19.1 REVIEW OF CURRENT METRODS FOR POPULATION HEALTH MANAGEMENT FOR YOUTH WITH BEHAVIORAL HEALTH PROBLEMS

• Published in: Journal of the American Academy of Child and Adolescent Psychiatry Vol. 55; no. 10; p. S29
• Main Author: Knutson, Katherine Hobbs
• Format: Journal Article
• Language: English
• Published: Baltimore Elsevier BV 01.10.2016
• Subjects: Algorithms; Automation; Behavior disorders; Behavior problems; Ca2+-transporting ATPase; Care delivery; Child & adolescent psychiatry; Clinical outcomes; Complexity; Delivery Systems; Depression; Disease management; Health behavior; Health care delivery; Health care industry; Health problems; Health status; Hospital discharged; Integrated care; Medical screening; Mental disorders; Mental health; Mental health care; Mental Health Programs; Outcome Measures; Pediatrics; Primary care; Professional associations; Purchasing; Social services delivery; Specialists; Technological change
• ISSN: 0890-8567; 1527-5418

Objectives: Population health approaches rely on stratifying the population according to risk and allocating scarce resources appropriately based on identified need. There are not enough pediatric behavioral health (BH) specialists to meet the needs of most populations, so developing methods for identifying these youth, stratifying according to BH complexity, and monitoring health outcomes could guide the effective use of resources. Methods: We reviewed the literature supporting common methods for identifying and stratifying risk for youth with BH problems, with particular attention to emerging methods incorporating data and new technologies. We reviewed healthcare delivery systems that use population-based patient registries and emerging methods for measuring and monitoring BH outcomes. Results: Many medical professional organizations and value-based purchasing entities support screening for behavioral health problems within pediatric primary care, and although limited, data suggest that BH problems such as adolescent depression may be identified accurately by these methods. The Pediatric Medical Complexity Algorithm (PMCA) uses paid claims or hospital discharge data to identify youth with medical complexity and stratify risk, with 89 percent sensitivity and 85 to 91 percent specificity. Collaborative care models emphasize the use of population-based patient registries, and pediatric BH outcome measures are currently available through the Healthcare Effectiveness Data and Information Set (HEDIS). Conclusions: Many payment and healthcare systems currently engage in population health management for youth with BH problems, and screening for BH problems within primary care is a common method for identifying cases. Besides the PMCA, we found few examples of data-driven and automated methods for identifying youth with BH problems and stratifying risk. Likewise, there were few pediatric BH outcome measures available in HEDIS, and more are currently in development. Further research to improve these methodologies could support more effective use of scarce pediatric mental health resources and improve access for youth with complex conditions.