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.

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.

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.

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 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.

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.

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.

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.

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.

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.

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.

Association between GP participation in a primary care group and monitoring of biomedical and lifestyle target indicators in people with type 2 diabetes: a cohort study (ELZHA cohort-1).

OBJECTIVE: Whether care group participation by general practitioners improves delivery of diabetes care is unknown. Using 'monitoring of biomedical and lifestyle target indicators as recommended by professional guidelines' as an operationalisation for quality of care, we explored whether (1) in new practices monitoring as recommended improved a year after initial care group participation (aim 1); (2) new practices and experienced practices differed regarding monitoring (aim 2). DESIGN: Observational, real-life cohort study. SETTING: Primary care registry data from Eerstelijns Zorggroep Haaglanden (ELZHA) care group. PARTICIPANTS: Aim 1: From six new practices (n=538 people with diabetes) that joined care group ELZHA in January 2014, two practices (n=211 people) were excluded because of missing baseline data; four practices (n=182 people) were included. Aim 2: From all six new practices (n=538 people), 295 individuals were included. From 145 experienced practices (n=21 465 people), 13 744 individuals were included. EXPOSURE: Care group participation includes support by staff nurses on protocolised diabetes care implementation and availability of a system providing individual monitoring information. 'Monitoring as recommended' represented minimally one annual registration of each biomedical (HbA1c, systolic blood pressure, low-density lipoprotein) and lifestyle-related target indicator (body mass index, smoking behaviour, physical exercise). PRIMARY OUTCOME MEASURES: Aim 1: In new practices, odds of people being monitored as recommended in 2014 were compared with baseline (2013). Aim 2: Odds of monitoring as recommended in new and experienced practices in 2014 were compared. RESULTS: Aim 1: After 1-year care group participation, odds of being monitored as recommended increased threefold (OR 3.00, 95% CI 1.84 to 4.88, p<0.001). Aim 2: Compared with new practices, no significant differences in the odds of monitoring as recommended were found in experienced practices (OR 1.21, 95% CI 0.18 to 8.37, p=0.844). CONCLUSIONS: We observed a sharp increase concerning biomedical and lifestyle monitoring as recommended after 1-year care group participation, and subsequently no significant difference between new and experienced practices-indicating that providing diabetes care within a collective approach rapidly improves registration of care.

SERIES: eHealth in primary care. Part 2: Exploring the ethical implications of its application in primary care practice.

Background: eHealth promises to increase self-management and personalised medicine and improve cost-effectiveness in primary care. Paired with these promises are ethical implications, as eHealth will affect patients' and primary care professionals' (PCPs) experiences, values, norms, and relationships.Objectives: We argue what ethical implications related to the impact of eHealth on four vital aspects of primary care could (and should) be anticipated.Discussion: (1) EHealth influences dealing with predictive and diagnostic uncertainty. Machine-learning based clinical decision support systems offer (seemingly) objective, quantified, and personalised outcomes. However, they also introduce new loci of uncertainty and subjectivity. The decision-making process becomes opaque, and algorithms can be invalid, biased, or even discriminatory. This has implications for professional responsibilities and judgments, justice, autonomy, and trust. (2) EHealth affects the roles and responsibilities of patients because it can stimulate self-management and autonomy. However, autonomy can also be compromised, e.g. in cases of persuasive technologies and eHealth can increase existing health disparities. (3) The delegation of tasks to a network of technologies and stakeholders requires attention for responsibility gaps and new responsibilities. (4) The triangulate relationship: patient-eHealth-PCP requires a reconsideration of the role of human interaction and 'humanness' in primary care as well as of shaping Shared Decision Making.Conclusion: Our analysis is an essential first step towards setting up a dedicated ethics research agenda that should be examined in parallel to the development and implementation of eHealth. The ultimate goal is to inspire the development of practice-specific ethical recommendations.

A national eHealth vision developed by University Medical Centres: A concept mapping study.

