Compliance measurement-guided medication management programs in hypertension : a systematic review

Objectif principal: Il n’est pas démontré que les interventions visant à maîtriser voire modérer la médicamentation de patients atteints d’hypertension peuvent améliorer leur gestion de la maladie. Cette revue systématique propose d’évaluer les programmes de gestion contrôlée de la médicamentation pour l’hypertension, en s’appuyant sur la mesure de l’observance des traitements par les patients (CMGM). Design: Revue systématique. Sources de données: MEDLINE, EMBASE, CENTRAL, résumés de conférences internationales sur l’hypertension et bibliographies des articles pertinents. Méthodes: Des essais contrôlés randomisés (ECR) et des études observationnelles (EO) ont été évalués par 2 réviseurs indépendants. L’évaluation de la qualité (de ce matériel) a été réalisée avec l’aide de l’outil de Cochrane de mesure du risque de biais, et a été estimée selon une échelle à quatre niveaux de qualité Une synthèse narrative des données a été effectuée en raison de l'hétérogénéité importante des études. Résultats: 13 études (8 ECR, 5 EO) de 2150 patients hypertendus ont été prises en compte. Parmi elles, 5 études de CMGM avec l’utilisation de dispositifs électroniques comme seule intervention ont relevé une diminution de la tension artérielle (TA), qui pourrait cependant être expliquée par les biais de mesure. L’amélioration à court terme de la TA sous CMGM dans les interventions complexes a été révélée dans 4 études à qualité faible ou modérée. Dans 4 autres études sur les soins intégrés de qualité supérieure, il n'a pas été possible de distinguer l'impact de la composante CMGM, celle-ci pouvant être compromise par des traitements médicamenteux. L’ensemble des études semble par ailleurs montrer qu’un feed-back régulier au médecin traitant peut être un élément essentiel d’efficacité des traitements CMGM, et peut être facilement assuré par une infirmière ou un pharmacien, grâce à des outils de communication appropriés. Conclusions: Aucune preuve convaincante de l'efficacité des traitements CMGM comme technologie de la santé n’a été établie en raison de designs non-optimaux des études identifiées et des ualités méthodologiques insatisfaisantes de celles-ci. Les recherches futures devraient : suivre les normes de qualité approuvées et les recommandations cliniques actuelles pour le traitement de l'hypertension, inclure des groupes spécifiques de patients avec des problèmes d’attachement aux traitements, et considérer les résultats cliniques et économiques de l'organisation de soins ainsi que les observations rapportées par les patients.

Impact of type of drug insurance on adherence, persistence and costs of antidepressant drugs : a Quebec population-based study

Contexte: À date, il existe peu de données sur l’adhésion, la persistance et les coûts associés aux antidépresseurs selon le type d’assurance médicament (privé ou public). Objectif: Comparer selon le régime d’assurance médicament (privé ou public), l'adhésion, la persistance et les coûts des antidépresseurs. Méthodes de recherche: Une étude de cohorte appariée a été réalisée en utilisant des bases de données du Québec. Sujets: Nous avons sélectionné 194 patients assurés par un régime privé et 1923 patients assurés par le régime public de la Régie de l’assurance maladie du Québec (RAMQ) (18-64 ans) qui ont rempli au moins une ordonnance pour un antidépresseur entre décembre 2007 et septembre 2009. Mesures: L’adhésion, mesurée sur une période d’un an, a été estimée en utilisant le proportion of prescribed days covered (PPDC). Un modèle de régression linéaire a été utilisé afin d’estimer la différence moyenne en PPDC entre les patients assurés par un régime privé et ceux assurés par le régime public de la RAMQ. La persistance a été comparé entre ces deux groupes avec un modèle de régression de survie Cox, et le coût mensuel d'antidépresseurs ($ CAN) a été comparé entre ces deux groupes en utilisant un modèle de régression linéaire. Résultats: Le PPDC parmi les patients assurés par un régime privé était de 86,4% (intervalle de confiance (IC) 95%: 83,3%-89,5%) versus 81,3% (IC 95%: 80,1%-82,5%) pour les patients assurés par le régime public de la RAMQ, pour une différence moyenne ajustée de 6,7% (IC 95%: 3,0%-10,4%). La persistance après un an parmi les patients assurés par un régime privé était de 49,5% versus 18,9% pour les patients assurés par le régime public de la RAMQ (p <0,001), et le rapport de risque ajusté était de 0,48 (IC 95%: 0,30-0,76). Comparativement aux patients assurés par le régime public de la RAMQ, les patients ayant une assurance privée ont payé 14,94 $ CAD (95% CI: $12,30-$17,58) de plus par mois en moyenne pour leurs antidépresseurs. Conclusion: Les patients assurés par un régime privé avaient une meilleure adhésion, persistance, mais avaient aussi un plus haut coût pour leurs antidépresseurs que ceux assurés par le régime public de la RAMQ. Cette différence de coûts peut être due aux différentes exigences de paiement en pharmacie entre les deux régimes ainsi qu’aux limites des honoraires des pharmaciens imposés par le régime public.

