Toward an Interdisciplinary Approach to Constructing Care Delivery Pathways From Electronic Health Care Databases to Support Integrated Care in Chronic Conditions: Systematic Review of Quantification and Visualization Methods.

BACKGROUND: Electronic health care databases are increasingly used for informing clinical decision-making. In long-term care, linking and accessing information on health care delivered by different providers could improve coordination and health outcomes. Several methods for quantifying and visualizing this information into data-driven care delivery pathways (CDPs) have been proposed. To be integrated effectively and sustainably into routine care, these methods need to meet a range of prerequisites covering 3 broad domains: clinical, technological, and behavioral. Although advances have been made, development to date lacks a comprehensive interdisciplinary approach. As the field expands, it would benefit from developing common standards of development and reporting that integrate clinical, technological, and behavioral aspects. OBJECTIVE: We aimed to describe the content and development of long-term CDP quantification and visualization methods and to propose recommendations for future work. METHODS: We conducted a systematic review following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) recommendations. We searched peer-reviewed publications in English and reported the CDP methods by using the following data in the included studies: long-term care data and extracted data on clinical information and aims, technological development and characteristics, and user behaviors. The data are summarized in tables and presented narratively. RESULTS: Of the 2921 records identified, 14 studies were included, of which 13 (93%) were descriptive reports and 1 (7%) was a validation study. Clinical aims focused primarily on treatment decision-making (n=6, 43%) and care coordination (n=7, 50%). Technological development followed a similar process from scope definition to tool validation, with various levels of detail in reporting. User behaviors (n=3, 21%) referred to accessing CDPs, planning care, adjusting treatment, or supporting adherence. CONCLUSIONS: The use of electronic health care databases for quantifying and visualizing CDPs in long-term care is an emerging field. Detailed and standardized reporting of clinical and technological aspects is needed. Early consideration of how CDPs would be used, validated, and implemented in clinical practice would likely facilitate further development and adoption. TRIAL REGISTRATION: PROSPERO CRD42019140494; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=140494. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2019-033573.

Longitudinal Trajectory Modeling to Assess Adherence to Sacubitril/Valsartan among Patients with Heart Failure.

Medication adherence in chronic conditions is a long-term process. Modeling longitudinal trajectories using routinely collected prescription data is a promising method for describing adherence patterns and identifying at-risk groups. The study aimed to characterize distinct long-term sacubitril/valsartan adherence trajectories and factors associated with them in patients with heart failure (HF). Subjects with incident HF starting sac/val in 2017-2018 were identified from the Campania Regional Database for Medication Consumption. We estimated patients' continuous medication availability (CMA9; R package AdhereR) during a 12-month period. We selected groups with similar CMA9 trajectories (Calinski-Harabasz criterion; R package kml). We performed multinomial regression analysis, assessing the relationship between demographic and clinical factors and adherence trajectory groups. The cohort included 4455 subjects, 70% male. Group-based trajectory modeling identified four distinct adherence trajectories: high adherence (42.6% of subjects; CMA mean 0.91 ± 0.08), partial drop-off (19.6%; CMA 0.63 ± 0.13), moderate adherence (19.3%; CMA 0.54 ± 0.11), and low adherence (18.4%; CMA 0.17 ± 0.12). Polypharmacy was associated with partial drop-off adherence (OR 1.194, 95%CI 1.175-1.214), while the occurrence of ≥1 HF hospitalization (OR 1.165, 95%CI 1.151-1.179) or other hospitalizations (OR 1.481, 95%CI 1.459-1.503) were associated with low adherence. This study found that tailoring patient education, providing support, and ongoing monitoring can boost adherence within different groups, potentially improving health outcomes.

New terminology of medication adherence enabling and supporting activities: ENABLE terminology.

