Background: A growing body of evidence supports the potential effectiveness of electronic health (eHealth) self management interventions in improving disease self-management skills and health... Show moreBackground: A growing body of evidence supports the potential effectiveness of electronic health (eHealth) self management interventions in improving disease self-management skills and health outcomes of patients suffering from chronic kidney disease (CKD). However, current research on CKD eHealth self-management interventions has almost exclusively focused on high-income, western countries. Objective: To inform the adaptation of a tailored eHealth self-management intervention for patients with CKD in China based on the Dutch Medical Dashboard (MD) intervention, we examined the perceptions, attitudes and needs of Chinese patients with CKD and health care professionals (HCPs) towards eHealth based (self -management) interventions in general and the Dutch MD intervention in specific. Methods: We conducted a basic interpretive, cross-sectional qualitative study comprising semi-structured interviews with 11 patients with CKD and 10 HCPs, and 2 focus group discussions with 9 patients with CKD. This study was conducted in the First Affiliated Hospital of Zhengzhou University in China. Data collection continued until data saturation was reached. All data were transcribed verbatim and analyzed using a framework approach. Results: Three themes emerged: (1) experience with eHealth in CKD (self-management), (2) needs for supporting CKD self-management with the use of eHealth, and (3) adaptation and implementation of the Dutch MD intervention in China. Both patients and HCPs had experience with and solely mentioned eHealth to 'inform, monitor and track' as potentially relevant interventions to support CKD self-management, not those to support 'interaction' and 'data utilization'. Factors reported to influence the implementation of CKD eHealth self-management interventions included information barriers (i.e. quality and consistency of the disease-related information obtained via eHealth), perceived trustworthiness and safety of eHealth sources, clinical compatibility and complexity of eHealth, time constraints and eHealth literacy. Moreover, patients and HCPs expressed that eHealth interventions should support CKD self-management by improving the access to reliable and relevant disease related knowledge and optimizing the timeliness and quality of patient and HCPs interactions. Finally, suggestions to adaptation and implementation of the Dutch MD intervention in China were mainly related to improving the intervention functionalities and content of MD such as addressing the complexity of the platform and compatibility with HCPs' workflows. Conclusions: The identified perceptions, attitudes and needs towards eHealth self-management interventions in Chinese settings should be considered by researchers and intervention developers to adapt a tailored eHealth self management intervention for patients with CKD in China. In more detail, future research needs to engage in co creation processes with vulnerable groups during eHealth development and implementation, increase eHealth literacy and credibility of eHealth (information resource), ensure eHealth to be easy to use and well-integrated into HCPs' workflows. Show less
Shen, H.X.; Kleij, R. van der; Boog, P.J.M. van der; Wang, W.J.; Song, X.Y.; Li, Z.Y.; ... ; Chavannes, N. 2022
BackgroundA growing body of evidence supports the potential effectiveness of electronic health (eHealth) self-management interventions in improving disease self-management skills and health... Show moreBackgroundA growing body of evidence supports the potential effectiveness of electronic health (eHealth) self-management interventions in improving disease self-management skills and health outcomes of patients suffering from chronic kidney disease (CKD). However, current research on CKD eHealth self-management interventions has almost exclusively focused on high-income, western countries.ObjectiveTo inform the adaptation of a tailored eHealth self-management intervention for patients with CKD in China based on the Dutch Medical Dashboard (MD) intervention, we examined the perceptions, attitudes and needs of Chinese patients with CKD and health care professionals (HCPs) towards eHealth based (self-management) interventions in general and the Dutch MD intervention in specific.MethodsWe conducted a basic interpretive, cross-sectional qualitative study comprising semi-structured interviews with 11 patients with CKD and 10 HCPs, and 2 focus group discussions with 9 patients with CKD. This study was conducted in the First Affiliated Hospital of Zhengzhou University in China. Data collection continued until data saturation was reached. All data were transcribed verbatim and analyzed using a framework approach.ResultsThree themes emerged: (1) experience with eHealth in CKD (self-management), (2) needs for supporting CKD self-management with the use of eHealth, and (3) adaptation and implementation of the Dutch MD intervention in China. Both patients and HCPs had experience with and solely