The use of electronic health records in advanced practice nursing education: a scoping review.

Electronic health records are integral to the advanced practice registered nurse role, yet access and training during academic preparation are profoundly limited. Lack of exposure to electronic health records prevents students from becoming fully prepared for the responsibilities of clinical practice and potentially impacts quality of care, patient safety, and communication among patients and providers. This scoping review of 20 articles on electronic health record use in advanced practice registered nursing student education shows significant gaps in current research. Nine articles were classified as research. The remaining 11 were non-research reports of teaching innovations describing the use of simulated electronic health records in graduate nursing education or the use of an electronic health record in interprofessional education activities. Most of the limited research did not use valid and reliable instruments or robust designs, employed disparate approaches and tools to study the phenomenon, and measured low-level outcomes such as student navigation and confidence in using electronic health records. The non-research literature draws attention to the deficits in educational resources, including unaffordable electronic health records for academic use. Although rigorous evidence is lacking, a common theme throughout the reviewed literature was the benefit of simulation to develop electronic health record skills.

What Influences Work Engagement Among Registered Nurses: Implications for Evidence-Based Action.

BACKGROUND: Previous studies evaluating work engagement of nurses revealed work-related factors and nurse demographics affecting work engagement. Low work engagement yields a decrease in productivity, high turnover, loss of revenue, and, most importantly, patient safety concerns. AIM: To investigate the relationship between nurse-related and work-related variables associated with work engagement and provide a model that explains work engagement. METHOD: This study employed an observational, cross-sectional study design, with 201 registered nurses working in acute care hospitals in the United States participating in the study. Four work-related and five nurse-related variables were evaluated and used in the work engagement model. A standard multiple regression was performed using the work- and nurse-related factors regressed onto work engagement. Structural equation model procedures were performed to examine the association between predictive variables and work engagement. RESULTS: Of the 201 participants, just over a third of the participants were over 50 years of age (33.5%), female (91.6%), married (68%), had a bachelor of science in nursing (58.1%), and have been a nurse <5 years (42.4%). Five of the variables were found to make a unique statistically significant contribution to the variance in work engagement, age (ß = .31, p = .001), workload (ß = .30, p < .001), Core Self-Evaluation Scale (ß = 0 .22, p = .002), Coping with Change Scale (ß = .20, p = .001), and Maslach Burnout Inventory (MBI)-General Scale score (ß = -.17, p = .03). The work engagement model indicated a satisfactory overall model fit of the model (GFI = .996; χ2 (2, N = 201) = 4.02, p = .135; RMSEA = .07; CFI = .983; NFI = .976). LINKING EVIDENCE TO ACTION: The results of this study confirm a work engagement model that incorporates both nurse- and work-related factors. Overall, the results indicate that the level of work engagement is predicted more by nurse-related factors than by work-related factors.

Home pregnancy tests in the hands of the intended user.

The objectives of this study were to investigate the usability and performance of seven visual home pregnancy tests, available in Europe. Part one of the study was home-based and involved volunteers testing a selection of four home pregnancy tests. The tests used and order of use were randomized. Part two, performed at a study site, involved volunteers reading and interpreting the results of the same selection of home pregnancy tests used in part one, but using urine standards representing early pregnancy (25 mIU/mL human chorionic gonadotropin) or a 'not pregnant' (0 mIU/mL human chorionic gonadotropin) sample. The volunteers completed a questionnaire after each test in both parts. Three of the seven tests met their accuracy/reliability claims: tests A (99.8%), B (100%), and F (97.6%) (not statistically different from the claimed 99% accuracy). The remaining four tests had accuracies/reliabilities of <99% at 81.6% (C), 89.0% (E), 92.5% (D), and 95.9% (G), respectively. Test A was the highest-rated test for each attribute tested in both settings. Test D was ranked the lowest in part one and test C was ranked lowest overall for part two. Home pregnancy tests vary in performance and usability, therefore requiring better standardization and performance evaluation in Europe.Clinical Trials Reference Number: NCT03589534.

Home ovulation test use and stress during subfertility evaluation: Subarm of a randomized controlled trial.

OBJECTIVES: A prospective, randomized controlled trial in women seeking to conceive examined the impact of using ovulation tests on self-reported levels of stress, psychological well-being, and quality of life in women with unexplained infertility. METHOD: The test group used a home ovulation test to detect the day of ovulation, whereas the control group were provided with a predicted day of ovulation based on the average length of menstrual cycle reported during study recruitment. Volunteers collected their first morning urine samples to evaluate biochemical levels of stress (urinary cortisol and estrone-3-glucouronide) and completed questionnaires over two complete menstrual cycles. RESULTS: Overall, the use of digital ovulation tests by sub-fertile women under medical care had negligible negative effects and no detectable positive benefit on psychological well-being, according to multiple measurements of stress by questionnaire and biochemical markers. No significant differences were found between groups for all stress measures at the various study time points, except in relation to "couple concordance" where the test group scored much higher than the control group (mean difference at end of study was 21.25 (95% confidence interval: 9.25, 33.25; P = 0.0015)). The maximum difference in log cortisol: creatinine ratio between the test and control groups was -0.28 (95% confidence interval: -0.69, 0.13). CONCLUSIONS: These results do not support propositions that using digital ovulation tests can cause stress in women trying to conceive.