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Browsing by Subject "patient"

Now showing 1 - 2 of 2
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    Asthma: What can I do?
    (2010-07-22) Ward, Jason
    Asthma action plans fitted to individuals using medication dose training, asthma education, and allergy skin testing is unlikely to increase the chances that a patient will take his or her inhaled steroid (control) asthma medication. Intense counseling may reduce the use of rescue inhalers short term and allow patients to be more confident in their control of asthma, but the cost of such treatment reduces the overall benefit.
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    Charge Nurse Expertise: Implications for Decision Support of the Nurse-Patient Assignment Process
    (2019-05) Meyers, Elizabeth
    Each day, across thousands of medical-surgical inpatient nursing units, charge nurses make decisions about which nurse will care for each patient. Recent attempts have been made to introduce health information technology (HIT) solutions to automate the nurse-patient assignment process. This research investigated charge nurse decision making during the nurse-patient assignment process as an exemplar of the larger question: How can we leverage information technology to improve decision making in healthcare, while respecting individual clinician expertise and the unique context of individualized patient care? Four primary questions were used to guide research of the process, decision factors, goals and context of nurse-patient assignments. A mixed-methods approach of qualitative interviews (N = 11) and quantitative surveys (N = 135) was used. Findings related to the charge nurse decision making process indicate that measurable, nurse-sensitive indicators of patient outcomes have not yet been standardized for nurse-patient assignments. HIT solutions and quality improvement efforts should define, collect and analyze measurable outcome criteria prior to attempting to improve or augment existing nurse-patient assignment practices to prevent unintended consequences. When clear outcome measurements have been identified, informatics researchers and professionals should investigate the ability of machine learning to recognize goal priorities and factor weighting from patient, nurse and environmental factors within existing HIT solutions. Until that time, HIT solutions augmenting the nurse-patient assignment process should be designed with flexible configurations, to enable goals, decision factors and factor weights can be varied by hospital, unit, charge nurse and shift, in order to best meet the needs of charge nurses.