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BackgroundHealth 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. ObjectiveThe 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. MethodsA 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. ResultsEleven 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. ConclusionsThree 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.

BackgroundHospitalization for acute exacerbation of chronic obstructive pulmonary disease (COPD) is associated with poor prognosis. eHealth interventions might improve outcomes and decrease costs. ObjectiveThis study aimed to evaluate the effect of an eHealth program on COPD hospitalizations and exacerbations. MethodsThis 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. ResultsThe 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. ConclusionsThe eHealth program seems to reduce the number of total exacerbations and number of days of hospitalization due to exacerbations of COPD.

BackgroundThe 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. ObjectiveThis study aims to develop an online tool to assess the long-term burden of COVID-19 in patients. MethodsIn 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. ResultsAs 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. ConclusionsThis 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.

BackgroundChronic obstructive pulmonary disease (COPD) and asthma have a high prevalence and disease burden. Blended self-management interventions, which combine eHealth with face-to-face interventions, can help reduce the disease burden. ObjectiveThis systematic review and meta-analysis aims to examine the effectiveness of blended self-management interventions on health-related effectiveness and process outcomes for people with COPD or asthma. MethodsPubMed, Web of Science, COCHRANE Library, Emcare, and Embase were searched in December 2018 and updated in November 2020. Study quality was assessed using the Cochrane risk of bias (ROB) 2 tool and the Grading of Recommendations, Assessment, Development, and Evaluation. ResultsA total of 15 COPD and 7 asthma randomized controlled trials were included in this study. The meta-analysis of COPD studies found that the blended intervention showed a small improvement in exercise capacity (standardized mean difference [SMD] 0.48; 95% CI 0.10-0.85) and a significant improvement in the quality of life (QoL; SMD 0.81; 95% CI 0.11-1.51). Blended intervention also reduced the admission rate (relative ratio [RR] 0.61; 95% CI 0.38-0.97). In the COPD systematic review, regarding the exacerbation frequency, both studies found that the intervention reduced exacerbation frequency (RR 0.38; 95% CI 0.26-0.56). A large effect was found on BMI (d=0.81; 95% CI 0.25-1.34); however, the effect was inconclusive because only 1 study was included. Regarding medication adherence, 2 of 3 studies found a moderate effect (d=0.73; 95% CI 0.50-0.96), and 1 study reported a mixed effect. Regarding self-management ability, 1 study reported a large effect (d=1.15; 95% CI 0.66-1.62), and no effect was reported in that study. No effect was found on other process outcomes. The meta-analysis of asthma studies found that blended intervention had a small improvement in lung function (SMD 0.40; 95% CI 0.18-0.62) and QoL (SMD 0.36; 95% CI 0.21-0.50) and a moderate improvement in asthma control (SMD 0.67; 95% CI 0.40-0.93). A large effect was found on BMI (d=1.42; 95% CI 0.28-2.42) and exercise capacity (d=1.50; 95% CI 0.35-2.50); however, 1 study was included per outcome. There was no effect on other outcomes. Furthermore, the majority of the 22 studies showed some concerns about the ROB, and the quality of evidence varied. ConclusionsIn patients with COPD, the blended self-management interventions had mixed effects on health-related outcomes, with the strongest evidence found for exercise capacity, QoL, and admission rate. Furthermore, the review suggested that the interventions resulted in small effects on lung function and QoL and a moderate effect on asthma control in patients with asthma. There is some evidence for the effectiveness of blended self-management interventions for patients with COPD and asthma; however, more research is needed. Trial RegistrationPROSPERO International Prospective Register of Systematic Reviews CRD42019119894; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=119894