Introduction: Medication non-adherence negatively affects the effectiveness of evidence-based therapies and sustainability of healthcare systems. Lack of agreed terminology of medication adherence enabling and supporting activities leads to underuse of the available tools. The ENABLE COST Action was aimed at proposing a new terminology for these activities in order to help both scientific research and its clinical application. Methods: Initial discussions within the ENABLE Working Groups allowed for the conceptualization of four interlinked terms related to adherence, i.e., "medication adherence technology", "medication adherence enhancing intervention", "best practice" and "reimbursement". The iterative process of internal discussion was structured around two dedicated international workshops. Moreover, extensive stakeholder consultations have been organised, including an interactive online survey used to assess the level of agreement with, and the clarity of relevant terms and definitions proposed. Results: Detailed analysis of the results of this process allowed for fine-tuning of the items, and finally, for proposing the final set of definitions. Across all the three phases of this process, the definitions were substantially modified to better reflect the concepts, simplify the language, and assure completeness and cohesiveness of terminology. Feedback obtained from the stakeholders helped this process and confirmed that the final terms and definitions were well received by the experts active in the field of medication adherence. Discussion: Covering the gap in the existing terminology, this work proposes a cohesive set of terms and definitions applicable to medication adherence enabling and supporting activities. Promoting evidence-based approach to this field, this terminology may help research, clinical practice and policy.

A Participatory Approach Involving Patients with Cystic Fibrosis and Healthcare Professionals for the Co-Design of an Adherence-Enhancing Intervention Toolkit.

Purpose: Cystic fibrosis (CF) is an inherited life-shortening disease involving a significant treatment burden. Few interventions have been proven effective in improving adherence, and of these fewer have been adopted for implementation. Patient participation in research is increasingly desired in developing relevant health care services. A participatory approach was implemented in an adult CF center to co-design an adherence-enhancing intervention toolkit. We aimed to report on the participatory process and the results regarding the co-designed intervention. Patients and Methods: Two focus group sessions and four working sessions were conducted at 4-week intervals with three healthcare professionals (HCP; physician, nurse, physiotherapist), eight patients, and two researchers (sociologist, public health pharmacist). The two initial focus group sessions were dedicated to the collection of narratives about CF treatment experiences to identify drivers of adherence. The next four working sessions were dedicated to the reflection on solutions that could alleviate the difficulties identified and be used in current clinical practice. The researchers observed during all sessions the interactions between participants, group dynamics, and process of implementation of the collective reflection. Results: The process facilitated an active participation of patients and HCP, who contributed equally to the intervention development. The co-design adherence-enhancing intervention toolkit consisted in a self-questionnaire to be completed by patients before the medical consultation and used as a communication support during the consultation, plus a toolkit of solutions to be proposed by the HCP for each barrier identified by patients, and to be followed up during the next consultation. Conclusion: This study demonstrated that a participatory approach involving CF patients and HCP lead to the development of an adherence-enhancing intervention toolkit, using a 6-session format; the benefits of the co-designed intervention on the medication adherence have yet to be tested in a multicenter, open-label study in 3 centers in France.

Behavior Change Content, Understandability, and Actionability of Chronic Condition Self-Management Apps Available in France: Systematic Search and Evaluation.

