Telemedicine and home monitoring for COPD - a narrative review of recent literature.

PURPOSE OF REVIEW: Home monitoring is one of the methods of using telemedical technologies aimed to provide care at home and maintain a connection between patients and healthcare providers. The purpose of this review is to describe recent advancements in the use of home monitoring for the care and management of chronic obstructive pulmonary disease (COPD) patients. RECENT FINDINGS: Recent studies focused on remote monitoring for patients with COPD proved the positive effect of home monitoring interventions on the frequency of exacerbations and unscheduled healthcare visits, duration of patients' physical activity, proved sensitivity and overall specificity of such interventions and highlighted the effectiveness of self-management.Assessing end-user experience revealed high satisfaction levels among patients and healthcare staff who used home monitoring interventions. The majority of physicians and staff responded positively about the interventions' facilitation of communication with patients. Moreover, healthcare staff considered such technologies useful for their practice. SUMMARY: Home monitoring for COPD patients improves medical care and disease management despite minor drawbacks and obstacles to its wide implementation. Involving end-users in evaluating and co-creating new telemonitoring interventions has the potential to improve the quality of remote monitoring for COPD patients in the near future.

Development of a Quality Management Model and Self-assessment Questionnaire for Hybrid Health Care: Concept Mapping Study.

BACKGROUND: Working with eHealth requires health care organizations to make structural changes in the way they work. Organizational structure and process must be adjusted to provide high-quality care. This study is a follow-up study of a systematic literature review on optimally organizing hybrid health care (eHealth and face to face) using the Donabedian Structure-Process-Outcome (SPO) framework to translate the findings into a modus operandi for health care organizations. OBJECTIVE: This study aimed to develop an SPO-based quality assessment model for organizing hybrid health care using an accompanying self-assessment questionnaire. Health care organizations can use this model and a questionnaire to manage and improve their hybrid health care. METHODS: Concept mapping was used to enrich and validate evidence-based knowledge from a literature review using practice-based knowledge from experts. First, brainstorming was conducted. The participants listed all the factors that contributed to the effective organization of hybrid health care and the associated outcomes. Data from the brainstorming phase were combined with data from the literature study, and duplicates were removed. Next, the participants rated the factors on importance and measurability and grouped them into clusters. Finally, using multivariate statistical analysis (multidimensional scaling and hierarchical cluster analysis) and group interpretation, an SPO-based quality management model and an accompanying questionnaire were constructed. RESULTS: All participants (n=39) were familiar with eHealth and were health care professionals, managers, researchers, patients, or eHealth suppliers. The brainstorming and literature review resulted in a list of 314 factors. After removing the duplicates, 78 factors remained. Using multivariate statistical analyses and group interpretations, a quality management model and questionnaire incorporating 8 clusters and 33 factors were developed. The 8 clusters included the following: Vision, strategy, and organization; Quality information technology infrastructure and systems; Quality eHealth application; Providing support to health care professionals; Skills, knowledge, and attitude of health care professionals; Attentiveness to the patient; Patient outcomes; and Learning system. The SPO categories were positioned as overarching themes to emphasize the interrelations between the clusters. Finally, a proposal was made to use the self-assessment questionnaire in practice, allowing measurement of the quality of each factor. CONCLUSIONS: The quality of hybrid care is determined by organizational, technological, process, and personal factors. The 33 most important factors were clustered in a quality management model and self-assessment questionnaire called the Hybrid Health Care Quality Assessment. The model visualizes the interrelations between the factors. Using a questionnaire, each factor can be assessed to determine how effectively it is organized and developed over time. Health care organizations can use the Hybrid Health Care Quality Assessment to identify improvement opportunities for solid and sustainable hybrid health care.

The Impact of Patient Characteristics on Their Attitudes Toward an Online Patient Portal for Communicating Laboratory Test Results: Real-World Study.

