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M Kiley

Publications and source records attributed to M Kiley.

17 recordsLinked to original sources
PubMed1996

Adequacy of two organizing principles for the classification of lay caregiving decisions.

The specific aims of this study were to examine two organizing principles for caregiver planning and the consistency with which four nurses independently classified 1,096 caregiving decisions into one of 12 categories of a taxonomic structure. The typology for classification consisted of a coordinate for goal structure made up of three categories and a coordinate for human need orientation-made up of four categories. The 3-by-4 classification schema was used to develop a coding manual of theoretical and operational definitions for 12 mutually exclusive cell categories of caregiver planning. The criterion for consistency of the nurses' classification judgments was the assignment of a caregiving decision to a cell category identical to the a priori assignment of the principal investigator. The findings from the study provide initial support for content validity of the organizing principles for caregiver planning and interrater reliability of the nurses' judgments when controlling for the effect of chance agreements. The nurses "correctly" classified 63.75% of the targeted caregiving decisions and did not "incorrectly" classify 83.74% of the decisions. The respective coefficient kappas for agreements made on the basis of goal structure and human need orientation were .72 and .65.

Classification↗
PubMed1995

Predictive validity of the Nursing Severity Index in patients with musculoskeletal disease. Nurses of University Hospitals of Cleveland.

Prior studies have not examined the validity of severity of illness instruments in patients at low risk for mortality. We, therefore, examined the predictive validity of a newly developed instrument, the Nursing Severity Index in 5347 adult medical and surgical patients with musculoskeletal diagnoses admitted to an academic medical center in 1985-88. The Index is based on aggregating 34 clinical observations which were recorded by primary nurses during patient care; observations reflect biologic, functional, cognitive and psychosocial abnormalities. Other data, including patient demographic data and outcomes were obtained from hospital data bases. We found that, among all study patients, admission Nursing Severity Index scores were highly related (p < 0.001) to in-hospital death rates-which were 0, 0.4, 0.8, 2.6, 6.7 and 23.5% in six hierarchical strata defined by the Index-and to nursing home discharge rates. In multivariate analyses, adjusting for diagnosis and other important covariates, each strata was associated with a 2.5-fold increased risk of mortality and a 1.6-fold increased risk of nursing home discharge. In addition, the Nursing Severity Index was an independent predictor (p < 0.001) of hospital charges and length of stay. We conclude that the Nursing Severity Index assesses multiple dimensions of illness, can be easily recorded during routine patient care, and accurately predicts hospital outcomes in an important 'low risk' group of patients. The validity of the Nursing Severity Index in other clinical subgroups should be further studied.

Adult↗
PubMed1992

Development and validation of the Nursing Severity Index. A new method for measuring severity of illness using nursing diagnoses. Nurses of University Hospitals of Cleveland.

The purpose of this study was to develop and validate the Nursing Severity Index, a new method used to measure the admission severity of illness of hospital patients using nursing diagnoses, which categorize biologic, functional, cognitive, and psychosocial abnormalities. This retrospective cohort study with independent development and testing phases was conducted at a U.S. academic medical center. In the development phase, data regarding 14,183 adult medical-surgical patients admitted to the medical center in 1985 and 1986 was used. In the testing phase, data regarding 7,302 patients admitted in 1987 and 1988 was used. Primary nurses prospectively recorded the presence or absence of 61 nursing diagnoses on admission. Demographic and clinical data were obtained from hospital data bases. In the development phase, the number of admission nursing diagnoses was highly related (P < 0.001) to in-hospital mortality. Using multiple logistic regression, 34 nursing diagnoses were identified as independent predictors of mortality; the Nursing Severity Index equals the number of these 34 diagnoses. In the testing phase of 7,302 patients, the Nursing Severity Index was related (P < 0.001) to mortality rates, which were 0.5%, 1%, 2%, 6%, 13%, 22%, and 31% in seven hierarchical strata defined by the Index. The Index was as accurate in predicting mortality as MedisGroups (receiver-operating-characteristic curve areas, 0.814 +/- 0.016 vs. 0.845 +/- 0.015, respectively, P = 0.12). Furthermore, the Nursing Severity Index and MedisGroups together (receiver operating characteristic curve area 0.880 +/- 0.014), were more accurate (P < 0.01) than either measure alone. The Nursing Severity Index assesses multiple dimensions of illness, can be easily measured during routine patient care, accurately predicts the risk of in-hospital death, and has similar prognostic accuracy as MedisGroups. Its usefulness in outcomes assessment, quality assurance, and case management merits further study.

Academic Medical Centers↗
PubMed1984

Case mix management.

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Costs and Cost Analysis↗