BACKGROUND: The quality of life of people living with chronic conditions is highly dependent on self-management behaviors. Mobile health (mHealth) apps could facilitate self-management and thus help improve population health. To achieve their potential, apps need to target specific behaviors with appropriate techniques that support change and do so in a way that allows users to understand and act upon the content with which they interact. OBJECTIVE: Our objective was to identify apps targeted toward the self-management of chronic conditions and that are available in France. We aimed to examine what target behaviors and behavior change techniques (BCTs) they include, their level of understandability and actionability, and the associations between these characteristics. METHODS: We extracted data from the Google Play store on apps labelled as Top in the Medicine category. We also extracted data on apps that were found through 12 popular terms (ie, keywords) for the four most common chronic condition groups-cardiovascular diseases, cancers, respiratory diseases, and diabetes-along with apps identified through a literature search. We selected and downloaded native Android apps available in French for the self-management of any chronic condition in one of the four groups and extracted background characteristics (eg, stars and number of ratings), coded the presence of target behaviors and BCTs using the BCT taxonomy, and coded the understandability and actionability of apps using the Patient Education Material Assessment Tool for audiovisual materials (PEMAT-A/V). We performed descriptive statistics and bivariate statistical tests. RESULTS: A total of 44 distinct native apps were available for download in France and in French: 39 (89%) were found via the Google Play store and 5 (11%) were found via literature search. A total of 19 (43%) apps were for diabetes, 10 for cardiovascular diseases (23%), 8 for more than one condition in the four groups (18%), 6 for respiratory diseases (14%), and 1 for cancer (2%). The median number of target behaviors per app was 2 (range 0-7) and of BCTs per app was 3 (range 0-12). The most common BCT was self-monitoring of outcome(s) of behavior (31 apps), while the most common target behavior was tracking symptoms (30 apps). The median level of understandability was 42% and of actionability was 0%. Apps with more target behaviors and more BCTs were also more understandable (ρ=.31, P=.04 and ρ=.35, P=.02, respectively), but were not significantly more actionable (ρ=.24, P=.12 and ρ=.29, P=.054, respectively). CONCLUSIONS: These apps target few behaviors and include few BCTs, limiting their potential for behavior change. While content is moderately understandable, clear instructions on when and how to act are uncommon. Developers need to work closely with health professionals, users, and behavior change experts to improve content and format so apps can better support patients in coping with chronic conditions. Developers may use these criteria for assessing content and format to guide app development and evaluation of app performance. TRIAL REGISTRATION: PROSPERO CRD42018094012; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=94012.

Beyond Adherence Thresholds: A Simulation Study of the Optimal Classification of Longitudinal Adherence Trajectories From Medication Refill Histories.

Background: The description of adherence based on medication refill histories relies on the estimation of continuous medication availability (CMA) during an observation period. Thresholds to distinguish adherence from non-adherence typically refer to an aggregated value across the entire observation period, disregarding differences in adherence over time. Sliding windows to divide the observation period into smaller portions, estimating adherence for these increments, and classify individuals with similar trajectories into clusters can retain this temporal information. Optimal methods to estimate adherence trajectories to identify underlying patterns have not yet been established. This simulation study aimed to provide guidance for future studies by analyzing the effect of different longitudinal adherence estimates, sliding window parameters, and sample characteristics on the performance of a longitudinal clustering algorithm. Methods: We generated samples of 250-25,000 individuals with one of six longitudinal refill patterns over a 2-year period. We used two longitudinal CMA estimates (LCMA1 and LCMA2) and their dichotomized variants (with a threshold of 80%) to create adherence trajectories. LCMA1 assumes full adherence until the supply ends while LCMA2 assumes constant adherence between refills. We assessed scenarios with different LCMA estimates and sliding window parameters for 350 independent samples. Individual trajectories were clustered with kml, an implementation of k-means for longitudinal data in R. We compared performance between the four LCMA estimates using the adjusted Rand Index (cARI). Results: Cluster analysis with LCMA2 outperformed other estimates in overall performance, correct identification of groups, and classification accuracy, irrespective of sliding window parameters. Pairwise comparison between LCMA estimates showed a relative cARI-advantage of 0.12-0.22 (p < 0.001) for LCMA2. Sample size did not affect overall performance. Conclusion: The choice of LCMA estimate and sliding window parameters has a major impact on the performance of a clustering algorithm to identify distinct longitudinal adherence trajectories. We recommend (a) to assume constant adherence between refills, (b) to avoid dichotomization based on a threshold, and (c) to explore optimal sliding windows parameters in simulation studies or selecting shorter non-overlapping windows for the identification of different adherence patterns from medication refill data.

Mapping of modifiable barriers and facilitators of medication adherence in bipolar disorder to the Theoretical Domains Framework: a systematic review protocol.