BackgroundCatheter-associated urinary tract infections (CAUTIs) are the main cause of health care–associated infections, and they increase the disease burden, antibiotic usage, and hospital stay. Inappropriate placement and unnecessarily prolonged usage of a catheter lead to an elevated and preventable risk of infection. The smartphone app Participatient has been developed to involve hospitalized patients in communication and decision-making related to catheter use and to control unnecessary (long-term) catheter use to prevent CAUTIs. Sustained behavioral changes for infection prevention can be promoted by empowering patients through Participatient. ObjectiveThe primary aim of our multicenter prospective interrupted time-series analysis is to reduce inappropriate catheter usage by 15%. We will evaluate the efficacy of Participatient in this quality improvement study in clinical wards. Our secondary endpoints are to reduce CAUTIs and to increase patient satisfaction, involvement, and trust with health care services. MethodsWe will conduct a multicenter interrupted time-series analysis—a strong study design when randomization is not feasible—consisting of a pre- and postintervention point-prevalence survey distributed among participating wards to investigate the efficacy of Participatient in reducing the inappropriate usage of catheters. After customizing Participatient to the wards’ requirements, it will be implemented with a catheter indication checklist among clinical wards in 4 large hospitals in the Netherlands. We will collect clinical data every 2 weeks for 6 months in the pre- and postintervention periods. Simultaneously, we will assess the impact of Participatient on patient satisfaction with health care services and providers and the patients’ perceived involvement in health care through questionnaires, and the barriers and facilitators of eHealth implementation through interviews with health care workers. ResultsTo reduce the inappropriate use of approximately 40% of catheters (currently in use) by 15%, we aim to collect 9-12 data points from 70-100 patients per survey date per hospital. Thereafter, we will conduct an interrupted time-series analysis and present the difference between the unadjusted and adjusted rate ratios with a corresponding 95% CI. Differences will be considered significant when P

BackgroundSeveral countries around the world have implemented multicomponent interventions to enhance primary care, as a way of strengthening their health systems to cope with an aging chronically ill population and rising costs. Some of these efforts have included technology-based enhancements as one of the features to support the overall intervention, but their details and impacts have not been explored. ObjectiveThis study aimed to identify the role of digital/health technologies within wider multifeature interventions that are aimed at enhancing primary care, and to describe their aims and stakeholders, types of technologies used, and potential impacts. MethodsA systematic review was performed following Cochrane guidelines. An electronic search, conducted on May 30, 2019, was supplemented with manual and grey literature searches in December 2019, to identify multicomponent interventions that included at least one technology-based enhancement. After title/abstract and full text screening, selected articles were assessed for quality based on their study design. A descriptive narrative synthesis was used for analysis and presentation of the results. ResultsOf 37 articles, 14 (38%) described the inclusion of a technology-based innovation as part of their multicomponent interventions to enhance primary care. The most commonly identified technologies were the use of electronic health records, data monitoring technologies, and online portals with messaging platforms. The most common aim of these technologies was to improve continuity of care and comprehensiveness, which resulted in increased patient satisfaction, increased primary care visits compared to specialist visits, and the provision of more health prevention education and improved prescribing practices. Technologies seem also to increase costs and utilization for some parameters, such as increased consultation costs and increased number of drugs prescribed. ConclusionsTechnologies and digital health have not played a major role within comprehensive innovation efforts aimed at enhancing primary care, reflecting that these technologies have not yet reached maturity or wider acceptance as a means for improving primary care. Stronger policy and financial support, and advocacy of key stakeholders are needed to encourage the introduction of efficient technological innovations, which are backed by evidence-based research, so that digital technologies can fulfill the promise of supporting strong sustainable primary care.

Despite significant efforts, the COVID-19 pandemic has put enormous pressure on health care systems around the world, threatening the quality of patient care. Telemonitoring offers the opportunity to carefully monitor patients with a confirmed or suspected case of COVID-19 from home and allows for the timely identification of worsening symptoms. Additionally, it may decrease the number of hospital visits and admissions, thereby reducing the use of scarce resources, optimizing health care capacity, and minimizing the risk of viral transmission. In this paper, we present a COVID-19 telemonitoring care pathway developed at a tertiary care hospital in the Netherlands, which combined the monitoring of vital parameters with video consultations for adequate clinical assessment. Additionally, we report a series of medical, scientific, organizational, and ethical recommendations that may be used as a guide for the design and implementation of telemonitoring pathways for COVID-19 and other diseases worldwide.

