Use Of Nursing Home Compare Website Appears Limited By Lack Of Awareness And Initial Mistrust Of The Data

Protecting Patients And Society In An Era Of Private Equity Provider Ownership: Challenges And Opportunities For Policy

Private equity (PE) acquisitions in health care delivery nearly tripled from 2010 to 2020. Despite concerns around clinical and economic implications, policy responses have remained limited. We discuss the US policy landscape around PE ownership, using policies in the European Union for comparison. We present four domains in which policy can be strengthened. First, to improve oversight of acquisitions, policy makers should lower reporting thresholds, review sequential acquisitions that together affect market power, automate reviews with potential denials based on market concentration effects, consider new regulatory mechanisms such as attorney general veto, and increase funding for this work. Second, policy makers should increase the longer-run transparency of PE ownership, including the health care prices garnered by acquired entities. Third, policy makers should protect patients and providers by establishing minimum staffing ratios, spending floors for direct patient care, and limits on layoffs and the sale of real estate after acquisition (forms of "asset stripping"). Finally, policy makers should mitigate risky financial behavior by limiting the amount or proportion of debt used to finance PE acquisitions in health care.

Preferences for Postacute Care at Home vs Facilities

Importance

Two in 5 US hospital stays result in rehabilitative postacute care, typically through skilled nursing facilities (SNFs) or home health agencies (HHAs). However, a lack of clear guidelines and understanding of patient and caregiver preferences make it challenging to promote high-value patient-centered care.

Objective

To assess preferences and willingness to pay for facility-based vs home-based postacute care among patients and caregivers, considering demographic variations.

Design, Setting, and Participants

In September 2022, a nationally representative survey was conducted with participants 45 years or older. Using a discrete choice experiment, participants acting as patients or caregivers chose between facility-based and home-based postacute care that best met their preferences, needs, and family conditions. Survey weights were applied to generate nationally representative estimates.

Main Outcomes and Measures

Preferences and willingness to pay for various attributes of postacute care settings were assessed, examining variation based on demographic factors, socioeconomic status, job security, and previous care experiences.

Results

A total of 2077 adults were invited to participate in the survey; 1555 (74.9%) completed the survey. In the weighted sample, 52.9% of participants were women, 6.5% were Asian or Pacific Islander, 1.7% were American Indian or Alaska Native, 11.2% were Black or African American, 78.4% were White; the mean (SD) age was 62.6 (9.6) years; and there was a survey completion rate of 74.9%. Patients and caregivers showed a substantial willingness to pay for home-based and high-quality care. Patients and caregivers were willing to pay an additional $58.08 per day (95% CI, 45.32-70.83) and $45.54 per day (95% CI, 31.09-59.99) for HHA care compared with a shared SNF room, respectively. However, increased demands on caregiver time within an HHA scenario and socioeconomic challenges, such as insecure employment, shifted caregivers' preferences toward facility-based care. There was a strong aversion to below average quality. To avoid below average SNF care, patients and caregivers were willing to pay $75.21 per day (95% CI, 61.68-88.75) and $79.10 per day (95% CI, 63.29-94.91) compared with average-quality care, respectively. Additionally, prior awareness and experience with postacute care was associated with willingness to pay for home-based care. No differences in preferences among patients and caregivers based on race, educational background, urban or rural residence, general health status, or housing type were observed.

Conclusions and Relevance

The findings of this survey study underscore a prevailing preference for home-based postacute care, aligning with current policy trends. However, attention is warranted for disadvantaged groups who are potentially overlooked during the shift toward home-based care, particularly those facing caregiver constraints and socioeconomic hardships. Ensuring equitable support and improved quality measure tools are crucial for promoting patient-centric postacute care, with emphasis on addressing the needs of marginalized groups.

Public Reporting and Consumer Demand in the Home Health Sector

Health care report cards improve information and are a crucial part of health care reform of the federal government of the United States. I exploit a natural experiment in the home health sector to assess whether a higher rating under the star ratings program affects patient choice. Higher rated agencies increased their market share by 1.4% or 0.25 (95% confidence interval: [-0.63, 1.12]) percentage points, a practically and statistically insignificant amount. I find no evidence of heterogeneous effects across the rating distribution or over time. I also find precise null effects among consumers expected to be more responsive, including community-entry patients and patients in competitive markets with more options and star types. Agencies may have modestly impeded consumer choice by engaging in some patient selection behaviors, although the evidence is only weakly suggestive. The star ratings are unlikely to improve home health quality despite continued policymaker interest.

New CMS Nursing Home Ownership Data: Major Gaps And Discrepancies

Nursing home ownership has become increasingly complicated, partly because of the growth of facilities owned by institutional investors such as private equity (PE) firms and real estate investment trusts (REITs). Although the ownership transparency and accountability of nursing homes have historically been poor, the Biden administration's nursing home reform plans released in 2022 included a series of data releases on ownership. However, our evaluation of the newly released data identified several gaps: One-third of PE and fewer than one-fifth of REIT investments identified in the proprietary Irving Levin Associates and S&P Capital IQ investment data were present in Centers for Medicare and Medicaid Services (CMS) publicly available ownership data. Similarly, we obtained different results when searching for the ten top common owners of nursing homes using CMS data and facility survey reports of chain ownership. Finally, ownership percentages were missing in the CMS data for 82.40 percent of owners in the top ten chains and 55.21 percent of owners across all US facilities. Although the new data represent an important step forward, we highlight additional steps to ensure that the data are timely, accurate, and responsive. Transparent ownership data are fundamental to understanding the adequacy of public payments to provide patient care, enable policy makers to make timely decisions, and evaluate nursing home quality.

