First Year of Skilled Nursing Facility Value-based Purchasing Program Penalizes Facilities With Poorer Financial Performance

作者
Hari Sharma,Jennifer Gaudet Hefele,Lili Xu,Bryant Conkling,Xiao Wang
出处
期刊:Medical Care [Lippincott Williams & Wilkins]
卷期号:59 (12): 1099-1106 被引量:7
标识
DOI:10.1097/mlr.0000000000001648
摘要

BACKGROUND: The Skilled Nursing Facility Value-based Purchasing Program (SNF-VBP) incentivizes facilities to coordinate care, improve quality, and lower hospital readmissions. However, SNF-VBP may unintentionally punish facilities with lower profit margins struggling to invest resources to lower readmissions. OBJECTIVE: The objective of this study was to estimate the SNF-VBP penalty amounts by skilled nursing facility (SNF) profit margin quintiles and examine whether facilities with lower profit margins are more likely to be penalized by SNF-VBP. RESEARCH DESIGN: We combined the first round of SNF-VBP performance data with SNF profit margins and characteristics data. Our outcome variables included estimated penalty amount and a binary measure for whether facilities were penalized by the SNF-VBP. We categorized SNFs into 5 profit margin quintiles and examined the relationship between profit margins and SNF-VBP performance using descriptive and regression analysis. RESULTS: The average profit margins for SNFs in the lowest profit margin quintile was -14.4% compared with the average profit margin of 11.1% for SNFs in the highest profit margin quintile. In adjusted regressions, SNFs in the lowest profit margin quintile had 17% higher odds of being penalized under SNF-VBP compared with facilities in the highest profit margin quintile. The average penalty for SNFs in the lowest profit margin quintile was $22,312. CONCLUSIONS: SNFs in the lowest profit margins are more likely to be penalized by the SNF-VBP, and these losses can exacerbate quality problems in SNFs with lower quality. Alternative approaches to measuring and rewarding SNFs under SNF-VBP or programs to assist struggling SNFs is warranted, particularly considering the coronavirus disease 2019 pandemic, which requires resources for prevention and management.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
李爱国应助陈陈陈采纳,获得20
1秒前
科研通AI6.2应助清浅时光采纳,获得10
2秒前
xyc完成签到,获得积分10
3秒前
ZZZ完成签到,获得积分10
3秒前
小熊西完成签到,获得积分10
6秒前
7秒前
7秒前
NexusExplorer应助儒雅的夏山采纳,获得10
7秒前
小二郎应助2025doctor采纳,获得10
8秒前
10秒前
包容的若风完成签到 ,获得积分10
11秒前
11秒前
12秒前
小圆完成签到,获得积分10
13秒前
runzhi发布了新的文献求助10
13秒前
14秒前
汉堡包应助Yyyang采纳,获得10
14秒前
15秒前
wanci应助尉迟笑蓝采纳,获得10
16秒前
16秒前
岁杪完成签到,获得积分10
17秒前
lijin发布了新的文献求助10
17秒前
18秒前
星河鹭起完成签到,获得积分10
19秒前
瓜酱酱发布了新的文献求助10
19秒前
19秒前
19秒前
银河系小熊完成签到,获得积分10
19秒前
在水一方应助Juanita采纳,获得10
19秒前
20秒前
张欢馨应助酷炫的问芙采纳,获得10
21秒前
啊啊啊完成签到 ,获得积分10
21秒前
21秒前
minkeyantong完成签到 ,获得积分10
21秒前
25秒前
26秒前
26秒前
27秒前
28秒前
啦啦啦啦啦完成签到 ,获得积分10
29秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Römisch-Germanische Forschungen 1000
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
Green Fire Retardants for Polymeric Materials 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7617224
求助须知:如何正确求助?哪些是违规求助? 9192435
关于积分的说明 19700144
捐赠科研通 7189573
什么是DOI,文献DOI怎么找? 3271994
关于科研通互助平台的介绍 2434749
邀请新用户注册赠送积分活动 2267014