Social media ratings of nursing homes associated with experience of care and “Nursing Home Compare” quality measures

Abstract The purpose of this study was to explore the relationship between nursing home volunteer programming and quality measures and increase the knowledge base of nursing home volunteer programming in various settings. Fifty-two nursing homes were surveyed using electronic surveys and personal interviews. Questions focused on the organization of the nursing home, characteristics of the volunteer program and volunteer activities. Of the 52 facilities surveyed, 19 were not part of a chain, 37 were in urban settings, and 24 were for-profit entities. Volunteers were used in 46 nursing homes with a mean number of volunteers of 51.7 onsite an average of 4.9 days per week. Bivariate analysis revealed statistically significant correlations (p<.05) between organizational and volunteer programming characteristics and six quality measures (pressure sores, urinary tract infections, depression, use of restraints, falls, use of antipsychotic and hypnotic drugs). Statistically significant (p<.05) inverse relationships were found between volunteers providing individualized activities (e.g., feeding assistance, combing hair, doing nails, and letter writing) and the incidence of urinary tract infections and the use of psychotropic drugs. Multiple regression analysis revealed a statistically significant (p<.05) inverse relationship between personal volunteer services such as combing hair and doing nails and the use of hypnotic drugs and antipsychotic drugs. This study indicates a significant correlation between volunteer programming and quality measure scores. A larger study of these relationships is indicated.

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Medical Staffing Organization and Quality of Care Outcomes in Post-acute Care Settings

The Gerontologist ◽

10.1093/geront/gnaa173 ◽

2020 ◽

Author(s):

Laura M Wagner ◽

Paul Katz ◽

Jurgis Karuza ◽

Connie Kwong ◽

Lori Sharp ◽

...

Keyword(s):

Nursing Home ◽

Quality Of Care ◽

Nursing Homes ◽

Acute Care ◽

Quality Measures ◽

Medical Providers ◽

Medical Provider ◽

Provider Characteristics ◽

The Impact

Abstract Background and Objectives Medical providers are significant drivers of care in post-acute long-term care (PALTC) settings, yet little research has examined the medical provider workforce and its role in ensuring quality of care. Research Design and Methods This study examined the impact of nursing home medical staffing organization (NHMSO) dimensions on the quality of care in U.S. nursing homes. The principal data source was a survey specifically designed to study medical staff organization for post-acute care. Respondents were medical directors and attending physicians providing PALTC. We linked a number of medical provider and nursing home characteristics to the Centers for Medicaid and Medicare Services Nursing Home Compare quality measures hypothesized to be sensitive to input by medical providers. Results From the sample of nursing home medical providers surveyed (n = 1,511), 560 responses were received, yielding a 37% response rate; 425 medical provider responses contained sufficient data for analysis. The results of the impact of NHMSO dimensions were mixed, with many domains not having any significance or having negative relationships between provider characteristics and quality measures. Respondents who reported having a formal process for granting privileges and nursing homes with direct employment of physicians reported significantly fewer emergency visits. Discussion and Implications Further research is needed regarding what quality measures are sensitive to both medical provider characteristics and NHMSO characteristics.

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Two Decades of Nursing Home Compare: What Have We Learned?

Medical Care Research and Review ◽

10.1177/1077558720931652 ◽

2020 ◽

pp. 107755872093165

Author(s):

R. Tamara Konetzka ◽

Kevin Yan ◽

Rachel M. Werner

Keyword(s):

Systematic Review ◽

Quality Improvement ◽

Nursing Home ◽

Quality Of Care ◽

Nursing Homes ◽

Risk Adjustment ◽

Public Reporting ◽

Review Of The Literature ◽

Nursing Home Compare

Approximately two decades ago, federally mandated public reporting began for U.S. nursing homes through a system now known as Nursing Home Compare. The goals were to provide information to enable consumers to choose higher quality nursing homes and to incent providers to improve the quality of care delivered. We conduct a systematic review of the literature on responses to Nursing Home Compare and its effectiveness in meeting these goals. We find evidence of modest but meaningful response by both consumers and providers. However, we also find evidence that some improvement in scores does not reflect true quality improvement, that disparities by race and income have increased, that risk-adjustment of the measures is likely inadequate, and that several key domains of quality are not represented. Our results support moderate success of Nursing Home Compare in achieving intended goals but also reveal the need for continued refinement.

