Background We adapted the eHealth Literacy Scale (eHEALS) for Hungary and tested its psychometric properties on a large representative online sample of the general population. Methods The Hungarian version of eHEALS was developed using forward–backward translation. For the valuation study, 1000 respondents were recruited in early 2019 from a large online panel by a survey company. We tested internal consistency, test–retest reliability and construct and criterion validity using classical test theory, as well as item characteristics using an item-response theory (IRT) graded response model (GRM). Results 55% of respondents were female, and 22.1% were ≥ 65 years old. Mean eHEALS score was 29.2 (SD: 5.18). Internal consistency was good (Cronbach’s α = 0.90), and test–retest reliability was moderate (intraclass correlation r = 0.64). We identified a single-factor structure by exploratory factor analysis, explaining 85% of test variance. Essential criteria for GRM analysis were met. Items 3 and 4 (search of health resources) were the least difficult, followed by items 5 and 8 (utilisation of health information), and then items 1 and 2 (awareness of health resources). Items 6 and 7 (appraisal of health resources) were most difficult. The measurement properties of eHEALS were not affected by gender, age, education or income levels. Female gender, older age, intensity of health information seeking, formal health education and visit at the electronic health-record website were associated with higher eHEALS scores, as well as best and worst self-perceived health states, BMI < 25 and participation at health screenings over the past year. Conclusions The Hungarian eHEALS is a useful and valid tool for measuring subjective eHealth literacy.

Hip fracture care delivery varies between hospitals, which might explain variations in patient outcomes and health costs. The aim of this study was to identify hospital-level organisational factors associated with long-term patient outcomes and costs after hip fracture. REDUCE was a record-linkage cohort study in which national databases for all patients aged 60 years and older who sustained a hip fracture in England and Wales were linked with hospital metrics from 18 organisational data sources. Multilevel models identified organisational factors associated with the case-mix adjusted primary outcomes: cumulative all-cause mortality, days spent in hospital, and inpatient costs over 365 days after hip fracture. Between April 1, 2016, and March 31, 2019, 178 757 patients with an index hip fracture were identified from 172 hospitals in England and Wales. 126 278 (70·6%) were female, 52 479 (29·4%) were male, and median age was 84 years (IQR 77-89) in England and 83 years (77-89) in Wales. 365 days after hip fracture, 50 354 (28·2%) patients had died. Patients spent a median 21 days (IQR 11-41) in hospital, incurring costs of £14 642 (95% CI 14 600-14 683) per patient, ranging from £10 867 (SD 5880) to £23 188 (17 223) between hospitals. 11 organisational factors were independently associated with mortality, 24 with number of days in hospital, and 25 with inpatient costs. Having all patients assessed by an orthogeriatrician within 72 h of admission was associated with a mean cost saving of £529 (95% CI 148-910) per patient and a lower 365-day mortality (odds ratio 0·85 [95% CI 0·76-0·94]). Consultant orthogeriatrician attendance at clinical governance meetings was associated with cost savings of £356 (95% CI 188-525) and 1·47 fewer days (95% CI 0·89-2·05) in the hospital in the 365 days after hip fracture per patient. The provision of physiotherapy to patients on weekends was associated with a cost saving of £676 (95% CI 67-1285) per patient and with 2·32 fewer days (0·35-4·29) in hospital in the 365 days after hip fracture. Multiple, potentially modifiable hospital-level organisational factors associated with important clinical outcomes and inpatient costs were identified that should inform initiatives to improve the effectiveness and efficiency of hip fracture services. Versus Arthritis.

At the beginning of 2007, health care reforms were implemented in Hungary in order to decrease public expenditure on health care. Reforms involved the increase of co-payments for pharmaceuticals and the introduction of co-payments for health care services.

Background: Digital health, which encompasses the use of information and communications technology in support of health, is a key driving force behind the cultural transformation of medicine toward people-centeredness. Thus, eHealth literacy, assisted by innovative digital health solutions, may support better experiences of care. Objective: The purpose of this study is to explore the relationship between eHealth literacy and patient-reported experience measures (PREMs) among users of outpatient care in Hungary. Methods: In early 2019, we conducted a cross-sectional survey on a large representative online sample recruited from the Hungarian general population. eHealth literacy was measured with the eHealth Literacy Scale (eHEALS). PREMs with outpatient care were measured with a set of questions recommended by the Organisation for Economic Co-operation and Development (OECD) for respondents who attended outpatient visit within 12 months preceding the survey. Bivariate relationships were explored via polychoric correlation, the Kruskal–Wallis test, and chi-square test. To capture nonlinear associations, after controlling covariates, we analyzed the relationship between eHEALS quartiles and PREMs using multivariate probit, ordinary least squares, ordered logit, and logistic regression models. Results: From 1000 survey respondents, 666 individuals (364 females, 54.7%) were included in the study with mean age of 48.9 (SD 17.6) years and mean eHEALS score of 29.3 (SD 4.9). Respondents with higher eHEALS scores were more likely to understand the health care professionals’ (HCPs’) explanations (χ29=24.2, P=.002) and to be involved in decision making about care and treatment (χ29=18.2, P=.03). In multivariate regression, respondents with lowest (first quartile) and moderately high (third quartile) eHEALS scores differed significantly, where the latter were more likely to have an overall positive experience (P=.02) and experience fewer problems (P=.02). In addition, those respondents had better experiences in terms of how easy it was to understand the HCPs’ explanations (P<.001) and being able to ask questions during their last consultation (P=.04). Patient-reported experiences of individuals with highest (fourth quartile) and lowest (first quartile) eHEALS levels did not differ significantly in any items of the PREM instrument, and neither did composite PREM scores generated from the PREM items (P>.05 in all models). Conclusions: We demonstrated the association between eHealth literacy and PREMs. The potential patient-, physician-, and system-related factors explaining the negative experiences among people with highest levels of eHealth literacy warrant further investigation, which may contribute to the development of efficient eHealth literacy interventions. Further research is needed to establish causal relationship between eHealth literacy and patient-reported experiences.