Bisphosphonates adherence for treatment of osteoporosis

Background: Osteoporosis is a disease of bone metabolism in which bisphosphonates (BPS) are the most common medications used in its treatment, whose main objective is to reduce the risk of fractures. The aim of this study was to conduct a systematic review on BPs adherence for treatment of osteoporosis. Methods. Systematic review of articles on BPs adherence for treatment of osteoporosis, indexed on MEDLINE (via PubMed) databases, from inception of databases until January 2013. Search terms were Adherence, Medication (MeSH term), Bisphosphonates (MeSH term), and Osteoporosis (MeSH term). Results: Of the 78 identified studies, 27 met the eligibility criteria. Identified studies covered a wide range of aspects regarding adherence and associated factors, adherence and fracture, adherence and BPs dosage. The studies are mostly observational, conducted with women over 45 years old, showing low rates of adherence to treatment. Several factors may influence adherence: socio-economic and cultural, participation of physicians when guidance is given to the patient, the use of bone turnover markers, and use of generic drugs. The monthly dosage is associated with greater adherence compared to weekly dosage. Conclusions: Considering the methodological differences between the studies, the results converge to show that adherence to treatment of osteoporosis with BPs is still inadequate. Further experimental studies are needed to evaluate the adherence and suggest new treatment options. © 2013 Vieira et al.; licensee BioMed Central Ltd.

Adherence to statin treatment and associated factors in female users from the Unified Health System (SUS)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Behavioral measures to reduce non-adherence in renal transplant recipients: a prospective randomized controlled trial

Solid-organ transplant recipients present a high rate of non-adherence to drug treatment. Few interventional studies have included approaches aimed at increasing adherence. The objective of this study was to evaluate the impact of an educational and behavioral strategy on treatment adherence of kidney transplant recipients. In a randomized prospective study, incident renal transplant patients (n = 111) were divided into two groups: control group (received usual transplant patient education) and treatment group (usual transplant patient education plus ten additional weekly 30-min education/counseling sessions about immunosuppressive drugs and behavioral changes). Treatment adherence was assessed using ITAS adherence questionnaire after 3 months. Renal function at 3, 6, and 12 months, and the incidence of transplant rejection were evaluated. The non-adherence rates were 46.4 and 14.5 % in the control and treatment groups (p = 0.001), respectively. The relative risk for non-adherence was 2.59 times (CI 1.38-4.88) higher in the control group. Multivariate analysis demonstrated a 5.84 times (CI 1.8-18.8, p = 0.003) higher risk of non-adherence in the control group. There were no differences in renal function and rejection rates between groups. A behavioral and educational strategy addressing the patient's perceptions and knowledge about the anti-rejection drugs significantly improved the short-term adherence to immunosuppressive therapy.

Relationship among social support, treatment adherence and metabolic control of diabetes mellitus patients

This cross-sectional and quantitative study aimed to analyze the relationship among social support, adherence to non-pharmacological (diet and physical exercise) and pharmacological treatments (insulin and/or oral anti-diabetic medication) and clinical and metabolic control of 162 type 2 diabetes mellitus patients. Data were collected through instruments validated for Brazil. Social support was directly correlated with treatment adherence. Adherence to non-pharmacological treatment was inversely correlated with body mass index, and medication adherence was inversely correlated with diastolic blood pressure. There were no associations between social support and clinical and metabolic control variables. Findings indicate that social support can be useful to achieve treatment adherence. Studies with other designs should be developed to broaden the analysis of relations between social support and other variables.

Treatment Adherence and Blood Pressure Control in Older Individuals with Hypertension

