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.

Background Communicating laboratory test results online has several advantages for patients, such as improving clinical efficiency and accessibility, thereby helping patients to take an active role in managing their health. Objective This study aimed to investigate the experiences and self-efficacy of patients using an online patient portal that communicates laboratory test results. Methods We used the online-administered eHealth Impact Questionnaire to explore patients’ attitudes toward the portal. Patients visiting the portal were asked to complete the questionnaire. The subscale Information and Presentation 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. We used a cutoff score of 65 or greater to determine whether the portal was rated positively. Results The questionnaire was completed by 354 of 13,907 patients who viewed their laboratory results in the patient portal, with a response rate of 2.55%. The mean Information and Presentation score was 67.70 (SD 13.12) and the mean Motivation and Confidence to Act score was 63.59 (SD 16.22). We found a positive, significant correlation between the 2 subscales (r345=.77, P<.001). Conclusions Patients participating in the study rated the usability of the portal positively. However, the portal only slightly helped patients to take an active role in managing their own health. The low response rate precludes generalization of the results. Future research should examine avenues to further increase patients’ self-efficacy and study whether portal acceptability differs in subgroups. Patient portals conveying laboratory test results in understandable language seem usable and potentially provide a viable way to help patients take a more active role in managing their own health.

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.

BACKGROUND Healthcare organisations increasingly work with eHealth. However, the integration of eHealth into regular healthcare is challenging. It requires organisations to change the way they work. The organisation’s structure and care processes need to be adapted to ensure that eHealth supports the attainment of the desired outcomes. OBJECTIVE The aims of this study were to investigate whether there are identifiable indicators in the structure, process and outcome categories related to a successful integration of eHealth in regular healthcare, and to investigate which indicators of structure and process are related to outcome indicators. METHODS A systematic literature review was conducted, using Donabedian’s Structure-Process-Outcome framework (SPO), to identify indicators that are related to the integration of eHealth into healthcare organisations. Data extraction sheets were designed to provide an overview of the study characteristics, the eHealth characteristics, and the indicators. The extracted indicators were organised 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 structure, process, outcomes was respectively 175, 84, and 88. The themes with the most-noted indicators and their mutual interaction were the inner setting (51 indicators, 16 interactions), care receiver (40 indicators, 11 interactions) and technology (38 indicators, 12 interactions) themes, all three in the structure category, the healthcare actions theme (38 indicators, 15 interactions) in the process category and the efficiency theme (30 indicators, 15 interactions) in the outcome category. In-depth examination showed four most-reported indicators, namely indicator ‘deployment of human resources’ (n=11) of the inner setting theme in the structure category, the ‘ease of use’ (n=16) and ‘technical issue’ (n=10) indicators, both in the technology theme within the structure category, and the ‘health logistics’ (n=26) indicator in the efficiency theme within the outcome category. CONCLUSIONS This study showed that three principles are important for the successful integration of eHealth into healthcare. First, the role of the care receiver needs to be incorporated into the organisational structure and daily care process. Second, the technology must be well attuned to the organisational structure and daily care process. Third, the deployment of human resources in the daily care processes needs to be aligned with the desired end results. Not adhering to these points could negatively affect the organisation, daily process, or the end results.

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.