The effect of predictive analytics-driven interventions on healthcare utilization
- Collection:
- Health Policy and Services Research
- Series Title(s):
- Research brief (Leonard Davis Institute of Health Economics)
- Author(s):
- David, Guy, author Smith-McLallen. Aaron, author Ukert, Benjamin, author
- Contributor(s):
- Leonard Davis Institute of Health Economics, issuing body.
- Publication:
- Philadelphia, PA : Leonard Davis Institute of Health Economics, 2019
- Language(s):
- English
- Format:
- Text
- Subject(s):
- Algorithms Data Science Facilities and Services Utilization -- statistics & numerical data Heart Failure -- therapy Risk Assessment Emergency Medical Services -- statistics & numerical data Hospitalization -- statistics & numerical data Medicare Part C Office Visits -- statistics & numerical data Risk Humans United States
- Genre(s):
- Technical Report
- Abstract:
- Among high-risk Medicare Advantage members with congestive heart failure, a proactive outreach program driven by a claims-based predictive algorithm reduced the likelihood of an emergency department (ED) or specialist visit in one year by 20% and 21%, respectively. The average number of visits dropped as well, with a 40% reduction in the volume of ED visits and a 27% reduction in the volume of cardiology visits after the first year.
- Copyright:
- Reproduced with permission of the copyright holder. Further use of the material is subject to CC BY license. (More information)
- Extent:
- 1 online resource (1 PDF file (2 unnumbered pages))
- Illustrations:
- Illustrations and Portraits
- NLM Unique ID:
- 101750238 (See catalog record)
- Permanent Link:
- http://resource.nlm.nih.gov/101750238