Background: Telehealth interventions, that is, health care provided over a distance using information and communication technology, are suggested as a solution to rising health care costs by reducing hospital service use. However, the extent to which this is possible is unclear. Objective: The aim of this study is to evaluate the effect of telehealth on the use of hospital services, that is, (duration of) hospitalizations, and to compare the effects between telehealth types and health conditions. Methods: We searched PubMed, Scopus, and the Cochrane Library from inception until April 2019. Peer-reviewed randomized controlled trials (RCTs) reporting the effect of telehealth interventions on hospital service use compared with usual care were included. Risk of bias was assessed using the Cochrane Risk of Bias 2 tool and quality of evidence according to the Grading of Recommendations Assessment, Development and Evaluation guidelines. Results: We included 127 RCTs in the meta-analysis. Of these RCTs, 82.7% (105/127) had a low risk of bias or some concerns overall. High-quality evidence shows that telehealth reduces the risk of all-cause or condition-related hospitalization by 18 (95% CI 0-30) and 37 (95% CI 20-60) per 1000 patients, respectively. We found high-quality evidence that telehealth leads to reductions in the mean all-cause and condition-related hospitalizations, with 50 and 110 fewer hospitalizations per 1000 patients, respectively. Overall, the all-cause hospital days decreased by 1.07 (95% CI −1.76 to −0.39) days per patient. For hospitalized patients, the mean hospital stay for condition-related hospitalizations decreased by 0.89 (95% CI −1.42 to −0.36) days. The effects were similar between telehealth types and health conditions. A trend was observed for studies with longer follow-up periods yielding larger effects. Conclusions: Small to moderate reductions in hospital service use can be achieved using telehealth. It should be noted that, despite the large number of included studies, uncertainties around the magnitude of effects remain, and not all effects are statistically significant.

Assessment of (digital) health literacy in the hospital can raise staff awareness and facilitate tailored communication, leading to improved health outcomes. Assessment tools should ideally address multiple domains of health literacy, fit to the complex hospital context and have a short administration time, to enable routine assessment. This review aims to create an overview of tools for measuring (digital) health literacy in hospitals. A search in Scopus, PubMed, WoS and CINAHL, following PRISMA guidelines, generated 7252 hits; 251 studies were included in which 44 assessment tools were used. Most tools (57%) were self-reported and 27% reported an administration time of <5 min. Almost all tools addressed the domain ‘understanding’ (98%), followed by ‘access’ (52%), ‘apply’ (50%), ‘appraise’ (32%), ‘numeracy’ (18%), and ‘digital’ (18%). Only four tools were frequently used: the Newest Vital Sign (NVS), the Short Test of Functional Health Literacy for Adults ((S)TOFHLA), the Brief Health Literacy Screener (BHLS), and the Health Literacy Questionnaire (HLQ). While the NVS and BHLS have a low administration time, they cover only two domains. HLQ covers the most domains: access, understanding, appraise, and apply. None of these four most frequently used tools measured digital skills. This review can guide health professionals in choosing an instrument that is feasible in their daily practice, and measures the required domains.

Patients with a presumed diagnosis of acute coronary syndrome (ACS) or stroke may have had contact with several healthcare providers prior to hospital arrival. The aim of this study was to describe the various prehospital paths and the effect on time delays of patients with ACS or stroke. This prospective observational study included patients with presumed ACS or stroke who may choose to contact four different types of health care providers. Questionnaires were completed by patients, general practitioners (GP), GP cooperatives, ambulance services and emergency departments (ED). Additional data were retrieved from hospital registries. Two hundred two ACS patients arrived at the hospital by 15 different paths and 243 stroke patients by ten different paths. Often several healthcare providers were involved (60.8 % ACS, 95.1 % stroke). Almost half of all patients first contacted their GP (47.5 % ACS, 49.4 % stroke). Some prehospital paths were more frequently used, e.g. GP (cooperative) and ambulance in ACS, and GP or ambulance and ED in stroke. In 65 % of all events an ambulance was involved. Median time between start of symptoms and hospital arrival for ACS patients was over 6 h and for stroke patients 4 h. Of ACS patients 47.7 % waited more than 4 h before seeking medical advice compared to 31.6 % of stroke patients. Median time between seeking medical advice to arrival at hospital was shortest in paths involving the ambulance only (60 min ACS, 54 min stroke) or in combination with another healthcare provider (80 to 100 min ACS, 99 to 106 min stroke). Prehospital paths through which patients arrived in hospital are numerous and often complex, and various time delays occurred. Delays depend on the entry point of the health care system, and dialing the emergency number seems to be the best choice. Since reducing patient delay is difficult and noticeable differences exist between various prehospital paths, further research into reasons for these different entry choices may yield possibilities to optimize paths and reduce overall time delay.