BACKGROUND: Patient portals are promising tools to increase patient involvement and allow them to manage their health. To optimally facilitate patients, laboratory test results should be explained in easy language. Patient characteristics affect the usage of portals and the user satisfaction. However, limited research is available, specified for online communicating laboratory test results, on whether portal use and acceptance differ between groups. OBJECTIVE: The aim of this study was to assess the effect of patient characteristics (gender, age, education, and chronic disease) on the self-efficacy and perceived usability of an online patient portal that communicates diagnostic test results. METHODS: We used the online-administered eHealth impact questionnaire (eHIQ) to explore patients' attitudes toward the portal. Patients visiting the portal were asked to complete the questionnaire and to answer questions regarding gender, age, education, and chronic disease. The subscale "information and presentation" of the eHIQ assessed the usability of the patient portal and the subscale "motivation and confidence to act" assessed self-efficacy to determine whether patients were motivated to act on the presented information. Age, gender, education, and chronic disease were the determinants to analyze the effect on usability and self-efficacy. Descriptive analyses were performed to explore patient characteristics, usability, and self-efficacy. Univariable and multivariable regression analyses were performed with age, gender, education, and chronic disease as determinants, and usability and self-efficacy as outcomes. RESULTS: The questionnaire was completed by 748 respondents, of which 428 (57.2%) were female, 423 (56.6%) were highly educated, and 509 (68%) had no chronic disease. The mean age was 58.5 years (SD 16.4). Higher age, high education, and asthma or chronic obstructive pulmonary disease were significant determinants for decreased usability; respectively, b=-.094, 95% CI -1147 to 0.042 (P<.001); b=-2.512, 95% CI -4.791 to -0.232 (P=.03); and b=-3.630, 95% CI -6.545 to -0.715 (P=.02). High education was also a significant determinant for a lower self-efficacy (b=-3.521, 95% CI -6.469 to -0.572; P=.02). Other determinants were not significant. CONCLUSIONS: This study showed that the higher-educated users of a patient portal scored lower on usability and self-efficacy. Usability was also lower for older people and for patients with asthma or chronic obstructive pulmonary disease. The results portal is not tailored for different groups. Further research should investigate which factors from a patient's perspective are essential to tailor the portal for different groups and how a result portal can be optimally integrated within the daily practice of a doctor.

Experiences with tailoring of primary diabetes care in well-organised general practices: a mixed-methods study.

BACKGROUND: Dutch standard diabetes care is generally protocol-driven. However, considering that general practices wish to tailor diabetes care to individual patients and encourage self-management, particularly in light of current COVID-19 related constraints, protocols and other barriers may hinder implementation. The impact of dispensing with protocol and implementation of self-management interventions on patient monitoring and experiences are not known. This study aims to evaluate tailoring of care by understanding experiences of well-organised practices 1) when dispensing with protocol; 2) determining the key conditions for successful implementation of self-management interventions; and furthermore exploring patients' experiences regarding dispensing with protocol and self-management interventions. METHODS: in this mixed-methods prospective study, practices (n = 49) were invited to participate if they met protocol-related quality targets, and their adult patients with well-controlled type 2 diabetes were invited if they had received protocol-based diabetes care for a minimum of 1 year. For practices, study participation consisted of the opportunity to deliver protocol-free diabetes care, with selection and implementation of self-management interventions. For patients, study participation provided exposure to protocol-free diabetes care and self-management interventions. Qualitative outcomes (practices: 5 focus groups, 2 individual interviews) included experiences of dispensing with protocol and the implementation process of self-management interventions, operationalised as implementation fidelity. Quantitative outcomes (patients: routine registry data, surveys) consisted of diabetes monitoring completeness, satisfaction, wellbeing and health status at baseline and follow-up (24 months). RESULTS: Qualitative: In participating practices (n = 4), dispensing with protocol encouraged reflection on tailored care and selection of various self-management interventions A focus on patient preferences, team collaboration and intervention feasibility was associated with high implementation fidelity Quantitative: In patients (n = 126), likelihood of complete monitoring decreased significantly after two years (OR 0.2 (95% CI 0.1-0.5), p < 0.001) Satisfaction decreased slightly (- 1.6 (95% CI -2.6;-0.6), p = 0.001) Non-significant declines were found in wellbeing (- 1.3 (95% CI -5.4; 2.9), p = 0.55) and health status (- 3.0 (95% CI -7.1; 1.2), p = 0.16). CONCLUSIONS: To tailor diabetes care to individual patients within well-organised practices, we recommend dispensing with protocol while maintaining one structural annual monitoring consultation, combined with the well-supported implementation of feasible self-management interventions. Interventions should be selected and delivered with the involvement of patients and should involve population preferences and solid team collaborations.

