Coming full circle in the measurement of medication adherence: opportunities and implications for health care

Ethical considerations in using sensors to remotely assess pediatric health behaviors

Sensors, including accelerometer-based and electronic adherence monitoring devices, have transformed health data collection. Sensors allow for unobtrusive, real-time sampling of health behaviors that relate to psychological health, including sleep, physical activity, and medication-taking. These technical strengths have captured scholarly attention, with far less discussion about the level of human touch involved in implementing sensors. Researchers face several subjective decision points when collecting health data via sensors, with these decisions posing ethical concerns for users and the public at large. Using examples from pediatric sleep, physical activity, and medication adherence research, we pose critical ethical questions, practical dilemmas, and guidance for implementing health-based sensors. We focus on youth given that they are often deemed the ideal population for digital health approaches but have unique technology-related vulnerabilities and preferences. Ethical considerations are organized according to Belmont principles of respect for persons (e.g., when sensor-based data are valued above the subjective lived experiences of youth and their families), beneficence (e.g., with sensor data management and sharing), and justice (e.g., with sensor access and acceptability among minoritized pediatric populations). Recommendations include the need to increase transparency about the extent of subjective decision making with sensor data management. Without greater attention to the human factors involved in sensor research, ethical risks could outweigh the scientific promise of sensors, thereby negating their potential role in improving child health and care. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

A framework for understanding sources of bias in medication adherence research

The sources of bias in medication adherence research have not been comprehensively explored. We aimed to identify biases expected to affect adherence research and to develop a framework for mapping these onto the phases of adherence (initiation, implementation and discontinuation). A literature search was conducted, key papers were reviewed and a Catalogue of Bias was consulted. The specific biases related to adherence measurement and metrics were mapped onto the phases of adherence using a tabular matrix. Twenty-three biases were identified, of which 11 were specifically relevant to adherence measures and metrics. The mapping framework showed differences in the numbers and types of biases associated with each measure and metric while highlighting those common to many adherence study designs (e.g., unacceptability bias and apprehension bias). The framework will inform the design of adherence studies and the development of risk of bias tools for adherence research.

Estimating medication adherence from Electronic Health Records: comparing methods for mining and processing asthma treatment prescriptions

BACKGROUND

Medication adherence is usually defined as the extent of the agreement between the medication regimen agreed to by patients with their healthcare provider and the real-world implementation. Proactive identification of those with poor adherence may be useful to identify those with poor disease control and offers the opportunity for ameliorative action. Adherence can be estimated from Electronic Health Records (EHRs) by comparing medication dispensing records to the prescribed regimen. Several methods have been developed in the literature to infer adherence from EHRs, however there is no clear consensus on what should be considered the gold standard in each use case. Our objectives were to critically evaluate different measures of medication adherence in a large longitudinal Scottish EHR dataset. We used asthma, a chronic condition with high prevalence and high rates of non-adherence, as a case study.

METHODS

Over 1.6 million asthma controllers were prescribed for our cohort of 91,334 individuals, between January 2009 and March 2017. Eight adherence measures were calculated, and different approaches to estimating the amount of medication supply available at any time were compared.

RESULTS

Estimates from different measures of adherence varied substantially. Three of the main drivers of the differences between adherence measures were the expected duration (if taken as in accordance with the dose directions), whether there was overlapping supply between prescriptions, and whether treatment had been discontinued. However, there are also wider, study-related, factors which are crucial to consider when comparing the adherence measures.

CONCLUSIONS

We evaluated the limitations of various medication adherence measures, and highlight key considerations about the underlying data, condition, and population to guide researchers choose appropriate adherence measures. This guidance will enable researchers to make more informed decisions about the methodology they employ, ensuring that adherence is captured in the most meaningful way for their particular application needs.

Using a medication event monitoring system to evaluate self-report and pill count for determining treatment completion with self-administered, once-weekly isoniazid and rifapentine

BACKGROUND

Treatment completion is essential for the effectiveness of any latent tuberculosis infection (LTBI) regimen. The Tuberculosis Trials Consortium (TBTC) Study 33 (iAdhere) combined self-report and pill counts - standard of care (SOC) with a medication event monitoring system (MEMS) to determine treatment completion for 12-dose once-weekly isoniazid and rifapentine (3HP). Understanding the performance of SOC relative to MEMS can inform providers and suggest when interventions may be applied to optimize LTBI treatment completion.