Background: Continuous monitoring using wireless wearable sensors is a promising solution for use in clinical practice and in the home setting. It is important to involve nurses to ensure successful implementation. This paper aims to provide an overview of 1) factors affecting implementation of continuous monitoring using wireless wearable sensors by evaluating nurses’ experiences with its use on the nursing ward, and 2) nurses’ expectations for use in the home setting. Methods: Semi-structured interviews were conducted with 16 nurses from three teaching hospitals in the Netherlands, covering constructs from the Consolidated Framework for Implementation Research (CFIR). A deductive approach of directed content analysis was applied. One additional factor was added using the Unified Theory for Acceptance of Technology (UTAUT). The quotes and domains were rated on valence (positive, neutral, negative) and strength (strong: − 2, + 2, neutral 0, and weak: − 1, + 1). Results: Data was collected on 27 CFIR constructs and 1 UTAUT construct. In the experience of at least 8 nurses, five constructs had a strong positive influence on implementation on the nursing ward, including relative advantage (e.g., early detection of deterioration), patient needs and resources (e.g. feeling safe), networks and communications (e.g. execute tasks together), personal attributes (e.g. experience with intervention), and implementation leaders (e.g., project leader). Five constructs had a strong negative influence: evidence strength and quality (e.g. lack of evidence from practical experience), complexity (e.g. number of process steps), design quality and packaging (e.g., bad sensor quality), compatibility (e.g, change in work) and facilitating conditions (e.g, Wi-Fi connection). Nurses expected continuous monitoring in the home setting to be hindered by compatibility with work processes and to be facilitated by staff’s access to information. Technical facilitating conditions (e.g. interoperability) were suggested to be beneficial for further development. Conclusions: This paper provides an overview, of factors influencing implementation of continuous monitoring including relative importance, based on nurses’ experiences with use on nursing wards, and their perspectives for use in the home setting. Implementation of continuous monitoring is affected by a wide range of factors. This overview may be used as a guideline for future implementations.

Background: In a previous trial, higher 5‐year mortality was observed following treatment with biodegradable polymer Orsiro sirolimus‐eluting stents (SES). We assessed 5‐year safety and efficacy of all‐comers as well as patients with diabetes treated with SES or Synergy everolimus‐eluting stents (EES) versus durable polymer Resolute Integrity zotarolimus‐eluting stents (ZES). Methods and Results: The randomized BIO‐RESORT (Comparison of Biodegradable Polymer and Durable Polymer Drug‐Eluting Stents in an All Comers Population) trial enrolled 3514 all‐comer patients at 4 Dutch cardiac centers. Patients aged ≥18 years who required percutaneous coronary intervention were eligible. Participants were stratified for diabetes and randomized to treatment with SES, EES, or ZES (1:1:1). The main end point was target vessel failure (cardiac mortality, target vessel myocardial infarction, or target vessel revascularization). Five‐year follow‐up was available in 3183 of 3514 (90.6%) patients. The main end point target vessel failure occurred in 142 of 1169 (12.7%) patients treated with SES, 130 of 1172 (11.6%) treated with EES, versus 157 of 1173 (14.1%) treated with ZES (hazard ratio [HR], 0.89 [95% CI, 0.71–1.12], P _log‐rank =0.31; and HR, 0.82 [95% CI, 0.65–1.04], P _log‐rank =0.10, respectively). Individual components of target vessel failure showed no significant between‐stent difference. Very late definite stent thrombosis rates were low and similar (SES, 1.1%; EES, 0.6%; ZES, 0.9%). In patients with diabetes, target vessel failure did not differ significantly between stent‐groups (SES, 19.8%; EES, 19.2%; versus ZES, 21.1% [ P _log‐rank =0.69 and P _log‐rank =0.63]). Conclusions: Orsiro SES, Synergy EES, and Resolute Integrity ZES showed similar 5‐year outcomes of safety and efficacy, including mortality. A prespecified stent comparison in patients with diabetes also revealed no significant differences in 5‐year clinical outcomes. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01674803.