Successes of and Lessons From the First Joint eHealth Program of the Dutch University Hospitals: Evaluation Study.

BACKGROUND: A total of 8 Dutch university hospitals are at the forefront of contributing meaningfully to a future-proof health care system. To stimulate nationwide collaboration and knowledge-sharing on the topic of evidence-based eHealth, the Dutch university hospitals joined forces from 2016 to 2019 with the first Citrien Fund (CF) program eHealth; 29 eHealth projects with various subjects and themes were selected, supported, and evaluated. To determine the accomplishment of the 10 deliverables for the CF program eHealth and to contribute to the theory and practice of formative evaluation of eHealth in general, a comprehensive evaluation was deemed essential. OBJECTIVE: The first aim of this study is to evaluate whether the 10 deliverables of the CF program eHealth were accomplished. The second aim is to evaluate the progress of the 29 eHealth projects to determine the barriers to and facilitators of the development of the CF program eHealth projects. METHODS: To achieve the first aim of this study, an evaluation study was carried out using an adapted version of the Commonwealth Scientific and Industrial Research Organization framework. A mixed methods study, consisting of a 2-part questionnaire and semistructured interviews, was conducted to analyze the second aim of the study. RESULTS: The 10 deliverables of the CF program eHealth were successfully achieved. The program yielded 22 tangible eHealth solutions, and significant knowledge on the development and use of eHealth solutions. We have learned that the patient is enthusiastic about accessing and downloading their own medical data but the physicians are more cautious. It was not always possible to implement the Dutch set of standards for interoperability, owing to a lack of information technology (IT) capacities. In addition, more attention needed to be paid to patients with low eHealth skills, and education in such cases is important. The eHealth projects' progress aspects such as planning, IT services, and legal played an important role in the success of the 29 projects. The in-depth interviews illustrated that a novel eHealth solution should fulfill a need, that partners already having the knowledge and means to accelerate development should be involved, that clear communication with IT developers and other stakeholders is crucial, and that having a dedicated project leader with sufficient time is of utmost importance for the success of a project. CONCLUSIONS: The 8 Dutch university hospitals were able to collaborate successfully and stimulate through a bottom-up approach, nationwide eHealth development and knowledge-sharing. In total, 22 tangible eHealth solutions were developed, and significant eHealth knowledge about their development and use was shared. The eHealth projects' progress aspects such as planning, IT services, and legal played an important role in the successful progress of the projects and should therefore be closely monitored when developing novel eHealth solutions. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1016/j.ceh.2020.12.002.

Factors associated with physical activity among COPD patients with mild or moderate airflow obstruction.

Physical inactivity is already present among patients with chronic obstructive pulmonary disease (COPD) of mild or moderate airflow obstruction. Most previous studies that reported on determinants of physical activity in COPD included patients with severe COPD. Therefore, the aim of this study was to explore which patient characteristics were related with physical activity in COPD patients with mild or moderate airflow obstruction. Cross-sectional analyses were performed on patients selected from the population-based Netherlands Epidemiology of Obesity study. Patients were included if they had a physician-diagnosed COPD GOLD 0-2 or had newly diagnosed COPD GOLD 1-2. Physical activity was evaluated using the Short Questionnaire to Assess Health-Enhancing Physical Activity (SQUASH) questionnaire and reported in hours per week of metabolic equivalents (MET-h/week). Associations between sociodemographic, lifestyle, clinical and functional characteristics were examined using regression analysis. 323 patients were included in research (77 with physician-diagnosed and 246 with newly diagnosed COPD). We found that physical activity was positively associated with pulmonary function: FEV1 (regression coefficient 0.40 (95% CI 0.09,0.71)) and FVC (regression coefficient 0.34 (95% CI 0.06,0.61)). Physical activity was associated with anxiety (regression coefficient =0.9 (95% CI 0.3,1.6)) only for physician-diagnosed patients. Lung function and anxiety level determine level of physical activity among COPD patients with mild or moderate airflow obstruction. Thus, integrating it into the physical activity plans could help to increase physical activity level of the patients.

Long-term effect of α1-antitrypsin augmentation therapy on the decline of FEV1 in deficient patients: an analysis of the AIR database.