METHOD

iAdhere randomized participants to directly observed therapy (DOT), SAT, or SAT with text reminders in Hong Kong, South Africa, Spain and the United States (U.S.). This post-hoc secondary analysis evaluated treatment completion in both SAT arms, and compared completion based on SOC with MEMS to completion based on SOC only. Treatment completion proportions were compared. Characteristics associated with discordance between SOC and SOC with MEMS were identified.

RESULTS

Overall 80.8% of 665 participants completed treatment per SOC, compared to 74.7% per SOC with MEMS, a difference of 6.1% (95%CI: 4.2%, 7.8%). Among U.S. participants only, this difference was 3.3% (95% CI: 1.8%, 4.9%). Differences in completion was 3.1% (95% CI: -1.1%, 7.3%) in Spain, and 36.8% (95% CI: 24.3%, 49.4%) in South Africa. There was no difference in Hong Kong.

CONCLUSION

When used for monitoring 3HP, SOC significantly overestimated treatment completion in U.S. and South Africa. However, SOC still provides a reasonable estimate of treatment completion of the 3HP regimen, in U.S., Spain, and Hong Kong.

Overcoming barriers to patient adherence: the case for developing innovative drug delivery systems

Poor medication adherence is a pervasive issue with considerable health and socioeconomic consequences. Although the underlying reasons are generally understood, traditional intervention strategies rooted in patient-centric education and empowerment have proved to be prohibitively complex and/or ineffective. Formulating a pharmaceutical in a drug delivery system (DDS) is a promising alternative that can directly mitigate many common impediments to adherence, including frequent dosing, adverse effects and a delayed onset of action. Existing DDSs have already positively influenced patient acceptability and improved rates of adherence across various disease and intervention types. The next generation of systems have the potential to instate an even more radical paradigm shift by, for example, permitting oral delivery of biomacromolecules, allowing for autonomous dose regulation and enabling several doses to be mimicked with a single administration. Their success, however, is contingent on their ability to address the problems that have made DDSs unsuccessful in the past.

Estimating the minimum antiretroviral adherence required for plasma HIV-1 RNA viral load suppression among people living with HIV who use unregulated drugs

OBJECTIVES

Owing to advances in antiretroviral therapy (ART), we re-examined minimum ART adherence levels necessary to achieve sustained HIV-1 viral load (VL) suppression among people with HIV who use drugs (PHIV-PWUD).

DESIGN AND METHODS

We used data from ACCESS, a community-recruited prospective cohort of PHIV-PWUD in Vancouver, Canada. We calculated adherence using the proportion of days of ART dispensed in the year before each VL measurement. We used generalized linear mixed-effects models to identify adherence- and ART regimen-related correlates of VL suppression (<200 copies/ml). We employed probit regression models and generated dose-response curves to estimate the minimum adherence level needed to produce VL suppression in 90% of measures, stratified by regimen and calendar-year.

RESULTS

Among 837 ART-exposed PHIV-PWUD recruited between 1996 and 2017, the overall estimated adherence level necessary to achieve 90% VL suppression was 93% (95% confidence interval [CI]: 90-96). This differed by regimen: 69% (95% CI: 45-92) for integrase inhibitor (INSTI)-, 96% (95% CI: 92-100) for boosted protease inhibitor (bPI)-, and 98% (95% CI: 91-100) for non-nucleoside reverse transcriptase inhibitor-based regimens. In multivariable analysis, INSTI-based regimens were positively associated with VL suppression (vs. bPIs), while un-boosted PIs and other regimens were negatively associated. We observed a decreasing temporal trend of estimated adherence necessary for 90% VL suppression, dropping to 64% (95% CI: 50-77) during 2016-2017.

CONCLUSION

Although high levels of ART adherence were necessary to achieve consistent VL suppression, the minimum necessary adherence levels decreased over time. Overall, INSTI-based regimens performed the best, suggesting that they should be preferentially prescribed to PHIV-PWUD.

Feasibility of a pharmacist-led symptom monitoring and management intervention to improve breast cancer endocrine therapy adherence

BACKGROUND

Adjuvant endocrine therapy (AET) for breast cancer reduces mortality, but one-third to one-half of patients discontinue it early or are nonadherent.

OBJECTIVE

We developed a pilot single-site study of patients with evidence of early nonadherence to AET to assess the feasibility of a novel, clinical pharmacist-led intervention targeting symptom and medication management.

