Engagement of medication users in the development and implementation of digital medication adherence technologies: a multi-stakeholder study.

BACKGROUND: This study aims to create a comprehensive framework for the development and implementation of digital medication adherence technologies (DMATech), focusing on critical stages where engagement of medication users (MU) is considered meaningful, i.e. adds significant value, as agreed upon by participating stakeholders. METHODS: Through a literature review and expert consensus, a framework was outlined covering key DMATech development and implementation phases and steps. An in-person workshop with MU representatives and adherence experts, using the Nominal Group Technique, further refined these stages for MU engagement. RESULTS: The DMATech framework included three phases: 'Innovation,' 'Research and Development,' and 'Launch and Implementation,' each encompassing multiple steps. The workshop, attended by five MU representatives and nine adherence experts, identified critical stages for MU input including context analysis, ideation, proof of concept, prototype creation, DMATech's iteration, critical evaluation, healthcare implementation, real-world assessment, and improvement. Nevertheless, there was a divergence of consensus regarding the importance of MUs engagement in regulatory, financial, and marketing aspects. CONCLUSIONS: This study provides a holistic framework for DMATech development and implementation and underscores the necessity of MU engagement at various stages. Modes of MU engagement cannot be generalized; a case-by-case evaluation of engagement strategies is essential.

The impacts of undetected nonadherence in phase II, III and post-marketing clinical trials: An overview.

AIMS: This research aims to provide an overview of the consequences of undiagnosed nonadherence (noninitiation, suboptimal implementation, nonpersistence) in randomized clinical trials (RCTs). METHODS: This research was conducted by combining a literature review and qualitative semistructured interviews with key opinion leaders. Based on this groundwork, the consequences of undiagnosed nonadherence in RCTs were summarized and reported in a figure. This study focused on phases II, III and post-marketing in ambulatory settings across a variety of therapeutic areas and indications. RESULTS: Various consequences of nonadherence in RCTs were investigated. In phase II, drug efficacy may be underestimated, variability in the outcomes may be high and a distorted picture of side effects could be reported, resulting in an uncertain impression of the investigational product's profile and complicating decision-making. The sponsor may need to increase the sample size of the upcoming phase III study to improve its power, representing additional costs, or even terminate the study. In phase III, similar phenomena may be observed, making demonstration of efficacy to the regulatory bodies more difficult. Lastly, after commercialization, a distortion in pharmacometrics may occur: the drug may underperform, prescriptions may be refilled less often than expected or extra expenses may be incurred by the payers. This can result in post-marketing dose reduction, new competitors coming into the market and, eventually, product withdrawal. CONCLUSIONS: This research highlighted the many potential adverse consequences of undiagnosed nonadherence in RCTs, including additional costs. Collecting accurate data appeared to be crucial for decision-making throughout the drug development process.

Treatment Adherence and Adherence Patterns of Tofacitinib and Self-Injectable TNFi Use in People with Rheumatoid Arthritis.

OBJECTIVE: To assess tofacitinib and self-injectable tumor necrosis factor inhibitor (TNFi) adherence using the Medication Event Monitoring System (MEMS) and characterize association with adherence in patients with rheumatoid arthritis (RA). METHODS: Eligible patients were enrolled from the Forward Databank within 6 months of initiating tofacitinib or injectable TNFi or from participating clinics where these were first prescribed. MEMS caps and patient diaries were used to compile dosing over 9 months. Demographics and disease characteristics were collected every 6 months, and the Beliefs about Medicines Questionnaire only at baseline. Adherence along with its components, initiation, implementation, and persistence, were calculated. RESULTS: Of the 112 consented to participate, 82 (73%) remained in the final analysis with recruitment from clinics 47 (57%) and Forward 35 (43%). Sixty-two (76%) initiated tofacitinib with 87% taking it quaque die and twenty (24%) TNFi. At 9 months, 77% of tofacitinib were persistent versus 70% for TNFi (P = 0.65), and implementation was similar (0.84 vs. 0.82; P = 0.57). In multivariable models, increased baseline patient global assessment was consistently associated with discontinuation (hazard ratio 1.31 [1.07-1.61]). There was increased adherence to methotrexate (MTX) when taking tofacitinib that led to higher combined adherence for tofacitinib than TNFi (0.81 vs. 0.69; P = 0.03), but no significant differences remained in multivariable models. In sensitivity analysis, consistent morning intake for tofacitinib and evening intake for MTX was associated with improved adherence. CONCLUSION: We found no statistical differences in adherence between patients with RA initiating tofacitinib and self-injectable TNFi, although 15% to 30% were nonadherent. Concomitant MTX, patient global assessment, and a consistent time of day intake were associated with adherence.

