| 来源类型 | Publication |
| 来源ID | Issue Brief |
| New Denial and Disenrollment Coding Strategies to Drive State Enrollment Performance | |
| Mary Harrington; Christopher Trenholm; and Andrew Snyder | |
| 发表日期 | 2012-10-30 |
| 出版者 | Princeton, NJ: Robert Wood Johnson Foundation |
| 出版年 | 2012 |
| 语种 | 英语 |
| 概述 | Maximizing Enrollment, a national program of the Robert Wood Johnson Foundation, has worked intensively with eight states since 2009 to help them use enrollment and retention data to improve insurance coverage for eligible individuals.", |
| 摘要 | Maximizing Enrollment, a national program of the Robert Wood Johnson Foundation, has worked intensively with eight states since 2009 to help them use enrollment and retention data to improve insurance coverage for eligible individuals. This brief shares recommendations for classifying denials and disenrollments, discusses why this coding is a powerful tool to understand the effect of policy changes, and shows how states can bridge from their current complex coding systems to a more streamlined approach. |
| URL | https://www.mathematica.org/our-publications-and-findings/publications/new-denial-and-disenrollment-coding-strategies-to-drive-state-enrollment-performance |
| 来源智库 | Mathematica Policy Research (United States) |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/487227 |
| 推荐引用方式 GB/T 7714 | Mary Harrington,Christopher Trenholm,and Andrew Snyder. New Denial and Disenrollment Coding Strategies to Drive State Enrollment Performance. 2012. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| Coding_Strategies_St（728KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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