Web-Based Public Reporting as a Decision-Making Tool for Consumers of Long-Term Care in the United States and the United Kingdom: Systematic Analysis of Report Cards

BACKGROUND

Report cards can help consumers make an informed decision when searching for a long-term care facility.

OBJECTIVE

This study aims to examine the current state of web-based public reporting on long-term care facilities in the United States and the United Kingdom.

METHODS

We conducted an internet search for report cards, which allowed for a nationwide search for long-term care facilities and provided freely accessible quality information. On the included report cards, we drew a sample of 1320 facility profiles by searching for long-term care facilities in 4 US and 2 UK cities. Based on those profiles, we analyzed the information provided by the included report cards descriptively.

RESULTS

We found 40 report cards (26 in the United States and 14 in the United Kingdom). In total, 11 of them did not state the source of information. Additionally, 7 report cards had an advanced search field, 24 provided simplification tools, and only 3 had a comparison function. Structural quality information was always provided, followed by consumer feedback on 27 websites, process quality on 15 websites, prices on 12 websites, and outcome quality on 8 websites. Inspection results were always displayed as composite measures.

CONCLUSIONS

Apparently, the identified report cards have deficits. To make them more helpful for users and to bring public reporting a bit closer to its goal of improving the quality of health care services, both countries are advised to concentrate on optimizing the existing report cards. Those should become more transparent and improve the reporting of prices and consumer feedback. Advanced search, simplification tools, and comparison functions should be integrated more widely.

Hospice Quality, Race, and Disenrollment in Hospice Enrollees With Dementia

Background: Racial and ethnic minoritized people with dementia (PWD) are at high risk of disenrollment from hospice, yet little is known about the relationship between hospice quality and racial disparities in disenrollment among PWD. Objective: To assess the association between race and disenrollment between and within hospice quality categories in PWD. Design/Setting/Subjects: Retrospective cohort study of 100% Medicare beneficiaries 65+ enrolled in hospice with a principal diagnosis of dementia, July 2012-December 2017. Race and ethnicity (White/Black/Hispanic/Asian and Pacific Islander [AAPI]) was assessed with the Research Triangle Institute (RTI) algorithm. Hospice quality was assessed with the publicly-available Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey item on overall hospice rating, including a category for hospices exempt from public reporting (unrated). Results: The sample included 673,102 PWD (mean age 86, 66% female, 85% White, 7.3% Black, 6.3% Hispanic, 1.6% AAPI) enrolled in 4371 hospices nationwide. Likelihood of disenrollment was higher in hospices in the lowest quartile of quality ratings (vs. highest quartile) for both White (adjusted odds ratio [AOR] 1.12 [95% confidence interval 1.06-1.19]) and minoritized PWD (AOR range 1.2-1.3) and was substantially higher in unrated hospices (AOR range 1.8-2.0). Within both low- and high-quality hospices, minoritized PWD were more likely to be disenrolled compared with White PWD (AOR range 1.18-1.45). Conclusions: Hospice quality predicts disenrollment, but does not fully explain disparities in disenrollment for minoritized PWD. Efforts to improve racial equity in hospice should focus both on increasing equity in access to high-quality hospices and improving care for racial minoritized PWD in all hospices.

VA nursing home compare metrics as an indicator of skilled nursing facility quality for veterans

BACKGROUND

The Veterans Administration (VA) provides several post-acute care (PAC) options for Veterans, including VA-owned nursing homes (called Community Living Centers, CLCs). In 2016, the VA released CLC Compare star ratings to support decision-making. However, the relationship between CLC Compare star ratings and Veterans CLC post-acute outcomes is unknown.

METHODS

Retrospective observational study using national VA and Medicare data for Veterans discharged to a CLC for PAC. We used a multivariate regression model with hospital random effects to examine the association between CLC Compare overall star ratings and PAC outcomes while controlling for patient, facility, and hospital factors. Our sample included Veteran enrollees age 65+ who were community-dwelling, experienced a hospitalization, and were discharged to a CLC in 2016-2017. PAC outcomes included 30-day unplanned hospital readmission, 30-day mortality, 100-day successful community discharge, and a secondary composite outcome of unplanned readmission or death within 30-days of the hospital discharge.

RESULTS

Of the 25,107 CLC admissions, 4088 (16.3%) experienced an unplanned readmission, 4069 (16.2%) died within 30-days of hospital discharge, and 12,093 (48.2%) had a successful 100-day community discharge. Admission to a lower-quality (1-star) facility was associated with lower odds of successful community discharge (OR 0.78; 95% CI 0.66, 0.91) and higher odds of a combined endpoint of 30-day mortality and readmission (OR 1.27; 95% CI 1.09, 1.49), compared to 5-star facilities. However, outcomes were not consistently different between 5-star and 2, 3, or 4-star facilities. Star ratings were not associated with individual readmission or mortality outcomes when considered separately.

CONCLUSION

These findings suggest comparisons of 1-star and 5-star CLCs may provide meaningful information for Veterans making decisions about post-acute care. Identifying ways to alter the star ratings so they are differentially associated with outcomes meaningful to Veterans at each level is essential. We found that 1-star facilities had higher rates of 30-day unplanned hospital readmission/death, and lower rates of 100-day successful community discharges compared to 5-star facilities. Yet, like past work on CMS Nursing Home Compare ratings, these relationships were found to be inconsistent or not meaningful across all star levels. CLC Compare may provide useful information for discharge and organizational planning, with some limitations.

Consumer selection and home health agency quality and patient experience stars

OBJECTIVE

To compare the impact of the introduction of two distinct sets of star ratings, quality of care, and patient experience, on home health agency (HHA) selection.