Background: Non-adherence to treatment has been identified as the main cause of uncontrolled blood pressure (BP), and may represent a greater risk in older individuals. Objective: The aim of this study was to evaluate and compare the rate of adherence to hypertension treatment using different methods, to estimate the BP control rate, and to observe if there is an association between BP control and adherence. Methods: Treatment adherence was evaluated in older patients with hypertension, followed by the public primary health care, through four methods, including the Morisky-Green test (reference), the Attitude regarding the Medication Intake questionnaire (AMI), an evaluation of adherence by the nurse in the office (Nurse Adherence Evaluation - NAE), and at home (Home Adherence Evaluation - HAE). Salt intake was estimated by 24-hour sodium urinary excretion. BP control was assessed by the awake ambulatory blood pressure monitoring. Results: Concordance between the Morisky-Green test and AMI (Kappa=0.27) or NAE (Kappa=0.05) was poor. There was a moderate concordance between the Morisky-Green test and HAE. Eighty percent had controlled BP, including 42% with white-coat effect. The group with lower salt excretion informed to avoid salt intake more times (p<0.001) and had better medication adherence (p<0.001) than the higher salt excretion group. Conclusion: The evaluated tests did not show a good concordance to the Morisky-Green test. Adherence to hypertension treatment was low; however, there was a high rate of BP control when subjects with the white-coat effect were included in the analysis. (Arq Bras Cardiol 2012;99(1):636-641)

Low levels of adherence with proton pump inhibitor therapy contribute to therapeutic failure in gastroesophageal reflux disease

To assess adherence to proton pump inhibitor (PPI) treatment and associated variables in patients with gastroesophageal reflux disease (GERD). Cross-sectional and prospective comprising 240 consecutive adult patients, diagnosed with GERD for whom continuous use of standard or double dose of omeprazole had been prescribed. Patients were ranked as ne-GERD (162: 67.5%) or e-GERD classified according to the Los Angeles classification as A (48:20.0%), B (21:8.6%), C (1:0.5%), D (1:0.5%), and Barrett's esophagus (7:2.9%). The Morisky questionnaire was applied to assess adherence to therapy and a GERD questionnaire to assess symptoms and their impact. Adherence was correlated with demographics, cotherapies, comorbidities, treatment duration, symptoms scores, endoscopic findings, and patient awareness of their disease. 126 patients (52.5%) exhibited high level of adherence and 114 (47.5%) low level. Youngers (P= 0.002) or married (O.R. 2.41, P= 0.03 vs. widowers) patients had lower levels of adherence; symptomatic patients exhibited lower adherence (P= 0.02). All other variables studied had no influence on adherence. Patients with GERD attending a tertiary referral hospital in Sao Paulo exhibited a high rate of low adherence to the prescribed PPI therapy that may play a role in the therapy failure. Age <60 years, marital status and being symptomatic were risk factors for low adherence.

Intentional and unintentional non-adherence to medications following an acute coronary syndrome: A longitudinal study

Objective Non-adherence to medication is common among coronary heart disease patients. Non-adherence to medication may be either intentional or unintentional. In this analysis we provide estimates of intentional and unintentional non-adherence in the year following an acute coronary syndrome (ACS). Method In this descriptive prospective observational study of patients with confirmed ACS medication adherence measures were derived from responses to the Medication Adherence Report Scale at approximately 2 weeks (n = 223), 6 months (n = 139) and 12 months (n = 136) following discharge from acute treatment for ACS. Results Total medication non-adherence was 20%, 54% and 53% at each of these time points respectively. The corresponding figures for intentional non-adherence were 8%, 15% and 15% and 15%, 52% and 53% for unintentional non-adherence. There were significant increases in the levels of medication non-adherence between the immediate discharge period (2 weeks) and 6 months that appeared to stabilize between 6 and 12 months after acute treatment for ACS. Conclusion Unintentional non-adherence to medications may be the primary form of non-adherence in the year following ACS. Interventions delivered early in the post-discharge period may prevent the relatively high levels of non-adherence that appear to become established by 6 months following an ACS.

A technological framework based on automatic messaging for improving adherence of diabetic patients