mentioned eHealth to ‘inform, monitor and track’ as potentially relevant interventions to support CKD self-management, not those to support ‘interaction’ and ‘data utilization’. Factors reported to influence the implementation of CKD eHealth self-management interventions included information barriers (i.e. quality and consistency of the disease-related information obtained via eHealth), perceived trustworthiness and safety of eHealth sources, clinical compatibility and complexity of eHealth, time constraints and eHealth literacy. Moreover, patients and HCPs expressed that eHealth interventions should support CKD self-management by improving the access to reliable and relevant disease related knowledge and optimizing the timeliness and quality of patient and HCPs interactions. Finally, suggestions to adaptation and implementation of the Dutch MD intervention in China were mainly related to improving the intervention functionalities and content of MD such as addressing the complexity of the platform and compatibility with HCPs’ workflows.ConclusionsThe identified perceptions, attitudes and needs towards eHealth self-management interventions in Chinese settings should be considered by researchers and intervention developers to adapt a tailored eHealth self-management intervention for patients with CKD in China. In more detail, future research needs to engage in co-creation processes with vulnerable groups during eHealth development and implementation, increase eHealth literacy and credibility of eHealth (information resource), ensure eHealth to be easy to use and well-integrated into HCPs’ workflows. Show less
Shen, H.X.; Kleij, R. van der; Boog, P.J.M. van der; Wang, W.J.; Song, X.Y.; Li, Z.Y.; ... ; Chavannes, N. 2022
BackgroundA growing body of evidence supports the potential effectiveness of electronic health (eHealth) self-management interventions in improving disease self-management skills and health... Show moreBackgroundA growing body of evidence supports the potential effectiveness of electronic health (eHealth) self-management interventions in improving disease self-management skills and health outcomes of patients suffering from chronic kidney disease (CKD). However, current research on CKD eHealth self-management interventions has almost exclusively focused on high-income, western countries.ObjectiveTo inform the adaptation of a tailored eHealth self-management intervention for patients with CKD in China based on the Dutch Medical Dashboard (MD) intervention, we examined the perceptions, attitudes and needs of Chinese patients with CKD and health care professionals (HCPs) towards eHealth based (self-management) interventions in general and the Dutch MD intervention in specific.MethodsWe conducted a basic interpretive, cross-sectional qualitative study comprising semi-structured interviews with 11 patients with CKD and 10 HCPs, and 2 focus group discussions with 9 patients with CKD. This study was conducted in the First Affiliated Hospital of Zhengzhou University in China. Data collection continued until data saturation was reached. All data were transcribed verbatim and analyzed using a framework approach.ResultsThree themes emerged: (1) experience with eHealth in CKD (self-management), (2) needs for supporting CKD self-management with the use of eHealth, and (3) adaptation and implementation of the Dutch MD intervention in China. Both patients and HCPs had experience with and solely mentioned eHealth to ‘inform, monitor and track’ as potentially relevant interventions to support CKD self-management, not those to support ‘interaction’ and ‘data utilization’. Factors reported to influence the implementation of CKD eHealth self-management interventions included information barriers (i.e. quality and consistency of the disease-related information obtained via eHealth), perceived trustworthiness and safety of eHealth sources, clinical compatibility and complexity of eHealth, time constraints and eHealth literacy. Moreover, patients and HCPs expressed that eHealth interventions should support CKD self-management by improving the access to reliable and relevant disease related knowledge and optimizing the timeliness and quality of patient and HCPs interactions. Finally, suggestions to adaptation and implementation of the Dutch MD intervention in China were mainly related to improving the intervention functionalities and content of MD such as addressing the complexity of the platform and compatibility with HCPs’ workflows.ConclusionsThe identified perceptions, attitudes and needs towards eHealth self-management interventions in Chinese settings should be considered by researchers and intervention developers to adapt a tailored eHealth self-management intervention for patients with CKD in China. In more detail, future research needs to engage in co-creation processes with vulnerable groups during eHealth development and implementation, increase eHealth literacy and credibility of eHealth (information resource), ensure eHealth to be easy to use and well-integrated into HCPs’ workflows. Show less
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... Show moreBackground: 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. Show less
