An evaluation of two patient classification systems as the determinants of a staffing pattern for medical patients

• Main Author: Chubbs, Judy A.
• Other Authors: Memorial University of Newfoundland. School of Nursing
• Format: Thesis
• Language: English
• Published: 1994
• Subjects: Hospital patients; Medical care > Cost shifting; Nursing services > Administration; Nursing services > Planning; Newfoundland studies; University of Newfoundland
• Online Access: http://collections.mun.ca/cdm/ref/collection/theses3/id/1333

Thesis (M.N.)--Memorial University of Newfoundland, 1994. Nursing Bibliography: leaves 130-138 A descriptive correlational study was conducted to (a) assess the psychometric properties of two patient classification systems, (b) explore the relationship between nursing care time and intensity and (c) integrate nursing care time and intensity data to predict a staffing pattern. Seventy-one medical patients representing 373 patient days constituted the sample. The Nursing Intensity Index (Nil) and the GRASP instruments were used for data collection. Descriptive and inferential statistics were used for data analysis. -- High internal consistency and inter rater reliability were demonstrated for both the Nil and GRASP. Factor analysis generated nine factors to explain 73.6% of the variance in GRASP and three factors to explain 59.4% of the variance in the Nil. Nil scores were significantly correlated with GRASP scores indicating a shared variability of 49%. Regression analysis indicated that seven Nil items explained 55% of the total GRASP score, thus leaving 45% of the variability in nursing workload unexplained. Integration of GRASP and Nil data produced a skill mix ratio of 80 percent RN to 20 percent RNA. However, this ratio was not supported by the perceptions of direct caregivers. Methodological and application problems may have influenced this result. More research is needed to identify other factors that may affect skill mix before firm conclusions can be made. -- Key Words: patient classification system; nursing care time; hours of care; quantity; nursing care complexity; intensity; skill mix; staffing pattern.