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Examination of the New Short-Stay Nursing Home Quality Measures: Rehospitalizations, Emergency Department Visits, and Successful Returns to the Community

INQUIRY The Journal of Health Care Organization Provision and Financing ◽

10.1177/0046958018786816 ◽

2018 ◽

Vol 55 ◽

pp. 004695801878681 ◽

Cited By ~ 2

Author(s):

Debra Saliba ◽

David L. Weimer ◽

Yuxi Shi ◽

Dana B. Mukamel

Keyword(s):

Emergency Department ◽

Nursing Home ◽

Nursing Homes ◽

Regression Models ◽

Quality Measures ◽

Emergency Department Visits ◽

Descriptive Statistics ◽

Short Stay ◽

Nursing Home Quality ◽

Second Year

In 2016, the Centers for Medicare & Medicaid Services (CMS) introduced 3 new quality measures (QMs) to its report card, Nursing Home Compare (NHC). These measures—rehospitalizations, emergency department visits, and successful discharges to the community—focus on short-stay residents. We offer a first analysis of nursing homes’ performance in terms of these new measures. We examined their properties and distribution across nursing homes using descriptive statistics and regression models. We found that, similar to other QMs, performance varies across the country, and that there is very minimal correlation between these 3 new QMs as well as between these QMs and other NHC QMs. Regression models reveal that better performance on these QMs tends to be associated with fewer deficiencies, higher staffing and more skilled staffing, nonprofit ownership, and lower proportion of Medicaid residents. Other characteristics are associated with better performance for some but not all 3 QMs. We also found improvement in all 3 QMs in the second year of publication. This study contributes to the validity of these measures by demonstrating their relationship to these structural QMs. It also suggests that these QMs are important by demonstrating their large variation across the country, suggesting substantial room for improvement, and finding that nursing homes are already responding to the incentives created by publication of these QMs.

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Nursing Homes' Response to the Nursing Home Compare Report Card

The Journals of Gerontology Series B ◽

10.1093/geronb/62.4.s218 ◽

2007 ◽

Vol 62 (4) ◽

pp. S218-S225 ◽

Cited By ~ 49

Author(s):

D. B. Mukamel ◽

W. D. Spector ◽

J. S. Zinn ◽

L. Huang ◽

D. L. Weimer ◽

...

Keyword(s):

Nursing Home ◽

Nursing Homes ◽

Report Card ◽

Nursing Home Compare

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A Systematic Literature Review of Efficiency Measurement in Nursing Homes

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph16122186 ◽

2019 ◽

Vol 16 (12) ◽

pp. 2186 ◽

Cited By ~ 3

Author(s):

Alice Tran ◽

Kim-Huong Nguyen ◽

Len Gray ◽

Tracy Comans

Keyword(s):

Quality Of Life ◽

Nursing Home ◽

Nursing Homes ◽

Measurement Techniques ◽

Quality Measures ◽

Efficiency Measurement ◽

Sensitivity Analyses ◽

Special Focus ◽

Operational Environment

Background: As our population ages at an increasing rate, the demand for nursing homes is rising. The challenge will be for nursing homes to maintain efficiency with limited resources while not compromising quality. This study aimed to review the nursing home efficiency literature to survey the application of efficiency methods and the measurements of inputs, outputs, facility characteristics and operational environment, with a special focus on quality measurement. Methods: We systematically searched three databases for eligible studies published in English between January 1995 and December 2018, supplemented by an exhaustive search of reference lists of included studies. The studies included were available in full text, their units of analysis were nursing homes, and the analytical methods and efficiency scores were clearly reported. Results: We identified 39 studies meeting the inclusion criteria, of which 31 accounted for quality measures. Standard efficiency measurement techniques, data envelopment analysis and stochastic frontier method, and their specifications (orientation, returns to scale, functional forms and error term assumptions) were adequately applied. Measurements of inputs, outputs and control variables were relatively homogenous while quality measures varied. Notably, most studies did not include all three quality dimensions (structure, process and outcome). One study claimed to include quality of life; however, it was not a well-validated and widely used measure. The impacts of quality on efficiency estimates were mixed. The effect of quality on the ranking of nursing home efficiency was rarely reported. Conclusions: When measuring nursing home efficiency, it is crucial to adjust for quality of care and resident’s quality of life because the ultimate output of nursing homes is quality-adjusted days living in the facility. Quality measures should reflect their multidimensionality and not be limited to quality of throughput (health-related events). More reliable estimation of nursing home efficiencies will require better routine data collection within the facility, where well-validated quality measures become an essential part of the minimum data requirement. It is also recommended that different efficiency methods and assumptions, and alternative measures of inputs, outputs and quality, are used for sensitivity analyses to ensure the robustness and validity of findings.

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