The Importance of Assessing Drug Exposure and Medication Adherence in Evaluating Investigational Medications: Ensuring Validity and Reliability of Clinical Trial Results.

The objective of this current opinion paper is to draw global attention to medication adherence, emphasizing its crucial role in drug trials. Frequently, trialists lean on traditional approaches to assess medication adherence, which, while comfortable, may only reveal what trialists desire rather than offering the essential insights needed for informed decision making in drug development. Understanding drug exposure and medication adherence is paramount when evaluating the effectiveness and safety of investigational medications. Without a comprehensive understanding of how patients adhere to their prescribed treatment regimens, the integrity and dependability of clinical trial results can be compromised. This paper emphasizes the need for measures that accurately and reliably assess medication intake behaviors, enabling the differentiation between minor dosing errors and significant deviations that may impact the drug's efficacy and safety. Accurate knowledge of drug exposure empowers researchers to make informed decisions, identify potential confounding factors, and appropriately interpret study outcomes, ultimately ensuring the validity and reliability of the research findings. By prioritizing drug exposure assessment and medication adherence measurement, clinical trials can enhance their scientific rigor, contribute to more accurate evaluations of investigational medications, and ultimately speed up the development process.

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.

Translation and cross-cultural adaptation of the ABC taxonomy for medication adherence into Portuguese - Updating patients into people.

BACKGROUND: The Ascertaining Barriers to Compliance (ABC) taxonomy for describing medication adherence was created in 2012, aiming to standardize terms and definitions in research and practice. The taxonomy comprises seven terms and definitions. Originally developed in English, subsequently translated into French and German, is currently being translated to Portuguese, Spanish, Czech, Romanian and Italian, aiming to promote its global use and overcome cultural barriers. OBJECTIVES: To cross-culturally translate the ABC taxonomy into Portuguese for Portugal and Brazil. METHODS: A systematic literature search was conducted to identify published taxonomy terms and definitions in Portuguese, and to identify panelists in medication adherence. Initial mapping of terms and definitions retrieved was scrutinized by the research team to build an e-survey. The e-survey was piloted and then sent to panelists in both countries seeking consensus using a three-round Delphi method. Consensus was defined as ≥ 85% for round 1 and ≥ 75% for round 2. Terms with agreement <10% were dropped between rounds. In round 3, terms and definitions reaching agreement between 50 and 75% were classified as moderate consensus,>75-95% as consensus and >95% as strong consensus. RESULTS: A total of 778 studies were identified and 84 included, enabling the extraction of 154 terms and 32 definitions. In round 1, 164 panelists participated, 115 in round 2 and 99 in the round 3. Consensus was achieved in both countries for all seven terms and definitions, although with varying intensity of agreement. The term "Management of adherence" and the definition of "Discontinuation" obtained moderate consensus in both countries. CONCLUSIONS: A unified and unique ABC taxonomy in Portuguese was possible to develop for use in Portugal and in Brazil. Its use will harmonize and standardize the terms and definitions used in clinical practice and research.

Evaluating Objective Metrics of habit strength for taking medications.