METHODS

Patients with prescription fill records showing nonadherence were enrolled in a single-arm feasibility study. Automated reminders were sent by e-mail or text with a link to symptom monitoring assessments weekly for 1 month and monthly until 6 months. Clinical oncology pharmacists used guideline-based symptom management and other medication management tools to support adherence and ameliorate symptoms reported on the assessments. Patient-reported outcome assessments included physical, mental, and social health domains and self-efficacy to manage symptoms and medications. Feasibility outcomes included completion of symptom reports and pharmacist recommendations.

RESULTS

Of 19 participants who were nonadherent who enrolled and completed initial assessments, 18 completed all final study procedures, with 14 completing all assessments and no patient missing more than 3 assessments. All 18 participants reported at least one of 3 symptom types, and the majority reported attempting pharmacist recommendations. Patient-reported measures of physical, mental, and social health and self-efficacy improved, and 44% of the patients became adherent.

CONCLUSION

An intervention using pharmacists in an oncology practice to systematically monitor and manage symptoms shows promise to reduce symptoms, enhance support and self-efficacy, and improve adherence to AET.

Patient-Reported Outcomes as Endpoints in Clinical Trials of Kidney Transplantation Interventions

Patient-reported outcomes (PROs) that assess individuals' perceptions of life participation, medication adherence, disease symptoms, and therapy side effects are extremely relevant in the context of kidney transplantation. All PROs are potentially suitable as primary or secondary endpoints in interventional trials that aim to improve outcomes for transplant recipients. Using PRO measures (PROMs) in clinical trials facilitates assessment of the patient's perspective of their health, but few measures have been developed and evaluated in kidney transplant recipients; robust methodologies, which use validated instruments and established frameworks for reporting, are essential. Establishing a core PROM for life participation in kidney transplant recipients is a critically important need, which is being developed and validated by the Standardized Outcomes in Nephrology (SONG)-Tx Initiative. Measures involving electronic medication packaging and smart technologies are gaining traction for monitoring adherence, and could provide more robust information than questionnaires, interviews, and scales. This article summarizes information on PROs and PROMs that was included in a Broad Scientific Advice request on clinical trial design and endpoints in kidney transplantation. This request was submitted to the European Medicines Agency (EMA) by the European Society for Organ Transplantation in 2016. Following modifications, the EMA provided its recommendations in late 2020.

Methodological considerations on estimating medication adherence from self-report, electronic monitoring, and electronic healthcare databases using the TEOS framework

AIM

Measuring adherence to medication is complex due to the diversity of contexts in which medications are prescribed, dispensed, and used. The Timelines-Events-Objectives-Sources (TEOS) framework outlined a process to operationalize adherence. We aimed to develop practical recommendations for quantification of medication adherence using self-report (SR), electronic monitoring (EM), and electronic healthcare databases (EHD) consistent with the TEOS framework for adherence operationalization.

METHODS

An adherence methodology working group of the International Society for Medication Adherence (ESPACOMP) analysed implications of the process of medication adherence for all data sources and discussed considerations specific to SR, ED, and EHD regarding the information available on the prescribing, dispensing, recommended and actual use timelines, the four events relevant for distinguishing the adherence phases, the study objectives commonly addressed with each type of data, and the potential sources of measurement error and quality criteria applicable.

RESULTS

Four key implications for medication adherence measurement are common to all data sources: adherence is a comparison between two series of events (recommended and actual use); it refers to one or more specific medication(s); it applies to regular repeated events coinciding with known recommended dosing; and it requires separate measurement of the three adherence phases for a complete picture of patients' adherence. We propose recommendations deriving from these statements, and aspects to be considered in study design when measuring adherence with SR, EM and EHD using the TEOS framework.

CONCLUSION

The quality of medication adherence estimates is the result of several design choices that may optimize the data available.

Effectiveness of a medication adherence management intervention in a community pharmacy setting: a cluster randomised controlled trial

BACKGROUND

Non-adherence to medications continues to be a burden worldwide, with significant negative consequences. Community pharmacist interventions seem to be effective at improving medication adherence. However, more evidence is needed regarding their impact on disease-specific outcomes. The aim was to evaluate the impact of a community pharmacist-led adherence management intervention on adherence and clinical outcomes in patients with hypertension, asthma and chronic obstructive pulmonary disease (COPD).

