Innovations in Design and Utilization of Measurement Systems to Promote Children's Cognitive, Affective, and Behavioral Health Workshop Summary (2015) / Chapter Skim
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6 Breakout Group Discussions
6 Breakout Group Discussions
Pages 63-70
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From page 63... ...
Several important features of families are not currently well measured, such as family structure, family functioning, parental mental health, and child and family strengths. Some children may be more biologically susceptible to adversity, but individual-level markers are not currently measured or incorporated into decision making or datasets.
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From page 64... ...
Similarly, differing cultures and languages across professions can have a strong influence on the ability to share data and set measurement priorities. For instance, in the context of adult health care, behavioral health may refer to chronic disease self-management, self-efficacy, management of substance abuse, or other personal attributes.
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From page 65... ...
Data collection could also be structured in such a way as to counter the fragmentation of health care if data were made available not just to single providers but to teams of service providers in ways that maintain the trust of individuals. Individuals and families often do not have ready access to the services they need.
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From page 66... ...
Data collected at the federal, state, and local levels are not well connected, and public- and private-sector data are isolated from each other. Greater integration, dissemination, and use of these disparate data sources could help achieve many of the objectives sought by workshop participants while reducing duplicated effort.
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From page 67... ...
States currently collect and have access to a wide variety of data, but gaps remain. Examples mentioned by breakout group members include predictor variables, like risk and protective factors; the specific services individual children are receiving; longitudinal information on children; and the early identification of problems.
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From page 68... ...
As Mary Ann McCabe, George Washington University, added, these considerations differ among data types. For example, deidentified administrative data tends to be viewed differently than personally identifiable health care data, particularly in sensitive areas such as mental health.
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From page 69... ...
Legislators tend to react more forcefully to stories than to data, Schiff said, so he always tries to talk about data in the form of stories. At the same time, a little bit of data can go a long way, especially if it drives home an important point.
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