Opti-Med: the effectiveness of optimised clinical medication reviews in older people with 'geriatric giants' in general practice; study protocol of a cluster randomised controlled trial

Deprescribing Interventions for Older Patients: A Systematic Review and Meta-Analysis

OBJECTIVES

Deprescribing reduces polypharmacy in older adults. A thorough study of the effect of deprescribing interventions on clinical outcomes in older adults is presently lacking. As a result, we evaluated the impact of deprescribing on clinical outcomes in older patients.

DESIGN

Meta-analysis and systematic review of randomized controlled trials (RCTs). PubMed, EMBASE, and Cochrane Library were searched from the time of creation to March 2023.

SETTING AND PARTICIPANTS

Randomized controlled trial with participants at least 60 years old.

MEASURES

Mortality, falls (number of fallers), hospitalization rates, emergency department visits, medication adherence, HRQoL (health-regulated quality of life), incidence of ADR (adverse drug reactions), PIM (potentially inappropriate medication), and PPO (potentially prescription omission) were evaluated in the meta-analysis.

RESULTS

A total of 32 RCTs (18,670 patients) were included. Deprescribing interventions significantly reduced proportions of older adults with PIM, PPO, and the incidence of ADRs. The interventions group also improved medication compliance.

CONCLUSIONS AND IMPLICATIONS

Compared to routine care, deprescribing interventions significantly improve clinical outcome indicators for older adults.

Predicting hospital admissions from individual patient data (IPD): an applied example to explore key elements driving external validity

OBJECTIVE

To explore factors that potentially impact external validation performance while developing and validating a prognostic model for hospital admissions (HAs) in complex older general practice patients.

STUDY DESIGN AND SETTING

Using individual participant data from four cluster-randomised trials conducted in the Netherlands and Germany, we used logistic regression to develop a prognostic model to predict all-cause HAs within a 6-month follow-up period. A stratified intercept was used to account for heterogeneity in baseline risk between the studies. The model was validated both internally and by using internal-external cross-validation (IECV).

RESULTS

Prior HAs, physical components of the health-related quality of life comorbidity index, and medication-related variables were used in the final model. While achieving moderate discriminatory performance, internal bootstrap validation revealed a pronounced risk of overfitting. The results of the IECV, in which calibration was highly variable even after accounting for between-study heterogeneity, agreed with this finding. Heterogeneity was equally reflected in differing baseline risk, predictor effects and absolute risk predictions.

CONCLUSIONS

Predictor effect heterogeneity and differing baseline risk can explain the limited external performance of HA prediction models. With such drivers known, model adjustments in external validation settings (eg, intercept recalibration, complete updating) can be applied more purposefully.

TRIAL REGISTRATION NUMBER

PROSPERO id: CRD42018088129.

Predicting negative health outcomes in older general practice patients with chronic illness: Rationale and development of the PROPERmed harmonized individual participant data database

The prevalence of multimorbidity and polypharmacy increases significantly with age and are associated with negative health consequences. However, most current interventions to optimize medication have failed to show significant effects on patient-relevant outcomes. This may be due to ineffectiveness of interventions themselves but may also reflect other factors: insufficient sample sizes, heterogeneity of population. To address this issue, the international PROPERmed collaboration was set up to obtain/synthesize individual participant data (IPD) from five cluster-randomized trials. The trials took place in Germany and The Netherlands and aimed to optimize medication in older general practice patients with chronic illness. PROPERmed is the first database of IPD to be drawn from multiple trials in this patient population and setting. It offers the opportunity to derive prognostic models with increased statistical power for prediction of patient-relevant outcomes resulting from the interplay of multimorbidity and polypharmacy. This may help patients from this heterogeneous group to be stratified according to risk and enable clinicians to identify patients that are likely to benefit most from resource/time-intensive interventions. The aim of this manuscript is to describe the rationale behind PROPERmed collaboration, characteristics of the included studies/participants, development of the harmonized IPD database and challenges faced during this process.

Effect of a patient-centred deprescribing procedure in older multimorbid patients in Swiss primary care - A cluster-randomised clinical trial

Background

Management of patients with polypharmacy is challenging, and evidence for beneficial effects of deprescribing interventions is mixed. This study aimed to investigate whether a patient-centred deprescribing intervention of PCPs results in a reduction of polypharmacy, without increasing the number of adverse disease events and reducing the quality of life, among their older multimorbid patients.