En todo el mundo se ha observado un crecimiento exponencial en la incidencia de enfermedades crónicas como la hipertensión y enfermedades cardiovasculares y respiratorias, así como la diabetes mellitus, que causa un número de muertes cada vez mayor en todo el mundo (Beaglehole et al., 2008). En concreto, la prevalencia de diabetes mellitus (DM) está aumentando de manera considerable en todas las edades y representa un serio problema de salud mundial. La diabetes fue la responsable directa de 1,5 millones de muertes en 2012 y 89 millones de años de vida ajustados por discapacidad (AVAD) (OMS, 2014). Uno de los principales dilemas que suelen asociarse a la gestión de EC es la adherencia de los pacientes a los tratamientos, que representa un aspecto multifactorial que necesita asistencia en lo relativo a: educación, autogestión, interacción entre los pacientes y cuidadores y compromiso de los pacientes. Medir la adherencia del tratamiento es complicado y, aunque se ha hablado ampliamente de ello, aún no hay soluciones “de oro” (Reviews, 2002). El compromiso de los pacientes, a través de la participación, colaboración, negociación y a veces del compromiso firme, aumentan las oportunidades para una terapia óptima en la que los pacientes se responsabilizan de su parte en la ecuación de adherencia. Comprometer e involucrar a los pacientes diabéticos en las decisiones de su tratamiento, junto con expertos profesionales, puede ayudar a favorecer un enfoque centrado en el paciente hacia la atención a la diabetes (Martin et al., 2005). La motivación y atribución de poder de los pacientes son quizás los dos factores interventores más relevantes que afectan directamente a la autogestión de la atención a la diabetes. Se ha demostrado que estos dos factores desempeñan un papel fundamental en la adherencia a la prescripción, así como en el fomento exitoso de un estilo de vida sana y otros cambios de conducta (Heneghan et al., 2013). Un plan de educación personalizada es indispensable para proporcionarle al paciente las herramientas adecuadas que necesita para la autogestión efectiva de la enfermedad (El-Gayar et al. 2013). La comunicación efectiva es fundamental para proporcionar una atención centrada en el paciente puesto que influye en las conductas y actitudes hacia un problema de salud ((Frampton et al. 2008). En este sentido, la interactividad, la frecuencia, la temporalización y la adaptación de los mensajes de texto pueden promover la adherencia a un régimen de medicación. Como consecuencia, adaptar los mensajes de texto a los pacientes puede resultar ser una manera de hacer que las sugerencias y la información sean más relevantes y efectivas (Nundy et al. 2013). En este contexto, las tecnologías móviles en el ámbito de la salud (mHealth) están desempeñando un papel importante al conectar con pacientes para mejorar la adherencia a medicamentos recetados (Krishna et al., 2009). La adaptación de los mensajes de texto específicos de diabetes sigue siendo un área de oportunidad para mejorar la adherencia a la medicación y ofrecer motivación a adultos con diabetes. Sin embargo, se necesita más investigación para entender totalmente su eficacia. Los consejos de texto personalizados han demostrado causar un impacto positivo en la atribución de poder a los pacientes, su autogestión y su adherencia a la prescripción (Gatwood et al., 2014). mHealth se puede utilizar para ofrecer programas de asistencia de autogestión a los pacientes con diabetes y, al mismo tiempo, superar las dificultades técnicas y financieras que supone el tratamiento de la diabetes (Free at al., 2013). El objetivo principal de este trabajo de investigación es demostrar que un marco tecnológico basado en las teorías de cambios de conducta, aplicado al campo de la mHealth, permite una mejora de la adherencia al tratamiento en pacientes diabéticos. Como método de definición de una solución tecnológica, se han adoptado un conjunto de diferentes técnicas de conducta validadas denominado marco de compromiso de retroacción conductual (EBF, por sus siglas en inglés) para formular los mensajes, guiar el contenido y evaluar los resultados. Los estudios incorporan elementos del modelo transteórico (TTM, por sus siglas en inglés), la teoría de la fijación de objetivos (GST, por sus siglas en inglés) y los principios de comunicación sanitaria persuasiva y eficaz. Como concepto general, el modelo TTM ayuda a los pacientes a progresar a su próxima fase de conducta a través de mensajes de texto motivados específicos y permite que el médico identifique la fase actual y adapte sus estrategias individualmente. Además, se adoptan las directrices del TTM para fijar objetivos personalizados a un nivel apropiado a la fase de cambio del paciente. La GST encierra normas que van a ponerse en práctica para promover la intervención educativa y objetivos de pérdida de peso. Finalmente, los principios de comunicación sanitaria persuasiva y eficaz aplicados a la aparición de los mensajes se han puesto en marcha para aumentar la efectividad. El EBF tiene como objetivo ayudar a los pacientes a mejorar su adherencia a la prescripción y encaminarlos a una mejora general en la autogestión de la diabetes mediante mensajes de texto personalizados denominados mensajes de retroacción automáticos (AFM, por sus siglas en inglés). Después de una primera revisión del perfil, consistente en identificar características significativas del paciente basadas en las necesidades de tratamiento, actitudes y conductas de atención sanitaria, el sistema elige los AFM personalizados, los aprueba el médico y al final se transfieren a la interfaz del paciente. Durante el tratamiento, el usuario recopila los datos en dispositivos de monitorización de pacientes (PMD, por sus siglas en inglés) de una serie de dispositivos médicos y registros manuales. Los registros consisten en