DATA SOURCES

We utilized 2014-2016 home health Outcome and Assessment Information Set (OASIS) assessments, as well as publicly reported data from the Home Health Compare website.

DATA COLLECTION/EXTRACTION METHODS

We identified a 5% random sample of admissions (186,498 admissions) for new Medicare Fee-for-Service home health users.

STUDY DESIGN

This admission-level assessment compared HHA selection before (July 2014-June 2015) and after (February-December 2016) star ratings were published. We utilized a conditional logit, discrete choice model, which accounted for all HHAs that each patient could have selected (i.e., the choice set) based on ZIP codes. Our explanatory variables of interest were the interactions between star ratings and time period (pre/post stars). We stratified our analyses by race, admission source, and Medicaid eligibility. We adjusted for HHA characteristics and distance between patients' homes and HHAs.

PRINCIPAL FINDINGS

The introduction of star ratings was associated with a 0.88-percentage-point increase in the probability of selecting a high-quality HHA and a 0.81-percentage-point increase in the probability of selecting a highly ranked patient experience HHA. Patients admitted from the community, and black and Medicare-Medicaid dual-eligible beneficiaries experienced larger increases in their likelihood of selecting high-rated agencies than inpatient, white, and nondual beneficiaries.

CONCLUSIONS

The introduction of quality of care and patient experience stars were associated with changes in HHA selection; however, the strength of these relationships was weaker than observed in other health care settings where a single star rating was reported. The introduction of star ratings may mitigate disparities in HHA selection. Our findings highlight the importance of reporting information about quality and satisfaction separately and conducting research to understand the mechanisms driving HHA selection.

Seniors don't use Medicare.Gov: how do eligible beneficiaries obtain information about Medicare Advantage Plans in the United States?

BACKGROUND

Managed care programs in the US are becoming a preferred alternative among low-income individuals in the US. Every year during open enrollment, seniors can enroll in Medicare Advantage (MA) or switch MA plans. However, there is very limited information about how seniors obtain information to help them make their choices. While the Centers for Medicaid and Medicare offer online resources that are designed to enable potential beneficiaries to make informed coverage decisions, there is no information as to whether seniors use these resources, and therefore whether these resources are effective compared to other information retrieval methods.

METHODS

The purpose of the present study was to qualitatively explore how seniors obtain information about insurance plans in MA. We conducted semi-structured interviews with 26 MA beneficiaries from Rhode Island.

RESULTS

We found that most seniors have strong preferences for obtaining information in-person regarding benefits, cost and other plan information. Some seniors relied heavily on insurance brokers or representatives, and considered the information provided to them without questioning the potential for bias. Others consulted with family and/or friends for guidance, or to compare costs and benefits. Only a few of these seniors used the available internet resources, and in fact most of them mentioned that they did not have a computer/smart device with internet capabilities. However, among those who used and appeared to be comfortable with navigating the internet, www.medicare.gov was not discussed as a useful resource for making decisions regarding health insurance.

CONCLUSIONS

This study suggests that existing online medical resource usage and effects among senior citizens in the United States may need supplementing with in-person communication among influential agents.

"It's Pure Panic": The Portrayal of Residential Care in American Newspapers During COVID-19

Background and Objectives

This study examines the discursive construction of residential care during the COVID-19 pandemic in three leading American newspapers: The New York Times, USA Today, and The New York Post.

Research Design and Methods

A total of 54 news articles between 21 January and 8 May 2020 were identified from the LexisNexis academic database for analysis. The articles were analyzed using both a critical discourse analysis approach and a thematic analytical framework.

Results

Findings indicate that residents’ voices are excluded and superseded by others, namely their family members. Literary elements were used to portray residential care as shockingly dangerous, deceptive, and problematic. Blame was often assigned to an individual or group according to the political tendency of the newspaper.

Discussion and Implications

A cultural model of panic and dishonesty begins to take shape through the COVID-19 pandemic. Fearmongering and the portrayal of residential care as lacking transparency will likely create future mistrust of the industry. The depiction of vulnerability and the illusion of resident inclusion in the news coverage enable paternalistic decision-making and care practices in the name of supposed protection.

Restorative Quality Improvement: Novel Application of Six Sigma in a Skilled Nursing Facility

BACKGROUND

Six Sigma is a quality improvement (QI) method used in hospitals, but not typically in nursing homes (NHs), to reduce service variability and expenditures.

LOCAL PROBLEM

The existing QI process for functional maintenance program (FMP) charting/auditing in an urban NH allowed variability and lost revenue.

METHODS

A single-group pre/posttest design with analysis of variance and t-test analysis was used to implement Six Sigma for the FMP process.

INTERVENTION

Phases of Define, Measure, Analyze, Improve, and Control addressed performance objectives of FMP capacity; staff retention; congruence between prescribed, performed, and charted FMPs; and month-end summaries of resident status on FMPs.

RESULTS

With the existing staff, capability was increased by 17 residents ($200 000 revenue) and 90% to 100% charting congruence was achieved. Limited success was attributed to lack of skill diffusion, team communication, manager availability, and project prioritization.

CONCLUSIONS

Six Sigma was moderately successful when applied in a single NH for QI.

Evaluating national trends in outcomes after implementation of a star rating system: Results from dialysis facility compare

OBJECTIVE

To examine which factors are driving improvement in the Dialysis Facility Compare (DFC) star ratings and to test whether nonclinical facility characteristics are associated with observed longitudinal changes in the star ratings.

DATA SOURCES

Data were collected from eligible patients in over 6,000 Medicare-certified dialysis facilities from three annual star rating and individual measure updates, publicly released on DFC in October 2015, October 2016, and April 2018.