INTRODUCTION: People with bipolar disorder require long-term treatment but it is estimated that 40% of these people do not adhere to prescribed medication regimens. Non-adherence increases the risk of relapse, hospitalisation and suicide. Some evidence syntheses report barriers to mental health treatment adherence but rarely delineate between modifiable and non-modifiable barriers. They also fail to distinguish between the patients' perspective and that of other stakeholders such as clinicians despite of their different understanding and priorities about adherence. Facilitators of adherence, which are also important for informing adherence intervention design, are also lacking from syntheses and few syntheses focus on medications for bipolar disorder.This systematic review aims to identify modifiable barriers and facilitators (determinants) of medication adherence in bipolar disorder. We also plan to report determinants of medication adherence from perspectives of patients, carers, healthcare professionals and other third parties. A unique feature of this systematic review in the context of mental health is the use of the Theoretical Domains Framework (TDF) to organise the literature identified determinants of medication adherence. METHODS AND ANALYSIS: The protocol adheres to Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols and ENhancing Transparency in REporting the synthesis of Qualitative research (ENTREQ) guidelines. This review will include both qualitative and quantitative primary studies exploring determinants of medication adherence in bipolar disorder. We will search the following databases using a preplanned strategy: CINAHL, Cochrane Library (CENTRAL), Embase, LiLACS, Medline, PsychINFO, PubMed without date restrictions. We will report the quality of included studies. We will use framework synthesis using the TDF as an a priori 'framework'. We will map the literature identified modifiable determinants to the domains of TDF. ETHICS AND DISSEMINATION: Ethical approval is not required as primary data will not be collected. The results will be disseminated through a peer-reviewed publication. PROSPERO REGISTRATION NUMBER: CRD42018096306.

The Virtual Care Climate Questionnaire: Development and Validation of a Questionnaire Measuring Perceived Support for Autonomy in a Virtual Care Setting.

BACKGROUND: Web-based health behavior change interventions may be more effective if they offer autonomy-supportive communication facilitating the internalization of motivation for health behavior change. Yet, at this moment no validated tools exist to assess user-perceived autonomy-support of such interventions. OBJECTIVE: The aim of this study was to develop and validate the virtual climate care questionnaire (VCCQ), a measure of perceived autonomy-support in a virtual care setting. METHODS: Items were developed based on existing questionnaires and expert consultation and were pretested among experts and target populations. The virtual climate care questionnaire was administered in relation to Web-based interventions aimed at reducing consumption of alcohol (Study 1; N=230) or cannabis (Study 2; N=228). Item properties, structural validity, and reliability were examined with item-response and classical test theory methods, and convergent and divergent validity via correlations with relevant concepts. RESULTS: In Study 1, 20 of 23 items formed a one-dimensional scale (alpha=.97; omega=.97; H=.66; mean 4.9 [SD 1.0]; range 1-7) that met the assumptions of monotonicity and invariant item ordering. In Study 2, 16 items fitted these criteria (alpha=.92; H=.45; omega=.93; mean 4.2 [SD 1.1]; range 1-7). Only 15 items remained in the questionnaire in both studies, thus we proceeded to the analyses of the questionnaire's reliability and construct validity with a 15-item version of the virtual climate care questionnaire. Convergent validity of the resulting 15-item virtual climate care questionnaire was confirmed by positive associations with autonomous motivation (Study 1: r=.66, P<.001; Study 2: r=.37, P<.001) and perceived competence for reducing alcohol intake (Study 1: r=.52, P<.001). Divergent validity could only be confirmed by the nonsignificant association with perceived competence for learning (Study 2: r=.05, P=.48). CONCLUSIONS: The virtual climate care questionnaire accurately assessed participants' perceived autonomy-support offered by two Web-based health behavior change interventions. Overall, the scale showed the expected properties and relationships with relevant concepts, and the studies presented suggest this first version of the virtual climate care questionnaire to be reasonably valid and reliable. As a result, the current version may cautiously be used in future research and practice to measure perceived support for autonomy within a virtual care climate. Future research efforts are required that focus on further investigating the virtual climate care questionnaire's divergent validity, on determining the virtual climate care questionnaire's validity and reliability when used in the context of Web-based interventions aimed at improving nonaddictive or other health behaviors, and on developing and validating a short form virtual climate care questionnaire.

