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A data-driven typology of asthma medication adherence using cluster analysis.

ABSTRACT: Asthma preventer medication non-adherence is strongly associated with poor asthma control. One-dimensional measures of adherence may ignore clinically important patterns of medication-taking behavior. We sought to construct a data-driven multi-dimensional typology of medication non-adherence in children with asthma. We analyzed data from an intervention study of electronic inhaler monitoring devices, comprising 211 patients yielding 35,161 person-days of data. Five adherence measures were extracted: the percentage of doses taken, the percentage of days on which zero doses were taken, the percentage of days on which both doses were taken, the number of treatment intermissions per 100 study days, and the duration of treatment intermissions per 100 study days. We applied principal component analysis on the measures and subsequently applied k-means to determine cluster membership. Decision trees identified the measure that could predict cluster assignment with the highest accuracy, increasing interpretability and increasing clinical utility. We demonstrate the use of adherence measures towards a three-group categorization of medication non-adherence, which succinctly describes the diversity of patient medication taking patterns in asthma. The percentage of prescribed doses taken during the study contributed to the prediction of cluster assignment most accurately (84% in out-of-sample data).

SUBMITTER: Tibble H

PROVIDER: S-EPMC7490405 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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A data-driven typology of asthma medication adherence using cluster analysis.

Tibble Holly H Chan Amy A Mitchell Edwin A EA Horne Elsie E Doudesis Dimitrios D Horne Rob R Mizani Mehrdad A MA Sheikh Aziz A Tsanas Athanasios A

Scientific reports 20200914 1

Asthma preventer medication non-adherence is strongly associated with poor asthma control. One-dimensional measures of adherence may ignore clinically important patterns of medication-taking behavior. We sought to construct a data-driven multi-dimensional typology of medication non-adherence in children with asthma. We analyzed data from an intervention study of electronic inhaler monitoring devices, comprising 211 patients yielding 35,161 person-days of data. Five adherence measures were extrac ...[more]

PMID: 32929109

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Project description:BackgroundEmpirical research and health policies on asthma have focused on children and young adults, even though asthma morbidity and mortality are higher among older asthmatics.ObjectiveTo explore the relationship of asthma-related beliefs and self-reported controller medication adherence in older asthmatics.DesignAn observational study of asthma beliefs and self-management among older adults.ParticipantsAsthmatics ages ? 60 years (N?=?324, mean age 67.4 ± 6.8, 28 % white, 32 % black, 30 % Hispanic) were recruited from primary care practices in New York City and Chicago.Main measuresSelf-reported controller medication adherence was assessed using the Medication Adherence Report Scale. Based on the Common Sense Model of Self-Regulation, patients were asked if they believe they only have asthma with symptoms, their physician can cure their asthma, and if their asthma will persist. Beliefs on the benefit, necessity and concerns of treatment use were also assessed. Multivariate logistic regression was used to examine the association of beliefs with self-reported medication adherence.Key resultsThe majority (57.0 %) of patients reported poor adherence. Poor self-reported adherence was more common among those with erroneous beliefs about asthma illness and treatments, including the "no symptoms, no asthma" belief (58.7 % vs. 31.7 %, respectively, p?<?0.001), "will not always have asthma" belief (34.8 % vs. 12.5 %, p?<?0.001), and the "MD can cure asthma" belief (21.7 % vs. 9.6 %, p?=?0.01). Adjusting for illness beliefs, treatment beliefs and demographics, patients with a "no symptoms, no asthma" belief had lower odds of having good self-reported adherence (odds ratio [OR] 0.45, 95 % confidence interval [CI] 0.23-0.86), as did those with negative beliefs about the benefits (OR 0.73, 95 % CI 0.57-0.94) and necessity (OR 0.89, 95 % CI 0.83-0.96) of treatment.ConclusionsIllness and treatment beliefs have a strong influence on self-reported medication adherence in older asthmatics. Interventions to improve medication adherence in older asthmatics by modifying illness and treatment beliefs warrant study.

Project description:ObjectivesAdherence to nebulizer treatment in adults with Cystic Fibrosis (CF) is poor, and interventions are needed. This research aimed to identify the factors affecting nebulizer adherence using the Theoretical Domains Framework (TDF) and to compare these for participants with different levels of adherence.DesignData-prompted interviews using the TDF.MethodsEighteen semi-structured interviews were conducted with adults with CF during which objectively measured adherence data were discussed. Framework analysis was used to code the data into TDF domains, and inductive qualitative content analysis was used to code different beliefs and experiences. Aspects of the TDF that differed between participants with different adherence levels were explored.ResultsFactors influencing adherence to treatment included all 14 domains of the TDF, 10 of which appeared to vary by adherence level: Skills; Memory and decision-making; and Behavioural regulation; Environmental context and resources; Social influences; Beliefs about consequences; Beliefs about capability; Reinforcement; Social role and identify; Intentions; Optimism; and Emotions.ConclusionsThis study is the first to use objectively measured adherence data in a data-prompted interview using the TDF framework to systematically assess the full range of factors potentially influencing adherence. The results highlighted that interventions need to consider issues of capability, opportunity, and motivation. Interventions that challenge dysfunctional beliefs about adherence and which support the development of routines or habits and problem-solving may be particularly useful for adults with CF. Statement of contribution What is already known? Adherence to medication in adults with cystic fibrosis is poor. Previous research has identified a range of contributing factors in relation to subjective reports of adherence. There is a wide discrepancy between self-reported adherence and objectively measured adherence. What this study adds A data-prompted interview using objectively measured adherence data enabled the systematic assessment of potential factors that could be targeted in an intervention to increase adherence. There were some differences in the factors that were identified by high and low adherers. There is not one-size fits all intervention for adherence to medication in cystic fibrosis.

Project description:BACKGROUND:Mobile health (mHealth) apps have the potential to support patients' medication use and are therefore increasingly used. Apps with broad functionality are suggested to be more effective; however, not much is known about the actual use of different functionalities and the effective engagement. OBJECTIVE:The aim of this study was to explore the use and the effective engagement of adolescents (aged 12 to 18 years) with the Adolescent Adherence Patient Tool (ADAPT). METHODS:The ADAPT intervention consisted of an app for patients, which was connected to a management system for their pharmacist. The aim of the ADAPT intervention was to improve medication adherence and, therefore, the app contained multiple functionalities: questionnaires to monitor symptoms and adherence, medication reminders, short movies, pharmacist chat, and peer chat. For this study, data of the ADAPT study and a cluster randomized controlled trial were used. Adolescents with asthma had 6 months' access to the ADAPT intervention, and all app usage was securely registered in a log file. RESULTS:In total, 86 adolescents (mean age 15.0, SD 2.0 years) used the ADAPT app 17 times (range 1-113) per person. Females used the app more often than males (P=.01) and for a longer period of time (P=.03). On average, 3 different functionalities were used, and 13% of the adolescents used all functionalities of the app. The questionnaires to monitor symptoms and adherence were used by most adolescents. The total app use did not affect adherence; however, activity in the pharmacist chat positively affected medication adherence (P=.03), in particular, if patients sent messages to their pharmacist (P=.01). CONCLUSIONS:mHealth apps for adolescents with asthma should contain different functionalities to serve the diverging needs and preferences of individual patients. Suggested key functionalities to promote use and effectiveness in adolescents with asthma are questionnaires to monitor symptoms and a health care provider chat.

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A data-driven typology of asthma medication adherence using cluster analysis.

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A data-driven typology of asthma medication adherence using cluster analysis.

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