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Due to the advance of mobile technology, use of mobile devices such as smartphones has been growing rapidly in the U.S. and worldwide. Many health related mobile apps have been developed for care professionals and patients as well. However, studies indicate that there is a gap between science and commercially developed mobile apps. In addition to this, there is no framework to guide devlopment of a mobile app to overcome many challenges and obstacles. Through the development of a pain management mobile app for cancer patients, a framework was developed. A proposed framework was based on the technology acceptance model, ensuring usefulness and ease of use for end users. The first two steps in the framework enforce accurate knowledge translation and communication to build a science based mobile app. Iterative decisions points between steps enhance accomplishment of each step. [ABSTRACT FROM AUTHOR]

To enhance patient safety from falls, many hospital information systems have been implemented to collect clinical data from the bedside and have used the information to improve fall prevention care. However, most of them use administrative data not clinical nursing data. This necessitated the development of a web-based Nursing Practice and Research Information Management System (NPRIMS) that processes clinical nursing data to measure nurses' delivery of fall prevention care and its impact on patient outcomes. This pilot study developed computer algorithms based on a falls prevention protocol and programmed the prototype NPRIMS. It successfully measured the performance of nursing care delivered and its impact on patient outcomes using clinical nursing data from the study site. Results of the study revealed that NPRIMS has the potential to pinpoint components of nursing processes that are in need of improvement for preventing patient from falls. [ABSTRACT FROM AUTHOR]

Innovative nursing education methods became essential due to the COVID-19 pandemic. Immersive Virtual Reality (VR) education offers nursing students authentic patient encounters in a realistic simulated environment. A pilot study was conducted to identify nursing education clinical scenarios that should be developed for immersive VR and to assess students' perception of immersive VR in education. We formed a focus group composed of nursing faculty (N=10) with expertise in the clinical setting and simulation. Faculty participants identified important topics and aspects of immersive VR scenarios during focus group discussions. We assessed nursing student participants' (N=11) perception of immersive VR in nursing education using a VR game (Anatomy Explorer 2020). Most student participants indicated that a VR game was immersive and realistic and recommended using immersive VR to learn clinical nursing skills. Realistic immersive VR clinical education scenarios could result in effective clinical nursing education., (©2022 AMIA - All rights reserved.)

Nursing has embraced flexible online advanced education as a means of increasing the supply of nurse professionals. Virtual simulation and other adaptive learning technologies enhance learning efficiency and student outcomes. A simulated electronic health record (DocuCare) was adopted in an online graduate nursing informatics course. An assignment using DocuCare to learn core concepts of nursing informatics was developed for graduate students enrolled in a nursing informatics course. A validated standard informatics survey instrument was used to measure three individual domains (basic computer skills, roles, and advanced computer skills (clinical informatics)) as well as the combined informatics competency level. Overall, the nursing informatics competency level was between competent and proficient; basic computer skills and roles were above proficient; and advanced computer skills (clinical informatics) fell between competence and proficient levels.

Studies indicate opioid prevention programs should be designed differently for men and women. Since a website is an effective means of providing behavioral interventions, tailoring one to meet the specific needs of women is a logical step in assisting them to overcome opioid misuse. We identified essential components for inclusion in a website following a community engagement project.

The study demonstrated an application of machine learning techniques in building a depression prediction model. We used the NSHAP II data (3,377 subjects and 261 variables) and built the models using a logistic regression with and without L1 regularization. Depression prediction rates ranged 58.33% to 90.48% and 83.33% to 90.44% in the model with and without L1 regularization, respectively. The moderate to high prediction rates imply that the machine learning algorithms built the prediction models successfully.

We explored the feasibility of representing nursing research data with the Observational Medical Outcomes Partners (OMOP) Common Data Model (CDM) to understand the challenges and opportunities in representing various types of health data not limited to diseases and drug treatments. We collected 1,431 unique data items from 256 nursing articles and mapped them to the OMOP CDM. A deeper level of mapping was explored by simulating 10 data search use cases. Although the majority of the data could be represented in the OMOP CDM, potential information loss was identified in contents related to patient reported outcomes, socio-economic information, and locally developed nursing intervention protocols. These areas will be further investigated in a follow up study. We will use lessons learned in this study to inform the metadata development efforts for data discovery.

In recent years, Decision Support Systems (DSSs) have been developed and used to achieve "meaningful use". One approach to developing DSSs is to translate clinical guidelines into a computer-interpretable format. However, there is no specific guideline modeling approach to translate nursing guidelines to computer-interpretable guidelines. This results in limited use of DSSs in nursing. Unified modeling language (UML) is a software writing language known to accurately represent the end-users' perspective, due to its expressive characteristics. Furthermore, standard terminology enabled DSSs have been shown to smoothly integrate into existing health information systems. In order to facilitate development of nursing DSSs, the UML was used to represent a guideline for medication management for older adults encode with the International Classification for Nursing Practice (ICNP®). The UML was found to be a useful and sufficient tool to model a nursing guideline for a DSS.

Many hospital information systems have been developed and implemented to collect clinical data from the bedside and have used the information to improve patient care. Because of a growing awareness that the use of clinical information improves quality of care and patient outcomes, measuring tools (electronic and paper based) have been developed, but most of them require multiple steps of data collection and analysis. This necessitated the development of a Web-based Nursing Practice and Research Information Management System that processes clinical nursing data to measure nurses' delivery of care and its impact on patient outcomes and provides useful information to clinicians, administrators, researchers, and policy makers at the point of care. This pilot study developed a computer algorithm based on a falls prevention protocol and programmed the prototype Web-based Nursing Practice and Research Information Management System. It successfully measured performance of nursing care delivered and its impact on patient outcomes successfully using clinical nursing data from the study site. Although Nursing Practice and Research Information Management System was tested with small data sets, results of study revealed that it has the potential to measure nurses' delivery of care and its impact on patient outcomes, while pinpointing components of nursing process in need of improvement.