BACKGROUND: EHealth solutions are envisaged to contribute significantly to a sustainable healthcare system. Between 2016 and 2018 the eight Dutch University Medical Centers (UMCs) received Dutch Government's funding to undertake research into the clinical impact, cost-effectiveness and ethical consideration of eHealth. The UMCs collaborated within the consortium 'Citrien fund (CF) program eHealth' and found that, in order to increase the value of eHealth in routine care, a national vision on eHealth developed by the UMCs was warranted. OBJECTIVE: The objective of this paper was to elucidate the process of the 'Netherlands Federation of UMCs (NFU) eHealth vision' development by describing the results of the performed concept mapping study. METHODS: A concept mapping approach was followed. Sixteen members of the steering committee of the CF program eHealth were selected as participants. First, each member selected relevant objectives from the eight individual UMC eHealth vision documents, which was to be incorporated into the overall 'NFU eHealth vision'. Second, objectives were rated for necessary to be included in the vision document and the need to achieve the objective within five years. Thereafter, the objectives were sorted into self-created thematic clusters. And finally, the concept map with the thematic clusters and corresponding objectives was discussed with the steering committee to determine the major themes of the 'NFU eHealth vision'. RESULTS: 38 objectives were determined by the steering committee and grouped into the following 6 thematic clusters on the concept map: 'patient participation and empowerment'; 'infrastructure'; 'education and research'; 'multi-disciplinary care'; 'organisational restructuring'; and 'essential conditions for development of eHealth solutions'. After discussing the concept mapping results with the steering committee, the following five major themes were determined to be addressed in the vision document: 'patient and caregiver'; 'research and innovation'; 'education'; 'organisation of care'; and 'essential conditions for development of eHealth solutions'. CONCLUSION: Concept mapping was successfully applied to conceptualise the different values and opinions of the eight Dutch UMCs in order to develop a national vision on eHealth. This vision document will give direction to the development, evaluation and implementation of eHealth in the eight Dutch UMCs and their adherent healthcare providers.

SERIES: eHealth in primary care. Part 1: Concepts, conditions and challenges.

Primary care is challenged to provide high quality, accessible and affordable care for an increasingly ageing, complex, and multimorbid population. To counter these challenges, primary care professionals need to take up new and innovative practices, including eHealth. eHealth applications hold the promise to overcome some difficulties encountered in the care of people with complex medical and social needs in primary care. However, many unanswered questions regarding (cost) effectiveness, integration with healthcare, and acceptability to patients, caregivers, and professionals remain to be elucidated. What conditions need to be met? What challenges need to be overcome? What downsides must be dealt with? This first paper in a series on eHealth in primary care introduces basic concepts and examines opportunities for the uptake of eHealth in primary care. We illustrate that although the potential of eHealth in primary care is high, several conditions need to be met to ensure that safe and high-quality eHealth is developed for and implemented in primary care. eHealth research needs to be optimized; ensuring evidence-based eHealth is available. Blended care, i.e. combining face-to-face care with remote options, personalized to the individual patient should be considered. Stakeholders need to be involved in the development and implementation of eHealth via co-creation processes, and design should be mindful of vulnerable groups and eHealth illiteracy. Furthermore, a global perspective on eHealth should be adopted, and eHealth ethics, patients' safety and privacy considered.

Effects of use of an eHealth platform e-Vita for COPD patients on disease specific quality of life domains.

BACKGROUND: Integrated disease management with self-management for Chronic Obstructive Pulmonary Disease (COPD) is effective to improve clinical outcomes. eHealth can improve patients' involvement to be able to accept and maintain a healthier lifestyle. Eventhough there is mixed evidence of the impact of eHealth on quality of life (QoL) in different settings. AIM: The primary aim of the e-Vita-COPD-study was to investigate the effect of use of eHealth patient platforms on disease specific QoL of COPD patients. METHODS: We evaluated the impact of an eHealth platform on disease specific QoL measured with the clinical COPD questionnaire (CCQ), including subscales of symptoms, functional state and mental state. Interrupted time series (ITS) design was used to collect CCQ data at multiple time points. Multilevel linear regression modelling was used to compare trends in CCQ before and after the intervention. RESULTS: Of 742 invited COPD patients, 244 signed informed consent. For the analyses, we only included patients who actually used the eHealth platform (n = 123). The decrease of CCQ-symptoms was 0.20% before the intervention and 0.27% after the intervention; this difference in slopes was statistically significant (P = 0.027). The decrease of CCQ-mental was 0.97% before the intervention and after the intervention there was an increase of 0.017%; this difference was statistically significant (P = 0.01). No significant difference was found in the slopes of CCQ (P = 0.12) and CCQ-function (P = 0.11) before and after the intervention. CONCLUSION: The e-Vita eHealth platform had a potential beneficial impact on the CCQ-symptoms of COPD patients, but not on functional state. The CCQ-mental state remained stable after the intervention, but this was a deterioration compared to the improving situation before the start of the eHealth platform. Therefore, health care providers should be aware that, although symptoms improve, there might be a slight increase in anxiety and depression after introducing an eHealth intervention to support self-management. TRIAL REGISTRATION: Our study is registered in the Dutch Trial Register (national registration of clinical trails, mandatory for publication) with number NTR4098 and can be found at http://www.trialregister.nl/trial/3936 . Date registered: 2013-07-31. First participant: 2014-01-01.