An innovative and comprehensive technique to evaluate different measures of medication adherence: The network meta-analysis

Interrupting the Cycle: Association of Parental Stress and Child/Youth Psychotropic Medication Nonadherence

Efficacy of psychotropic medication depends in large part on successful adherence to prescribed regimens. This study investigated child/youth nonadherence in relation to family dynamics and informal support. The participants were 10,225 children and youth prescribed psychotropic medication and receiving services from 50 Ontario mental health agencies, assessed with the interRAI™ Child and Youth Mental Health (ChYMH) and ChYMH-Developmental Disability (ChYMH-DD) tools. Findings suggest a cycle of parental stress and child/youth medication nonadherence possibly leading to or even perpetuated by worsening psychiatric symptoms. Informal supports do not appear to moderate this cycle. While the present data cannot speak to causes of medication nonadherence in children/youth or where the cycle begins, the results are consistent with the extant literature calling for attention to parental wellbeing to support children/youth for optimal therapeutic benefits. Understanding home dynamics related to nonadherence can assist care planning that engages the family to achieve best possible child/youth outcomes.

Nonadherence to antiseizure medications: what have we learned and what can be done next?

INTRODUCTION

Nonadherence to antiseizure medications (ASMs) is associated with increased mortality, morbidity, health care utilization, and costs.

AREAS COVERED

This article reviewed 18 randomized controlled trials published between Jan 2010 and Feb 2024 on Medication Adherence Enhancing Intervention (MAEI) for people with epilepsy. The adequacy of reporting intervention development process was assessed using the GUIDance for the rEporting of intervention Development (GUIDED). The adequacy of the intervention description was assessed using the Template for Intervention Description and Replication (TIDieR) checklist. The interventions were categorized as educational (n = 7), behavioral (n = 5), or mixed (n = 6). The impact of MAEIs on adherence is mixed with majority of studies either reporting no difference between intervention and control groups (n = 6) or improvement in the intervention group (n = 7). The shortcomings in the reporting of MAEIs development, MAEIs description, and MAEIs impact measurement were discussed.

EXPERT OPINION

Future research needs to accomplish the following tasks: 1) develop and test valid epilepsy-specific self-report measures for assessing adherence; 2) optimize intervention design; and 3) increase transparency in reporting all stages of research.

Adherence enhancing interventions for pharmacological and oxygen therapy in patients with COPD: protocol for a systematic review and component network meta-analyses

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is characterised by hyperinflation and expiratory airflow limitation due to long-term exposure to irritants. The variety and complexity of COPD treatment and the possible added comorbidities may make the patients find it difficult to cope with the required medications. That is why supporting patients' adherence is critical because not taking medications correctly increases the risk of complications and creates an additional financial burden. A range of interventions aiming to improve patient adherence were used, and most of them are complex since they involve a mix of elements. Furthermore, despite the variety of available tools, assessing adherence is challenging because clinicians usually do not get a concrete judgement if their patients followed their treatment plan reliably. We aim to evaluate the effectiveness of adherence-enhancing interventions for COPD patients, explore which intervention (component) works for which patients and check the factors influencing the implementation and participant responses.

METHODS

We will perform a comprehensive literature search (Medline, Embase, Cochrane Library, trial registries) without restrictions on language and publication status, and we will include all controlled studies investigating the effect of adherence-enhancing intervention on patients with COPD. We plan to involve COPD patients in the systematic review development through two patient interviews (one before and one after the systematic review). Two reviewers will perform the screening, data extraction and risk of bias (ROB) assessment. For ROB, we will use ROB 2.0 to assess randomised controlled trials, and ROBINS-I to assess non-randomised studies. We will perform pair-wise random-effects meta-analyses and component network meta-analyses to identify the most effective components and combinations of components. We will use the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach to assess the quality of evidence. To determine the degree of complexity, we will use the iCAT_SR checklist, and then, following a logical model, we will group the interventions according to prespecified criteria.

DISCUSSION

This systematic review aims to point out the most effective and implementable adherence-enhancing interventions by using methods for synthesising evidence on complex interventions and involving COPD patients all along with the review process.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42022353977.

