Background Patients’ access to and use of electronic medical records (EMRs) places greater information in their hands, which helps them better comanage their health, leading to better clinical outcomes. Despite numerous benefits that promote health and well-being, patients’ acceptance and use of EMRs remains low. We study the impact of predictors that affect the use of EMR by patients to understand better the underlying causal factors for the lower use of EMR. Objective This study aims to examine the critical system (eg, performance expectancy and effort expectancy) and patient characteristics (eg, health condition, issue involvement, preventive health behaviors, and caregiving status) that influence the extent of patients’ EMR use. Methods We used secondary data collected by Health Information National Trends Survey 5 cycle 3 and performed survey data analysis using structural equation modeling technique to test our hypotheses. Structural equation modeling is a technique commonly used to measure and analyze the relationships of observed and latent variables. We also addressed common method bias to understand if there was any systematic effect on the observed correlation between the measures for the predictor and predicted variables. Results The statistically significant drivers of the extent of EMR use were performance expectancy (β=.253; P<.001), perceived behavior control (β=.236; P<.001), health knowledge (β=–.071; P=.007), caregiving status (β=.059; P=.013), issue involvement (β=.356; P<.001), chronic conditions (β=.071; P=.016), and preventive health behavior (β=.076; P=.005). The model accounted for 32.9% of the variance in the extent of EMR use. Conclusions The study found that health characteristics, such as chronic conditions and patient disposition (eg, preventive health behavior and issue involvement), directly affect the extent of EMR use. The study also revealed that issue involvement mediates the impact of preventive health behaviors and the presence of chronic conditions on the extent of patients’ EMR use.

Background Health care delivery and patient satisfaction are improved when patients engage with their medical information through patient portals. Despite their wide availability and multiple functionalities, patient portals and their functionalities are still underused. Objective We seek to understand factors that lead to patient engagement through multiple portal functionalities. We provide recommendations that could lead to higher patients’ usage of their portals. Methods Using data from the Health Information National Trends Survey 5, Cycle 3 (N=2093), we performed descriptive statistics and used a chi-square test to analyze the association between the demographic variables and the use of mobile health apps for accessing medical records. We further fitted a generalized linear model to examine the association between access type and the use of portal functionalities. We further examined the moderation effects of age groups on the impact of access type on portal usage. Results Our results show that accessing personal health records using a mobile health app is positively associated with greater patient usage of access capabilities (β=.52; P<.001), patient-provider interaction capabilities (β=.24, P=.006), and patient–personal health information interaction capabilities (β=.23, P=.009). Patients are more likely to interact with their records and their providers when accessing their electronic medical records using a mobile health app. The impacts of mobile health app usage fade with age for tasks consisting of viewing, downloading, and transmitting medical results to a third party (β=–.43, P=.005), but not for those involving patient-provider interaction (β=.05, P=.76) or patient–personal health information interaction (β=–.15, P=.19). Conclusions These findings provide insights on how to increase engagement with diverse portal functionalities for different age groups and thus improve health care delivery and patient satisfaction.

AimsAnalysis of the demographics, patterns of presentation and outcomes of all children <1yr old presenting with injuries to 9 Emergency departments in one health board over a 3 month period, with critical analysis of those requiring full child protection investigation.MethodsThe Health Board has 9 Emergency departments, and in a 3 month period in 2014, 2531 children attended. A protocol for ‘Recognition and management of maltreatment in infants’ exists, and 388 infants met the inclusion criteria of presentation with injury. Case records for 375 children were able to be analysed for demographics; previous attendances; nature of injury; environmental risk factors for NAI; investigations; and follow up where welfare concerns were identified.Abstract G304(P) Figure 1In cases where injury were found the majority of infants, (59%) presented with head injury. Burns (9%) and lacerations (6%) were next most prevalentAbstract G304(P) Figure 2Accidental injury was the concluding diagnosis in 97%. 11 (2.9%) children fulfilled the protocol criteria for full child protection investigations consisting of skeletal survey, intracranial imaging, ophthalmology review and bloods. All 11 were admitted to the ward for investigation where the mean length of stay was 4.5 daysResults375 children <1 yrs presented with injuries, 42.6% female, 56.8% male. Age at attendance rose from 1.9% <1 month to a peak of 17.3% at 11 months.Of these 11 infants, the conclusion was that 4 were accidental injury, 4 remained unexplained and 3 were NAI.Abstract G304(P) Table 1ConclusionWe describe the presentation of injuries in a large group of children under the age of 1, of whom 2.9% fulfilled the criteria for full child protection investigation. Only 7 (1.8%) were deemed to have NAI or unexplained injury. The majority had a multi-agency child protection case conference with safeguarding plans agreed prior to discharge, following which all were returned to parental care or kinship care.

BACKGROUND Patients’ access to and use of electronic medical records (EMRs) places greater information in their hands, which helps them better co-manage their health, leading to better clinical outcomes. Despite numerous benefits that promote health and well-being, patients’ acceptance and use of EMRs remains low. OBJECTIVE This study aims to examine the critical system and patient characteristics that influence the extent of patients’ EMR use. METHODS We employed the patient technology acceptance model as a starting point and included new constructs specific to patient characteristics, such as chronic conditions, preventive health behavior, and issue involvement. To test our hypotheses, we used structural equation modeling. RESULTS The statistically significant drivers of the extent of EMR use were performance expectancy (β = 0.253; P < .000), perceived behavior control (β = 0.236; P < .000), health knowledge (β = -0.071; P < .01), caregiving status (β = 0.059; P < .05), issue involvement (β = 0.356; P < .000), chronic conditions (β = 0.071; P < .05), and preventive health behavior (β = 0.076; P < .01). The model accounted for 32.9% of the variance in the extent of EMR use. CONCLUSIONS The study found that health characteristics, such as chronic conditions and patient disposition (e.g., preventive health behavior and issue involvement), directly affect the extent of EMR use. The study also revealed that issue involvement mediates the impacts of preventive health behaviors and the presence of chronic conditions on the extent of patients’ EMR use.