Methods

This is a cluster-randomised clinical study among 46 primary care physicians (PCPs) with a 12 months follow-up. We randomised PCPs into an intervention and a control group. They recruited 128 and 206 patients if ≥60 years and taking ≥five drugs for ≥6 months. The intervention consisted of a 2-h training of PCPs, encouraging the use of a validated deprescribing-algorithm including shared-decision-making, in comparison to usual care. The primary outcome was the mean difference in the number of drugs per patient (dpp) between baseline and after 12 months. Additional outcomes focused on patient safety and quality of life (QoL) measures.

Results

Three hundred thirty-four patients, mean [SD] age of 76.2 [8.5] years participated. The mean difference in the number of dpp between baseline and after 12 months was 0.379 in the intervention group (8.02 and 7.64; p = 0.059) and 0.374 in the control group (8.05 and 7.68; p = 0.065). The between-group comparison showed no significant difference at all time points, except for immediately after the intervention (p = 0.002). There were no significant differences concerning patient safety nor QoL measures.

Conclusion

Our straight-forward and patient-centred deprescribing procedure is effective immediately after the intervention, but not after 6 and 12 months. Further research needs to determine the optimal interval of repeated deprescribing interventions for a sustainable effect on polypharmacy at mid- and long-term. Integrating SDM in the deprescribing process is a key factor for success.

Trial registration

Current Controlled Trials, prospectively registered ISRCTN16560559 Date assigned 31/10/2014.

The Prevention of Polypharmacy in Primary Care Patients Trial (4P-RCT).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-020-01870-8.

A prognostic model predicted deterioration in health-related quality of life in older patients with multimorbidity and polypharmacy

OBJECTIVES

To develop and validate a prognostic model to predict deterioration in health-related quality of life (dHRQoL) in older general practice patients with at least one chronic condition and one chronic prescription.

STUDY DESIGN AND SETTING

We used individual participant data from five cluster-randomized trials conducted in the Netherlands and Germany to predict dHRQoL, defined as a decrease in EQ-5D-3 L index score of ≥5% after 6-month follow-up in logistic regression models with stratified intercepts to account for between-study heterogeneity. The model was validated internally and by using internal-external cross-validation (IECV).

RESULTS

In 3,582 patients with complete data, of whom 1,046 (29.2%) showed deterioration in HRQoL, and 12/87 variables were selected that were related to single (chronic) conditions, inappropriate medication, medication underuse, functional status, well-being, and HRQoL. Bootstrap internal validation showed a C-statistic of 0.71 (0.69 to 0.72) and a calibration slope of 0.88 (0.78 to 0.98). In the IECV loop, the model provided a pooled C-statistic of 0.68 (0.65 to 0.70) and calibration-in-the-large of 0 (-0.13 to 0.13). HRQoL/functionality had the strongest prognostic value.

CONCLUSION

The model performed well in terms of discrimination, calibration, and generalizability and might help clinicians identify older patients at high risk of dHRQoL.

REGISTRATION

PROSPERO ID: CRD42018088129.

Interventions for improving medication-taking ability and adherence in older adults prescribed multiple medications

BACKGROUND

Older people taking multiple medications represent a large and growing proportion of the population. Managing multiple medications can be challenging, and this is especially the case for older people, who have higher rates of comorbidity and physical and cognitive impairment than younger adults. Good medication-taking ability and medication adherence are necessary to ensure safe and effective use of medications.

OBJECTIVES

To evaluate the effectiveness of interventions designed to improve medication-taking ability and/or medication adherence in older community-dwelling adults prescribed multiple long-term medications.

SEARCH METHODS

We searched MEDLINE, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), PsycINFO, CINAHL Plus, and International Pharmaceutical Abstracts from inception until June 2019. We also searched grey literature, online trial registries, and reference lists of included studies.

SELECTION CRITERIA

We included randomised controlled trials (RCTs), quasi-RCTs, and cluster-RCTs. Eligible studies tested interventions aimed at improving medication-taking ability and/or medication adherence among people aged ≥ 65 years (or of mean/median age > 65 years), living in the community or being discharged from hospital back into the community, and taking four or more regular prescription medications (or with group mean/median of more than four medications). Interventions targeting carers of older people who met these criteria were also included.