Economic evaluation of interventions to improve medication adherence among patients with chronic diseases: an overview of systematic reviews

INTRODUCTION

This overview aimed to find, assess, and synthesize systematic reviews that compared the cost-effectiveness of interventions designed to improve medication adherence among patients with chronic disease.

AREAS COVERED

PubMed, Web of Science, Cochrane Database of Systematic Reviews, and Center for Review and Dissemination were searched. The quality of the included reviews was assessed using two validated checklists. The review characteristics and findings were summarized narratively. A total of 9 systematic reviews were included. Interventions reported to be cost-effective were simplification of the medication regimen, financial incentives, improved coverage or reduced out-of-pocket spending, and pharmacist care. The most common interventions were patient education and counseling, with mixed results of cost-effectiveness. This evidence comes from economic evaluations with varying degrees of quality.

EXPERT OPINION

Future evaluations of adherence interventions' cost-effectiveness will be improved in quality as our understanding of the reasons behind intentional and unintentional nonadherence and factors associated with this behavior advances. The development of criteria for the value assessment of medication adherence-enhancing interventions will contribute to improving the quality of adherence intervention cost-effectiveness research.

The prevalence of bovine mastitis-associated Staphylococcus aureus in China and its antimicrobial resistance rate: A meta-analysis

In this study, to optimize the Staphylococcus aureus control program, a meta-analysis was conducted to investigate the epidemiology and antimicrobial resistance (AMR) profile of S. aureus-associated bovine mastitis in China from 2000 to 2020. A total of 33 publications from PubMed, Google Scholar, and China National Knowledge Infrastructure (CNKI) database were included in our research, among which nine publications included the AMR test. The pooled prevalence of S. aureus was 36.23%, and subgroup analysis revealed that the prevalence dropped from 2000-2010 to 2011-2020, which shows that China is on the right track. The pooled AMR rate indicate isolates were most resistant to β-lactams (50.68%), followed by quinolones (36.23%), macrolides (34.08%), sulfonamides (32.25%), tetracyclines (27.83%), aminoglycosides (26.44%), lincosamides (23.39%), and amphenicol (10.33%). Both the pooled prevalence and AMR of S. aureus in China are higher than those in Western countries, such as Germany, Belgium, Ireland, and the United States-countries with a long animal husbandry history and good management. Thus, there is still room to improve the treatment of S. aureus-associated bovine mastitis in China.

Principles of pharmacoeconomic analysis: the case of pharmacist-led interventions

In the past years, several factors such as evidence-based healthcare culture, quality-linked incentives, and patient-centered actions, associated with an important increase of financial constraints and pressures on healthcare budgets, resulted in a growing interest by policy-makers in enlarging pharmacists' roles in care. Numerous studies have demonstrated positive therapeutic outcomes associated with pharmaceutical services in a wide array of diseases. Yet, the evidence of the economic impact of the pharmacist in decreasing total health expenditures, unnecessary care, and societal costs relies on well-performed, reliable, and transparent economic evaluations, which are scarce. Pharmacoeconomics is a branch of health economics that usually focuses on balancing the costs and benefits of an intervention towards the use of limited resources, aiming at maximizing value to patients, healthcare payers and society through data driven decision making. These decisions can be guide by a health technology assessment (HTA) process that inform governmental players about medical, social, and economic implications of development, diffusion, and use of health technologies - including clinical pharmacy interventions. This paper aims to provide an overview of the important concepts in costing in healthcare, including studies classification according to the type of analysis method (e.g. budget-impact analysis, cost-minimization analysis, cost-effectiveness analysis, cost-utility analysis), types of costs (e.g. direct, indirect and intangible costs) and outcomes (e.g. events prevented, quality adjusted life year - QALY, disability adjusted life year - DALY). Other key components of an economic evaluation such as the models' perspective, time horizon, modelling approaches (e.g. decision trees or simulation models as the Markov model) and sensitivity analysis are also briefly covered. Finally, we discuss the methodological issues for the identification, measurement and valuation of costs and benefits of pharmacy services, and suggest some recommendations for future studies, including the use of Value of Assessment Frameworks.