la toma de medicación, dieta y actividad física y tareas de aprendizaje y control de la medida del metabolismo. El compromiso general del paciente se comprueba al estimar el uso del sistema y la adherencia del tratamiento y el estado de los objetivos del paciente a corto y largo plazo. El módulo de análisis conductual, que consiste en una serie de reglas y ecuaciones, calcula la conducta del paciente. Tras lograr el análisis conductual, el módulo de gestión de AFM actualiza la lista de AFM y la configuración de los envíos. Las actualizaciones incluyen el número, el tipo y la frecuencia de mensajes. Los AFM los revisa periódicamente el médico que también participa en el perfeccionamiento del tratamiento, adaptado a la fase transteórica actual. Los AFM se segmentan en distintas categorías y niveles y los pacientes pueden ajustar la entrega del mensaje de acuerdo con sus necesidades personales. El EBF se ha puesto en marcha integrado dentro del sistema METABO, diseñado para facilitar al paciente diabético que controle sus condiciones relevantes de una manera menos intrusiva. El dispositivo del paciente se vincula en una plataforma móvil, mientras que una interfaz de panel médico permite que los profesionales controlen la evolución del tratamiento. Herramientas específicas posibilitan que los profesionales comprueben la adherencia del paciente y actualicen la gestión de envíos de AFM. El EBF fue probado en un proyecto piloto controlado de manera aleatoria. El principal objetivo era examinar la viabilidad y aceptación del sistema. Los objetivos secundarios eran también la evaluación de la eficacia del sistema en lo referente a la mejora de la adherencia, el control glucémico y la calidad de vida. Se reclutaron participantes de cuatro centros clínicos distintos en Europa. La evaluación del punto de referencia incluía datos demográficos, estado de la diabetes, información del perfil, conocimiento de la diabetes en general, uso de las plataformas TIC, opinión y experiencia con dispositivos electrónicos y adopción de buenas prácticas con la diabetes. La aceptación y eficacia de los criterios de evaluación se aplicaron para valorar el funcionamiento del marco tecnológico. El principal objetivo era la valoración de la eficacia del sistema en lo referente a la mejora de la adherencia. En las pruebas participaron 54 pacientes. 26 fueron asignados al grupo de intervención y equipados con tecnología móvil donde estaba instalado el EBF: 14 pacientes tenían T1DM y 12 tenían T2DM. El grupo de control estaba compuesto por 25 pa cientes que fueron tratados con atención estándar, sin el empleo del EBF. La intervención profesional tanto de los grupos de control como de intervención corrió a cargo de 24 cuidadores, entre los que incluían diabetólogos, nutricionistas y enfermeras. Para evaluar la aceptabilidad del sistema y analizar la satisfacción de los usuarios, a través de LimeSurvey, se creó una encuesta multilingüe tanto para los pacientes como para los profesionales. Los resultados también se recopilaron de los archivos de registro generados en los PMD, el panel médico profesional y las entradas de la base de datos. Los mensajes enviados hacia y desde el EBF y los archivos de registro del sistema y los servicios de comunicación se grabaron durante las cinco semanas del estudio. Se entregaron un total de 2795 mensajes, lo que supuso una media de 107,50 mensajes por paciente. Como se muestra, los mensajes disminuyen con el tiempo, indicando una mejora global de la adherencia al plan de tratamiento. Como se esperaba, los pacientes con T1DM recibieron más consejos a corto plazo, en relación a su estado. Del mismo modo, al ser el centro de T2DM en cambios de estilo de vida sostenible a largo plazo, los pacientes con T2DM recibieron más consejos de recomendación, en cuanto a dietas y actividad física. También se ha llevado a cabo una comparación de la adherencia e índices de uso para pacientes con T1DM y T2DM, entre la primera y la segunda mitad de la prueba. Se han observado resultados favorables para el uso. En lo relativo a la adherencia, los resultados denotaron una mejora general en cada dimensión del plan de tratamiento, como la nutrición y las mediciones de inserción de glucosa en la sangre. Se han llevado a cabo más estudios acerca del cambio a nivel educativo antes y después de la prueba, medidos tanto para grupos de control como de intervención. Los resultados indicaron que el grupo de intervención había mejorado su nivel de conocimientos mientras que el grupo de control mostró una leve disminución. El análisis de correlación entre el nivel de adherencia y las AFM ha mostrado una mejora en la adherencia de uso para los pacientes que recibieron los mensajes de tipo alertas, y unos resultados no significativos aunque positivos relacionados con la adherencia tanto al tratamiento que al uso correlacionado con los recordatorios. Por otra parte, los AFM parecían ayudar a los pacientes que no tomaban suficientemente en serio su tratamiento en el principio y que sí estaban dispuestos a responder a los mensajes recibidos. Aun así, los pacientes que recibieron demasiadas advertencias, comenzaron a considerar el envío de mensajes un poco estresante. El trabajo de investigación llevado a cabo al desarrollar este proyecto ofrece respuestas a las cuatro hipótesis de investigación que fueron la motivación para el trabajo. • Hipótesis 1 : es posible definir una serie de criterios para medir la adherencia en pacientes diabéticos. • Hipótesis 2: es posible diseñar un marco tecnológico basado en los criterios y teorías de cambio de conducta mencionados con anterioridad para hacer que los pacientes diabéticos se comprometan a controlar su enfermedad y adherirse a planes de atención. • Hipótesis 3: es posible poner en marcha el marco tecnológico en el sector de la salud móvil. • Hipótesis 4: es posible