Habit strength for taking medication is associated with medication adherence. However, habit strength is typically measured via self-reports, which have limitations. Objective sensors may provide advantages to self-reports. To evaluate whether habit-strength metrics derived from objective sensor data (MEMS® Caps; AARDEX Group) are associated with self-reported habit strength and adherence (objective and self-reported) and whether objective and self-reported habit strength are independently associated with adherence. Patients (N = 79) on oral medications for type 2 diabetes completed self-reports of habit strength and medication adherence and used MEMS® Caps to take their prescribed medication for one month. MEMS® Caps data were used to create five objective metrics of habit strength (e.g., individual-level variance in pill timing) and quantify medication adherence (% days correct dosing). Consistency in behavior from week to week (versus across each day) had the greatest association with self-reported habit strength (r(78) = 0.29, p = 0.01), self-reported adherence (r(78) = 0.32, p = 0.005), and objective adherence (r(78) = 0.61, p < 0.001). Objective and self-reported habit strength were independently associated with adherence. Weekly pill-timing consistency may be more useful than daily pill-timing consistency for predicting adherence and understanding patients' medication-taking habits. Self-reports and objective metrics of habit strength may be measuring different constructs, warranting further research.

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

AIMS: 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, EM 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.

Analysing breast cancer survivors' acceptance profiles for using an electronic pillbox connected to a smartphone application using Seintinelles, a French community-based research tool.

Introduction: Up to 50% of breast cancer (BC) survivors discontinue their adjuvant endocrine therapy (AET) before the recommended 5 years, raising the issue of medication non-adherence. eHealth technologies have the potential to support patients to enhance their medication adherence and may offer an effective way to complement the healthcare. In order for eHealth technologies to be successfully implemented into the healthcare system, end-users need to be willing and accepting to use these eHealth technologies. Aim: This study aims to evaluate the current usability of eHealth technologiesin and to identify differences in BC SURVIVORS BC survivors accepting a medication adherence enhancing eHealth technology to support their AET to BC survivors that do not accept such a medication adherence enhancing eHealth technology. Methods: This study was conducted in 2020 including volunteering BC survivors belonging to the Seintinelles Association. Eligible participants were women, diagnosed with BC within the last 10 years, and been exposed to, an AET. Univariable and multivariable logistic regression analyses were performed to investigate medication adherence enhancing eHealth technology acceptance profiles among BC survivors. The dependent variable was defined as acceptance of an electronic pillbox connected to a smartphone application (hereafter: medication adherence enhancing eHealth technology). Results: Overall, 23% of the participants already use a connected device or health application on a regular basis. The mean age of the participants was 52.7 (SD 10.4) years. In total, 67% of 1268 BC survivors who participated in the survey declared that they would accept a medication adherence enhancing eHealth technology to improve their AET. BC survivors accepting a medication adherence enhancing eHealth technology for their AET, are younger (OR = 0.97, 95% CI [0.95; 0.98]), do take medication for other diseases (OR = 0.31, 95% CI [0.13; 0.68]), already use a medication adherence enhancing eHealth technology or technique (OR = 1.74, 95% CI [1.06; 2.94]) and are willing to possess or currently possess one or more connected devices or health applications (OR = 2.89, 95% CI [2.01; 4.19]). Conclusion: Understanding acceptance profiles of BC survivors is fundamental for conceiving an effective eHealth technology enhancing AET among BC survivors. Hence, such profiling will foster the development of personalized medication adherence enhancing eHealth technology.

Delta T, a Useful Indicator for Pharmacy Dispensing Data to Monitor Medication Adherence.

INTRODUCTION: Calculating patients' medication availability from dispensing or refill data is a common method to estimate adherence. The most often used measures, such as the medication possession ratio (MPR), average medication supplies over an arbitrary period. Averaging masks the variability of refill behavior over time. GOAL: To derive a new absolute adherence estimate from dispensing data. METHOD: Dispensing histories of patients with 19 refills of direct oral anticoagulants (DOAC) between 1 January 2008 and 31 December 2017 were extracted from 39 community pharmacies in Switzerland. The difference between the calculated and effective refill day (ΔT) was determined for each refill event. We graphed ΔT and its dichotomized version (dΔT) against the MPR, calculated mean ΔT and mean dΔT per refill, and applied cluster analysis. RESULTS: We characterized 2204 refill events from 116 DOAC patients. MPR was high (0.975 ± 0.129) and showed a positive correlation with mean ΔT. Refills occurred on average 17.8 ± 27.9 days "too early", with a mean of 75.8 ± 20.2 refills being "on time". Four refill behavior patterns were identified including constant gaps within or at the end of the observation period, which were critical. CONCLUSION: We introduce a new absolute adherence estimate ΔT that characterizes every refill event and shows that the refill behavior of DOAC patients is dynamic.

