Publications by authors named "P A Mehmert"

Since a substantial component of health care delivery is reflected in nursing's work, it is imperative that nursing expedites implementation of a standardized language that reflects nursing's work and ultimately allows outcome evaluation. This paper will summarize the state of development and related issues of standardized language in nursing, including: Nursing Minimum Data Set, Taxonomies of Nursing Diagnoses, Nursing Interventions, Outcomes, and the Nursing Management Minimum Data Set. The Nursing Minimum Data Set, including nursing care, patient or client demographic, and service elements, reflects a standardized collection of essential nursing data used by multiple data users in the health care delivery system across all types of settings.

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The clinical presence of impaired physical mobility documented for acute-care patients was studied. The frequency, individual, and group sensitivity levels of the defining characteristics documented as empirical referents for the diagnosis were examined. The frequency of the related factors associated with the diagnosis, patient demographics, length of stay (LOS), discharge destination, and diagnostic-related groups (DRGs) were also examined.

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As the use of nursing diagnoses in clinical practice increases, systematic research is necessary to appropriately validate them. Validity studies could be expedited by the use of information technology and computerized clinical data bases. The purpose of the following descriptive study was to validate the defining characteristics (risk factors for potential diagnoses) of the four nursing diagnoses related to alterations in fluid volume proposed by the North American Nursing Diagnosis Association using a nursing minimum data set (NMDS) collected from a computerized nursing data base.

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The purpose of this descriptive study was to validate the nursing diagnosis, bathing/hygiene self-care deficit. Defining characteristics and related factors were abstracted retrospectively from a computerized patient care planning database. Data were treated to descriptive statistics and chi-square analysis to determine frequencies and percentages.

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