BACKGROUND: Patients with ZZ (Glu342Lys) α-1-antitrypsin deficiency (ZZ-AATD) who received augmentation therapy with α-1-antitrypsin (AAT) in randomised controlled trials over 2-3 years failed to show a significant reduction of the annual decline of forced expiratory volume in 1 s (FEV1). METHODS: To compare the trajectory of FEV1 change during 4 or more years in ZZ-AATD patients with emphysema receiving or not receiving intravenous augmentation therapy, a retrospective analysis of FEV1 values entered in the Alpha-1 International Registry (AIR) of ZZ-AATD patients from five different European countries (Germany, UK, Spain, Italy and the Netherlands) was performed. The post-bronchodilator FEV1 % predicted values for baseline and follow-up over time from patients were analysed using linear mixed effects models. RESULTS: Data of 374 patients were analysed: 246 untreated and 128 treated with intravenous AAT augmentation therapy. The mean±sd follow-up duration of the untreated group was 8.60±3.34 years and 8.59±2.62 years for the treated group. The mixed effects model analysis showed a mean FEV1 decline of -0.931% predicted per year (95% CI -1.144 to -0.718) in the untreated group and a decline of -1.016% predicted per year (95% CI -1.319 to -0.7145) in the treated group. The likelihood ratio test showed no difference between the two groups (p=0.71). CONCLUSION: In our study population, we could not detect a significant difference in the annual decline of FEV1 by AAT augmentation treatment over a mean period of 8.6 years. Other approaches are needed to validate any benefit of augmentation therapy.

SERIES: eHealth in primary care. Part 5: A critical appraisal of five widely used eHealth applications for primary care - opportunities and challenges.

BACKGROUND: Given the pressure on modern healthcare systems, eHealth can offer valuable opportunities. However, understanding the potential and challenges of eHealth in daily practice can be challenging for many general practitioners (GPs) and their staff. OBJECTIVES: To critically appraise five widely used eHealth applications, in relation to safe, evidence-based and high-quality eHealth. Using these applications as examples, we aim to increase understanding of eHealth among GPs and highlight the opportunities and challenges presented by eHealth. DISCUSSION: eHealth applications can support patients while increasing efficiency for GPs. A three-way division (inform, monitor, track; interaction; data utilisation) characterises many eHealth applications, with an increasing degree of complexity depending on the domain. All applications provide information and some have extra functionalities that promote interaction, while data analysis and artificial intelligence may be applied to support or (fully) automate care processes. Applications in the inform domain are relatively easy to use and implement but their impact on clinical outcomes may be limited. More demanding applications, in terms of privacy and ethical aspects, are found in the data utilisation domain and may potentially have a more significant impact on care processes and patient outcomes. When selecting and implementing eHealth applications, we recommend that GPs remain critical regarding preconditions on safe, evidence-based and high-quality eHealth, particularly in the case of more complex applications in the data utilisation domain.

The Challenge of Integrating eHealth Into Health Care: Systematic Literature Review of the Donabedian Model of Structure, Process, and Outcome.

BACKGROUND: Health care organizations are increasingly working with eHealth. However, the integration of eHealth into regular health care is challenging. It requires organizations to change the way they work and their structure and care processes to be adapted to ensure that eHealth supports the attainment of the desired outcomes. OBJECTIVE: The aims of this study are to investigate whether there are identifiable indicators in the structure, process, and outcome categories that are related to the successful integration of eHealth in regular health care, as well as to investigate which indicators of structure and process are related to outcome indicators. METHODS: A systematic literature review was conducted using the Donabedian Structure-Process-Outcome (SPO) framework to identify indicators that are related to the integration of eHealth into health care organizations. Data extraction sheets were designed to provide an overview of the study characteristics, eHealth characteristics, and indicators. The extracted indicators were organized into themes and subthemes of the structure, process, and outcome categories. RESULTS: Eleven studies were included, covering a variety of study designs, diseases, and eHealth tools. All studies identified structure, process, and outcome indicators that were potentially related to the integration of eHealth. The number of indicators found in the structure, process, and outcome categories was 175, 84, and 88, respectively. The themes with the most-noted indicators and their mutual interaction were inner setting (51 indicators, 16 interactions), care receiver (40 indicators, 11 interactions), and technology (38 indicators, 12 interactions)-all within the structure category; health care actions (38 indicators, 15 interactions) within the process category; and efficiency (30 indicators, 15 interactions) within the outcome category. In-depth examination identified four most-reported indicators, namely "deployment of human resources" (n=11), in the inner setting theme within the structure category; "ease of use" (n=16) and "technical issue" (n=10), both in the technology theme within the structure category; and "health logistics" (n=26), in the efficiency theme within the outcome category. CONCLUSIONS: Three principles are important for the successful integration of eHealth into health care. First, the role of the care receiver needs to be incorporated into the organizational structure and daily care process. Second, the technology must be well attuned to the organizational structure and daily care process. Third, the deployment of human resources to the daily care processes needs to be aligned with the desired end results. Not adhering to these points could negatively affect the organization, daily process, or the end results.