STUDY DESIGN

Changes in the star rating and individual quality measures were investigated across three public data releases. Year-to-year changes in the star ratings were linked to facility characteristics, adjusting for baseline differences in quality measure performance.

DATA COLLECTION

Data from publicly reported quality measures, including standardized mortality, hospitalization, and transfusion ratios, dialysis adequacy, type of vascular access for dialysis, and management of mineral and bone disease, were extracted from annual DFC data releases.

PRINCIPAL FINDINGS

The proportion of four- and five-star facilities increased from 30.0% to 53.4% between October 2015 and April 2018. Quality improvement was driven by the domain of care containing the dialysis adequacy and hypercalcemia measures. Additionally, independently owned facilities and facilities belonging to smaller dialysis organizations had significantly lower odds of year-to-year improvement than facilities belonging to either of the two large dialysis organizations (Odds Ratio [OR]: 0.736, 95% Confidence Interval [CI]: 0.631-0.856 and OR: 0.797, 95% CI: 0.723-0.879, respectively).

CONCLUSIONS

The percentage of four- and five-star facilities has increased markedly over a three-year time period. These changes were driven by improvement in the specific quality measures that may be most directly under the control of the dialysis facility.

Purchasing Quality Nursing Home Care in the Veterans Health Administration

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.

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

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.

Association of Online Consumer Reviews of Skilled Nursing Facilities With Patient Rehospitalization Rates

Importance

There are areas of skilled nursing facility (SNF) experience of importance to the public that are not currently included in public reporting initiatives on SNF quality. Whether patients, hospitals, and payers can leverage the information available from unsolicited online reviews to reduce avoidable rehospitalizations from SNFs is unknown.

Objectives

To assess the association between rehospitalization rates and online ratings of SNFs; to compare the association of rehospitalization with ratings from a review website vs Medicare Nursing Home Compare (NHC) ratings; and to identify specific topics consistently reported in reviews of SNFs with the highest vs lowest rehospitalization rates using natural language processing.

Design, Setting, and Participants

A retrospective cross-sectional study of 1536 SNFs with online reviews on Yelp (a website that allows consumers to rate and review businesses and services, scored on a 1- to 5-star rating scale, with 1 star indicating the lowest rating and 5 stars indicating the highest rating) posted between January 1, 2014, and December 31, 2018. The combined data set included 1536 SNFs with 8548 online reviews, NHC ratings, and readmission rates.

Main Outcomes and Measures

A mean rating from the review website was calculated through the end of each year. Risk-standardized rehospitalization rates were obtained from NHC. Linear regression was used to measure the association between the rehospitalization rate of a SNF and the online ratings. Natural language processing was used to identify topics associated with reviews of SNFs in the top and bottom quintiles of rehospitalization rates.

Results

The 1536 SNFs in the sample had a median of 6 reviews (interquartile range, 3-13 reviews), with a mean (SD) review website rating of 2.7 (1.1). The SNFs with the highest rating on both the review website and NHC had 2.0% lower rehospitalization rates compared with the SNFs with the lowest rating on both websites (21.3%; 95% CI, 20.7%-21.8%; vs 23.3%; 95% CI, 22.7%-24.0%; P = .04). Compared with the NHC ratings alone, review website ratings were associated with an additional 0.4% of the variation in rehospitalization rates across SNFs (adjusted R2 = 0.009 vs adjusted R2 = 0.013; P = .003). Thematic analysis of qualitative comments on the review website for SNFs with high vs low rehospitalization rates identified several areas of importance to the reviewers, such as the quality of physical infrastructure and equipment, staff attitudes and communication with caregivers.

Conclusions and Relevance

Skilled nursing facilities with the best rating on both a review website and NHC had slightly lower rehospitalization rates than SNFs with the best rating on NHC alone. However, there was marked variation in the volume of reviews, and many SNF characteristics were underrepresented. Further refinement of the review process is warranted.

Prioritizing LTSS Quality: Exploring the Views of Older Adults, Families, and Professionals

We conducted a cross-sectional survey involving 349 older adults, family members, and long-term services and supports (LTSS) professionals in Minnesota to assess their views on priorities for residential LTSS quality. We found considerable agreement among the three groups on the highest priorities to ensure the wellbeing of older adults who use LTSS: safety, dignity, and staffing. Relationships were also viewed as a high priority. However, older adults prioritized the physical environment over professionals, and they expressed more varied opinions on priorities overall. Older adults also consistently rated autonomy/choice as less important than other quality domains, a finding worth further exploration.

Cognitive Biases Influence Decision-Making Regarding Postacute Care in a Skilled Nursing Facility

BACKGROUND

Decisions about postacute care are increasingly important as the United States population ages, its use becomes increasingly common, and payment reforms target postacute care. However, little is known about how to improve these decisions.

OBJECTIVE

To understand whether cognitive biases play an important role in patient and clinician decision-making regarding postacute care in skilled nursing facilities (SNFs) and identify the most impactful biases.

DESIGN

Secondary analysis of 105 semistructured interviews with patients, caregivers, and clinicians.

SETTING

Three hospitals and three SNFs in a single metropolitan area.

PATIENTS

Adults over age 65 discharged to SNFs after hospitalization as well as patients, caregivers, and multidisciplinary frontline clinicians in both hospital and SNF settings.

MEASUREMENTS

We identified potential cognitive biases from prior systematic and narrative reviews and conducted a team-based framework analysis of interview transcripts to identify potential biases.

RESULTS

Authority bias/halo effect and framing bias were the most prevalent and seemed the most impactful, while default/status quo bias and anchoring bias were also present in decision-making about SNFs.