METHODS

A 6-month cluster randomised controlled trial was conducted in Spanish community pharmacies. Patients suffering from hypertension, asthma and COPD were recruited. Patients in the intervention group received a medication adherence management intervention and the control group received usual care. The intervention was based on theoretical frameworks for changing patient behaviour. Medication adherence, disease-specific outcomes (Asthma Control Questionnaire (ACQ) scores, Clinical COPD Questionnaire (CCQ) scores and blood pressure levels) and disease control were evaluated. A multilevel regression model was used to analyse the data.

RESULTS

Ninety-eight pharmacies and 1186 patients were recruited, with 1038 patients completing the study. Patients receiving the intervention had an OR of 5.12 (95% CI 3.20 to 8.20, p<0.05) of being adherent after the 6 months. At the end of the study, patients in the intervention group had lower diastolic blood pressure levels (mean difference (MD) -2.88, 95% CI -5.33 to -0.43, p=0.02), lower CCQ scores (MD -0.50, 95% CI -0.82 to -0.18, p<0.05) and lower ACQ scores (MD -0.28, 95% CI -0.56 to 0.00, p<0.05) when compared with the control group.

CONCLUSIONS

A community pharmacist-led medication adherence intervention was effective at improving medication adherence and clinical outcomes in patients suffering from hypertension, asthma and COPD. Future research should explore the implementation of these interventions in routine practice.

TRIAL REGISTRATION NUMBER

ACTRN12618000410257.

Leveraging Digital Medicine to Support Providers and Their Patients in Managing Serious Mental Illness

Recent national statistics show that an estimated 11.2 million American adults live with serious, chronic forms of mental illness. The burden of mental illness is considerable for these individuals, their families, and communities. Effective medical treatment for serious mental illness (SMI) requires a patient-centered approach that engages patients in shared decision-making and supports the therapeutic alliance. Information regarding medication-taking behavior is essential for making treatment decisions, particularly in the instance of suboptimal therapeutic response. However, the evidence suggests that the probability of nonconformity with prescribed medication is elevated for individuals with SMI and that clinicians often overestimate their patients' adherence to medication-taking behaviors. In patients with SMI, unidentified problems with adherence may lead to unnecessary changes in treatment regimen and increased rates of hospitalization. Although various approaches have been used to assess medication ingestion with greater accuracy, none are without limitation. The growing field of digital medicine has introduced tools that engage patients for clinical purposes, gather and organize clinical data, and help measure care quality. Physician surveys show an appreciable increase in physician adoption of digital clinical tools, and studies suggest that a significant population of patients with SMI own and are comfortable using digital devices and tools. Digital tools designed to help people with SMI have the potential to transform the support and care available to people with mental health disorders, bridging a technology gap in mental health services.

Impact of a Medication Adherence Packaging Service on Patient-Centered Outcomes at an Independent Community Pharmacy

The purpose of this project was to evaluate the impact of a comprehensive medication adherence packaging (RxMAP) service on patient medication-taking behaviors and patient-centered outcomes. Adult patients who utilized a single independent community pharmacy, enrolled in the RxMAP service for at least two consecutive cycles, and managed their own medications were eligible. The RxMAP service consists of multi-dose blister packaging in 28-day cycles, medication synchronization, monthly touchpoint calls, and delivery/mailing. A 13-item telephonic survey was administered, and patients’ verbal responses were captured by audio-recording and detailed note taking. Descriptive statistics were used to quantify the results and illustrative quotes representing the interview domains were selected. There were 42 patients who completed the survey: 88% reported they missed fewer doses compared to before using RxMAP; 71% were more likely to take their medications on time each day; 86% were more confident with managing their medications; and 74% were more independent. Finally, 64% of patients stated their overall quality of life was better now compared to before using the packaging service. These results demonstrate that medication adherence packaging services can positively impact patients’ medication-taking behaviors, increase their confidence in medication management, and improve perceived quality of life.

TEOS: A framework for constructing operational definitions of medication adherence based on Timelines-Events-Objectives-Sources

AIMS

Managing adherence to medications is a priority for health systems worldwide. Adherence research is accumulating, yet the quality of the evidence is reduced by various methodological limitations. In particular, the heterogeneity and low accuracy of adherence measures have been highlighted in many literature reviews. Recent consensus-based guidelines advise on best practices in defining adherence (ABC) and reporting of empirical studies (EMERGE). While these guidelines highlight the importance of operational definitions in adherence measurement, such definitions are rarely included in study reports. To support researchers in their measurement decisions, we developed a structured approach to formulate operational definitions of adherence.