DATA COLLECTION AND ANALYSIS

Two review authors independently reviewed abstracts and full texts of eligible studies, extracted data, and assessed risk of bias of included studies. We conducted meta-analyses when possible and used a random-effects model to yield summary estimates of effect, risk ratios (RRs) for dichotomous outcomes, and mean differences (MDs) or standardised mean differences (SMDs) for continuous outcomes, along with 95% confidence intervals (CIs). Narrative synthesis was performed when meta-analysis was not possible. We assessed overall certainty of evidence for each outcome using Grades of Recommendation, Assessment, Development and Evaluation (GRADE). Primary outcomes were medication-taking ability and medication adherence. Secondary outcomes included health-related quality of life (HRQoL), emergency department (ED)/hospital admissions, and mortality.

MAIN RESULTS

We identified 50 studies (14,269 participants) comprising 40 RCTs, six cluster-RCTs, and four quasi-RCTs. All included studies evaluated interventions versus usual care; six studies also reported a comparison between two interventions as part of a three-arm RCT design. Interventions were grouped on the basis of their educational and/or behavioural components: 14 involved educational components only, 7 used behavioural strategies only, and 29 provided mixed educational and behavioural interventions. Overall, our confidence in results regarding the effectiveness of interventions was low to very low due to a high degree of heterogeneity of included studies and high or unclear risk of bias across multiple domains in most studies. Five studies evaluated interventions for improving medication-taking ability, and 48 evaluated interventions for improving medication adherence (three studies evaluated both outcomes). No studies involved educational or behavioural interventions alone for improving medication-taking ability. Low-quality evidence from five studies, each using a different measure of medication-taking ability, meant that we were unable to determine the effects of mixed interventions on medication-taking ability. Low-quality evidence suggests that behavioural only interventions (RR 1.22, 95% CI 1.07 to 1.38; 4 studies) and mixed interventions (RR 1.22, 95% CI 1.08 to 1.37; 12 studies) may increase the proportions of people who are adherent compared with usual care. We could not include in the meta-analysis results from two studies involving mixed interventions: one had a positive effect on adherence, and the other had little or no effect. Very low-quality evidence means that we are uncertain of the effects of educational only interventions (5 studies) on the proportions of people who are adherent. Low-quality evidence suggests that educational only interventions (SMD 0.16, 95% CI -0.12 to 0.43; 5 studies) and mixed interventions (SMD 0.47, 95% CI -0.08 to 1.02; 7 studies) may have little or no impact on medication adherence assessed through continuous measures of adherence. We excluded 10 studies (4 educational only and 6 mixed interventions) from the meta-analysis including four studies with unclear or no available results. Very low-quality evidence means that we are uncertain of the effects of behavioural only interventions (3 studies) on medication adherence when assessed through continuous outcomes. Low-quality evidence suggests that mixed interventions may reduce the number of ED/hospital admissions (RR 0.67, 95% CI 0.50 to 0.90; 11 studies) compared with usual care, although results from six further studies that we were unable to include in meta-analyses indicate that the intervention may have a smaller, or even no, effect on these outcomes. Similarly, low-quality evidence suggests that mixed interventions may lead to little or no change in HRQoL (7 studies), and very low-quality evidence means that we are uncertain of the effects on mortality (RR 0.93, 95% CI 0.67 to 1.30; 7 studies). Moderate-quality evidence shows that educational interventions alone probably have little or no effect on HRQoL (6 studies) or on ED/hospital admissions (4 studies) when compared with usual care. Very low-quality evidence means that we are uncertain of the effects of behavioural interventions on HRQoL (1 study) or on ED/hospital admissions (2 studies). We identified no studies evaluating effects of educational or behavioural interventions alone on mortality. Six studies reported a comparison between two interventions; however due to the limited number of studies assessing the same types of interventions and comparisons, we are unable to draw firm conclusions for any outcomes.

AUTHORS' CONCLUSIONS

Behavioural only or mixed educational and behavioural interventions may improve the proportion of people who satisfactorily adhere to their prescribed medications, but we are uncertain of the effects of educational only interventions. No type of intervention was found to improve adherence when it was measured as a continuous variable, with educational only and mixed interventions having little or no impact and evidence of insufficient quality to determine the effects of behavioural only interventions. We were unable to determine the impact of interventions on medication-taking ability. The quality of evidence for these findings is low due to heterogeneity and methodological limitations of studies included in the review. Further well-designed RCTs are needed to investigate the effects of interventions for improving medication-taking ability and medication adherence in older adults prescribed multiple medications.

