- “Naturalistic” studies (e.g., epidemiological studies, such as incidence and prevalence studies, including by detailed subpopulations ).
- Patterns of service use by subpopulations (including creating typologies, latent classes, and trajectories by subpopulations).
- Tracking outcomes associated with interventions, intervention doses or durations.
- Identifying risk or protective factors in data sources that may mediate the presence of a given problem or condition, or the impact of a given intervention.
- Looking at how interventions in a single agency impact outcomes across multiple agencies.
- Identifying high-risk of high cost groups or multisystem service users, for whom improved services coordination is indicated.
Intervention and Evaluation Research
(Experimental or quasi-experimental studies)
- Testing program interventions to assess their impact on utilization uptake or outcomes.
- Random assignment of people, neighborhood, or counties to different interventions to assess the impact of a program.
- Creating comparison groups of people not exposed to an intervention to estimate the potential effects of intervention, including using propensity score matching or regression discontinuity approaches.
- Monitoring community-level impacts of population-level interventions (e.g., public service announcements, educational campaigns).
- Time series analysis to examine whether policy changes impact aggregate program utilization.
AISP aims to improve education, health and human services through the integration of data. Integrated data allow foundations, practitioners, and executive leaders in municipal, county, and state government to evaluate, improve, and invest in effective programs and services for the people they serve.
The value of integrated data is routinely demonstrated through projects in areas such as education, housing, justice, workforce, and health and human services that directly impact policy analysis and foster program improvement. Integrated data serves to better illustrate how interventions affect the communities and people they are designed to impact.
Examples of IDS Benefits
- Los Angeles County IDS Use Example: Project 50: Ending Chronic Homelessness with Permanent Supportive Housing and Integrated Data Systems – Project 50 was a coordinated effort among multiple government agencies to provide permanent housing and supportive services to 50 of the most vulnerable chronically homeless individuals living in LA
County’s Skid Row.
- South Carolina IDS Use Example: Expanding Crisis Mental Health Care Using Telepsychiatry and Integrated Data Systems
- New York City IDS Use Example: Paving the Way for a More Prosperous Future for Young Adults: Preliminary Results of an Outcomes Study of the Chelsea Foyer at the Christopher
- The Massachusetts Opioid Epidemic: A data visualization of findings from the Chapter 55 report
Given the pivotal role of integrated data systems in generating actionable intelligence, John Fantuzzo and Dennis Culhane and and their co-authors created the book: Actionable Intelligence for Social Policy: Using Integrated Data Systems to Achieve More Effective, Efficient, and Ethical Government. The book presents the AISP model in detail and indicates how it has more promise than existing approaches to public administration. Chapters focus on the core components necessary to establish well-developed, sustainable IDS, case studies of national models of well-developed state and local IDS, illustrations of exemplary uses and how the AISP model is confluent with a number of social policy innovation strategies emanating from the federal, state and local governments, as well as the private sector. Learn more about the AISP book.