Emerging Therapeutics, Technologies, and Drug Development Strategies to Address Patient Nonadherence and Improve Tuberculosis Treatment.

Imperfect medication adherence remains the biggest predictor of treatment failure for patients with tuberculosis. Missed doses during treatment lead to relapse, tuberculosis resistance, and further spread of disease. Understanding individual patient phenotypes, population pharmacokinetics, resistance development, drug distribution to tuberculosis lesions, and pharmacodynamics at the site of infection is necessary to fully measure the impact of adherence on patient outcomes. To decrease the impact of expected variabilityin drug intake on tuberculosis outcomes, an improvement in patient adherence and new forgiving regimens that protect against missed doses are needed. In this review, we summarize emerging technologies to improve medication adherence in clinical practice and provide suggestions on how digital adherence technologies can be incorporated in clinical trials and practice and the drug development pipeline that will lead to more forgiving regimens and benefit patients suffering from tuberculosis.

Persistence as a Robust Indicator of Medication Adherence-Related Quality and Performance.

Medication adherence is a priority for health systems worldwide and is widely recognised as a key component of quality of care for disease management. Adherence-related indicators were rarely explicitly included in national health policy agendas. One barrier is the lack of standardised adherence terminology and of routine measures of adherence in clinical practice. This paper discusses the possibility of developing adherence-related performance indicators highlighting the value of measuring persistence as a robust indicator of quality of care. To standardise adherence and persistence-related terminology allowing for benchmarking of adherence strategies, the European Ascertaining Barriers for Compliance (ABC) project proposed a Taxonomy of Adherence in 2012 consisting of three components: initiation, implementation, discontinuation. Persistence, which immediately precedes discontinuation, is a key element of taxonomy, which could capture adherence chronology allowing the examination of patterns of medication-taking behaviour. Advances in eHealth and Information Communication Technology (ICT) could play a major role in providing necessary structures to develop persistence indicators. We propose measuring persistence as an informative and pragmatic measure of medication-taking behaviour. Our view is to develop quality and performance indicators of persistence, which requires investing in ICT solutions enabling healthcare providers to review complete information on patients' medication-taking patterns, as well as clinical and health outcomes.

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.

Measuring and reporting treatment adherence: What can we learn by comparing two respiratory conditions?

Medication non-adherence, defined as any deviation from the regimen recommended by their healthcare provider, can increase morbidity, mortality and side effects, while reducing effectiveness. Through studying two respiratory conditions, asthma and tuberculosis (TB), we thoroughly review the current understanding of the measurement and reporting of medication adherence. In this paper, we identify major methodological issues in the standard ways that adherence has been conceptualised, defined and studied in asthma and TB. Between and within the two diseases there are substantial variations in adherence reporting, linked to differences in dosing intervals and treatment duration. Critically, the communicable nature of TB has resulted in dose-by-dose monitoring becoming a recommended treatment standard. Through the lens of these similarities and contrasts, we highlight contemporary shortcomings in the generalised conceptualisation of medication adherence. Furthermore, we outline elements in which knowledge could be directly transferred from one condition to the other, such as the application of large-scale cost-effective monitoring methods in TB to resource-poor settings in asthma. To develop a more robust evidence-based approach, we recommend the use of standard taxonomies detailed in the ABC taxonomy when measuring and discussing adherence. Regimen and intervention development and use should be based on sufficient evidence of the commonality and type of adherence behaviours displayed by patients with the relevant condition. A systematic approach to the measurement and reporting of adherence could improve the value and generalisability of research across all health conditions.

The Need to Develop Standard Measures of Patient Adherence for Big Data: Viewpoint.

