Computers, informatics, nursing : CIN
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The purpose of this pilot study was to assess the feasibility and usability of an ecological momentary assessment smartphone application. The app collected real-time data on chronic low back pain and time-contingent ecological momentary assessment surveys during a 4-week auricular point acupressure intervention, and on the consistency between recalled and momentary clinical measures. Eighteen participants received auricular point acupressure treatment weekly for 4 weeks. ⋯ Self-reported average pain interference with daily activities showed a similar result. Spearman rank correlation coefficients were greater than +0.70; P < .01 for the associations among recalled and momentary measurements. In conclusion, the study demonstrated promising adherence rates and supported the usability and feasibility of using an ecological momentary assessment application on a smartphone to collect real-time data on chronic lower back pain, which eliminated recall bias.
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Effective nurse decision making is essential for best patient outcomes in the acute care nurse practice environment. The purpose of this study was to explore acute care RNs' perceptions of clinical decision making for a patient who experienced a clinical event. Clinical events include changes in patient condition and are manifested by fever, pain, bleeding, changes in output, changes in respiratory status, and changes in level of consciousness. ⋯ The emergent categories included Awareness of Patient Status, Experience and Decision Making, Following Established Routine, Time Pressure, Teamwork/Support From Staff, Goals, Education, Resources, Patient Education, Consideration of Options to Meet Goals, and Nursing Roles. Acute care nurses incorporated a wide variety of complex factors when decision making. This study sought to improve understanding of the factors nurses found important to their decision making for the potential development of improved decision support in the electronic health record.
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Home care nurses have multiple goals at the patient admission visit. Electronic health records support some of these goals, including high-quality documentation, but nurses may not complete the electronic documentation at the point of care. To characterize admission nurses' practices at the point of care and lay the foundation for design recommendations, this study investigates admission nurses' documentation strategies with respect to entering electronic data and how nursing goals affect them. ⋯ Home care admission nurses distribute the electronic documentation temporally due to their goals. Nurses developed memory aids to support completion of the documentation after leaving the patients' homes. Design and training should support the distributed manner in which home care nurses document patient encounters.
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Assessing usability of an electronic medical record is useful for organizations wishing to customize their electronic medical record and determine the impact on usability. The purpose of this article is to describe the development of a protocol to measure electronic medical record usability from a nursing perspective and to develop a scoring methodology. The Technical Evaluation, Testing, and Validation of the Usability of Electronic Health Records (NISTIR 7804), published by the National Institute of Standards and Technology, guided protocol development. ⋯ Protocol implementation and the scoring/grading calculations can be replicated to assess electronic medical record usability. The three scenarios used in this protocol will be made available upon request from the primary author to promote the use of electronic medical record usability assessment. Using and expanding upon the government's recommended usability assessment guidelines, we were successful in measuring nursing electronic medical record usability and rating an electronic medical record.
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Timely detection of deterioration in status for intensive care unit patients can be problematic due to variation in data availability and the necessity of integrating data from multiple sources. This can lead to opaqueness of clinical trends and failure to rescue. Automated deterioration detection using electronic medical record data can reduce the risk of failure to rescue. ⋯ Positive and negative predictive values and sensitivity and specificity measures varied across studies. Three systems generated clinician alerts. Automated deterioration detection using electronic medical record data may be an important aid in caring for intensive care unit patients, but its usefulness is limited by variable electronic medical record detection approaches and performance.