CONCLUSIONS

Cognitive biases play an important role in decision-making about postacute care in SNFs. The combination of authority bias/halo effect and framing bias may synergistically increase the likelihood of patients accepting SNFs for postacute care. As postacute care undergoes a transformation spurred by payment reforms, it is increasingly important to ensure that patients understand their choices at hospital discharge and can make high-quality decisions consistent with their goals.

The Relationship Between Reported Staffing and Expenditures in Nursing Homes

Dramatic improvements in reported nursing home quality, including staffing ratios, have come under increased scrutiny in recent years because they are based on data self-reported by nursing homes. In contrast to other domains, the key mechanism for real improvement in the staffing ratios domain is clearer: to improve scores, nursing homes should increase staffing expenditures. We analyze the relationship between changes in expenditures and reported staffing quality pre- versus post the 5-star rating system. Our results show that the relationship between expenditures and licensed practical nurse staffing is weaker in the post-5-star period, overall, and across subgroups; furthermore, there is a weaker relationship between expenditures and registered nurse staffing among for-profit facilities with a high share of Medicaid residents in the post-5-star period. The weaker relationship between staffing expenditures and staffing scores in the post-5-star era underscores the potential for gaming of the self-reported staffing scores and the need for more reliable sources.

Do report cards predict future quality? The case of skilled nursing facilities

Report cards on provider performance are intended to improve consumer decision-making and address information gaps in the market for quality. However, inadequate risk adjustment of report-card measures often biases comparisons across providers. We test whether going to a skilled nursing facility (SNF) with a higher star rating leads to better quality outcomes for a patient. We exploit variation over time in the distance from a patient's residential ZIP code to SNFs with different ratings to estimate the causal effect of admission to a higher-rated SNF on health care outcomes, including mortality. We found that patients who go to higher-rated SNFs achieved better outcomes, supporting the validity of the SNF report card ratings.

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

Background

Social media platforms offer unique opportunities for patients and families to provide real-time feedback on their healthcare experiences. Consumer-generated social media ratings of hospitals tend to reflect the more subjective aspects of inpatient care experiences; however, evidence on nursing home care is extremely limited.

Methods

We collected consumer-reported 5-star ratings of Maryland nursing homes posted from July 2015 to July 2017 on 4 popular social media or online review sites (Facebook, Yelp, Google Consumer Reviews, and Caring.com). We determined if the average score of social media ratings was associated with experience-of-care ratings derived from survey of family members or other responsible parties of nursing home residents, and with “Nursing Home Compare” (NHC) 5-star ratings and individual quality measures.

Results

One hundred ninety-six out of 206 nursing homes in Maryland were reviewed on at least one site and thus had one or more star ratings posted. The overall ratings were 3.11 on average on these sites and 3.03 on the NHC website, with a Pearson correlation of 0.41 (p < 0.001) between the 2 sets of ratings. The correlations between the social media rating and survey-based experience-of-care ratings ranged from 0.40 to 0.60, and the correlations between the social media rating and individual NHC quality measures of citations, nurse staffing, and complaints were about 0.35 (in absolute values). The social media rating also predicted well NHC and experience-of-care measures after adjusting for nursing home covariates and market competition.

Conclusions

The 5-star ratings collected from 4 social networking sites was correlated with and predictive of the NHC and survey-based experience-of-care measures for Maryland nursing homes.

Consumer Response to Composite Ratings of Nursing Home Quality

Health care report cards are intended to address information asymmetries and enable consumers to choose providers of better quality. However, the form of the information may matter to consumers. Nursing Home Compare, a website that publishes report cards for nursing homes, went from publishing a large set of indicators to a composite rating in which nursing homes are assigned one to five stars. We evaluate whether the simplified ratings motivated consumers to choose better-rated nursing homes. We use a regression discontinuity design to estimate changes in new admissions six months after the publication of the ratings. Our main results show that nursing homes that obtained an additional star gained more admissions, with heterogeneous effects depending on baseline number of stars. We conclude that the form of quality reporting matters to consumers, and that the increased use of composite ratings is likely to increase consumer response.

Medicaid and Nursing Home Choice: Why Do Duals End Up in Low-Quality Facilities?

We provide empirical evidence on the relative importance of specific observable factors that can explain why individuals enrolled in both Medicare and Medicaid (duals) are concentrated in lower quality nursing homes, relative to those not on Medicaid. Descriptive results show that duals are 9.7 percentage points more likely than nonduals to be admitted to a low-quality (1-2 stars) nursing home. Using the Blinder-Oaxaca decomposition approach in a multivariate framework, we find that 35.4% of the difference in admission to low-quality nursing homes can be explained by differences in the distribution of observable characteristics. Differences in education and distance to high-quality nursing homes are important drivers, as are health status and race. Our findings highlight the need for creative policy solutions targeting the modifiable factors to reduce the disparity.

Investigating Barriers to Family Visitation of Nursing Home Residents: A Systematic Review

Families are integral in helping nursing home residents maintain feelings of social inclusion and an overall sense of belonging, thus reducing consequences of social exclusion. Preliminary research, particularly of the culture change movement in long-term care, shows there are barriers to family engagement and visitation of residents. The objective of this study is to: (1) identify and summarize the barriers most reported to family visitation and (2) synthesize the findings to determine which barriers are most often reported in literature, and which may pose the greatest challenges to family involvement. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a final sample of 15 articles across 11 databases report seven barriers to visitation: psychological, health, staff to family member relationship, employment/finances, travel time, access to transportation, and other. Findings suggest barriers to family visitation and point toward a need for further research as relationships between resident and family member is complex and warrants attention across professions. Interprofessional efforts between social work, allied professionals, and transportation planners are necessary to address this pressing concern experienced by residents in nursing homes, with the ultimate goal of lessening such barriers.