Despite half a century of dedicated studies, medication adherence remains far from perfect, with many patients not taking their medications as prescribed. The magnitude of this problem is rising, jeopardizing the effectiveness of evidence-based therapies. An important reason for this is the unprecedented demographic change at the beginning of the 21st century. Aging leads to multimorbidity and complex therapeutic regimens that create a fertile ground for nonadherence. As this scenario is a global problem, it needs a worldwide answer. Could this answer be provided, given the new opportunities created by the digitization of health care? Daily, health-related information is being collected in electronic health records, pharmacy dispensing databases, health insurance systems, and national health system records. These big data repositories offer a unique chance to study adherence both retrospectively and prospectively at the population level, as well as its related factors. In order to make full use of this opportunity, there is a need to develop standardized measures of adherence, which can be applied globally to big data and will inform scientific research, clinical practice, and public health. These standardized measures may also enable a better understanding of the relationship between adherence and clinical outcomes, and allow for fair benchmarking of the effectiveness and cost-effectiveness of adherence-targeting interventions. Unfortunately, despite this obvious need, such standards are still lacking. Therefore, the aim of this paper is to call for a consensus on global standards for measuring adherence with big data. More specifically, sound standards of formatting and analyzing big data are needed in order to assess, uniformly present, and compare patterns of medication adherence across studies. Wide use of these standards may improve adherence and make health care systems more effective and sustainable.

Community pharmacy-based study of adherence to non-vitamin K antagonist oral anticoagulants.

OBJECTIVE: This study aimed to assess implementation adherence (how well the patient's actual intake matches the prescribed dosing regimen) to non-vitamin K antagonist oral anticoagulants (NOACs) and to explore experiences with and beliefs about NOACs in a real-world sample of long-term NOAC users. METHODS: A cross-sectional observational study was conducted in home-dwelling adults who started taking a NOAC at least 1 year prior to inclusion. Pharmacy dispensing data were used to calculate the Medication Possession Ratio (MPR). Patients were recruited in 158 community pharmacies in Flanders, Belgium. They completed a questionnaire collecting basic characteristics and exploring self-reported adherence to NOACs (using the Medication Adherence Report Scale, MARS) and experiences with and beliefs about NOACs (using the Beliefs about Medicines Questionnaire, BMQ). RESULTS: A total of 766 patients (mean age 76.2±8.8 years, median CHA2DS2-VASc score 4 (IQR=3-4)) were included. The majority (93.5%) used NOAC for stroke prevention in atrial fibrillation. The median MPR was 95.2% (IQR=87.8-99.7) which corresponds with half of the study population not taking their NOAC on at least 17 cumulative days per year. Almost 21% of participants reported non-adherence on the MARS (score <25), with unintentional non-adherence (forgetfulness) most frequently reported (15.4%). Although two-thirds of NOAC users indicated to experience adverse drug reactions, the BMQ demonstrated a positive attitude towards NOAC therapy, where necessity beliefs outweigh the concerns. CONCLUSIONS: Our data indicate that long-term NOAC users have high implementation adherence and a positive attitude towards NOAC therapy. However, taking into account patients' thromboembolic risk and NOACs' short half-lives, further optimisation of NOAC use seems warranted in this population.

How the EMERGE guideline on medication adherence can improve the quality of clinical trials.

Medication adherence in drug trials is suboptimal, affecting the quality of these studies and adding significant costs. Nonadherence in this setting can lead to null findings, unduly large sample sizes and the need for dose modification after a drug has been approved. Despite these drawbacks, adherence behaviours are not consistently measured, analysed or reported appropriately in trial settings. The ESPACOMP Medication Adherence Reporting Guideline (EMERGE) offers a solution by facilitating a sound protocol design that takes this crucial factor into account. This article summarises key evidence on traditional and newer measurements of adherence, discusses implementation in clinical trial settings and makes recommendations about the analysis and interpretation of adherence data. Given the potential benefits of this approach, the authors call on regulators and the pharmaceutical industry to endorse the EMERGE guideline.

