrist. For the estimation of the number of unsolved DRP, all DRP that were identified during the hospital stay by the standardized pharmaceutical medication reviews in control group and intervention group were documented and branded as solved or unsolved depending on whether they were elucidated.
Occasionally, the medical records were not available or the psychiatrist firstly wanted to discuss the changes in therapy with the patient before they were implemented. In that case, the pharmacists afterwards checked the medical charts of respective patients to verify that the recommendations were implemented. DRP were also marked as solved if the recommended intervention was implemented after discharge but within the study period, which terminated three months after discharge. If a recommendation was not accepted for any reason or accepted but not certainly implemented, the DRP were labeled as unsolved.
Furthermore, if a recommended intervention was accepted, but it had not been implemented within the entire study period, it was also marked as unsolved. Only DRP that were identified during the hospital stay were included because the pharmacists did not have access to valid medical information after patient discharge.
The PIO system has been demonstrated to be reliable according to its internal and external reliabilities [ 30 , 32 ]. The PIO system was selected because of its comprehensiveness and the lack of a valid result classification of the other classification systems in German [ 30 ]. Additional information regarding the DRP, including the causal drug, acceptance of recommendations and relevance, were also documented in the APOSTAT [ 31 ] database and were evaluated.
The relevance of the DRP were estimated as minor, moderate or high in concordance with a previous pharmaceutical care project in psychiatry [ 34 ]. The potential of medications to cause DRP was calculated by dividing the number of DRP that were triggered by the respective drug by its number of prescriptions at admission. The classification and relevance of the identified DRP were also verified independently by the senior psychiatric physician who was not working on the study wards.
Only the patient MAI score was used to perform the power calculation because no data were available for the number of unsolved DRP. According to Hanlon et al [ 35 ], an effect size of the intervention of 0. Following the intention-to-treat principle, only the patients who were discharged prior to the first pharmaceutical interview were excluded from the analysis. To investigate the efficacy of the intervention on the primary endpoints, we performed a regression analysis to adjust for group differences at admission.
For the number of unsolved DRP, which represent the count data, a generalized linear model for the negative binomial distribution with log-link was computed. The number of unsolved DRP served as the response variable; the treatment group, sex, age, gender, comorbidities, number of drugs, length of hospital stays and total number of DRP were included as predictors. For the patient MAI score, which was assessed at admission, discharge and follow-up, we applied a linear mixed-effect model approach to adjust for the longitudinal structure of the data.
The outcome variable was the MAI score at the three different time points. This longitudinal modeling approach builds up a design matrix with one row for each measurement instead of for each patient; therefore, a missing outcome at follow-up e. As predictors, we included the same variables as for the DRP, with an additional interaction between the treatment group and time categories. Prior to the first pharmaceutical interview four patients were discharged and were excluded from the analysis. The second pharmaceutical interview at discharge was completed by The study protocol was completed by At this time, ten six control, four intervention patients no longer took medications.
Thus, the evaluation of their MAI scores was not possible. For the analysis of the number of unsolved DRP, all patients who completed the first interview were included Fig 1. Gender, age and number of comorbidities significantly differed at baseline between the control and intervention groups. Consequently, the analysis of the primary outcomes were adjusted for these variables via regression models.
The other demographic data were similar between the groups. The baseline assessment of the MAI score was calculated via the summation of the weighted MAI scores, which were assessed with the scoring system of Samsa et al [ 28 ] of every drug the patient regularly took at admission; there were no significant differences Table 1. The change in the MAI score and the number of unsolved DRP were chosen as primary outcomes to assess the effect of the pharmaceutical interventions. The procedure of the pharmaceutical interventions is summarized in Fig 2.
The appropriateness of therapy was significantly improved in the intervention group compared with the control group from admission through discharge to follow-up, which correlates with the decrease in the patient MAI scores. An average of 2. In the patients in the control group, the MAI score slightly decreased from admission 2.