Post-Acute Care After Joint Replacement in Medicare's Bundled Payments for Care Improvement Initiative

IMPORTANCE

Bundled payments, in which services provided around a care episode are linked together, are being tested under Medicare's Bundled Payments for Care Improvement (BPCI) program. Reducing post-acute care (PAC) is critical under bundled payment, but little is known about whether this is done through provider selection or consolidation, and whether particular patterns of changes in PAC are associated with success under the program.

OBJECTIVE

To characterize patterns of change in PAC under lower-extremity joint replacement episodes in BPCI.

DESIGN

Retrospective difference-in-differences study.

SETTING

US Medicare, 2013 to 2015.

PARTICIPANTS

A total of 264 US hospitals participating in BPCI for lower-extremity joint replacement and matched controls.

EXPOSURES

Participation in BPCI.

MEASUREMENTS

Use and duration of institutional PAC (proportion discharged to a skilled nursing facility, an inpatient rehabilitation facility, and a long-term care hospital), dispersion of PAC (proportion of discharges to commonly used providers), and quality of PAC (Star Ratings, readmission rates, length of stay, and nurse staffing); part A Medicare payments.

RESULTS

BPCI participants decreased the use and duration of institutional PAC compared to controls: overall institutional PAC declined 4.4% in BPCI hospitals vs 2.1% in non-BPCI hospitals (difference = -2.2%; P = .033), and duration decreased by 1.6 days in BPCI hospitals compared to 0.0 days in non-BPCI hospitals (difference in differences = -1.5 days; P < .001). However, BPCI participants did not change their PAC referral patterns to reduce dispersion or refer patients to higher-quality PAC providers. Hospitals that were more successful in reducing Medicare payments started with higher payments and higher use of institutional PAC settings and demonstrated greater drops in use and duration of institutional PAC, but no differences in dispersion or referral to high-quality providers.

CONCLUSIONS AND RELEVANCE

Reductions in spending under BPCI were driven by a shift from higher- to lower-cost discharge settings, and by shortening the duration of institutional PAC. Hospitals that reduced payments the most had the highest spending at baseline. J Am Geriatr Soc 67:1027-1035, 2019.

Staff Perceptions of Key Factors Guiding Nursing Home Search and Selection Within the Veterans Health Administration

Background and Objectives

Veterans enter nursing homes (NHs) for short-term postacute, rehabilitation, respite, or end-of-life care. They also enter NHs on a long-term basis due to frailty, disability, functional deficits, and cognitive impairment. Little is known about how a particular NH is chosen once the decision to enter a NH has been made. This study identified VA staff perceptions of the key factors influencing the search and selection of NHs within the Veterans Health Administration (VHA).

Research Design and Methods

Data derived from 35 semistructured interviews with discharge planning and contracting staff from 12 Veterans Affairs Medical Centers (VAMCs).

Results

VA staff placed a premium on Veteran and family preferences in the NH selection process, though VA staff knowledge and familiarity with placement options established the general parameters within which NH placement decisions were made. Geographic proximity to Veterans' homes and families was a major factor in NH choice. Other key considerations included Veterans' specialty care needs (psychiatric, postacute, ventilator) and Veteran/facility demographics (age, race/ethnicity, Veteran status). VA staff tried to remain neutral in NH selection, thus instructing families to visit facilities and review publicly available quality data. VA staff report that amenities (private rooms, activities, smoking) and aesthetics (cleanliness, smell, layout, décor) often outweighed objective quality indicators in Veteran and family decision making.

Discussion and Implications

Findings suggest that VAMCs facilitate Veteran and family decision making around NH selection. They also suggest that VAMCs endeavor to identify and recruit a broader array of higher quality NHs to better match the specific needs of Veterans and families to the choice set available.

Are Recessions Good for Staffing in Nursing Homes?

The quality and cost of care in nursing homes depend critically on the number and types of nurses. Recent research suggests that the nursing supply adjusts to macroeconomic conditions. However, prior work has failed to consider the effect of macroeconomic conditions on demand for nurses through the effect on revenues. We test how county-level unemployment rates affect direct-care staffing rates in nursing homes using California data. We exploit the wide variation in the unemployment rates across counties and over time in 2005-2012. We also test whether there are heterogeneous effects of unemployment rates by facility size, staffing level, and profit status. We find that as unemployment rates increase, staffing by registered nurses (RNs) decreases but staffing by licensed practical nurses (LPNs) increases. The increase in LPNs is larger in large nursing homes, nursing homes with higher staffing levels, and in for-profit nursing homes. We also find that as unemployment rates increase, nursing home revenue decreases. While the effect of macroeconomic conditions on nursing supply may be important for cost and quality of care, the mechanism is not simple, direct, or homogeneous for all types of nurses and nursing homes.

Hospital Discharge and Selecting a Skilled Nursing Facility: A Comparison of Experiences and Perspectives of Patients and Their Families

PURPOSE OF STUDY

A currently proposed rule by the Centers for Medicare & Medicaid Services would require providers to devote more resources to discharge planning from hospitals to ensure the prioritization of patient preferences and goals in the discharge planning process. Annually, more than 3 million persons enter a nursing home in the United States, with the vast majority of patients coming directly from hospitals. Although early evidence suggests more family involvement than patient involvement in the discharge process, most of this work has relied on retrospective reports of the decision-making process postplacement. This article seeks to examine and compare the experiences and perspectives of patients and others involved in the selection of the nursing home (predominately adult children and spouses).

PRIMARY PRACTICE SETTING

Large academic medical hospital with patients being discharged to a skilled nursing facility.