The impact of the involvement of a healthcare professional on the usage of an eHealth platform: a retrospective observational COPD study.

BACKGROUND: Ehealth platforms, since the outbreak of COVID-19 more important than ever, can support self-management in patients with Chronic Obstructive Pulmonary Disease (COPD). The aim of this observational study is to explore the impact of healthcare professional involvement on the adherence of patients to an eHealth platform. We evaluated the usage of an eHealth platform by patients who used the platform individually compared with patients in a blended setting, where healthcare professionals were involved. METHODS: In this observational cohort study, log data from September 2011 until January 2018 were extracted from the eHealth platform Curavista. Patients with COPD who completed at least one Clinical COPD Questionnaire (CCQ) were included for analyses (n = 299). In 57% (n = 171) of the patients, the eHealth platform was used in a blended setting, either in hospital (n = 128) or primary care (n = 29). To compare usage of the platform between patients who used the platform independently or with a healthcare professional, we applied propensity score matching and performed adjusted Poisson regression analysis on CCQ-submission rate. RESULTS: Using the eHealth platform in a blended setting was associated with a 3.25 higher CCQ-submission rate compared to patients using the eHealth platform independently. Within the blended setting, the CCQ-submission rate was 1.83 higher in the hospital care group than in the primary care group. CONCLUSION: It is shown that COPD patients used the platform more frequently in a blended care setting compared to patients who used the eHealth platform independently, adjusted for age, sex and disease burden. Blended care seems essential for adherence to eHealth programs in COPD, which in turn may improve self-management.

eHealth Program to Reduce Hospitalizations Due to Acute Exacerbation of Chronic Obstructive Pulmonary Disease: Retrospective Study.

BACKGROUND: Hospitalization for acute exacerbation of chronic obstructive pulmonary disease (COPD) is associated with poor prognosis. eHealth interventions might improve outcomes and decrease costs. OBJECTIVE: This study aimed to evaluate the effect of an eHealth program on COPD hospitalizations and exacerbations. METHODS: This was a real-world study conducted from April 2018 to December 2019 in the Bravis Hospital, the Netherlands. An eHealth program (EmmaCOPD) was offered to COPD patients at risk of exacerbations. EmmaCOPD consisted of an app that used questionnaires (to monitor symptoms) and a step counter (to monitor the number of steps) to detect exacerbations. Patients and their buddies received feedback when their symptoms worsened or the number of steps declined. Generalized estimating equations were used to compare the number of days admitted to the hospital and the total number of exacerbations 12 months before and (max) 18 months after the start of EmmaCOPD. We additionally adjusted for the potential confounders of age, sex, COPD severity, and inhaled corticosteroid use. RESULTS: The 29 included patients had a mean forced expiratory volume in 1 second of 45.5 (SD 17.7) %predicted. In the year before the intervention, the median total number of exacerbations was 2.0 (IQR 2.0-3.0). The median number of hospitalized days was 8.0 days (IQR 6.0-16.5 days). Afterwards, there was a median 1.0 (IQR 0.0-2.0) exacerbation and 2.0 days (IQR 0.0-4.0 days) of hospitalization. After initiation of EmmaCOPD, both the number of hospitalized days and total number of exacerbations decreased significantly (incidence rate ratio 0.209, 95% CI 0.116-0.382; incidence rate ratio 0.310, 95% CI 0.219-0.438). Adjustment for confounders did not affect the results. CONCLUSIONS: The eHealth program seems to reduce the number of total exacerbations and number of days of hospitalization due to exacerbations of COPD.

Online Tool for the Assessment of the Burden of COVID-19 in Patients: Development Study.

