A model predicting the health status of patients with heart failure
Abstract
Objective: To test the causal relationships among the components of sociodemographics,illnesscharacteristics, and selfmanagement ability, and health status in the model of health status of patients with heart failure (HSHF).
Design: Descriptive cross-sectional study
Materials and methods: Four hundred heart failure patients, either hospitalized or attending out-patient clinics at six hospitals in southern Thailand, were interviewed. Questionnaires covered sociodemographics, the duration of illness, severity of illness, comorbid diseases, measured by the New York Heart Association Functional Classification (NYHA-FC) using the Charlson Comorbidity Index, self-management ability, using the Self-Care of Heart Failure Index (SCHFI), and health status using the Short Form-36 Health Survey (SF-36). The relationships among the study variables were tested and modified under the structural equation modeling (SEM) technique by using LISREL.
Results: The collected data were found not to fit with the initial hypothesized model but after modification the new derived model gave an adequate fit with the data and accounted for 64% of the variance in health status. Age had a direct negative effect on health status (β=-0.20, p < 0.01) and had an indirect negative effect on health status through self-management ability, severity of illness and comorbid disease (β=-0.13, p < 0.01). Education had a direct positive effect on health status (β=0.12, p < 0.01). Gender and income had indirect negative effects on health status through severity of illness (β=-0.05; -0.05, p < 0.05). Duration of illness had an indirect positive effect on health status through self-management ability (β=0.09, p < 0.05). Severity of illness and comorbid disease had a direct negative effect on health status (β=-0.31; -0.16, p < 0.01, respectively) and indirect negative effect on health status through self-management ability (β=-0.06; -0.05, p < 0.05, respectively). Selfmanagement ability had a direct positive effect on health status (β=0.38, p < 0.01).
Conclusions: The final model provides a guideline for explaining and predicting the health status of patients with heart failure. To improve health status continuity care programs promoting self management ability should be developed and imple-mented both in hospital-based and home-based settings.
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