METHODS

A group of adherence and research methodology experts used theoretical, methodological and practical considerations to examine the process of applying adherence definitions to various research settings, questions and data sources. Consensus was reached through iterative review of discussion summaries and framework versions.

RESULTS

We introduce TEOS, a four-component framework to guide the operationalization of adherence concepts: (1) describe treatment as four simultaneous interdependent timelines (recommended and actual use, conditional on prescribing and dispensing); (2) locate four key events along these timelines to delimit the three ABC phases (first and last recommended use, first and last actual use); (3) revisit study objectives and design to fine-tune research questions and assess measurement validity and reliability needs, and (4) select data sources (e.g., electronic monitoring, self-report, electronic healthcare databases) that best address measurement needs.

CONCLUSION

Using the TEOS framework when designing research and reporting explicitly on these components can improve measurement quality.

Statistical considerations for medication adherence research

OBJECTIVE

Medication non-adherence is a widespread problem and has been known to be associated with worse health outcomes and increased healthcare costs. Although many measures of adherence have been developed, their usage is not consistent across studies. Furthermore, statistical methods for analyzing adherence measures have not been rigorously evaluated.

METHODS

Using Proportion of Days Covered (PDC), a commonly used adherence measure, we examine the variability inherent to study inclusion criteria and several variations of the PDC calculation method using a motivating data example. We illustrated via sensitivity analyses the potential for flawed inference when modeling PDC as an outcome measure. We also performed simulation studies to investigate the statistical properties of three statistical models: logistic regression, negative binomial, and ordinal logistic regression models.

RESULTS

Our sensitivity analysis showed that parameter estimates can vary greatly depending on the rules for determining the study end date in calculating PDC, or the minimum number of fills in defining the cohort. In simulation studies, logistic regression had lower power than ordinal logistic and negative binomial regression models. Naivete to treatment was an important predictor of adherence and omitting it from statistical models can lead to inflated type I errors.

CONCLUSIONS

We discourage dichotomizing adherence data as it results in low power. The negative binomial model offers advantages in modeling adherence data, as it avoids the problematic use of a ratio in regression models. The ordinal logistic regression is robust to distributional assumptions with greater power, but naivete to treatment should be adjusted to reserve type I error rate. We also provide a recommendation for defining the observation window in calculating PDC.

Antiretroviral Adherence Level Necessary for HIV Viral Suppression Using Real-World Data

BACKGROUND

A benchmark of near-perfect adherence (≥95%) to antiretroviral therapy (ART) is often cited as necessary for HIV viral suppression. However, given newer, more effective ART medications, the threshold for viral suppression may be lower. We estimated the minimum ART adherence level necessary to achieve viral suppression.

SETTINGS

The Patient-centered HIV Care Model demonstration project.

METHODS

Adherence to ART was calculated using the proportion of days covered measure for the 365-day period before each viral load test result, and grouped into 5 categories (<50%, 50% to <80%, 80% to <85%, 85% to <90%, and ≥90%). Binomial regression analyses were conducted to determine factors associated with viral suppression (HIV RNA <200 copies/mL); demographics, proportion of days covered category, and ART regimen type were explanatory variables. Generalized estimating equations with an exchangeable working correlation matrix accounted for correlation within subjects. In addition, probit regression models were used to estimate adherence levels required to achieve viral suppression in 90% of HIV viral load tests.

RESULTS

The adjusted odds of viral suppression did not differ between persons with an adherence level of 80% to <85% or 85% to <90% and those with an adherence level of ≥90%. In addition, the overall estimated adherence level necessary to achieve viral suppression in 90% of viral load tests was 82% and varied by regimen type; integrase inhibitor- and nonnucleoside reverse transcriptase inhibitor-based regimens achieved 90% viral suppression with adherence levels of 75% and 78%, respectively.

CONCLUSIONS

The ART adherence level necessary to reach HIV viral suppression may be lower than previously thought and may be regimen-dependent.