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... Show moreBackground: 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. Show less
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... Show moreBackground: 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. Show less
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... Show moreBackground: 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. Show less
Deursen, L. van; Versluis, A.; Vaart, R. van der; Standaar, L.; Struijs, J.; Chavannes, N.; Aardoom, J.J. 2022
Background: Globally, the burden of cancer on population health is growing. Recent trends such as increasing survival rates have resulted in a need to adapt cancer care to ensure a good care... Show moreBackground: Globally, the burden of cancer on population health is growing. Recent trends such as increasing survival rates have resulted in a need to adapt cancer care to ensure a good care experience and manageable expenditures. eHealth is a promising way to increase the quality of cancer care and support patients and survivors. Objective: The aim of this systematic review was 2-fold. First, we aimed to provide an overview of eHealth interventions and their characteristics for Dutch patients with and survivors of cancer. Second, we aimed to provide an overview of the empirical evidence regarding the impact of eHealth interventions in cancer care on population health, quality of care, and per capita costs (the Triple Aim domains). Methods: The electronic databases Web of Science, PubMed, Cochrane, and Ovid PsycINFO were searched using 3 key search themes: eHealth interventions, cancer care, and the Netherlands. The identified interventions were classified according to predetermined criteria describing the intervention characteristics (eg, type, function, and target population). Their impact was subsequently examined using the Triple Aim framework. Results: A total of 38 interventions were identified. Most of these were web portals or web applications functioning to inform and self-manage, and target psychosocial factors or problems. Few interventions have been tailored to age, disease severity, or gender. The results of this study indicate that eHealth interventions could positively affect sleep quality, fatigue, and physical activity of patients with and survivors of cancer. Inconclusive results were found regarding daily functioning and quality of life, psychological complaints, and psychological adjustment to the disease. Conclusions: eHealth can improve outcomes in the Triple Aim domains, particularly in the population health and quality of care domains. Cancer-related pain and common symptoms of active treatment were not targeted in the included interventions and should receive more attention. Further research is needed to fully understand the impact of eHealth interventions in cancer care on participation, accessibility, and costs. The latter can be examined in economic evaluations by comparing eHealth interventions with care as usual. (JMIR Cancer 2022;8(2):e37093) doi: 10.2196/37093 Show less
Asthma and chronic obstructive pulmonary diseases (COPD) are highly prevalent chronic lung diseases that require ongoing self-management, which itself is often suboptimal. Therefore, telemonitoring... Show moreAsthma and chronic obstructive pulmonary diseases (COPD) are highly prevalent chronic lung diseases that require ongoing self-management, which itself is often suboptimal. Therefore, telemonitoring has been used to help patients measure their symptoms, share data with healthcare providers and receive education and feedback to improve disease management. In this study, we conducted a narrative review of recent evidence on the effectiveness of telemonitoring for asthma and COPD in adults. Of the thirteen identified studies, eleven focused on COPD and two focused on asthma. All studies were reviewed, and effects were compared between intervention and care as usual groups. Of the study interventions, seven showed a positive outcome on at least one outcome measure, and six had no significant results on any of the outcome measures. All of the interventions with a positive outcome included an educational component, while only one of the six interventions without positive outcomes included an educational component. We conclude that telemonitoring interventions for asthma and COPD seem more effective if they included an educational component regarding different aspects of self-management. Show less
Car, L.T.; Kyaw, B.M.; Panday, R.S.N.; Kleij, R. van der; Chavannes, N.; Majeed, A.; Car, J. 2021