utilizar el marco tecnológico como solución de salud móvil en un contexto real y tener efectos positivos en lo referente a indicadores de control de diabetes. La verificación de cada hipótesis permite ofrecer respuesta a la hipótesis principal: La hipótesis principal es: es posible mejorar la adherencia diabética a través de un marco tecnológico mHealth basado en teorías de cambio de conducta. El trabajo llevado a cabo para responder estas preguntas se explica en este trabajo de investigación. El marco fue desarrollado y puesto en práctica en el Proyecto METABO. METABO es un Proyecto I+D, cofinanciado por la Comisión Europea (METABO 2008) que integra infraestructura móvil para ayudar al control, gestión y tratamiento de los pacientes con diabetes mellitus de tipo 1 (T1DM) y los que padecen diabetes mellitus de tipo 2 (T2DM). ABSTRACT Worldwide there is an exponential growth in the incidence of Chronic Diseases (CDs), such as: hypertension, cardiovascular and respiratory diseases, as well as diabetes mellitus, leading to rising numbers of deaths worldwide (Beaglehole et al. 2008). In particular, the prevalence of diabetes mellitus (DM) is largely increasing among all ages and constitutes a major worldwide health problem. Diabetes was directly responsible for 1,5 million deaths in 2012 and 89 million Disability-adjusted life year (DALYs) (WHO 2014). One of the key dilemmas often associated to CD management is the patients’ adherence to treatments, representing a multi-factorial aspect that requires support in terms of: education, self-management, interaction between patients and caregivers, and patients’ engagement. Measuring adherence is complex and, even if widely discussed, there are still no “gold” standards ((Giardini et al. 2015), (Costa et al. 2015). Patient’s engagement, through participation, collaboration, negotiation, and sometimes compromise, enhance opportunities for optimal therapy in which patients take responsibility for their part of the adherence equation. Engaging and involving diabetic patients in treatment decisions, along with professional expertise, can help foster a patient-centered approach to diabetes care (Martin et al. 2005). Patients’ motivation and empowerment are perhaps the two most relevant intervening factors that directly affect self-management of diabetes care. It has been demonstrated that these two factors play an essential role in prescription adherence, as well as for the successful encouragement of a healthy life-style and other behavioural changes (Heneghan et al. 2013). A personalised education plan is indispensable in order to provide the patient with the appropriate tools needed for the effective self-management of the disease (El-Gayar et al. 2013). Effective communication is at the core of providing patient-centred care since it influences behaviours and attitudes towards a health problem (Frampton et al. 2008). In this regard, interactivity, frequency, timing, and tailoring of text messages may promote adherence to a medication regimen. As a consequence, tailoring text messages to patients can constitute a way of making suggestions and information more relevant and effective (Nundy et al. 2013). In this context, mobile health technologies (mHealth) are playing significant roles in improving adherence to prescribed medications (Krishna et al. 2009). The tailoring of diabetes-specific text messages remains an area of opportunity to improve medication adherence and provide motivation to adults with diabetes but further research is needed to fully understand their effectiveness. Personalized text advices have proven to produce a positive impact on patients’ empowerment, self-management, and adherence to prescriptions (Gatwood et al. 2014). mHealth can be used for offering self-management support programs to diabetes patients and at the same time surmounting the technical and financial difficulties involved in diabetes treatment (Free et al. 2013). The main objective of this research work is to demonstrate that a technological framework, based on behavioural change theories, applied to mHealth domain, allows improving adherence treatment in diabetic patients. The framework, named Engagement Behavioural Feedback Framework (EBF), is built on top of validated behavioural techniques to frame messages, guide the definition of contents and assess outcomes: elements from the Transtheoretical Model (TTM), the Goal-Setting Theory (GST), Effective Health Communication (EHC) guidelines and Principles of Persuasive Technology (PPT) were incorporated. The TTM helps patients to progress to a next behavioural stage, through specific motivated text messages, and allow clinician’s identifying the current stage and tailor its strategies individually. Moreover, TTM guidelines are adopted to set customised goals at a level appropriate to the patient’s stage of change. The GST was used to build rules to be applied for enhancing educational intervention and weight loss objectives. Finally, the EHC guidelines and the PPT were applied to increase the effectiveness of messages. The EBF aims to support patients on improving their prescription adherence and persuade them towards a general improvement in diabetes self-management, by means of personalised text messages, named Automatic Feedback Messages (AFM). After a first profile screening, consisting in identifying meaningful patient characteristics based on treatment needs, attitudes and health care behaviours, customised AFMs are selected by the system, approved by the professional, and finally transferred into the patient interface. During the treatment, the user collects the data into a Patient Monitoring Device (PMD) from a set of medical devices and from manual inputs. Inputs consist in medication intake, diet and physical activity, metabolic measurement monitoring and learning tasks. Patient general