The change in the patient MAI score from admission to discharge or follow-up is shown in Table 2. A negative score reflects an enhancement in the appropriateness of therapy, whereas a positive score indicates a deterioration. The adjusted effect of the intervention on the patient MAI score was an improvement of 1. Of the identified DRP, Both the preventable and non-preventable ADE were primarily resolved during the intervention in contrast with the control group.
The adjusted effect of the intervention on the number of unsolved DRP after the entire study period was 1. In addition, the number of DRP per 1, patient-days was also evaluated for comparison with other medication safety studies in psychiatry, in which this denominator has commonly been used. The 4, and 5, patient-days in the control and intervention groups comply with In the control group, The relevance of the identified DRP was typically estimated as minor Examples for DRP that were communicated to the physicians within the control phase were the concomitant prescription of omeprazole and clopidogrel, a patient with major depression that was not treated with an antidepressant or the concomitant use of two benzodiazepines, mirtazapine and risperidone in a patient that was fallen due to this combination.
Psychotropic drugs accounted for Considering their prescribing frequency at admission, the potential to cause DRP of both psychotropic and non-psychotropic drugs were similar with 0. The potentials of the 10 most commonly applied drugs to cause DRP were calculated and are illustrated in Table 4.
Quetiapin most frequently caused DRP with 0. A reduction in the number of drug prescriptions with an increased potential to induce DRP, such as Imipramine and Carbamazepine, can be assumed in the intervention patients compared with the control. Imipramine and Carbamazepine induced 10 and 7 errors and were applied five and three times in the control; however, these drugs were not prescribed in the intervention group.
The majority of problems that frequently occurred but were not elucidated in the control patients were solved in the intervention group Table 5. Most of the interventions that caused negative outcome were related to the change, dose reduction or discontinuation of a drug e. Collectively, the pharmaceutical recommendations were highly accepted by the ward staff To our knowledge, this is the first study in psychiatric patients to provide evidence regarding the impact of a structured, interdisciplinary medicines management on the appropriateness of therapy and the number of DRP as indicators of medication safety compared with usual psychiatric care.
Here, the MAI was first used as a valid tool to assess the therapy appropriateness in a psychiatric setting. The trial identified a significant improvement in the appropriateness of therapy, which was sustained after discharge, and substantially less unsolved DRP as a result of our structured, interdisciplinary medication reviews with the subsequent implementation of changes in the therapeutic regimen.
Problems that had the potential to cause harm were solved. Common sources of errors were identified and disseminated to the ward staff. Attempts to improve medication safety are typically aimed at the identification and resolution of DRP and the enhancement in drug prescription [ 20 , 21 ].
Therefore, our first primary endpoint was the appropriateness of drug prescribing, which was assessed with the MAI. Prior research that addressed the impact of pharmaceutical interventions on the appropriateness of drug prescription was extended with this study because an evaluation in a psychiatric setting or a study in non-geriatric patients did not exist.
As demonstrated for geriatric patients in several medical conditions [ 35 — 39 ], the intervention in our study significantly improved the appropriateness of the therapy measured by the MAI in middle aged, psychiatric patients. In contrast to these studies, the patient MAI scores at baseline were low in our study 2. A younger study population with half as many drugs prescribed per patient 49 versus 83 years and 3 versus 8 drugs per patient in the intervention group contributed to this finding. Nevertheless, the interdisciplinary approach evaluated in our study decreased the patient MAI score by In our trial, the enhanced appropriateness of therapy was also observed three months after discharge, which represents the sustainability of the intervention and the benefit of pharmaceutical patient contacts after discharge.
Improvements in the appropriateness of prescriptions can be associated with fewer ADE [ 35 ] and improved outcomes [ 41 ], as well as decreased hospital revisits and total costs [ 42 ] in geriatric patients. However, the evaluation of these outcomes was beyond the scope of our study. Although these outcomes are considered transferable to non-geriatric psychiatric inpatients, no confirmatory data is available.
