D029 Annotated Bibliography
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Western Governors University
D029 Informatics for Transforming Nursing Care
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Annotated Bibliography
Factors Influencing the Use of Electronic Personal Health Records (ePHRs)
What are electronic personal health records (ePHRs) and what functionalities do they offer?
Electronic personal health records (ePHRs) are secure digital platforms designed to give patients access to their own medical information. These platforms enable functionalities such as communicating directly with healthcare providers, sharing health data, scheduling and managing appointments, and handling prescription refills. By providing these capabilities, ePHRs empower patients to take an active role in managing their health, promoting a more patient-centered healthcare experience.
Which factors influence the adoption and use of ePHRs by patients?
A systematic review analyzing 97 studies identified over 150 factors impacting ePHR adoption, highlighting 18 key elements grouped into five categories:
| Factor Category | Specific Influencing Factors |
|---|---|
| Demographic | Sex, ethnicity, marital status, language, place of residence |
| Socioeconomic | Income, education level, employment status, socioeconomic status |
| Health-Related | Overall health condition |
| Technological & Access | Access to technology, internet availability, frequency of use |
| Perceptions & Awareness | Awareness of ePHRs, perceived ease and usefulness |
| Privacy & Security | Concerns about data privacy and security |
These factors play a crucial role in whether patients adopt and effectively utilize ePHRs for health management.
Why are these factors important for healthcare stakeholders?
For healthcare providers and organizations implementing ePHRs, understanding these determinants is essential to boost patient adoption. Tailoring ePHR designs and communication strategies to address demographic, socioeconomic, technological, and privacy concerns can lead to improved patient engagement. This, in turn, enhances health outcomes through more inclusive and efficient health management systems (Abd-alrazaq et al., 2019).
Using Virtual Simulation to Teach Evidence-Based Practice (EBP) in Nursing Education
What types of virtual simulations are used to teach evidence-based practice in nursing?
Nursing education utilizes two main types of virtual simulations (VS) for teaching evidence-based practice (EBP): screen-based simulations, which may feature live actors or avatars, and virtual reality simulations (VRS), which use immersive headset technology. Both methods present interactive clinical scenarios where students can practice decision-making based on evidence.
How do virtual simulations benefit nursing students?
These simulations offer a risk-free environment for students to refine clinical decision-making skills without endangering patients. They are particularly valuable when real-life clinical placements are limited, providing critical hands-on experience. Virtual simulations also enhance students’ confidence and competence in applying evidence-based nursing practices.
What conclusions have been drawn about integrating virtual simulations into nursing curricula?
A rapid review of 37 case studies demonstrated that both VS and VRS positively influence undergraduate nursing education by improving outcomes related to evidence-based practice. The findings advocate for the inclusion of these technologies in nursing curricula to better prepare students for clinical challenges and foster effective nursing care based on evidence (Cant et al., 2022).
Development and Impact of an Inpatient Staffing Dashboard
What was the objective of the inpatient staffing dashboard project?
The project at Loma Linda University Medical Center aimed to enhance staffing management through a collaborative dashboard designed to increase transparency and optimize resource allocation.
How was the dashboard developed and implemented?
A multidisciplinary team comprising nursing staff from the staffing department and analytics experts from the Information Systems group worked together to design and refine dashboard mockups. The completed dashboard was integrated within Epic Hyperspace and SharePoint platforms, with access tailored to user roles.
What functionalities does the dashboard provide?
| Dashboard Tab | Description |
|---|---|
| Main Page | Overview of current staffing status |
| Staffing by Labor Mix | Comparison of staffing requirements versus actual staffing levels |
| Productive-Nonproductive Hours | Historical and projected hours spent on productive vs. nonproductive tasks |
| Filled Percentage by Position | Staffing fulfillment rate for each role |
What was the impact of the dashboard?
The dashboard improved transparency and enabled leadership to make data-driven staffing decisions customized to both unit and institutional needs. This collaborative approach led to better utilization of staffing resources and improved quality of patient care (Role et al., 2021).
Telehealth to Improve Delirium Screening in ICU Nurses
Why is delirium screening critical in the ICU?
Delirium is a common and serious condition in ICU patients. Early and accurate screening is vital for timely diagnosis and intervention, which can significantly reduce complications and improve patient recovery.
How was telehealth applied in this study?
The study observed 13 ICU nurses across several hospitals remotely via telehealth as they conducted delirium screenings using the Confusion Assessment Method for the ICU (CAM-ICU). An expert geriatrician provided real-time feedback and coaching through the telehealth platform.
What challenges were found in delirium assessments?
Several issues were noted, including incorrect sedation scale usage (RASS), improper CAM-ICU administration, lack of baseline cognition knowledge, inappropriate “unable to assess” usage, and confusion about assessment timing.
What outcomes resulted from telehealth-based training?
After receiving telehealth feedback, nurses showed marked improvements in assessment accuracy. The nurses viewed telehealth coaching positively, recognizing its value for ongoing education and enhancing delirium screening quality in ICU settings (Sinvani et al., 2022).
Wearable and Mobile Applications in Preventative Healthcare
What expertise is necessary to develop wearable health technologies?
Creating effective wearable health devices and apps requires interdisciplinary collaboration among electronic engineers, computer scientists, user experience designers, psychologists, health professionals, and clinicians.
What types of wearable devices and biosensors exist today?
Current wearable technologies include consumer products like Apple Watches and heart monitors, as well as specialized biosensors such as portable electrocardiographs and physiological patches. These devices generally pair with smartphone applications to provide real-time data visualization and analysis.
What are the advantages of wearable health technologies?
Wearables enhance patient engagement by enabling self-monitoring of health metrics and supporting fitness goals. Their design balances clinical accuracy with user comfort, aesthetics, and ease of use.
What is the future focus for wearable health data?
A key challenge lies in effectively analyzing and interpreting the extensive data generated by these devices. Future efforts will aim to convert raw data into actionable insights that support preventive healthcare and improve patient outcomes (Huang, Li, & Alem, 2018).
References
Abd-alrazaq, A. A., Bewick, B. M., Farragher, T., & Gardner, P. (2019). Factors that affect the use of electronic personal health records among patients: A systematic review. International Journal of Medical Informatics, 126, 164–175. https://doi.org/10.1016/j.ijmedinf.2019.03.014
Cant, R., Cooper, S., & Ryan, C. (2022). Using virtual simulation to teach evidence-based practice in nursing curricula: A rapid review. Worldviews on Evidence-Based Nursing, 19(5), 415–422. https://doi.org/10.1111/wvn.12572
Role, J., Chao, H., Rosario, C., Ho, P., & Hodgkins, M. (2021). Inpatient staffing dashboard: A nursing-information technology collaborative project. Computers, Informatics, Nursing: CIN, 39(11), 772–779. https://doi.org/10.1097/CIN.0000000000000778
Sinvani, L., Hertz, C., Chandra, S., Ilyas, A., Ardito, S., & Hajizadeh, N. (2022). Using telehealth to improve the accuracy of delirium screening by bedside critical care nurses. American Journal of Critical Care, 31(1), 73–76. https://doi.org/10.4037/ajcc2022773
Huang, W., Li, J., & Alem, L. (2018). Towards preventative healthcare: A review of wearable and mobile applications. Studies in Health Technology & Informatics, 251, 11–14. https://search.ebscohost.com/login.aspx?direct=true&db=mdc&AN=29968589&site=edslive&scope=site&authtype=sso&custid=ns017578
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