BACKGROUND: The impact of COVID-19 has been felt worldwide, yet we are still unsure about its full impact. One of the gaps in our current knowledge relates to the long-term mental and physical impact of the infection on affected individuals. The COVID-19 pandemic hit the Netherlands at the end of February 2020, resulting in over 900,000 people testing positive for the virus, over 24,000 hospitalizations, and over 13,000 deaths by the end of January 2021. Although many patients recover from the acute phase of the disease, experience with other virus outbreaks has raised concerns regarding possible late sequelae of the infection. OBJECTIVE: This study aims to develop an online tool to assess the long-term burden of COVID-19 in patients. METHODS: In this paper, we describe the process of development, assessment, programming, implementation, and use of this new tool: the assessment of burden of COVID-19 (ABCoV) tool. This new tool is based on the well-validated assessment of burden of chronic obstructive pulmonary disease tool. RESULTS: As of January 2021, the new ABCoV tool has been used in an online patient platform by more than 2100 self-registered patients and another 400 patients in a hospital setting, resulting in over 2500 patients. These patients have submitted the ABCoV questionnaire 3926 times. Among the self-registered patients who agreed to have their data analyzed (n=1898), the number of females was high (n=1153, 60.7%), many were medically diagnosed with COVID-19 (n=892, 47.0%), and many were relatively young with only 7.4% (n=141) being older than 60 years. Of all patients that actually used the tool (n=1517), almost one-quarter (n=356, 23.5%) used the tool twice, and only a small group (n=76, 5.0%) used the tool 6 times. CONCLUSIONS: This new ABCoV tool has been broadly and repeatedly used, and may provide insight into the perceived burden of disease, provide direction for personalized aftercare for people post COVID-19, and help us to be prepared for possible future recurrences.

The Computer Will See You Now: Overcoming Barriers to Adoption of Computer-Assisted History Taking (CAHT) in Primary Care.

Patient health information is increasingly collected through multiple modalities, including electronic health records, wearables, and connected devices. Computer-assisted history taking could provide an additional channel to collect highly relevant, comprehensive, and accurate patient information while reducing the burden on clinicians and face-to-face consultation time. Considering restrictions to consultation time and the associated negative health outcomes, patient-provided health data outside of consultation can prove invaluable in health care delivery. Over the years, research has highlighted the numerous benefits of computer-assisted history taking; however, the limitations have proved an obstacle to adoption. In this viewpoint, we review these limitations under 4 main categories (accessibility, affordability, accuracy, and acceptability) and discuss how advances in technology, computing power, and ubiquity of personal devices offer solutions to overcoming these.

Socioeconomic status is not associated with the delivery of care in people with diabetes but does modify HbA1c levels: An observational cohort study (Elzha-cohort 1).

BACKGROUND: Structured primary diabetes care within a collectively supported setting is associated with better monitoring of biomedical and lifestyle-related target indicators amongst people with type 2 diabetes and with better HbA1c levels. Whether socioeconomic status affects the delivery of care in terms of monitoring and its association with HbA1c levels within this approach, is unclear. This study aims to understand whether, within a structured care approach, (1) socioeconomic categories differ concerning diabetes monitoring as recommended; (2) socioeconomic status modifies the association between monitoring as recommended and HbA1c. METHODS: Observational real-life cohort study with primary care registry data from general practitioners within diverse socioeconomic areas, who are supported with the implementation of structured diabetes care. People with type 2 diabetes mellitus were offered quarterly diabetes consultations. "Monitoring as recommended" by professional guidelines implied minimally one annual registration of HbA1c, systolic blood pressure, LDL, BMI, smoking behaviour and physical activity. Regarding socioeconomic status, deprived, advantageous urban and advantageous suburban categories were compared to the intermediate category concerning (a) recommended monitoring; (b) association between recommended monitoring and HbA1c. RESULTS: Aim 1 (n = 13 601 people): Compared to the intermediate socioeconomic category, no significant differences in odds of being monitored as recommended were found in the deprived (OR 0.45 (95% CI 0.19-1.08)), advantageous urban (OR 1.27 (95% CI 0.46-3.54)) and advantageous suburban (OR 2.32 (95% CI 0.88-6.08)) categories. Aim 2 (n = 11 164 people): People with recommended monitoring had significantly lower HbA1c levels than incompletely monitored people (-2.4 (95% CI -2.9; -1.8) mmol/mol). SES modified monitoring-related HbA1c differences, which were significantly higher in the deprived (-3.3 (95% CI -4.3; -2.4) mmol/mol) than the intermediate category (-1.3 (95% CI -2.2; -0.4) mmol/mol). CONCLUSIONS: Within a structured diabetes care setting, socioeconomic status is not associated with recommended monitoring. Socioeconomic differences in the association between recommended monitoring and HbA1c levels advocate further exploration of practice and patient-related factors contributing to appropriate monitoring and for care adjustment to population needs.

