CMS Star Rating

2020 ◽  
pp. 115-137
Author(s):  
Kevin D. Masick ◽  
Eric Bouillon
Keyword(s):  
2010 ◽  
Vol 40 (4) ◽  
pp. 14
Author(s):  
MITCHEL L. ZOLER
Keyword(s):  

2019 ◽  
Author(s):  
Linn K. Aasheim ◽  
Antonio Freitas Miguel ◽  
Sofia Brito Ramos

2020 ◽  
Vol 4 (6) ◽  
Author(s):  
Orna Intrator ◽  
Edward Alan Miller ◽  
Portia Y Cornell ◽  
Cari Levy ◽  
Christopher W Halladay ◽  
...  

Abstract Background and Objectives U.S. Department of Veterans Affairs Medical Centers (VAMCs) contract with nursing homes (NHs) in their community to serve Veterans. This study compares the characteristics and performance of Veterans Affairs (VA)-paid and non-VA-paid NHs both nationally and within local VAMC markets. Research Design and Methods VA-paid NHs were identified, characterized, and linked to VAMC markets using data drawn from VA administrative files. NHs in the United States in December 2015 were eligible for the analysis, including. 1,307 VA-paid NHs and 14,253 non-VA-paid NHs with NH Compare measures in 128 VAMC markets with any VA-paid NHs. Measurements were derived from the Centers for Medicare and Medicaid Services (CMS) five-star rating system, NH Compare. Results VA-paid NHs had more beds, residents per day, and were more likely to be for-profit relative to non-VA-paid NHs. Nationally, the average CMS NH Compare star rating was slightly lower among VA-paid NHs than non-VA-paid NHs (3.05 vs. 3.21, p = .04). This difference was seen in all 3 domains: inspection (3.11 vs. 3.23, p < .001), quality (2.68 vs. 2.83, p < .001), and total nurse staffing (3.36 vs. 3.42, p < .10). There was wide variability across VAMC markets in the ratio of average star rating of VA-paid and non-VA-paid NHs (mean ratio = 0.93, interquartile range = 0.78–1.08). Discussion and Implications With increased community NH use expected following the implementation of the MISSION Act, comparison of the quality of purchased services to other available services becomes critical for ensuring quality, including for NH care. Methods presented in this article can be used to examine the quality of purchased care following the MISSION Act implementation. In particular, dashboards such as that for VA-paid NHs that compare to similar non-VA-paid NHs can provide useful information to quality improvement efforts.


BDJ ◽  
2008 ◽  
Vol 204 (2) ◽  
pp. 101-101
Keyword(s):  

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 22-23
Author(s):  
Latarsha Chisholm ◽  
Akbar Ghiasi ◽  
Justin Lord ◽  
Robert Weech-Maldonado

Abstract Racial/ethnic disparities have been well documented in long-term care literature. As the population ages and becomes more diverse over time, it is essential to identify mechanisms that may eliminate or mitigate racial/ethnic disparities. Culture change is a movement to transition nursing homes to more home-like environments. The literature on culture change initiatives and quality has been mixed, with little to no literature on the use of culture change initiatives in high Medicaid nursing homes and quality. The purpose of this study was to examine how the involvement of culture change initiatives among high Medicaid facilities was associated with nursing home quality. The study relied on both survey and secondary nursing home data for the years 2017-2018. The sample included high Medicaid (85% or higher) nursing homes. The outcome of interest was the overall nursing home star rating obtained from the Nursing Home Compare Five-Star Quality Rating System. The primary independent variable of interest was the years of involvement in culture change initiatives among nursing homes, which was obtained from the nursing home administrator survey. The final model consisted of an ordinal logistic regression with state-level fixed effects. High-Medicaid nursing homes with six or more years in culture change initiatives had higher odds of having a higher star rating, while facilities with one year or less had significantly lower odds of having a higher star rating. Culture change initiatives may require some time to effectively implement, but these initiatives are potential mechanisms to improve quality in high Medicaid nursing homes.


2018 ◽  
Vol 21 (15) ◽  
pp. 2776-2781 ◽  
Author(s):  
Zenobia Talati ◽  
Simone Pettigrew ◽  
Bridget Kelly ◽  
Kylie Ball ◽  
Bruce Neal ◽  
...  

AbstractObjectiveBy clearly conveying the healthiness of a food, front-of-pack (FOP) labels have the potential to influence the portion size considered appropriate for consumption. The present study examined the how the Daily Intake Guide (DIG), Multiple Traffic Lights (MTL) and Health Star Rating (HSR) FOP labels affect judgements of appropriate portion sizes of unhealthy foods compared with when no FOP label is present.DesignRespondents viewed mock packages of unhealthy variations of pizzas, cookies, yoghurts and cornflakes featuring the DIG, MTL, HSR or no FOP label, and indicated the portion size they believed should be eaten of each food on a single occasion.SettingThe survey was completed on the respondent’s personal computer.SubjectsA total of 1505 Australian adults provided 4166 ratings across 192 mock packages relating to four product categories: pizza, yoghurt, cornflakes and cookies.ResultsCompared with no FOP label, the HSR resulted in a small but significant reduction in the portion size selected as appropriate for consumption of pizzas and cornflakes (P<0·05). The MTL resulted in smaller portions of cornflakes being selected compared with no FOP label (P<0·05).ConclusionsRespondents perceived smaller portion sizes as appropriate for some, but not all, of the foods tested when FOP labels with more interpretative formats (HSR, MTL) appeared on-pack compared with no FOP label. No effect was found for the less interpretive FOP label (the DIG). Interpretive FOP labels may have the potential to influence portion size judgements, albeit at modest levels.


2020 ◽  
Vol 1 (4) ◽  
pp. 468-488
Author(s):  
Akiyo Nadamoto ◽  
Kazuhiro Akiyama ◽  
Tadahiko Kumamoto

Today, huge numbers of reviews are posted on the internet. Online shoppers often refer to reviews written about the products. A review has a star rating that represents what other people think about the product. However, the star rating is not always appropriate for evaluating the product. High-value reviews that affect the users' willingness to buy are independent of the number of stars in ratings. High-value reviews are those from which people find useful information those regarded as good reviews. As described in this paper, we investigated the relation between high-value reviews and the sentiment (positive/negative/neutral) of their clauses based on four hypotheses. We extract characteristics of high-value reviews based on our results. Furthermore, we propose a classification method that classifies clause level sentiment from reviews.


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