Effectiveness of medication review on the number of drug-related problems in patients visiting the outpatient cardiology clinic: A randomized controlled trial

AIMS

To assess the effectiveness of medication review on the number of drug-related problems (DRPs) in outpatient cardiology patients.

METHODS

In this randomized controlled trial, a computer-assisted and pharmacist-led medication review with patient involvement (questionnaire and telephone call with pharmacist) was conducted in intervention patients prior to their visit to the cardiologist. The control group received usual care. Adult outpatient cardiology patients without support concerning the administration of medication, without a medication review in the past 6 months and who gave permission to access their electronic medication record were included. The primary outcome measure was the number of DRPs 1 month after the visit. Secondary outcome measures concerned the type of DRP and the type of medication involved in the DRPs.

RESULTS

In total, 75 patients (mean [standard deviation, SD] age 66.0 [12.5] years, 41% female) were included. Intervention (n = 90) and control group (n = 85) were comparable at baseline. The mean (SD) number of drugs used per patient was 7.9 (3.9). After 1 month, the mean (SD) number of DRPs was 0.3 (0.7) and 0.8 (1.0) and the median (range) number of DRPs was 0 (0-4) and 0 (0-4) in the intervention group and control group, respectively (P < .001). In the intervention group, 74% of the DRPs identified at T0 were solved at T1 vs 14% in the control group.

CONCLUSION

This randomized controlled trial suggests that a pharmacist-led medication review in patients with a scheduled visit to the outpatient cardiology clinic decreases the number of DRPs.

Implementation fidelity of a clinical medication review intervention: process evaluation

Background Implementation of clinical medication reviews in daily practice is scarcely evaluated. The Opti-Med intervention applied a structured approach with external expert teams (pharmacist and physician) to conduct medication reviews. The intervention was effective with respect to resolving drug related problems, but did not improve quality of life. Objective The objective of this process evaluation was to gain more insight into the implementation fidelity of the intervention. Setting Process evaluation alongside a cluster randomized trial in 22 general practices and 518 patients of 65 years and over. Method A mixed methods design using quantitative and qualitative data and the conceptual framework for implementation fidelity was used. Implementation fidelity is defined as the degree to which the various components of an intervention are delivered as intended. Main outcome measure Implementation fidelity for key components of the Opti-Med intervention. Results Patient selection and preparation of the medication analyses were carried out as planned, although mostly by the Opti-Med researchers instead of practice nurses. Medication analyses by expert teams were performed as planned, as well as patient consultations and patient involvement. 48% of the proposed changes in the medication regime were implemented. Cooperation between expert teams members and the use of an online decision-support medication evaluation facilitated implementation. Barriers for implementation were time constraints in daily practice, software difficulties with patient selection and incompleteness of medical files. The degree of embedding of the intervention was found to influence implementation fidelity. The total time investment for healthcare professionals was 94 min per patient. Conclusion Overall, the implementation fidelity was moderate to high for all key components of the Opti-Med intervention. The absence of its effectiveness with respect to quality of life could not be explained by insufficient implementation fidelity.

The effectiveness of optimised clinical medication reviews for geriatric patients: Opti-Med a cluster randomised controlled trial

BACKGROUND

Inappropriate drug use is a frequent problem in older patients and associated with adverse clinical outcomes and an important determinant of geriatric problems. Clinical medication reviews (CMR) may reduce inappropriate drug use.

OBJECTIVE

The aim of this study is to investigate the effectiveness of CMR on quality of life (QoL) and geriatric problems in comparison with usual care in older patients with geriatric problems in the general practice.

METHODS

We performed a cluster randomised controlled trial in 22 Dutch general practices. Patients of ≥65 years were eligible if they newly presented with pre-specified geriatric symptoms in general practice and the chronic use of ≥1 prescribed drug. The intervention consisted of CMRs which were prepared by an independent expert team and discussed with the patient by the general practitioner. Primary outcomes: QoL and the presence of self-reported geriatric problems after a follow-up period of 6 months.

RESULTS

518 patients were included. No significant differences between the intervention and control group and over time were found for QoL, geriatric problems, satisfaction with medication and self-reported medication adherence. After 6 months the percentage of solved Drug Related Problems (DRPs) was significantly higher in the intervention group compared to the control group [B 22.6 (95%CI 14.1-31.1), P < 0.001].

CONCLUSION

The study intervention did not influence QoL and geriatric problems. The higher percentage of solved DRPs in the intervention group did not result in effects on the patient's health. CMRs on a large scale seem not meaningful and should be reconsidered.

