Children with Special Health Care Needs: Comparison of the Effects of Home Care Setting, Prescribed Pediatric Extended Care Setting, and Long-Term Care Setting on Child and Family Health Outcomes and Health Care Service Use

Technological advances during the past 30 years have dramatically improved survival rates for children with life-threatening conditions (preterm births, congenital anomalies, disease, or injury) resulting in children with special health care needs (CSHCN), children who have or are at increased risk for a chronic physical, developmental, behavioral, or emotional condition and who require health and related services beyond that required by children generally. There are approximately 10.2 million of these children in the United States or one in five households with a child with special health care needs. Care for these children is limited to home care, medical day care (Prescribed Pediatric Extended Care; P-PEC) or a long term care (LTC) facility. There is very limited research examining health outcomes of CSHCN and their families. The purpose of this research was to compare the effects of home care settings, P-PEC settings, and LTC settings on child health and functioning, family health and function, and health care service use of families with CSHCN. Eighty four CSHCN ages 2 to 21 years having a medically fragile or complex medical condition that required continual monitoring were enrolled with their parents/guardians. Interviews were conducted monthly for five months using the PedsQL TM Generic Core Module for child health and functioning, PedsQL TM Family Impact Module for family health and functioning, and Access to Care from the NS-CSHCN survey for health care services. Descriptive statistics, chi square, and ANCOVA were conducted to determine differences across care settings. Children in the P-PEC settings had a highest health care quality of life (HRQL) overall including physical and psychosocial functioning. Parents/guardians with CSHCN in LTC had the highest HRQL including having time and energy for a social life and employment. Parents/guardians with CSHCN in home care settings had the poorest HRQL including physical and psychosocial functioning with cognitive difficulties, difficulties with worry, communication, and daily activities. They had the fewest hours of employment and the most hours providing direct care for their children. Overall health care service use was the same across the care settings.

Network Construction and Graph Theoretical Analysis of Functional Language Networks in Pediatric Epilepsy

This dissertation introduces a new approach for assessing the effects of pediatric epilepsy on the language connectome. Two novel data-driven network construction approaches are presented. These methods rely on connecting different brain regions using either extent or intensity of language related activations as identified by independent component analysis of fMRI data. An auditory description decision task (ADDT) paradigm was used to activate the language network for 29 patients and 30 controls recruited from three major pediatric hospitals. Empirical evaluations illustrated that pediatric epilepsy can cause, or is associated with, a network efficiency reduction. Patients showed a propensity to inefficiently employ the whole brain network to perform the ADDT language task; on the contrary, controls seemed to efficiently use smaller segregated network components to achieve the same task. To explain the causes of the decreased efficiency, graph theoretical analysis was carried out. The analysis revealed no substantial global network feature differences between the patient and control groups. It also showed that for both subject groups the language network exhibited small-world characteristics; however, the patient’s extent of activation network showed a tendency towards more random networks. It was also shown that the intensity of activation network displayed ipsilateral hub reorganization on the local level. The left hemispheric hubs displayed greater centrality values for patients, whereas the right hemispheric hubs displayed greater centrality values for controls. This hub hemispheric disparity was not correlated with a right atypical language laterality found in six patients. Finally it was shown that a multi-level unsupervised clustering scheme based on self-organizing maps, a type of artificial neural network, and k-means was able to fairly and blindly separate the subjects into their respective patient or control groups. The clustering was initiated using the local nodal centrality measurements only. Compared to the extent of activation network, the intensity of activation network clustering demonstrated better precision. This outcome supports the assertion that the local centrality differences presented by the intensity of activation network can be associated with focal epilepsy.