Association between Adherence with an Atypical Antipsychotic and with Other Psychiatric Drugs in Patients with Bipolar Disorder

BACKGROUND

Using U.S. pharmacy and medical claims, medication adherence patterns of patients with serious mental illness suggest that adherence to atypical antipsychotics may be related to adherence to other prescription drugs. This study investigated whether adherence to an atypical antipsychotic was related to adherence to other prescribed psychiatric drugs using self-reported data from patients with bipolar disorder.

METHODS

Daily self-reported medication data were available from 123 patients with a diagnosis of bipolar disorder receiving treatment as usual who took at least 1 atypical antipsychotic over a 12-week period. Patients took a mean of 4.0±1.7 psychiatric drugs including the antipsychotic. The adherence rate for the atypical antipsychotic was compared to that for other psychiatric drugs to determine if the adherence rate for the atypical antipsychotic differed from that of the other psychiatric drug by at least ±10%.

RESULTS

Of the 123 patients, 58 (47.2%) had an adherence rate for the atypical antipsychotic that differed from the adherence rate for at least 1 other psychiatric drug by at least±10%, and 65 (52.8%) patients had no difference in adherence rates. The patients with a difference took a larger total number of psychiatric drugs (p<0.001), had a larger daily pill burden (p=0.020) and a lower adherence rate with the atypical antipsychotic (p=0.007), and were more likely to take an antianxiety drug (p<0.001).

CONCLUSION

Adherence with an atypical antipsychotic was not useful for estimating adherence to other psychiatric drugs in about half of the patients with bipolar disorder.

Temporal effectiveness of interventions to improve medication adherence: A network meta-analysis

Introduction

Adherence-enhancing interventions have been assessed in the literature, however heterogeneity and conflicting findings have prohibited a consensus on the most effective approach to maintain adherence over time. With the ageing population and growth of chronic conditions, evaluation of sustainable strategies to improve and maintain medication adherence long term is paramount. We aimed to determine the comparative effectiveness of interventions for improving medication adherence over time among adults with any clinical condition.

Materials and methods

Meta-analyses evaluating interventions to improve medication adherence were searched in PubMed in January 2019 and reviewed for primary studies. Experimental studies with a comparison group assessing an intervention to enhance medication adherence in adult patients with reported adherence outcomes were included. Two authors extracted data for study characteristics, interventions and adherence outcomes. Interventions were categorized into four groups or combinations: educational, attitudinal, technical and rewards. Four network meta-analyses were performed to compare interventions based on patient follow-up time. Medication adherence effect sizes were reported as odds ratios (OR) with a 95% credibility interval (CrI) and surface under the cumulative ranking curve (SUCRA) to allow ranking probabilities. Risk of bias was assessed as per Cochrane guidelines.

Results

Data was obtained from 69 meta-analyses with 468 primary studies being included in qualitative synthesis. The four networks compromised of 249 studies in total (0–3 month follow-up: 99 studies, 4–6 months: 104, 7–9 months: 18, ≥10 months: 94). Interventions showing success in follow-ups of less than 10 months varied across time. Significant effects compared to standard of care (SOC) were found in technical (4–6 months: OR 0.34, 95% CrI 0.25–0.45) and attitudinal interventions (7–9 months: 0.37, 0.17–0.84). Multicomponent interventions demonstrated effectiveness compared to standard of care with an additive effect displayed, particularly in longer follow-ups (educational + attitudinal + technical interventions ≥10 months: OR 0.49, 95% CrI 0.27–0.88).

Discussion

All interventions reviewed improved medication adherence compared to standard of care. Multicomponent interventions displayed the most promising results in maintenance of long-term medication adherence. Technical and reward components enhanced adherence on a short-term basis, while educational and attitudinal interventions evolved over time to be more effective in follow-ups greater than 7 months. Sustainability of adherence to medications over time is dependent upon multicomponent interventions including educational, attitudinal and technical aspects to modify and enhance patient medication-taking behavior. Future research should focus on the most cost-effective approaches able to be integrated into routine practice.