Background: Medical schools worldwide are accelerating the introduction of digital health courses into their curricula. The COVID-19 pandemic has contributed to this swift and widespread transition... Show moreBackground: Medical schools worldwide are accelerating the introduction of digital health courses into their curricula. The COVID-19 pandemic has contributed to this swift and widespread transition to digital health and education. However, the need for digital health competencies goes beyond the COVID-19 pandemic because they are becoming essential for the delivery of effective, efficient, and safe care.Objective: This review aims to collate and analyze studies evaluating digital health education for medical students to inform the development of future courses and identify areas where curricula may need to be strengthened.Methods: We carried out a scoping review by following the guidance of the Joanna Briggs Institute, and the results were reported in accordance with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. We searched 6 major bibliographic databases and gray literature sources for articles published between January 2000 and November 2019. Two authors independently screened the retrieved citations and extracted the data from the included studies. Discrepancies were resolved by consensus discussions between the authors. The findings were analyzed using thematic analysis and presented narratively.Results: A total of 34 studies focusing on different digital courses were included in this review. Most of the studies (22/34, 65%) were published between 2010 and 2019 and originated in the United States (20/34, 59%). The reported digital health courses were mostly elective (20/34, 59%), were integrated into the existing curriculum (24/34, 71%), and focused mainly on medical informatics (17/34, 50%). Most of the courses targeted medical students from the first to third year (17/34, 50%), and the duration of the courses ranged from 1 hour to 3 academic years. Most of the studies (22/34, 65%) reported the use of blended education. A few of the studies (6/34, 18%) delivered courses entirely digitally by using online modules, offline learning, massive open online courses, and virtual patient simulations. The reported courses used various assessment approaches such as paper-based assessments, in-person observations, and online assessments. Most of the studies (30/34, 88%) evaluated courses mostly by using an uncontrolled before-and-after design and generally reported improvements in students' learning outcomes.Conclusions: Digital health courses reported in literature are mostly elective, focus on a single area of digital health, and lack robust evaluation. They have diverse delivery, development, and assessment approaches. There is an urgent need for high-quality studies that evaluate digital health education. Show less
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... Show moreBackground: 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. Show less
Shen, H.X.; Kleij, R. van der; Boog, P.J.M. van der; Song, X.Y.; Wang, W.J.; Zhang, T.T.; ... ; Chavannes, N. 2020
Background: Chronic kidney disease (CKD) is a significant public health concern. In patients with CKD, interventions that support disease self-management have shown to improve health status and... Show moreBackground: Chronic kidney disease (CKD) is a significant public health concern. In patients with CKD, interventions that support disease self-management have shown to improve health status and quality of life. At the moment, the use of electronic health (eHealth) technology in self-management interventions is becoming more and more popular. Evidence suggests that eHealth-based self-management interventions can improve health-related outcomes of patients with CKD. However, knowledge of the implementation and effectiveness of such interventions in general, and in China in specific, is still limited. This study protocol aims to develop and tailor the evidence-based Dutch 'Medical Dashboard' eHealth self-management intervention for patients suffering from CKD in China and evaluate its implementation process and effectiveness.Methods: To develop and tailor a Medical Dashboard intervention for the Chinese context, we will use an Intervention Mapping (IM) approach. A literature review and mixed-method study will first be conducted to examine the needs, beliefs, perceptions of patients with CKD and care providers towards disease (self-management) and eHealth (self-management) interventions (IM step 1). Based on the results of step 1, we will specify outcomes, performance objectives, and determinants, select theory-based methods and practical strategies. Knowledge obtained from prior results and insights from stakeholders will be combined to tailor the core interventions components of the 'Medical Dashboard' self-management intervention to the Chinese context (IM step 2-5). Then, an intervention and implementation plan will be developed. Finally, a 9-month hybrid type 2 trial design will be employed to investigate the effectiveness of the intervention using a cluster randomized controlled trial with two parallel arms, and the implementation integrity (fidelity) and determinants of implementation (IM step 6).Discussion: Our study will result in the delivery of a culturally tailored, standardized eHealth self-management intervention for patients with CKD in China, which has the potential to optimize patients' self-management skills and improve health status and quality of life. Moreover, it will inform future research on the tailoring and translation of evidence-based eHealth self-management interventions in various contexts. Show less