Efficiency of Clinical Decision Support Systems Improves with Experience

Efficiency, or the resources spent while performing a specific task, is widely regarded as one the determinants of usability. In this study, the authors hypothesize that having a group of users perform a similar task over a prolonged period of time will lead to improvements in efficiency of that task. This study was performed in the domain of decision-supported medication reviews. Data was gathered during a randomized controlled trial. Three expert teams consisting of an independent physician and an independent pharmacist conducted 150 computerized medication reviews on patients in 13 general practices located in Amsterdam, the Netherlands. Results were analyzed with a linear mixed model. A fixed effects test on the linear mixed model showed a significant difference in the time required to conduct medication reviews over time; F(31.145) = 14.043, p < .001. The average time in minutes required to conduct medication reviews up to the first quartile was M = 20.42 (SD = 9.00), while the time from the third quartile up was M = 9.81 (SD = 6.13). This leads the authors to conclude that the amount of time users needed to perform similar tasks decreased significantly as they gained experience over time.

Information on actual medication use and drug-related problems in older patients: questionnaire or interview?

Background Information on medication use and drug-related problems is important in the preparation of clinical medication reviews. Critical information can only be provided by patients themselves, but interviewing patients is time-consuming. Alternatively, patient information could be obtained with a questionnaire. Objective In this study the agreement between patient information on medication use and drug-related problems in older patients obtained with a questionnaire was compared with information obtained during an interview. Setting General practice in The Netherlands. Method A questionnaire was developed to obtain information on actual medication use and drug-related problems. Two patient groups ≥65 years were selected based on general practitioner electronic medical records in nine practices; I. polypharmacy and II. ≥1 predefined general geriatric problems. Eligible patients were asked to complete the questionnaire and were interviewed afterwards. Main outcome measure Agreement on information on medication use and drug-related problems collected with the questionnaire and interview was calculated. Results Ninety-seven patients participated. Of all medications used, 87.6 % (95 % CI 84.7–90.5) was reported identically in the questionnaire and interview. Agreement for the complete medication list was found for 45.4 % (95 % CI 35.8–55.3) of the patients. On drug-related problem level, agreement between questionnaire and interview was 75 %. Agreement tended to be lower in vulnerable patients characterized by ≥4 chronic diseases, ≥10 medications used and low health literacy. Conclusion Information from a questionnaire showed reasonable agreement compared with interviewing. The patients reported more medications and drug-related problems in the interview than the questionnaire. Taking the limitations into account, a questionnaire seems a suitable tool for medication reviews that may replace an interview for most patients.

Effect of a patient-centered drug review on polypharmacy in primary care patients: study protocol for a cluster-randomized controlled trial

BACKGROUND

Managing patients with polypharmacy is a challenging issue in primary care. The aim of this study is to determine whether a patient-centered systematic review leads to more appropriate medication use in patients without negatively affecting quality of life and the course of the disease.

METHODS/DESIGN

The trial is a two-armed, double blinded cluster-randomized controlled trial. Primary care physicians (PCPs) will be randomly assigned to the intervention or control group. Physicians in the intervention group undergo training with instruction of the algorithm. The control group is given a lecture on multimorbidity and instructions for collecting data in a usual care manner. PCPs will approach patients aged 60 years or older who are taking 5 or more drugs. The study period is 1 year. The primary outcome measure is the change in the number of drugs 12 months after the algorithm was applied by the PCP during consultation with the patient. Secondary outcomes are: change in the number of drugs immediately after the encounter and 6 months later, reason for a change of the medication, discrepancy in the decision to change between PCP and patient, number of drugs for which the patient is suggesting a change, number of drugs the patient is taking that are not known to the PCP, time consumption of the intervention, disease-specific variables to evaluate the course of the disease(s) for which the patient is being treated , quality of life, barriers against using the algorithm, numbers of drugs readopted due to an unfavorable course of the disease, and numbers of drugs which have been started.

DISCUSSION

Answering the four questions of the algorithm requires a weighing-up of risks and benefits and contains a shared-decision-making approach: a prioritization of the treatment goals is necessary. This can only be done in collaboration with the patient. The majority of patients with multimorbidity are treated in the primary care setting. This underlines the significance of our study carried out in this setting: given the high prevalence of adverse drug events in patients with multimorbidity an intervention like ours has a large potential to reduce drug-related morbidity.

TRIAL REGISTRATION

ISRCTN16560559 13 November 2014.