Brief interventions for improving adherence in schizophrenia: A pilot study using electronic medication event monitoring.

Poor medication adherence remains frequent in schizophrenia. The present study examined the efficacy of two month-long pilot interventions using the Medication Event Monitoring System (MEMS®). Thirty-three outpatients at high risk for relapse were randomized to receive a smartphone-based intervention, a nurse-based intervention, or treatment as usual. All patients then used the MEMS® to objectively measure medication adherence over six months. No differences were observed in adherence measures or relapse rates across the three groups. When using electronic medication monitoring as an objective measure of adherence, easily-implemented interventions may not significantly improve adherence in patients at high risk for relapse.

A Digital Innovation for the Personalized Management of Adherence: Analysis of Strengths, Weaknesses, Opportunities, and Threats.

Introduction: Personalized medicine and management of adherence are potential solutions for the suboptimal use of medicines. Digital medication management innovations currently under development combine both aspects. This research aims to investigate facilitators for and barriers to the translation of digital innovations for personalized medicine and adherence management into clinical practice from the policymaker and regulator perspective. Methods: A mixed-method study was used combining a scoping review to identify main interests, semi-structured interviews (n = 5) with representatives of European health policymaking and regulatory organizations, and a supplementary literature review to investigate key subthemes. The SWOT analysis was used for the qualitative analysis. Results: The literature reviews and the qualitative interviews suggested that digital solutions can facilitate the personalized management of medications and improve quality and safety, especially as the openness for digital health solutions is increasing. Digital solutions may, on the other hand, add complexity to the treatment, which can be perceived as a potential barrier for their uptake. As more multidisciplinary and participative structures are emerging, digital solutions can promote the implementation of new services. Nevertheless, change progresses slowly in the task-oriented structures of health systems. Integration of digital solutions depends on all stakeholders' willingness and abilities to co-create this change. Patients have different capabilities to self-manage their medical conditions and use digital solutions. Personalization of digital health solutions and integration in existing service structures are crucial to ensure equality among population segments. Developments in the digital infrastructure, although they are partly slow and not well-aligned, enable the implementation of innovations in clinical practice leading to further advances in data generation and usage for future innovations. Discussion: This study suggests that digital solutions have the potential to facilitate high-quality medication management and improve adherence to medications, enable new service structures, and are essential to drive further innovations in health care. Nevertheless, increasing the self-responsibility of patients can have undesirable effects on health outcomes, especially within vulnerable population segments. Digital health solutions can be an opportunity to optimize the use of medicines and thus their efficiency. Well-conceived development and implementation processes are needed to also realize improvements in equality and solidarity within health systems.

The ABC taxonomy for medication adherence translated into French and German.

AIMS: We translated the ABC adherence taxonomy (i.e. 7 terms and their corresponding definitions) published by Vrijens et al. (2012) into French and German without changing the original meaning with the aim to promote a standardised taxonomy for medication adherence to French- and German-speaking researchers and clinicians. METHODS: A Delphi survey was performed. To generate round 1, we identified French and German synonyms for the 7 adherence terms through a literature search in PubMed. Investigators translated the original English definitions into French and German. Panellists were members of ESPACOMP-the International Society for Patient Medication Adherence; experts suggested by ESPACOMP members and first authors of medication adherence publications in French and German. Google forms were used to create online questionnaires. Delphi rounds were performed until consensus was reached. The consensus was defined according to the acceptance rate as moderate consensus (50-75%), consensus (>75-95%), and strong consensus (>95%). RESULTS: The literature search resulted in 4-6 (French) and 4-7 (German) items per English term. Delphi rounds were launched between November 2016 and April 2018. Three rounds sufficed to reach consensus on all terms and definitions from 26 French-speaking and 25 German-speaking panellists. Preferred terms for medication adherence are adhésion médicamenteuse (82%) in French and Medikamentenadhärenz (88%) in German. CONCLUSION: The use of a common terminology for medication adherence with translations in French and German will contribute to standardise the vocabulary, to harmonise research projects and ultimately ease comparison of study results among researchers and clinicians.