Avoiding common drug−drug interactions
Future studies should address this missing link. Other important factors in terms of drug therapy safety are the identification and the resolution of DRP [ 21 ]. As confirmed in our study, Grasso et al [ 8 ] and Rothschild et al [ 5 ] verified the effectiveness of a medication review in the identification of DRP in psychiatric inpatients. Additionally, the patient interviews supported the identification of DRP, which was also ascertained by Viktil et al [ 43 ]. It can be assumed that the values of DRP were lower in the evaluation of Rothschild et al [ 5 ] Furthermore, the group excluded DRP with little or no potential for harm in contrast to our study, which included and addressed these errors.
Errors with little or no potential for harm, such as an inadequate dosing frequency and a complex therapy, are likely to reduce patient adherence and are therefore worthy of identification, resolution and prevention [ 44 ]. To minimize the risk of medication-related harm for psychiatric patients, Rothschild et al [ 5 ] claimed the need for studies that evaluate strategies to reduce DRP caused by psychiatric and non-psychiatric drugs. The highly significant reduction in the number of unsolved DRP first emphasized the benefit of a strategy that implements pharmacist-led medication reviews with subsequent collaborative discussion of identified DRP in psychiatric wards to improve the drug therapy safety of psychiatric inpatients in a controlled trial.
The primary outcome measure that was applied in our study, the number of unsolved DRP after the entire study period, has not been previously used in other controlled studies that assessed the benefit of a collaborative care model. The strength of the measure is the opportunity to assess the added value of the inter-professional approach to solve all DRP that occurred within the hospital stay compared with usual care. The percent of solved DRP compared with the control group was substantially higher A study in internal medicine demonstrated a similar extensive percentage of solved DRP However, the percentage of solved DRP for control patients were not provided [ 45 ].
Nevertheless, these results likely indicate that the advantage of a structured pharmaceutical care program including medication reviews is independent of the medical discipline. However, the impact of 1. Following studies in psychiatry that focus on clinical outcomes are therefore needed. A major limitation of our study is that it was designed as a non-randomized but consecutive trial.
Assistant physicians alternated during the study period. We cannot rule out that the improvement in prescribing and the decrease in unsolved DRP was caused by the change of ward staff.
Nevertheless, the consecutive design attempted to avoid a knowledge bias in the control group when recommendations for the resolution of DRP in the intervention patients on the same ward were compiled and discussed with the attending physicians. For the first investigation to assess the impact of pharmacist-led medication reviews on therapy appropriateness and the number of unsolved DRP in a controlled clinical trial, we chose to abstain from the randomized trial to minimize confounding.
Moreover, the applied design did not ensure a comparable structure of patient characteristics at baseline; thus, the analysis of the primary outcome was adjusted for significant differences via a regression model. A one-month washout period between study phases were chosen based on the stated average length of patient stay in the hospital of 21 days. However, this mean length of stay comprised also patient, which stayed only for one or two days in hospital to obtain diagnostic tests for example to detect a dementia. As a hospital stay of less than seven days was an exclusion criterion of our trial, the mean length of stay of our study population was longer with a median of Two patients of the control group were still present at ward for three and seven days, respectively when intervention phase started at 1 May However, the overlap did not affect the results because the first pharmaceutical interview at admission in the intervention phase was performed on 8 May and therefore after discharge of these two control patients.
The scoring of the MAI and the number of identified and unsolved DRP were not assessed by an independent rater, but by the two pharmacists who performed the medication reviews on the wards and recommended changes in the therapy. To avoid an over-estimation of the effect of the intervention, the MAI scoring, the classification and the relevance of the DRP were verified by a senior psychiatrist. However, an inter-rater-reliability-score between the pharmacists and the psychiatrist was not assessed.