Correction: Online Guide for Electronic Health Evaluation Approaches: Systematic Scoping Review and Concept Mapping Study.

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Online Guide for Electronic Health Evaluation Approaches: Systematic Scoping Review and Concept Mapping Study.

BACKGROUND: Despite the increase in use and high expectations of digital health solutions, scientific evidence about the effectiveness of electronic health (eHealth) and other aspects such as usability and accuracy is lagging behind. eHealth solutions are complex interventions, which require a wide array of evaluation approaches that are capable of answering the many different questions that arise during the consecutive study phases of eHealth development and implementation. However, evaluators seem to struggle in choosing suitable evaluation approaches in relation to a specific study phase. OBJECTIVE: The objective of this project was to provide a structured overview of the existing eHealth evaluation approaches, with the aim of assisting eHealth evaluators in selecting a suitable approach for evaluating their eHealth solution at a specific evaluation study phase. METHODS: Three consecutive steps were followed. Step 1 was a systematic scoping review, summarizing existing eHealth evaluation approaches. Step 2 was a concept mapping study asking eHealth researchers about approaches for evaluating eHealth. In step 3, the results of step 1 and 2 were used to develop an "eHealth evaluation cycle" and subsequently compose the online "eHealth methodology guide." RESULTS: The scoping review yielded 57 articles describing 50 unique evaluation approaches. The concept mapping study questioned 43 eHealth researchers, resulting in 48 unique approaches. After removing duplicates, 75 unique evaluation approaches remained. Thereafter, an "eHealth evaluation cycle" was developed, consisting of six evaluation study phases: conceptual and planning, design, development and usability, pilot (feasibility), effectiveness (impact), uptake (implementation), and all phases. Finally, the "eHealth methodology guide" was composed by assigning the 75 evaluation approaches to the specific study phases of the "eHealth evaluation cycle." CONCLUSIONS: Seventy-five unique evaluation approaches were found in the literature and suggested by eHealth researchers, which served as content for the online "eHealth methodology guide." By assisting evaluators in selecting a suitable evaluation approach in relation to a specific study phase of the "eHealth evaluation cycle," the guide aims to enhance the quality, safety, and successful long-term implementation of novel eHealth solutions.

SERIES: eHealth in primary care. Part 3: eHealth education in primary care.

BACKGROUND: Education is essential to the integration of eHealth into primary care, but eHealth is not yet embedded in medical education. OBJECTIVES: In this opinion article, we aim to support organisers of Continuing Professional Development (CPD) and teachers delivering medical vocational training by providing recommendations for eHealth education. First, we describe what is required to help primary care professionals and trainees learn about eHealth. Second, we elaborate on how eHealth education might be provided. DISCUSSION: We consider four essential topics. First, an understanding of existing evidence-based eHealth applications and conditions for successful development and implementation. Second, required digital competencies of providers and patients. Third, how eHealth changes patient-provider and provider-provider relationships and finally, understanding the handling of digital data. Educational activities to address these topics include eLearning, blended learning, courses, simulation exercises, real-life practice, supervision and reflection, role modelling and community of practice learning. More specifically, a CanMEDS framework aimed at defining curriculum learning goals can support eHealth education by describing roles and required competencies. Alternatively, Kern's conceptual model can be used to design eHealth training programmes that match the educational needs of the stakeholders using eHealth. CONCLUSION: Vocational and CPD training in General Practice needs to build on eHealth capabilities now. We strongly advise the incorporation of eHealth education into vocational training and CPD activities, rather than providing it as a separate single module. How learning goals and activities take shape and how competencies are evaluated clearly requires further practice, evaluation and study.