Computation of adherence to medication and visualization of medication histories in R with AdhereR: Towards transparent and reproducible use of electronic healthcare data.

Adherence to medications is an important indicator of the quality of medication management and impacts on health outcomes and cost-effectiveness of healthcare delivery. Electronic healthcare data (EHD) are increasingly used to estimate adherence in research and clinical practice, yet standardization and transparency of data processing are still a concern. Comprehensive and flexible open-source algorithms can facilitate the development of high-quality, consistent, and reproducible evidence in this field. Some EHD-based clinical decision support systems (CDSS) include visualization of medication histories, but this is rarely integrated in adherence analyses and not easily accessible for data exploration or implementation in new clinical settings. We introduce AdhereR, a package for the widely used open-source statistical environment R, designed to support researchers in computing EHD-based adherence estimates and in visualizing individual medication histories and adherence patterns. AdhereR implements a set of functions that are consistent with current adherence guidelines, definitions and operationalizations. We illustrate the use of AdhereR with an example dataset of 2-year records of 100 patients and describe the various analysis choices possible and how they can be adapted to different health conditions and types of medications. The package is freely available for use and its implementation facilitates the integration of medication history visualizations in open-source CDSS platforms.

A Psychometric Analysis of the Italian Version of the eHealth Literacy Scale Using Item Response and Classical Test Theory Methods.

BACKGROUND: The eHealth Literacy Scale (eHEALS) is a tool to assess consumers' comfort and skills in using information technologies for health. Although evidence exists of reliability and construct validity of the scale, less agreement exists on structural validity. OBJECTIVE: The aim of this study was to validate the Italian version of the eHealth Literacy Scale (I-eHEALS) in a community sample with a focus on its structural validity, by applying psychometric techniques that account for item difficulty. METHODS: Two Web-based surveys were conducted among a total of 296 people living in the Italian-speaking region of Switzerland (Ticino). After examining the latent variables underlying the observed variables of the Italian scale via principal component analysis (PCA), fit indices for two alternative models were calculated using confirmatory factor analysis (CFA). The scale structure was examined via parametric and nonparametric item response theory (IRT) analyses accounting for differences between items regarding the proportion of answers indicating high ability. Convergent validity was assessed by correlations with theoretically related constructs. RESULTS: CFA showed a suboptimal model fit for both models. IRT analyses confirmed all items measure a single dimension as intended. Reliability and construct validity of the final scale were also confirmed. The contrasting results of factor analysis (FA) and IRT analyses highlight the importance of considering differences in item difficulty when examining health literacy scales. CONCLUSIONS: The findings support the reliability and validity of the translated scale and its use for assessing Italian-speaking consumers' eHealth literacy.

Level of Asthma Controller Therapy Before Admission to the Hospital.

BACKGROUND: In asthma, choice of controller therapy and adherence to treatment can affect the risk of future severe exacerbations leading to hospitalization. OBJECTIVE: Our objective was to characterize treatment dispensation profiles before hospital admission for asthma. METHODS: Using a 1/97th random sample of the national French claims data, patients with asthma aged 6 to 40 years were identified between 2006 and 2014. Patients with subsequent asthma-related hospitalization were selected. On the basis of controller therapy dispensed in the 12 months before admission, treatment profiles were categorized into clusters, using Ward's minimum-variance hierarchical clustering method. RESULTS: Of 17,846 patients with asthma, we identified 275 patients (1.5%) with an asthma-related hospitalization. Three distinct clusters were identified. The first cluster (63.6%) included patients with few dispensations of any controller medication (<1 unit). The second cluster (32.4%) consisted of patients with frequent dispensations of long-acting beta agonists (LABAs)/inhaled corticosteroids (ICS) in fixed-dose combinations. The third cluster (4%) comprised patients receiving free combinations of ICS and LABAs, with more dispensations of LABAs than of ICS. CONCLUSIONS: In France, before an asthma-related hospitalization, more than 60% of patients received little controller therapy and 4% were exposed to higher dispensation of LABAs than of ICS. These results indicate that a large fraction of asthma-related hospitalizations can potentially be prevented with better pharmacotherapy.