This second limitation will be addressed in a following evaluation when independent raters retrospectively assess the recorded therapy regimen. As a result of the exploratory nature of our study, indirect measures were applied to assess the impact of an interdisciplinary medicines management in psychiatry. Because a significant benefit was verified, further evaluations should consider the analysis of more direct measurements for patient outcomes, such as the length of hospital stay or readmission rates. Apart from this, the MAI does not address all issues of inappropriate prescribing.
Under-prescription, side effects or compliance were not evaluated with the items of the MAI. Therefore, the calculated MAI score does not precisely reflect the appropriateness of therapy. Nevertheless, the MAI with its ten implicit criteria were chosen over other measures of inappropriate prescribing e. When using explicit criteria individual patient preferences and clinical and patient individual knowledge of the prescriber cannot be recognized. However, the implicit character of the items of the MAI also allow its use in a younger study population, as we expected to have in our study.
Another limitation is the assessment of the MAI score three months after discharge. The calculation of the MAI score based on the medication plan that was verified by the pharmacists in collaboration with the patient by telephonic consultation. However, the pharmacists did not have any other information from community physicians or pharmacies. Therefore, it is possible that the medication plan was incomplete or information were missing.
Only two non-acute wards of the same university hospital in Germany were studied. Thus, the generalizability of the results is limited. Additionally, it would have been favorable to estimate the time that was needed for the discussion with the medical team to assess its impact on the workload of the pharmacists.
Future studies should focus on this topic. Finally, it was beyond the scope of our evaluation to assess the costs of DRP or additional services for example, pharmaceutical medication review. However, the economic aspect is an important factor in the consideration of the permanent implementation of a new care model in the daily clinical routine. Therefore, an economic calculation will also be performed in a subsequent study. In brief, despite several limitations, the structured pharmacist-led medication reviews with subsequent interdisciplinary discussion of DRP has been proven to be an effective tool to identify and solve DRP and therefore enhance the appropriateness of therapy in psychiatric inpatients.
Thus, the permanent implementation of the interdisciplinary pharmaceutical care model in psychiatric hospitals appears to be a worthy strategy to improve medication safety in psychiatric patients. The promising results of this trial warrant further research that evaluates the impact of collaborative pharmaceutical care programs regarding direct clinical outcomes and health-related costs in psychiatry. We thank the medical staff of the Department of Psychiatry and Psychotherapy for supporting the implementation of our trial.
Performed the experiments: CW AP. Browse Subject Areas? Click through the PLOS taxonomy to find articles in your field. Abstract Aim of the study This prospective, controlled trial aimed to assess the effect of pharmacist-led medication reviews on the medication safety of psychiatric inpatients by the resolution of Drug-Related Problems DRP.
Results The intervention led to a reduced MAI score by 1. Conclusion The pharmaceutical medication reviews with interdisciplinary discussion of identified DRP appears to be a worthy strategy to improve medication safety in psychiatry as reflected by less unsolved DRP per patient and an enhanced appropriateness of therapy. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Data Availability: All relevant data are within the paper and its Supporting Information files.
Introduction As a result of the high prevalence of risk factors, such as polypharmacy commonly applied by multiple prescribers, several comorbidities and inadequate adherence, psychiatric patients are at significant risk for Drug-Related Problems DRP [ 1 ]. Methods Setting and participants This prospective, non-randomized, open, controlled study was conducted on two non-acute wards in the Department of Psychiatry and Psychotherapy at the University Hospital of Erlangen.
Intervention After eligible patients gave written consent to take part in the study, both patients in the control group and the intervention group obtained detailed medication reconciliation at admission and medication reviews at discharge and three months after discharge, as well as weekly during the hospital stay by two clinical pharmacists. Outcome measure The primary outcome measures were the change of therapy appropriateness measured by the MAI [ 20 ] between admission and discharge and admission and follow-up, as well as the number of unsolved DRP per patient after the entire study period.
The MAI The MAI includes ten implicit and explicit criteria to review the appropriateness of each prescribed drug regarding the indication, effectiveness, dosage, correct directions, practical directions, drug-drug interaction, drug-disease interaction, duplication, duration and expense. Data Collection The demographic data included gender, age, number of prior psychiatric hospital stays, wards, length of hospital stay and number of drugs at admission, discharge and follow-up.