Adherence with brand versus generic bisphosphonates among osteoporosis patients: a new-user cohort study in the French National Healthcare Insurance database

Several studies documented declines in treatment adherence with generic forms of oral bisphosphonates in osteoporosis compared to branded forms, while others did not support this relation. Our aim was to compare medication adherence with brand versus generic forms of oral bisphosphonates. A new-user cohort study was conducted using routinely collected administrative and healthcare data linked at the individual level extracted from a nationwide representative sample of the French National Healthcare Insurance database. We included all patients aged 50 and older, new users of oral bisphosphonates for primary osteoporosis between 01/01/2009 and 31/12/2015. Two components of adherence were measured: implementation (continuous multiple-interval measure of medication availability version 7; CMA7) and persistence (time to discontinuation). The sample was composed of 1,834 in the "brand bisphosphonate" group and 1,495 patients in the "generic bisphosphonate" group. Initiating oral bisphosphonate treatment with brand was associated with a higher risk of discontinuation within 12 months (Hazard Ratio = 1.08; 95%CI = [1.02;1.14]). The risk of good implementation (CMA7 ≥ 0.90) was significantly lower in "brand bisphosphonate" group (Risk Ratio = 0.90; 95%CI = [0.85; 0.95]). We did not find any evidence to support the hypothesis of a lower adherence to generic bisphosphonates. In fact, prescribing of generic bisphosphonates led to a higher persistence rate and to better implementation at 1 year.

Refill Adherence Measures and Its Association with Economic, Clinical, and Humanistic Outcomes Among Pediatric Patients: A Systematic Review

Although refill adherence measures (RAMs) are widely reviewed on their use among adult patients, existing reviews on adherence among children have only focused on self-report measures and electronic monitoring. Hence, this systematic review aims to examine the use of RAMs and their association with economic, clinical, and humanistic outcomes (ECHO) among pediatric patients. A literature search was conducted in Pubmed, Embase, CINAHL, and PsycINFO. Studies published in English involving subjects aged ≤18 years were included if RAMs were analyzed with ECHO. Of the 35 included studies, the majority (n = 33) were conducted in high-income countries. Asthma was the most common condition (n = 9) studied. Overall, 60.6% of 33 clinical outcomes reported among 22 studies was positive (improved clinical outcomes with improved adherence), while 21.9% of 32 economic outcomes reported among 16 studies was positive (reduced healthcare utilization or cost outcomes with improved adherence). Only four studies evaluated the relationship of adherence with 11 humanistic outcomes, where the majority (72.7%) were considered unclear. RAMs are associated with ECHO and can be considered for use in the pediatric population. Future studies could explore the use of RAMs in low-income countries, and the association of RAMs with quality of life.

Self-Report for Measuring and Predicting Medication Adherence: Experts' Experience in Predicting Adherence in Stable Psychiatric Outpatients and in Pharmacokinetics

THE PROBLEM

Poor adherence to appropriately prescribed medication is a global challenge for psychiatrists.

PRIOR STUDIES

Measuring adherence is complicated. In our recent three-country naturalistic study including more than 1000 patients and their adherence to multiple medication prescriptions at the same time, patients' self-report of adherence to each specific drug was the only practical option for measuring adherence. Systematic literature reviews provide inconsistent results for sociodemographic, clinical and medication variables as predictors of adherence to psychiatric drugs. Our studies over the last 10 years in relatively stable psychiatric outpatients have shown that some self-reported health beliefs had consistent, strong effects and a better predictive role. Three dimensions of these health beliefs are characteristics of the individual: 1) attitudes toward psychiatric medication such as pharmacophobia (fear of taking drugs or medicines), 2) health locus of control (the belief patients have about who or what agent determines the state of their health), 3) psychological reactance (an emotional reaction in direct contradiction to rules or regulations that threaten or suppress certain freedoms in behavior). They can be measured by the Patient Health Beliefs Questionnaire on Psychiatric Treatment. The attitude toward each specific medication can be measured by the necessity-concern framework and summarized as the presence or absence of skepticism about that drug. After 25 years conducting pharmacokinetic studies in psychiatric drugs, particularly antipsychotics, we have limited understanding of how to use blood levels to predict the effects of non-adherence or to establish it.

EXPERT OPINION ON FUTURE STUDIES

Future studies to predict adherence should include the inpatient setting and explore insight. Studying the pharmacokinetics associated with non-adherence in each psychiatric drug is a major challenge. Medication adherence is a complex and dynamic process changing over time in the same patient. Personalizing adherence using psychological or pharmacological variables are in their initial stages.

Using Dispensing Data to Evaluate Adherence Implementation Rates in Community Pharmacy

Background: Medication non-adherence remains a significant problem for the health care system with clinical, humanistic and economic impact. Dispensing data is a valuable and commonly utilized measure due accessibility in electronic health data. The purpose of this study was to analyze the changes on adherence implementation rates before and after a community pharmacist intervention integrated in usual real life practice, incorporating big data analysis techniques to evaluate Proportion of Days Covered (PDC) from pharmacy dispensing data.

