PubMed · 11637762
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E Orosz. 1986. [Not Available].. https://pubmed.ncbi.nlm.nih.gov/11637762/
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STUDY DESIGN: Retrospective. OBJECTIVE: To predict satisfaction with medical rehabilitation. SUMMARY OF BACKGROUND DATA: While spinal cord injury (SCI) patient satisfaction with life and community services has been investigated, satisfaction with medical rehabilitation has not. METHODS: Information submitted to the Uniform Data System for Medical Rehabilitation (1998-2001) by 134 hospitals/rehabilitation facilities in the United States (n = 6,205 patients with SCI) was examined. Predictors were sociodemographic variables, Case Mix Groupings (CMG) (401-505, 5001), length of stay, rehospitalization, follow-up therapy, and health maintenance. Satisfaction was assessed at a mean of 92.2 days (SD 11.9 days) postdischarge. Data were analyzed according to who reported the outcome (patient, n = 3,858 or family/other, n = 1,869). Statistical modeling was conducted using logistic regression. RESULTS: High overall satisfaction was reported (94%). Significant predictors for the patient report data were CMG and rehospitalization. Compared with CMG 5001 (short stay, <3 days), patients in CMGs 401/2/3 and 501/2/3/4/5 had a 54% to 74% lower likelihood of being dissatisfied. Rehospitalized patients had a higher likelihood of dissatisfaction (odds ratio 2.3, 95% confidence interval 1.7 to 3.2). Significant predictors for the family/other report data were CMG (compared to CMG 5001, CMGs 401/2, 403, and 501/2 had a 70% lower likelihood of dissatisfaction), rehospitalization (odds ratio 1.7, 95% confidence interval 1.1-2.5), and marital status (married = 50% lower likelihood of dissatisfaction, 95% confidence interval 0.26-0.96). CONCLUSIONS: Satisfaction with medical rehabilitation services following SCI is related to functional abilities, rehospitalization, and marital status. Slightly different results were found for whether satisfaction was rated by the patient or family/other. The complex relationships among satisfaction, patient demographics, and functional status require continued examination.
The major role played by demographic stochasticity in determining the dynamics and persistence of childhood diseases, such as measles, chickenpox and pertussis, has long been realized. Techniques which can be used to estimate the magnitude of this stochastic effect are of clear importance. In this study, we assess and compare the use of two moment closure approximations to estimate the variability seen about the average behavior of stochastic models for the recurrent epidemics seen in childhood diseases. The performance of the approximations are assessed using analytic techniques available for the simplest epidemiological model and using numerical simulations in more complex settings. We also present epidemiologically important extensions of previous work, considering variability in the SEIR model and in situations for which there is seasonal variation in disease transmission. Important implications of stochastic effects for the dynamics of childhood diseases are highlighted, including serious deficiencies of deterministic descriptions of dynamical behavior.
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