Predicting the health insurance coverage impacts of complex policy changes: a new tool for states
- Collection:
- Health Policy and Services Research
- Series Title(s):
- State Health Reform Assistance Network issue brief
- Contributor(s):
- Sonier, Julie. Robert Wood Johnson Foundation. State Health Access Data Assistance Center, University of Minnesota. State Health Reform Assistance Network.
- Publication:
- [Princeton, N.J.] : State Health Reform Assistance Network, [2012]
- Language(s):
- English
- Format:
- Text
- Subject(s):
- Health Policy -- economics Health Policy -- trends Insurance Coverage -- economics Insurance Coverage -- trends Insurance, Health -- economics Insurance, Health -- trends Models, Econometric Data Collection Demography Forecasting Motivation Humans United States
- Genre(s):
- Technical Report
- Abstract:
- The passage of the Affordable Care Act (ACA) in March 2010 highlighted the ongoing need for tools that state officials can use to project the impacts of complex policy changes on health insurance coverage. Possible approaches to this task range from simple spreadsheets to complex microsimulation models, with each approach having variations and tradeoffs in terms of cost, time, complexity, and adaptability for ongoing state analysis needs. Microsimulation models seek to predict the impacts of policy changes on the decisions of individuals, households, and employers. By modeling decisions at the individual employer and person levels, these models attempt to take into account how varying individual circumstances will affect aggregate outcomes. Several private organizations have developed proprietary microsimulation models, and states that wish to do this type of analysis have typically contracted with one of these organizations. However, the models vary in their approaches, assumptions, and predictions. Although microsimulation models are a valuable tool for estimating state-level impacts of health policy changes, there are several reasons why state officials are interested in other approaches as well. Microsimulation modeling is expensive, and for states it is typically a "one-shot" effort that produces estimates for a limited number of scenarios, without the flexibility to update baseline data or test different assumptions after the fact. In addition, from the state perspective microsimulation modeling is not very transparent. In addition, many microsimulation models rely primarily on national data as inputs, and many states are interested in using state-specific data. To address the need among states for analysis that is timely, state-specific, less expensive, and more flexible for testing alternative assumptions, the State Health Access Data Assistance Center (SHADAC) at the University of Minnesota School of Public Health has developed a complex spreadsheet model--the SHADAC Projection Model--to predict the coverage impacts of policy changes at the state level. Although the model was constructed specifically to help states project the coverage impacts of the ACA, the approach can be adapted to model the coverage impacts of other reform approaches as well. The SHADAC Projection Model is designed to be flexible, evidence-based, transparent, and easy for state officials to understand and use independently. The model was developed with the support of the Robert Wood Johnson Foundation's State Health Reform Assistance Network program. The model was originally developed for one state, but it can be adapted and customized to meet the needs of other states relatively easily.
- Copyright:
- Reproduced with permission of the copyright holder. Further use of the material is subject to CC BY-NC-DC license. (More information)
- Illustrations:
- Illustrations
- NLM Unique ID:
- 101589684 (See catalog record)
- Permanent Link:
- http://resource.nlm.nih.gov/101589684