Pharmacist-led medication non-adherence intervention: reducing the economic burden placed on the Australian health care system

Background: Scarcity of prospective medication non-adherence cost measurements for the Australian population with no directly measured estimates makes determining the burden medication non-adherence places on the Australian health care system difficult. This study aims to indirectly estimate the national cost of medication non-adherence in Australia comparing the cost prior to and following a community pharmacy-led intervention. Methods: Retrospective observational study. A de-identified database of dispensing data from 20,335 patients (n=11,257 on rosuvastatin, n=6,797 on irbesartan and n=2,281 on desvenlafaxine) was analyzed and average adherence rate determined through calculation of PDC. Included patients received a pharmacist-led medication adherence intervention and had twelve months dispensing records; six months before and six months after the intervention. The national cost estimate of medication non-adherence in hypertension, dyslipidemia and depression pre- and post-intervention was determined through utilization of disease prevalence and comorbidity, non-adherence rates and per patient disease-specific adherence-related costs. Results: The total national cost of medication non-adherence across three prevalent conditions, hypertension, dyslipidemia and depression was $10.4 billion equating to $517 per adult. Following enrollment in the pharmacist-led intervention medication non-adherence costs per adult decreased $95 saving the Australian health care system and patients $1.9 billion annually. Conclusion: In the absence of a directly measured national cost of medication non-adherence, this estimate demonstrates that pharmacists are ideally placed to improve patient adherence and reduce financial burden placed on the health care system due to non-adherence. Funding of medication adherence programs should be considered by policy and decision makers to ease the current burden and improve patient health outcomes moving forward.

Comparison of Interventions to Improve Long-Term Medication Adherence Across Different Clinical Conditions: A Systematic Review With Network Meta-Analysis

Background: Medication non-adherence has a dynamic, temporal and multifactorial nature with a significant impact on economic and clinical outcomes. Interventions to improve adherence are complex and require adaptation to patients' needs, which may include patient's medical conditions. The aim of this study was to assess the comparative effectiveness of medication adherence interventions per type of clinical condition on adult patients.

Methods: A systematic review with network meta-analysis was performed (PROSPERO registration number of CRD42018054598). An initial Pubmed search was conducted to select meta-analyses reporting results of interventions aiming to improve medication adherence. Primary studies were selected and those reporting results with a long-term follow up (≥10 months) on adult patients were included for data extraction. Study characteristics, description of interventions and adherence outcomes were extracted. Adherence interventions were classified in four groups: educational, attitudinal, technical, and rewards. Clinical conditions were classified in four groups: circulatory system and metabolic diseases, infectious diseases, musculoskeletal diseases, and mental, behavioral or neurodevelopmental disorders. Network meta-analyses with effect sizes expressed as odds ratio (OR) with a 95% credibility interval (CrI) were built. Ranking probabilities for each measure of adherence were calculated by using surface under the cumulative ranking analysis (SUCRA).

Results: A total of 61 meta-analysis and 149 primary studies were included in the qualitative synthesis and 80 primary studies in the quantitative analysis. The most effective interventions were: educational + technical 79.6% [OR: 0.44 (CrI: 0.26, 0.73)] and 73.3% [OR: 0.56 (0.36, 0.84)] in circulatory system and metabolic diseases and infectious diseases respectively. Attitudinal intervention had the greatest probability for musculoskeletal diseases of 92.3% in SUCRA [OR: 0.30 (0.10, 0.86)]. Finally, educational + attitudinal interventions had the greatest effect (SUCRA 73.8%) for mental, behavioral or neurodevelopmental disorders, although this was not significant according to consistency analysis.

Conclusion: Effectiveness of interventions seems to be related to the clinical condition. Educational and technical interventions resulted in a major effect on long-term management of medication adherence in patients with infectious diseases (HIV) and circulatory system and metabolic diseases whereas attitudinal components presented a higher effect on musculoskeletal and mental, behavioral or neurodevelopmental disorders.