Predictors of Days at Home for Children with Mechanical Ventilator Assistance

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Project Summary/Abstract The research component of this application proposes using a mixed-methods approach to determine the predictors of increased days at home versus days hospitalized for children with invasive home mechanical ventilator (HMV) assistance throughout the US. These patients, with complex genetic, pulmonary, cardiac, and neuromuscular disorders, have prolonged hospital stays for non-medical reasons and contribute to high percentages of overall pediatric healthcare expenditures. Aim 1 of this proposal utilizes qualitative methodology to understand parental and home nursing perspectives on which circumstances, resources, and child characteristics lead to expeditious discharge and fewer readmissions. Aim 2 will utilize national Medicaid claims to determine which patient, family, and community healthcare factors, particularly home nursing availability, predict positive outcomes including a shorter index hospital stay after tracheostomy placement, a lower likelihood of readmissions and increased days at home. Aim 3 will describe, for a pilot cohort of children with HMV assistance living in the community, functional levels within motoric, cognitive, and communicative domains. The educational component of this application provides advanced training in qualitative, Medicaid claims, and cost-effectiveness analysis. Those skills are essential for Dr. Sobotka to transition into an independent health services research expert on children with medical complexity and neurodevelopmental disabilities. Toward that end, the proposed research project is focused on determining strategies to support children with HMV: the most medically fragile, neurodevelopmentally vulnerable, and highest resource-consuming pediatric patients. Dr. Sobotka’s expertise in neurodevelopment will enable her to assess abilities and disabilities within this cohort. The coursework described will complement and enable her long-term goals by expanding her capabilities in four educational areas: 1) Qualitative research methods; 2) Medicaid Claims analysis; 3) Advanced Epidemiology and Biostatistics; 4) Public Policy. The latter will inform future proposals considering the policy implications of her research findings within the larger healthcare framework. Dr. Sobotka will be supported by investigators and resources at the University of Chicago to provide educational and analytic support, including the Medicaid Data Analysis group, the Department of Public Health Sciences, and the Biostatistics Laboratory. She will be mentored by a team with diverse expertise: primary mentor, Dr. Michael E. Msall, and co-mentors, Dr. Monica E. Peek, Dr. Lucy A. Bilaver, and Dr. Jay G. Berry. Dr. Sobotka is additionally supported by content and methodologic collaborators, Dr. Kit N. Simpson, Dr. Michael T. Quinn, Dr. Rishi K. Agrawal, and Dr. Rob J. Graham. The K23 NICHD career development award will support Dr. Sobotka’s transition to independence.