Mapping the Asthma Care Process: Implications for Research and Practice.

BACKGROUND: Whether people with asthma gain and maintain control over their condition depends not only on the availability of effective drugs, but also on multiple patient and health care professional (HCP) behaviors. Research in asthma rarely considers how these behaviors interact with each other and drug effectiveness to determine health outcomes, which may limit real-life applicability of findings. OBJECTIVE: The objective of this study was to develop a logic process model (Asthma Care Model; ACM) that explains how patient and HCP behaviors impact on the asthma care process. METHODS: Within a European research project on asthma (ASTRO-LAB), we reviewed asthma care guidelines and empirical literature, and conducted qualitative interviews with patients and HCPs. Findings were discussed with the project team and respiratory care experts and integrated in a causal model. RESULTS: The model outlines a causal sequence of treatment events, from diagnosis and assessment to treatment prescription, drug exposure, and health outcomes. The relationships between these components are moderated by patient behaviors (medication adherence, symptom monitoring, managing triggers, and exacerbations) and HCP behaviors (medical care and self-management support). Modifiable and nonmodifiable behavioral determinants influence the behaviors of patients and HCPs. The model is dynamic as it includes feedback loops of behavioral and clinical outcomes, which influence future patient and HCP decision making. Key evidence for each relationship is summarized to derive research priorities and clinical recommendations. CONCLUSIONS: The ACM model is of interest to both researchers and practitioners, and intended as a first version (ACM-v1) of a common framework for generating and translating research evidence in asthma care.

Where we are now and how we can improve: a qualitative study of practitioners' perspectives on providing ART adherence support in Romania.

Supporting medication adherence is a priority in HIV care worldwide as low adherence threatens the effectiveness of antiretroviral treatment (ART). While evidence on adherence causes and consequences has steadily accumulated, investigating current practice and relevant determinants of practitioners' behaviors has only recently been highlighted as essential for developing effective and sustainable interventions. In Romania, ART adherence is low despite universal access to HIV care, and improving support services is a priority. We report a qualitative exploration of practitioners' experiences and views on ART adherence support, guided by current behavioral theory. Semi-structured interviews were performed with 10 practitioners from six HIV centers, aiming for maximum variation sampling on professional experience, location, and organization type. Questions addressed practitioners' views and experiences on assessing patients' adherence behaviors and determinants, content and format of adherence support, and perceived influences on their capacity to deliver support. Verbatim transcripts were analyzed via template analysis. Results show that adherence support is provided in Romania by trained psychologists in multidisciplinary teams that operate flexibly and perform multiple HIV care activities. Assessment of adherence behaviors and determinants is primarily interview-based, and practitioners use mostly psychotherapeutic techniques and theories with a degree of intervention tailoring. Practitioners' descriptions covered a broad range of common determinants and behavior change techniques, but showed limited use of behavioral theory. Participants also described difficulties to cope with limited resources, and lack of support for managing practical and emotional challenges. Several opportunities for improvement were identified, such as standardizing patient profiling and intervention delivery, conceptualizing and recording active intervention content based on behavioral theory, and actively monitoring intervention effectiveness. This qualitative inquiry provided valuable information for improving adherence support in this clinical context. Understanding practitioners' perspectives based on behavioral theory-informed analyses can help intervention developers increase intervention fidelity by integrating current practice information in program design.