engagement is checked by estimating the usage of the system and the adherence of treatment and patient goals status in the short and the long term period. The Behavioural Analysis Module, consisting in a set of rules and equations, calculates the patient’s behaviour. After behavioural analysis is accomplished, the AFM library and the dispatch setting are updated by the AFM Manager module. Updates include the number, the type and the frequency of messages. The AFMs are periodically supervised by the professional who also participates to the refinement of the treatment, adapted to the current transtheoretical stage. The AFMs are segmented in different categories and levels and patients can adjust message delivery in accordance with their personal needs. The EBF was integrated to the METABO system, designed to facilitate diabetic patients in managing their disease in a less intrusive approach. Patient device corresponds in a mobile platform, while a medical panel interface allows professionals to monitoring the treatment evolution. Specific tools allow professional to check patient adherence and to update the AFMs dispatch management. The EBF was tested in a randomised controlled pilot. The main objective was to examine the feasibility and acceptance of the system. Secondary objectives were also the assessment of the effectiveness of system in terms of adherence improvement, glycaemic control, and quality of life. Participants were recruited from four different clinical centres in Europe. The baseline assessment included demographics, diabetes status, profile information, knowledge about diabetes in general, usage of ICT platforms, opinion and experience about electronic devices and adoption of good practices with diabetes. Acceptance and the effectiveness evaluation criteria were applied to evaluate the performance of the technological framework. The main objective was the assessment of the effectiveness of system in terms of adherence improvement. Fifty-four patients participated on the trials. Twenty-six patients were assigned in the intervention group and equipped with mobile where the EBF was installed: 14 patients were T1DM and 12 were T2DM. The control group was composed of 25 patients that were treated through a standard care, without the usage of the EBF. Professional’s intervention for both intervention and control groups was carried out by 24 care providers, including endocrinologists, nutritionists, and nurses. In order to evaluate the system acceptability and analyse the users’ satisfaction, an online multi-language survey, using LimeSurvey, was produced for both patients and professionals. Results were also collected from the log-files generated in the PMDs, the professional medical panel and the entries of the data base. The messages sent to and from the EBF and the log-files of the system and communication services were recorded over 5 weeks of the study. A total of 2795 messages were submitted, representing an average of 107,50 messages per patient. As demonstrated, messages decrease over time indicating an overall improvement of the care plan’s adherence. As expected, T1DM patients were more loaded with short-term advices, in accordance with their condition. Similarly, being the focus of T2DM on long-term sustainable lifestyle changes, T2DM received more reminders advices, as for diet and physical activity. Favourable outcomes were observed for treatment and usage adherences of the intervention group: for both the adherence indices, results denoted a general improvement on each care plan’s dimension, such as on nutrition and blood glucose input measurements. Further studies were conducted on the change on educational level before and after the trial, measured for both control and intervention groups. The outcomes indicated the intervention group has improved its level of knowledge, while the control group denoted a low decrease. The correlation analysis between the level of adherences and the AFMs showed an improvement in usage adherence for patients who received warnings message, while non-significantly yet even positive indicators related to both treatment and usage adherence correlated with the Reminders. Moreover, the AFMs seemed to help those patients who did not take their treatment seriously enough in the beginning and who were willing to respond to the messages they received. Even though, patients who received too many Warnings, started to consider the message dispatch to be a bit stressful. The research work carried out in developing this research work provides responses to the four research hypothesis that were the motivation for the work: •Hypothesis 1: It is possible to define a set of criteria to measure adherence in diabetic patients. •Hypothesis 2: It is possible to design a technological framework, based on the aforementioned criteria and behavioural change theories, to engage diabetic patients in managing their disease and adhere to care plans. •Hypothesis 3: It is possible to implement the technological framework in the mobile health domain. •Hypothesis 4: It is possible to use the technological framework as a mobile health solution in a real context and have positive effects in terms of diabetes management indicators. The verification of each hypothesis allowed us to provide a response to the main hypothesis: The Main Hypothesis is: It is possible to improve diabetic adherence through a mHealth technological framework based on behavioural change theories. The work carried out to answer these questions is explained in this research work. The framework was developed and applied in the METABO project. METABO is an R&D project, co-funded by the European Commission (METABO 2008) that integrates mobile infrastructure for supporting the monitoring, management, and treatment of type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) patients.