Self-care of patients with type 2 diabetes mellitus over the course of illness: implications for tailoring support.

PURPOSE: Type 2 diabetes requires patients to make lifestyle changes and perform daily self-care. To determine at what stages patients may need particular self-management support, we examined (1) whether patients' performance of self-care related to their diabetes duration, and (2) whether illness characteristics (treatment and complications) and diabetes-related distress influenced this relationship. METHODS: Cross-sectional data from 590 type 2 diabetes patients were analysed through linear and logistic regression analysis. Self-care behaviours were assessed by the revised Summary of Diabetes Self-Care Activities (SDSCA) measure. Diabetes duration (model 1), treatment and complications (model 2), and distress, as assessed by the Problem Areas In Diabetes (PAID) scale (model 3), were stepwise included. Sociodemographic characteristics were added to all models to account for confounding. RESULTS: Patients with a longer history of diabetes were less physically active, but monitored their blood glucose levels more frequently than more recently diagnosed patients. These relationships were mediated by the presence of complications and the use of insulin, with lower levels of physical activity being found among patients with macrovascular complications and higher frequencies of glucose monitoring among patients on insulin. All predictors together explained maximally 5% of the variance in self-care, except for glucose monitoring (37%) and smoking (11%). CONCLUSION: Type 2 diabetes patients' self-care activity changes over the course of illness. To provide tailored self-management support, diabetes care providers should take into account patients' phase of illness, including their treatment and complications, as well as their personal characteristics and distress level.

Exploring characteristics of COPD patients with clinical improvement after integrated disease management or usual care: post-hoc analysis of the RECODE study.

BACKGROUND: The cluster randomized controlled trial on (cost-)effectiveness of integrated chronic obstructive pulmonary disease (COPD) management in primary care (RECODE) showed that integrated disease management (IDM) in primary care had no effect on quality of life (QOL) in COPD patients compared with usual care (guideline-supported non-programmatic care). It is possible that only a subset of COPD patients in primary care benefit from IDM. We therefore examined which patients benefit from IDM, and whether patient characteristics predict clinical improvement over time. METHOD: Post-hoc analyses of the RECODE trial among 1086 COPD patients. Logistic regression analyses were performed with baseline characteristics as predictors to examine determinants of improvement in QOL, defined as a minimal decline in Clinical COPD Questionnaire (CCQ) of 0.4 points after 12 and 24 months of IDM. We also performed moderation analyses to examine whether predictors of clinical improvement differed between IDM and usual care. RESULTS: Regardless of treatment type, more severe dyspnea (MRC) was the most important predictor of clinically improved QOL at 12 and 24 months, suggesting that these patients have most room for improvement. Clinical improvement with IDM was associated with female gender (12-months) and being younger (24-months), and improvement with usual care was associated with having a depression (24-months). CONCLUSIONS: More severe dyspnea is a key predictor of improved QOL in COPD patients over time. More research is needed to replicate patient characteristics associated with clinical improvement with IDM, such that IDM programs can be offered to patients that benefit the most, and can potentially be adjusted to meet the needs of other patient groups as well. TRIAL REGISTRATION: Netherlands Trial Register, NTR2268. Registered 31 March 2010.

Cross-Sectional Analysis of University Students' Health Using a Digitised Health Survey.

University student years are a particularly influential period, during which time students may adopt negative behaviours that set the precedent for health outcomes in later years. This study utilised a newly digitised health survey implemented during health screening at a university in Singapore to capture student health data. The aim of this study was to analyze the health status of this Asian university student population. A total of 535 students were included in the cohort, and a cross-sectional analysis of student health was completed. Areas of concern were highlighted in student's body weight, visual acuity, and binge drinking. A large proportion of students were underweight (body mass index (BMI) < 18.5)-18.9% of females and 10.6% of males-and 7% of males were obese (BMI > 30). Although the overall prevalence of alcohol use was low in this study population, 9% of females and 8% of males who consumed alcohol had hazardous drinking habits. Around 16% of these students (male and female combined) typically drank 3-4 alcoholic drinks each occasion. The prevalence of mental health conditions reported was very low (<1%). This study evaluated the results from a digitised health survey implemented into student health screening to capture a comprehensive health history. The results reveal potential student health concerns and offer the opportunity to provide more targeted student health campaigns to address these.