Children with multiple chronic conditions - two or more chronic conditions that affect the person at the same time - represent an important group of individuals who receive inadequate quality of healthcare and experience suboptimal health outcomes. Clinicians, researchers, administrators, and policy experts are currently uninformed on how to best improve care for these children. This is, in part, because of two methodological challenges that are particularly problematic when studying children with multiple chronic conditions: 1) the ability to comprehensively measure and group comorbid conditions in children and 2) the ability to assess pediatric comorbidity burden on a population level. This proposal will validate and test an innovative set of methods that will help overcome these challenges. Although the set of methods, collectively, is new to the study of children with multiple chronic conditions, we have found components of the set to be feasible and valuable in our prior work.
The specific aims of this proposal are 1) to adapt for children a publicly available diagnosis classification scheme (i.e., AHRQ's Chronic Condition Indicator and Clinical Classification System) to name and count coexisting chronic conditions in children;2) to determine the prevalence and the healthcare cost and utilization (total and excessive) of each type of child with multiple chronic conditions;3) to complete an evidenced-based prioritization process, based on the Pareto Principle, to describe the relative contribution of combinations of chronic conditions to prevalence and to healthcare cost and utilization;and 4) to employ an innovative, machine learning method (i.e., regression tree boosting) to systematically assess every interaction of coexisting chronic conditions in children to predict healthcare cost and utilization The proposed work will be conducted in existing datasets that contain 10.7 million children with comprehensive Medicaid claims data (i.e., community, emergency, home, inpatient, outpatient, pharmacy care, etc.) from 28 states as well as 3.7 million hospitalized children from the all-payer, nationally-representative Healthcare Cost and Utilization Project Kids'Inpatient Database developed by Agency for Healthcare Research and Quality. Use of the methods and results generated from this proposal will help clinics, hospitals, communities, states, health systems, payers, federal agencies, and others identify children with multiple chronic conditions, describe their coexisting conditions, determine which of these children have the largest impact on the pediatric healthcare system, and quantify how much of their health care cost and utilization could be avoided with high quality of care. This information will help prioritize which subgroups of children with multiple chronic conditions to target for comparative effectiveness research, quality improvement initiatives, and health system redesign. This proposal is aligned with the mission of the Agency for Healthcare Research and Quality to improve the quality of health care for all Americans.

Public Health Relevance

The research in this proposal is relevant to public health because it will rapidly advance our understanding of the U.S. population of children living with multiple chronic conditions. The research will help identify and describe the children living with multiple chronic conditions, as well as the health care cost and utilization experienced by them. The methods and findings from the research will help improve the health and wellbeing of these children.

National Institute of Health (NIH)
Agency for Healthcare Research and Quality (AHRQ)
Exploratory/Developmental Grants (R21)
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Special Emphasis Panel (ZHS1-HSR-C (02))
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Basu, Jayasree
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Children's Hospital Boston
United States
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