METHODOLOGY AND SAMPLE

A total of 225 patients or their family members and involved others who completed an exit survey assessing their experiences and perspectives in selecting a skilled nursing home and in experiencing the discharge process more generally.

RESULTS

Patients were the primary decision makers about 23% of the time but were often involved in the decision even when family members/involved others were primarily making decisions in the discharge process. Although patients were involved in the selection of the nursing home to a lesser degree than involved others, their level of satisfaction with the decision to be discharged to a skilled nursing home and their level of satisfaction with their personal level of involvement with the selection of the specific nursing home did not differ from the satisfaction ratings of the involved others. Furthermore, their confidence in the decision and their satisfaction with the decision did not differ from ratings provided by family members/involved others.

IMPLICATIONS FOR CASE MANAGEMENT PRACTICE

Recommendations for case management practice include (1) encouraging patients and their families to take an active role in the discharge process; (2) incorporating technology into the discharge process that promotes this active level of engagement; and (3) facilitating access to data to promote discharge to the highest quality nursing homes available.

Patients Are Not Given Quality-Of-Care Data About Skilled Nursing Facilities When Discharged From Hospitals

Hospitals are now being held at least partly accountable for Medicare patients' care after discharge, as a result of regulations and incentives imposed by the Affordable Care Act. However, little is known about how patients select a postacute care facility. We used a multiple case study approach to explore both how patients requiring postacute care decide which skilled nursing facility to select and the role of hospital staff members in this decision. We interviewed 138 staff members of sixteen hospitals and twenty-five skilled nursing facilities and 98 patients in fourteen of the skilled nursing facilities. Most patients described receiving only lists of skilled nursing facilities from hospital staff members, while staff members reported not sharing data about facilities' quality with patients because they believed that patient choice regulations precluded them from doing so. Consequently, patients' choices were rarely based on readily available quality data. Proposed changes to the Medicare conditions of participation for hospitals that pertain to discharge planning could rectify this problem. In addition, less strict interpretations of choice requirements would give hospitals flexibility in the discharge planning process and allow them to refer patients to higher-quality facilities.

Evaluating the Quality of Patient Decision-Making Regarding Post-Acute Care

BACKGROUND

Despite a national focus on post-acute care brought about by recent payment reforms, relatively little is known about how hospitalized older adults and their caregivers decide whether to go to a skilled nursing facility (SNF) after hospitalization.

OBJECTIVE

We sought to understand to what extent hospitalized older adults and their caregivers are empowered to make a high-quality decision about utilizing an SNF for post-acute care and what contextual or process elements led to satisfaction with the outcome of their decision once in SNF.

DESIGN

Qualitative inquiry using the Ottawa Decision Support Framework (ODSF), a conceptual framework that describes key components of high-quality decision-making.

PARTICIPANTS

Thirty-two previously community-dwelling older adults (≥ 65 years old) and 22 caregivers interviewed at three different hospitals and three skilled nursing facilities.

MAIN MEASURES

We used key components of the ODSF to identify elements of context and process that affected decision-making and to what extent the outcome was characteristic of a high-quality decision: informed, values based, and not associated with regret or blame.

KEY RESULTS

The most important contextual themes were the presence of active medical conditions in the hospital that made decision-making difficult, prior experiences with hospital readmission or SNF, relative level of caregiver support, and pressure to make a decision quickly for which participants felt unprepared. Patients described playing a passive role in the decision-making process and largely relying on recommendations from the medical team. Patients commonly expressed resignation and a perceived lack of choice or autonomy, leading to dissatisfaction with the outcome.

CONCLUSIONS

Understanding and intervening to improve the quality of decision-making regarding post-acute care supports is essential for improving outcomes of hospitalized older adults. Our results suggest that simply providing information is not sufficient; rather, incorporating key contextual factors and improving the decision-making process for both patients and clinicians are also essential.

Ratings game: an analysis of Nursing Home Compare and Yelp ratings

BACKGROUND

Two strategies for rating the quality of nursing homes (NHs) in the USA are exemplified by the Nursing Home Compare (NHC) website, launched by the federal Centers for Medicare and Medicaid Services in 1998, and Yelp.com, an online consumer review site that has grown in popularity since its founding in 2004. Both sites feature a 5-star rating system. While much is known about NHC ratings, little is known about NH Yelp ratings. This study examines Yelp ratings for NHs in California and compares these ratings with NHC ratings. Understanding how these ratings relate can inform efforts to empower consumers and enhance NH decision-making.

METHODS

We collected NHC and Yelp ratings for all California NHs between September and November 2016. For each NH with a Yelp review, we recorded the star rating and the total number of reviews. We also recorded the NHC 5-star rating and NHC ratings for inspections, staffing and quality measures (QMs). We conducted descriptive statistics and frequencies for these variables. We conducted correlations and tested means to compare the ratings.

RESULTS

A total of 675 NHs (68.1% of the total sample of 991 NHs) had both Yelp ratings and NHC ratings. Correlations between the Yelp and NHC ratings were relatively weak. The Yelp rating was significantly lower than the 5-star NHC rating and the NHC ratings for staffing and QMs. It was significantly higher than the NHC inspection rating.

CONCLUSIONS

This study found that when consumers rate NHs on Yelp, their ratings differ considerably from NHC ratings, a finding in keeping with similar studies of NH quality measurement. Further research is needed to analyse the content of Yelp reviews and compare the themes and topics consumers identify with those reported on NHC.