BackgroundDespite 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. ObjectiveThe 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. MethodsThree 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.” ResultsThe 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.” ConclusionsSeventy-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.

BackgroundDigital medical interview assistant (DMIA) systems, also known as computer-assisted history taking (CAHT) systems, have the potential to improve the quality of care and the medical consultation by exploring more patient-related aspects without time constraints and, therefore, acquiring more and better-quality information prior to the face-to-face consultation. The consultation in primary care is the broadest in terms of the amount of topics to be covered and, at the same time, the shortest in terms of time spent with the patient. ObjectiveOur aim is to explore how DMIA systems may be used specifically in the context of primary care, to improve the consultations for diabetes and depression, as exemplars of chronic conditions. MethodsA narrative review was conducted focusing on (1) the characteristics of the primary care consultation in general, and for diabetes and depression specifically, and (2) the impact of DMIA and CAHT systems on the medical consultation. Through thematic analysis, we identified the characteristics of the primary care consultation that a DMIA system would be able to improve. Based on the identified primary care consultation tasks and the potential benefits of DMIA systems, we developed a sample questionnaire for diabetes and depression to illustrate how such a system may work. ResultsA DMIA system, prior to the first consultation, could aid in the essential primary care tasks of case finding and screening, diagnosing, and, if needed, timely referral to specialists or urgent care. Similarly, for follow-up consultations, this system could aid with the control and monitoring of these conditions, help check for additional health issues, and update the primary care provider about visits to other providers or further testing. Successfully implementing a DMIA system for these tasks would improve the quality of the data obtained, which means earlier diagnosis and treatment. Such a system would improve the use of face-to-face consultation time, thereby streamlining the interaction and allowing the focus to be the patient's needs, which ultimately would lead to better health outcomes and patient satisfaction. However, for such a system to be successfully incorporated, there are important considerations to be taken into account, such as the language to be used and the challenges for implementing eHealth innovations in primary care and health care in general. ConclusionsGiven the benefits explored here, we foresee that DMIA systems could have an important impact in the primary care consultation for diabetes and depression and, potentially, for other chronic conditions. Earlier case finding and a more accurate diagnosis, due to more and better-quality data, paired with improved monitoring of disease progress should improve the quality of care and keep the management of chronic conditions at the primary care level. A somewhat simple, easily scalable technology could go a long way to improve the health of the millions of people affected with chronic conditions, especially if working in conjunction with already-established health technologies such as electronic medical records and clinical decision support systems.

The number of individuals with chronic illness and multimorbidity is growing due to the rapid ageing of the population and the greater longevity of individuals. This causes an increasing workload in care, which results in a growing need for structural changes of the health care system. In recent years this led to a strong focus on promoting “self-management” in chronically ill patients. Research showed that patients who understand more about their disease, health, and lifestyle have better experiences and health outcomes, and often use less health care resources; the effect is even more when these patients are empowered to and responsible for managing their health and disease. In addition to the skills of patients, health care professionals need to shift to a role of teacher, partner, and professional supervisor of their patients. One way of supervising patients is by the use of electronic health (eHealth), which helps patients manage and control their disease. The application of eHealth solutions can provide chronically ill patients high-quality care, to the satisfaction of both patients and health care professionals, alongside a reduction in health care consumption and costs.

The aim of this study was to quantify physical activity and sedentary behavior in older adults recovering from hip fracture and to identify groups based on movement patterns. In this cross-sectional cohort study, older adults (≥70 years) were included 3 months after surgery for proximal femoral fracture. Patients received an accelerometer for 7 days. Demographics and outcomes related to physical function, mobility, cognitive functions, quality of life, and hip fracture were assessed. In total, 43 patients with sufficient accelerometer wear time were included. Across all groups, participants engaged in very low levels of physical activity, spending an average of 11 hr/day in prolonged sedentary behavior. Based on the extracted components from a principal component analysis, three groups with substantial differences in levels of physical activity and sedentary behavior could be distinguished. [ABSTRACT FROM AUTHOR]