Effect of Depression and Substance Abuse on Antiretroviral Therapy (ART) Adherence in Men Who Have Sex With Men (MSM) of Mexican Descent on the US-Mexico Border

Thesis (Master's)--University of Washington, 2016-06

Adherence to antiepileptic medicines in children:a multiple-methods assessment involving dried blood spot sampling

Purpose - To evaluate adherence to prescribed antiepileptic drugs (AEDs) in children with epilepsy using a combination of adherence-assessment methods. Methods - A total of 100 children with epilepsy (≤17 years old) were recruited. Medication adherence was determined via parental and child self-reporting (≥9 years old), medication refill data from general practitioner (GP) prescribing records, and via AED concentrations in dried blood spot (DBS) samples obtained from children at the clinic and via self- or parental-led sampling in children's own homes. The latter were assessed using population pharmacokinetic modeling. Patients were deemed nonadherent if any of these measures were indicative of nonadherence with the prescribed treatment. In addition, beliefs about medicines, parental confidence in seizure management, and the presence of depressed mood in parents were evaluated to examine their association with nonadherence in the participating children. Key Findings - The overall rate of nonadherence in children with epilepsy was 33%. Logistic regression analysis indicated that children with generalized epilepsy (vs. focal epilepsy) were more likely (odds ratio [OR] 4.7, 95% confidence interval [CI] 1.37–15.81) to be classified as nonadherent as were children whose parents have depressed mood (OR 3.6, 95% CI 1.16–11.41). Significance - This is the first study to apply the novel methodology of determining adherence via AED concentrations in clinic and home DBS samples. The present findings show that the latter, with further development, could be a useful approach to adherence assessment when combined with other measures including parent and child self-reporting. Seizure type and parental depressed mood were strongly predictive of nonadherence.

Adherence to treatment in children and adolescents with cystic fibrosis:a cross-sectional, multi-method study investigating the influence of beliefs about treatment and parental depressive symptoms

Background: Adherence to treatment is often reported to be low in children with cystic fibrosis. Adherence in cystic fibrosis is an important research area and more research is needed to better understand family barriers to adherence in order for clinicians to provide appropriate intervention. The aim of this study was to evaluate adherence to enzyme supplements, vitamins and chest physiotherapy in children with cystic fibrosis and to determine if any modifiable risk factors are associated with adherence. Methods: A sample of 100 children (≤18 years) with cystic fibrosis (44 male; median [range] 10.1 [0.2-18.6] years) and their parents were recruited to the study from the Northern Ireland Paediatric Cystic Fibrosis Centre. Adherence to enzyme supplements, vitamins and chest physiotherapy was assessed using a multi-method approach including; Medication Adherence Report Scale, pharmacy prescription refill data and general practitioner prescription issue data. Beliefs about treatments were assessed using refined versions of the Beliefs about Medicines Questionnaire-specific. Parental depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale. Results: Using the multi-method approach 72% of children were classified as low-adherers to enzyme supplements, 59% low-adherers to vitamins and 49% low-adherers to chest physiotherapy. Variations in adherence were observed between measurement methods, treatments and respondents. Parental necessity beliefs and child age were significant independent predictors of child adherence to enzyme supplements and chest physiotherapy, but parental depressive symptoms were not found to be predictive of adherence. Conclusions: Child age and parental beliefs about treatments should be taken into account by clinicians when addressing adherence at routine clinic appointments. Low adherence is more likely to occur in older children, whereas, better adherence to cystic fibrosis therapies is more likely in children whose parents strongly believe the treatments are necessary. The necessity of treatments should be reinforced regularly to both parents and children.

What We Mean When We Talk About Adherence In Respiratory Medicine

Funding acknowledgements The Respiratory Effectiveness Group (REG; www.effectivenessevaluation.org) supported the Expert Adherence Panel Meeting at which many of the concepts presented in this paper were first discussed. REG also supported the manuscript submission costs. AD, EvG and MdB have received funding from the European Community’s 7th Framework (FP7/2007-2013) under grant agreement n°282593.

What We Mean When We Talk About Adherence In Respiratory Medicine

Funding acknowledgements The Respiratory Effectiveness Group (REG; www.effectivenessevaluation.org) supported the Expert Adherence Panel Meeting at which many of the concepts presented in this paper were first discussed. REG also supported the manuscript submission costs. AD, EvG and MdB have received funding from the European Community’s 7th Framework (FP7/2007-2013) under grant agreement n°282593.