Predictive Modelling of Covid-19 Stimulus Funds Paid for Nursing Home Quality Incentive Program

Painstaking measures should be taken to determine how federal dollars are spent. Proper justification for allocation of funds rooted in logic and fairness leads to trust and transparency. The COVID-19 pandemic has warranted rapid response by government agencies to provide vital aide to those in need. Decisions made should be evaluated in hindsight to see if they indeed achieve their objectives. In this paper, the data collected in the final four months of 2020 to determine funding for nursing home facilities via the Quality Incentive Program will be analysed using data mining techniques. The objective is to determine the relationships among numeric variables and formulae given. The dataset was assembled by the Health Resources and Services Administration. Results are given for the reader’s insight and interpretation. With the data collection and analytical process, new questions come to light. These questions should be pondered for further analysis.

When Is a Nursing Home Complaint Really a Complaint? Making Sense Out of Increased Complaints in U.S. Nursing Homes

Official complaints are one tool for addressing nursing home quality concerns in a timely manner. Similar to trends nationwide, the Ohio Department of Health (ODH) has noticed a trend in increasing nursing home complaints and has partnered with the Scripps Gerontology Center to learn more about facilities that receive complaints. Greater understanding may lead to proactive approaches to addressing and preventing issues. This study relies on two years of statewide Ohio nursing home complaint data. Between 2018 and 2019, the average complaint rate per 100 residents went from 6.59 to 7.06, with more than 70% of complaints unsubstantiated. Complaint information from 629 Ohio nursing homes in 2018 was linked with Centers for Medicare and Medicaid Services Nursing Home Compare data, the Ohio Biennial Survey of Long-Term Care Facilities, and Ohio Nursing Home Resident and Family Satisfaction Surveys. Using ordered logistic regression analyses, we investigated nursing home providers' characteristics using different levels of complaints and substantiated complaints. Findings suggest that providers with higher complaint rates are located in urban areas, had administrator and/or director of nursing (DON) turnover in the previous 3 years, experienced decreased occupancy rates, had reduced nurse aide retention, and received lower family satisfaction scores. Additionally, providers with administrator and/or DON turnover, and low family satisfaction scores are more likely to have substantiated complaints. Because increasing numbers of complaints are accompanied by relatively low substantiation rates, policy interventions targeted to specific types of providers may improve the cost-effectiveness of complaint resolution, as well as the quality of care.

Evaluation of Minnesota’s Long-Stay Nursing Home Quality Indicators

The Minnesota Nursing Home Report Card provides 19 clinical quality indictor (QI) ratings. Currently, face validity and expert opinions are employed to group the 19 long-stay QIs into 10 different domains. However, we do not know whether these domains are supported by the data. Under the current scoring program, some QIs may not discriminate very well between facilities. The objective was to evaluate the dimensionality of the QIs and the current scoring approach used to assign points to the domain and total QI scores. Risk-adjusted facility-level rates for the 19 QIs over the 2012-2019 period were used. Our findings indicate it is reasonable to categorize these QIs into 4 domains. Moreover, the current scoring approach is best suited for a facility QI distribution that is approximately normal. However, 11 QIs display a skewed distribution with facilities tightly grouped at the very bottom (floor) or top (ceiling) of the QI distribution. Our findings suggest that the current scoring approach may distort or exaggerate the differences in the QI rates with skewed distributions, assigning widely varying points to facilities that vary little in their QI rates. We recommend a zero-error approach for highly skewed QIs where the QI outcome is achievable and it reflects a serious quality problem. Our study of the QI scoring system is part of a package of recommendations to improve the Minnesota Nursing Home Report Card and value-based reimbursement system. Lessons learned from the study are readily applicable to Medicare’s Nursing Home Compare report.

Higher Star, Better Performance in US Nursing Homes during the Covid-19 Pandemic ?

The Covid-19 pandemic has brought terrible difficulties to nursing homes, as they were locations with the highest number of confirmed Covid-19 cases and deaths in the US. The Centers for Medicare & Medicaid Services (CMS) applies the Five-Star Quality Ratings to indicate the quality of care in nursing homes based on health inspection survey, staffing, and resident outcome. Studies to date have contradictory findings regarding the relationship between nursing home reported Quality Ratings and Covid-19 cases and deaths based on US regional data. The purpose of this study is to examine whether nursing homes’ Quality Ratings were related to the total number of resident Covid-19 cases and deaths at the US National level. The study examined US nursing homes (N=13,494) linked with CMS Nursing Home Compare data and Covid-19 Nursing Home data. Using multiple linear regression analyses, results showed nursing home Quality Ratings were significantly associated with Covid-19 residents’ cases and deaths controlling for ownership type, size, occupation rate, and years of operation (p<.001; p<.001). Five-star nursing homes were less likely to have Covid-19 cases and deaths. Further, comparing lower Star Ratings nursing homes, 1-Star nursing homes showed no significant difference to 2-Star and 3-Star nursing homes when examining Covid-19 cases and deaths. Overall, the Five-Star Quality Ratings is a useful measure when investigating nursing homes’ performance during the Covid-19 pandemic. Future policymakers and administrators should also focus on nursing homes with lower star ratings when improving the quality of nursing homes, particularly with regard to resident health.

Profit Status and Employee Turnover in Iowa Nursing Homes

Employee turnover is a huge concern for nursing homes that care for millions of older individuals whose physical and cognitive impairments make them vulnerable, especially in the middle of a pandemic like COVID-19. Existing research has shown that high turnover of employees can lead to poorer quality of care. Low pay is often cited as one of the key reasons for high turnover of employees in nursing homes. For-profit nursing homes may try to maximize profits by limiting wages paid to their employees. In this study, we examine whether profit-status of a facility is associated with high turnover of its employees. We obtain data on 415 nursing homes operating in Iowa between 2013-2017. We descriptively examine the turnover trends in nurse employees and all employees over time by profit status. We evaluate whether profit status is associated with high turnover using pooled linear regressions controlling for nursing home and resident characteristics. Descriptive results show that for-profit facilities had higher turnover of nurse employees (61.1% vs. 49.6%) and all employees (56.6% vs. 45.4%). Results from multivariate regressions show that, compared to non-profit facilities, for-profit facilities had 6.93 percentage points higher (p<0.01) turnover of all employees, and 7.76 percentage points higher (p<0.01) turnover of nurse employees after controlling for facility and resident characteristics. Given existing evidence on the adverse impact of high employee turnover on nursing home quality, we need policies aimed at lowering employee turnover, targeting for-profit nursing homes.