Statistical analysis Only the patient MAI score was used to perform the power calculation because no data were available for the number of unsolved DRP. Download: PPT. Primary Outcomes The change in the MAI score and the number of unsolved DRP were chosen as primary outcomes to assess the effect of the pharmaceutical interventions. Table 3. The potential and actual risk for patient harm of the identified DRP. Table 4.
Potential to cause DRP of the 10 most commonly prescribed drugs. Table 5. Discussion To our knowledge, this is the first study in psychiatric patients to provide evidence regarding the impact of a structured, interdisciplinary medicines management on the appropriateness of therapy and the number of DRP as indicators of medication safety compared with usual psychiatric care. Supporting Information. S1 File. Related manuscript by Pauly et al.
S1 Protocol. Study protocol German.
Medications for Psychiatric Disorders
S2 Protocol. Study protocol English. Acknowledgments We thank the medical staff of the Department of Psychiatry and Psychotherapy for supporting the implementation of our trial. References 1. Same-day exposures were not uncommon. Again, 2, patients were exposed by the same pharmacy on the same day, and 2, patients were exposed by the same prescriber on the same day. Table 4 shows patients exposed to interactions stratified by the antipsychotic taken, the significance of the interaction, the interaction type inhibitor or inducer , and the enzyme type. Patients taking risperidone were the most likely to be exposed to an interaction— The next most common combinations involved olanzapine The percentage of patients exposed to interaction pairs was highest for category 4 major or moderate interactions and lowest for category 2 moderate interactions.
The percentage of patients exposed to enzyme type CYP2D6 The results of a logistic regression that predicted exposure to a potentially harmful interaction pair are shown in Table 5. This study was a longitudinal, retrospective analysis of a large state's Medicaid claims database that quantified the proportion of patients with schizophrenia exposed to potentially harmful drug-drug interactions involving antipsychotic medication.
This finding is consistent with the findings of a similar study conducted by Howe and colleagues 58 with a PHARMetrics database. Frois and others 59 reported that only 9. Interestingly, the results of this study were similar to those of a study by Jones and others 43 of cisapride and contraindicated medications metabolized by enzyme type CPY3A4. Our study suggests that both prescribing and pharmacy-based dispensing may represent important intervention points for preventing potentially harmful interactions. Moreover, much intervention may be accomplished without involving complicated communications among different physicians or pharmacies.
The results from this study indicate that certain comorbidities, such as depression and COPD, are associated with a higher risk of a potentially harmful interaction. Prescribers need to be aware of these higher risks and monitor their prescribing habits for patients suffering from multiple diseases.
The literature suggests that although most pharmacies have computer-based warning systems, these systems do not consistently prevent the dispensing of contraindicated drugs. Regardless of potentially harmful drug-drug interactions, choosing a specific antipsychotic is nontrivial. Recent studies have associated metabolic effects, such as weight gain, diabetes mellitus, and dyslipidemia, with some of the second-generation antipsychotics, such as olanzapine and risperidone 46 , First-generation antipsychotic drugs carry high risks of parkinsonism and tardive dyskinesia Risks and benefits of the various pharmacologic treatments available must be carefully analyzed.
Jing and colleagues 48 reported that utilization of antipsychotic medication in state Medicaid programs increased dramatically in recent years because second-generation antipsychotic agents are now used to manage conditions other than schizophrenia. These drugs, except for clozapine, have been approved for use by the U. They are also often prescribed, off label, for obsessive-compulsive disorder, borderline personality disorder, and autism. A black box warning by the FDA in slowed their use by elderly patients for treatment of behavioral and psychological symptoms of dementia Identification and quantification of potentially harmful drug-drug interactions are clearly important for these additional populations and will require further study.
