HSRProj will be retired on September 14, 2021, no updates will be made to HSRProj after this date.
Detailed information about this transition can be found on the
June 3, 2021 Technical Bulletin post.
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Information about ongoing health services research and public health projects
| Model portability for complex patients
(Archived Project) |
|
|---|---|
| Investigator (PI): | Brown, Jonathan B |
| Performing Organization (PO): |
(Current): Kaiser Permanente, Center for Health Research, Center for Health Research Northwest / (503) 335-2400 |
| Supporting Agency (SA): | Agency for Healthcare Research and Quality (AHRQ) |
| Initial Year: | 2009 |
| Final Year: | 2011 |
| Record Source/Award ID: | CRISP/R21HS018596 |
| Award Type: | Grant |
| Abstract: | Computer simulation offers a promising technology to combine and make sense of all the disparate data and knowledge that influence, or should influence modern medical care for complex patients. But several issues deserve more study before simulation-assisted medicine can be considered safe and practical. One such issue is the extent to which risk equations estimated in one location can be used in other locations. A second issue is the need for personal accuracy for individuals, as distinguished from average accuracy in populations. We propose collaboration between the Center for Health Research in Portland, Oregon and the Institute for Health Research in Denver, Colorado, to address these issues. First, we will re-estimate the risk equations in the Evidence-Based Medicine Integrator, an open-source computer simulator for type 2 diabetes, using data from a new population and setting, the Kaiser Permanente Colorado Region (KPCO). We will then test whether new equations differ from equations that were estimated in Kaiser Permanente Northwest Region (KPNW) and test the practical impact of any differences in terms of model recommendations and simulated patient outcomes. Second, we will combine the KPCO and KPNW data into a single dataset and use the resulting large sample size to estimate separate risk equations for patient subgroups, including (a) older and younger patients; (b) ethnic and racial minorities, particularly African Americans, Asians, and Hispanic Americans; and (c) patients at higher levels of morbidity and clinical complexity, particularly those with co-existing depression, pulmonary disease, and treatable cancer. The new risk equations, together with all changes in the simulator, its underlying source code, and the run settings used to test simulator portability, will be placed in a free, open-source development environment. This will allow others to use the simulator for research, management and policy analyses, and clinical prioritization; and to improve the simulator with their own open-source changes and extensions. |
| MeSH Terms: |
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| Country: | United States |
| State: | Oregon |
| Zip Code: | 97227 |
| UI: | 20101132 |
| Project Status: | Archived |