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. Included patients received a pharmacist-led medication adherence intervention and had dispensing records before and after the intervention. As a measure of adherence implementation, PDC was utilized. Analysis of the database was performed using SQL and Python.

Results: Three months after the pharmacist intervention there was an increase on average PDC from 50.2% (SD: 30.1) to 66.9% (SD: 29.9) for rosuvastatin, from 50.8% (SD: 30.3) to 68% (SD: 29.3) for irbesartan and from 47.3% (SD: 28.4) to 66.3% (SD: 27.3) for desvenlafaxine. These rates declined over 12 months to 62.1% (SD: 32.0) for rosuvastatin, to 62.4% (SD: 32.5) for irbesartan and to 58.1% (SD: 31.1) for desvenlafaxine. In terms of the proportion of adherent patients (PDC >= 80.0%) the trend was similar, increasing after the pharmacist intervention from overall 17.4 to 41.2% and decreasing after one year of analysis to 35.3%.

Conclusion: Big database analysis techniques provided results on adherence implementation over 2 years of analysis. An increase in adherence rates was observed after the pharmacist intervention, followed by a gradual decrease over time. Enhancing the current intervention using an evidence-based approach and integrating big database analysis techniques to a real-time measurement of adherence could help community pharmacies improve and sustain medication adherence.

Side Effects, Self-Management Activities, and Adherence to Oral Anticancer Agents

PURPOSE

There are growing concerns about patients' adherence to oral anticancer agents (OAAs), and the need for patients to engage in self-management of OAA-related side effects. We assessed associations among adherence, severity of side effects, and effectiveness of self-management of side effects in patients taking capecitabine.

METHODS

Adherence to capecitabine at 6 weeks was measured by the Medication Event Monitoring System among 50 patients with gastrointestinal cancers. Severity of side effects related to capecitabine and effectiveness of self-management of side effects were captured using the Modified Self-Care Diary at the time of enrollment and weekly for 6 weeks. Spearman's correlation, Mann-Whitney U-tests, and multiple linear regression were conducted, p<0.05.

RESULTS

Overall mean adherence rate was 85.4±14.1%. Adherence rate was not significantly correlated to the mean severity of total side effects at any time point and was correlated with the mean effectiveness of self-management of total side effects only at week 2 (rho=0.29, p=0.04). However, adherence rate was associated with the mean severity of one specific side effect, diarrhea, at 6 weeks (rho=0.36, p=0.01) and marginally correlated to the mean effectiveness of self-management of diarrhea at 6 weeks (rho=0.28, p=0.05). Mean severity of diarrhea at 6 weeks was an independent predictor of adherence rate (b=4.97, p=0.01), with the control of age (b=0.52, p=0.002), number of outpatient medications (b=1.12, p=0.007), health literacy (b=2.53, p=0.04), diagnosis of colorectal cancer (b=11.6, p=0.03), and capecitabine in combination with other chemotherapies (b=16.8, p=0.001) in the model.

CONCLUSION

This pilot study suggests ongoing examination of both severity and effectiveness of self-management of side effects in future studies of adherence to OAAs is merited. There is a need for future studies with larger sample sizes that explore the complex relationships among adherence, severity of side effects, and effectiveness of self-management of side effects in OAA therapy.

Operationalization and validation of a novel method to calculate adherence to polypharmacy with refill data from the Australian pharmaceutical benefits scheme (PBS) database

Background

Electronic health care data contain rich information on medicine use from which adherence can be estimated. Various measures developed with medication claims data called for transparency of the equations used, predominantly because they may overestimate adherence, and even more when used with multiple medications. We aimed to operationalize a novel calculation of adherence with polypharmacy, the daily polypharmacy possession ratio (DPPR), and validate it against the common measure of adherence, the medication possession ratio (MPR) and a modified version (MPR_m).

Methods

We used linked health data from the Australian Pharmaceutical Benefits Scheme and Western Australian hospital morbidity dataset and mortality register. We identified a strict study cohort from 16,185 patients aged ≥65 years hospitalized for myocardial infarction in 2003–2008 in Western Australia as an illustrative example. We applied iterative exclusion criteria to standardize the dispensing histories according to previous literature. A SAS program was developed to calculate the adherence measures accounting for various drug parameters.