Of course, finding that patients with comorbidities are at a greater risk of potentially harmful drug-drug interactions is not particularly surprising. After all, taking more prescription medications automatically puts patients at greater risk. However, not all comorbidities were associated with a higher risk, so this explanation is not generally satisfying. White patients and female patients experienced a significantly higher risk of a potentially harmful interaction. The use of antidepressants to treat major depressive disorder, impulse-control disorder, and eating disorders and the relationship between the incidence of these comorbidities with gender and race may involve a complicated interaction that increases the risk among a certain group of patients.
In fact, estimates of a statistically significant association between death and potentially harmful interactions do not indicate the direction of causation. The results of this study may not be generalizable to other managed-care populations or to other diseases because the study population was limited to a state's Medicaid patients with schizophrenia. The design of the study limits the ability to infer the impact of potentially harmful drug pairs on resource use and cost.
Further research with a prospective design is needed to explore these relationships. There were limited clinical data to validate exposure to potentially harmful interactions. Because this study was based on claims from pharmacies and medical offices, we were unable to determine how often physicians chose to avoid or pharmacists chose not to dispense contraindicated medication pairs or how often pharmacists called physicians to question the prescriptions.
We also could not determine how often pharmacists dispensed overlapping prescriptions for an antipsychotic and a contraindicated medication but instructed the patient to discontinue one of the medications while taking the other. Moreover, regardless of whether physicians are well aware of the literature on potentially harmful effects of combining some drugs, the perceived benefit of the treatment regimen may outweigh the risks, especially for some patients with severe mental illness.
The physicians may be cautious and carefully monitor patient response in order to minimize the risk of an adverse event. Unfortunately, this type of detail cannot be captured by a study of such a large database. One-fourth of patients with schizophrenia were exposed to potentially harmful drug-drug interactions.
Because many of these patients were exposed by the same prescriber or the same pharmacy, and even on the same day, simple interventions by both physicians and pharmacies are recommended. Practitioners should be aware of the possible clinical consequences stemming from certain pairs of antipsychotics and other drugs.
Meanwhile, pharmacies need good systems in place to catch prescriptions for two contraindicated medications. This study was presented at the annual meetings of the American Psychiatric Association, Washington, D. The authors thank William H.
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Olson, C. Panish, and George Wong for their invaluable suggestions and support regarding research design and data analysis techniques, and they appreciate the comments of colleagues at the University of Cincinnati Medical Center. Jing, a graduate student at the time of this research, is an employee of Bristol-Myers Squibb and owns stock in the company.
Keck is a paid consultant to the advisory board of Bristol-Myers Squibb and to Pamlab and is a coinventor U. He has received no financial gain from this patent. The other authors report no competing interests. General Hospital Psychiatry e1—e2, Google Scholar. Psychosomatics 46 : —, Google Scholar. Journal of Clinical Psychiatry 5 suppl 6 —25, Google Scholar.
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Enter your email address below and we will send you your username. Back to table of contents. Previous article. Articles Full Access. Jeff Jianfei Guo Search for more papers by this author. Jasmanda Wu Search for more papers by this author. Christina M. Kelton Search for more papers by this author. Yonghua Jing Search for more papers by this author. Huihao Fan Search for more papers by this author.
Paul E. Keck Search for more papers by this author. Nick C. Patel Search for more papers by this author. Add to favorites Download Citations Track Citations. Table 1Demographic and clinical characteristics of patients who were or were not exposed to potentially dangerous drug-drug interactions a Enlarge table.
Volume 63 Issue 11 November Pages History Published online 1 November Close Figure Viewer. Previous Figure Next Figure. Female b. Age group b. Deceased b. Second-generation antipsychotic. Key comorbidity c. Depression b. Substance use disorder b. Anxiety disorder b. Impulse-control disorder b.
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Personality disorder b. Eating disorder b. Attention-deficit hyperactivity disorder. Diabetes mellitus. Hypertension b. Chronic obstructive pulmonary disease.