Nursing Home Referral Within the Veterans Health Administration: Practice Variation by Payment Source and Facility Type

Veterans enrolled within the Veterans Health Administration (VHA) of the U.S. Department of Veterans Affairs (VA) may receive nursing home (NH) care in VHA-operated Community Living Centers (CLCs), State Veterans Homes (SVHs), or community NHs, which may or may not be under contract with the VHA. This study examined VHA staff perceptions of how Veterans' eligibility for VA and other payment impacts NH referrals within VA Medical Centers (VAMCs). Thirty-five semistructured interviews were performed with discharge planning and contracting staff from 12 VAMCs from around the country. VA staff highlights the preeminent role that VA priority status played in determining placement in VA-paid NH care. VHA staff reported that Veterans' placement in a CLC, community NH, or SVH was contingent, in part, on potential payment source (VA, Medicare, Medicaid, and other) and anticipated length of stay. They also reported that variation in Veteran referral to VA-paid NH care across VAMCs derived, in part, from differences in local and regional policies and markets. Implications for NH referral within the VHA are drawn.

Nursing Home Response to Nursing Home Compare: The Provider Perspective

Nursing Home Compare (NHC) publishes composite quality ratings of nursing homes based on a five-star rating system, a system that has been subject to controversy about its validity. Using in-depth interviews, we assess the views of nursing home administrators and staff on NHC and unearth strategies used to improve ratings. Respondents revealed conflicting goals and strategies. Although nursing home managers monitor the ratings and expend effort to improve scores, competing goals of revenue maximization and avoidance of litigation often overshadow desire to score well on NHC. Some of the improvement strategies simply involve coding changes that have no effect on resident outcomes. Many respondents doubted the validity of the self-reported staffing data and stated that lack of risk adjustment biases ratings. Policy makers should consider nursing home incentives when refining the system, aiming to improve the validity of the self-reported domains to provide incentives for broader quality improvement.

Selecting a Skilled Nursing Facility for Postacute Care: Individual and Family Perspectives

OBJECTIVES

To describe individuals' experiences during the hospital discharge planning and skilled nursing facility (SNF) selection process.

DESIGN

Semistructured interviews focusing on discharge planning and nursing facility selection, including how facilities were chosen, who was involved, and what factors were important in decision-making.

SETTING

14 SNFs in five cities across the United States.

PARTICIPANTS

Newly admitted, previously community-dwelling SNF residents (N = 98) and their family members.

MEASUREMENT

Semistructured interviews were qualitatively coded to identify underlying themes.

RESULTS

Most respondents reported receiving only a list of SNF names and addresses from discharge planners and that hospital staff were minimally involved. Proximity to home and prior experience with the facility most often influenced choice of SNF. Most respondents reported being satisfied with their placement, although many stated that they would have been willing to travel further to another SNF were it recommended. Many reported feeling rushed and unprepared, stating that they did not know where or how to get help.

CONCLUSION

SNF placement is a stressful transition, occurring when people are physically vulnerable and with limited guidance from discharge planners. Therefore, most people select a facility based on its location, perhaps because they are provided with no other information. Given Centers for Medicare and Medicaid Services' proposed changes to the discharge planning process, this research highlights the value of providing people and family caregivers with quality data and assistance in interpreting it.

Assessing Quality of Care and Elder Abuse in Nursing Homes via Google Reviews

Background

It is challenging to assess the quality of care and detect elder abuse in nursing homes, since patients may be incapable of reporting quality issues or abuse themselves, and resources for sending inspectors are limited.

Objective

This study correlates Google reviews of nursing homes with Centers for Medicare and Medicaid Services (CMS) inspection results in the Nursing Home Compare (NHC) data set, to quantify the extent to which the reviews reflect the quality of care and the presence of elder abuse.

Methods

A total of 16,160 reviews were collected, spanning 7,170 nursing homes. Two approaches were tested: using the average rating as an overall estimate of the quality of care at a nursing home, and using the average scores from a maximum entropy classifier trained to recognize indications of elder abuse.

Results

The classifier achieved an F-measure of 0.81, with precision 0.74 and recall 0.89. The correlation for the classifier is weak but statistically significant: = 0.13, P < .001, and 95% confidence interval (0.10, 0.16). The correlation for the ratings exhibits a slightly higher correlation: = 0.15, P < .001. Both the classifier and rating correlations approach approximately 0.65 when the effective average number of reviews per provider is increased by aggregating similar providers.

Conclusions

These results indicate that an analysis of Google reviews of nursing homes can be used to detect indications of elder abuse with high precision and to assess the quality of care, but only when a sufficient number of reviews are available.

Personalizing Nursing Home Compare and the Discharge from Hospitals to Nursing Homes

OBJECTIVE

To test whether use of a personalized report card, Nursing Home Compare Plus (NHCPlus), embedded in a reengineered discharge process, can lead to better outcomes than the usual discharge process from hospitals to nursing homes.

DATA SOURCES/SETTING

Primary data collected in the Departments of Medicine and Surgery at a University Medical Center between March 2014 and August 2015.

STUDY DESIGN

A randomized controlled trial in which patients in the intervention group were given NHCPlus. Participants included 225 patients or their family members/surrogates.

DATA COLLECTION

Key strokes of NHCPlus users were recorded to obtain information about usage. Users were surveyed about usability and satisfaction with NHCPlus. All participants were surveyed at discharge from the hospital. Survey data were merged with medical records.

PRINCIPAL FINDINGS

About 85 percent of users indicated satisfaction with NHCPlus. Compared to controls, intervention patients were more satisfied with the choice process (by 40 percent of the standard deviation p < .01), more likely to go to higher ranked five-star nursing homes (OR = 1.8, p < .05), traveled to further nursing homes (IRR = 1.27, p < .10), and had shorter hospital stays (IRR = 0.84, p < .05).

CONCLUSIONS

Personalizing report cards and reengineering the discharge process may improve quality and may lower costs compared to the usual discharge process.