Results

The study cohort was 348 incident patients (mean age 74.6±6.8 years; 69% male) with an admission for myocardial infarction who had cardiovascular medications over a median of 727 days (range 74 to 3,798 days) prior to readmission. There were statins (96.8%), angiotensin converting enzyme inhibitors (88.8%), beta-blockers (85.6%), and angiotensin receptor blockers (13.2%) dispensed. As expected, observed adherence values were higher with mean MPR (median 89.2%; Q₁: 73.3%; Q_3: 104.6%) than mean MPR_m (median 82.8%; Q₁: 68.5%; Q_3: 95.9%). DPPR values were the most narrow (median 83.8%; Q₁: 70.9%; Q_3: 96.4%). Mean MPR and DPPR yielded very close possession values for 37.9% of the patients. Values were similar in patients with longer observation windows. When the traditional threshold of 80% was applied to mean MPR and DPPR values to signify the threshold for good adherence, 11.6% of patients were classified as good adherers with the mean MPR relative to the DPPR.

Conclusion

In the absence of transparent and standardized equations to calculate adherence to polypharmacy from refill databases, the novel DPPR algorithm represents a valid and robust method to estimate medication possession for multi-medication regimens.

Innovation at the Intersection of Clinical Trials and Real-World Data Science to Advance Patient Care

While efficacy and safety data collected from randomized clinical trials are the evidentiary standard for determining market authorization, this alone may no longer be sufficient to address the needs of key stakeholders (regulators, providers, and payers) and guarantee long-term success of pharmaceutical products. There is a heightened interest from stakeholders on understanding the use of real-world evidence (RWE) to substantiate benefit-risk assessment and support the value of a new drug. This review provides an overview of real-world data (RWD) and related advances in the regulatory framework, and discusses their impact on clinical research and development. A framework for linking drug development decisions with the value proposition of the drug, utilizing pharmacokinetic-pharmacodynamic-pharmacoeconomic models, is introduced. The summary presented here is based on the presentations and discussion at the symposium entitled Innovation at the Intersection of Clinical Trials and Real-World Data to Advance Patient Care at the American Society for Clinical Pharmacology and Therapeutics (ASCPT) 2017 Annual Meeting.

Advancing the Science and Practice of Medication Adherence

Medication adherence remains a significant unmet challenge for optimizing patient outcomes. Recent advances in the conceptualization, measurement, and support of medication adherence offer fresh opportunities to make a meaningful impact on adherence-related behavior and outcomes. These advances emphasize the multifaceted and dynamic nature of medication adherence, provide novel methods for monitoring medication adherence in clinical care, and articulate a set of multilevel strategies to more effectively improve and sustain medication adherence. Here, we offer recommendations for how clinicians can better engage with, and benefit from, these innovations to improve patient medication adherence and associated treatment outcomes.

Systematic literature review on patterns of pharmacological treatment and adherence among patients with bipolar disorder type I in the USA

BACKGROUND

Bipolar disorder type I (BD-I) is a chronic condition characterized by mania episodes followed by syndromic recovery periods, usually permeated by depressive symptoma-tology and recurring acute manic episodes. It requires long-term pharmacological treatment; thus, it is critical to understand the patterns of drug therapy use and medication compliance to better plan health care policies and needs. This systematic literature review aims to study these data among patients with BD-I in the USA, focusing on medications to treat mania.

METHODS

Articles published in the last 10 years to October 2016 were searched on MEDLINE and Embase. Studies on patterns of drug therapy, concordance of prescription with clinical practice guidelines, and adherence and persistence with pharmacological treatments for BD-I in the USA under observational conditions, with focus on treatments for mania, were selected.

RESULTS

Treatment prevalence for BD-I is low in the USA, with the most current study showing a 46% 12-month rate. There is a lack of studies addressing the use of long-acting injectable (LAI) antipsychotics. Second-generation antipsychotics (SGAs) have been used by nearly all patients receiving oral antipsychotics since the 2000s. However, 30%-60% of individuals with BD do not receive appropriate treatment, and adherence to oral therapies is poor, with medication possession ratios ≥80% seen in only approximately 60% of patients. For persistence rates, results suggest that treatment duration is short for a condition with recommendation for at least 6 months of maintenance therapy. Literature indicates that LAI SGAs may be related to better adherence and persistence.

CONCLUSION

There is a need for studies addressing specifically patterns of therapy and adherence to pharmacological treatment in BD-I patients in the USA to better understand the value of current standards, and an urgent need to improve the rates of adherence and persistence to BD-I pharmacotherapy and to increase the understanding of LAI SGAs' potential to address this issue.