Nursing Home Chains Research Articles

Assessing the representativeness of cluster randomized trials: Evidence from two large pragmatic trials in United States nursing homes.

When the randomized clusters in a cluster randomized trial are selected based on characteristics that influence treatment effectiveness, results from the trial may not be directly applicable to the target population. We used data from two large nursing home-based pragmatic cluster randomized trials to compare nursing home and resident characteristics in randomized facilities to eligible non-randomized and ineligible facilities. We linked data from the high-dose influenza vaccine trial and the Music & Memory Pragmatic TRIal for Nursing Home Residents with ALzheimer's Disease (METRICaL) to nursing home assessments and Medicare fee-for-service claims. The target population for the high-dose trial comprised Medicare-certified nursing homes; the target population for the METRICaL trial comprised nursing homes in one of four US-based nursing home chains. We used standardized mean differences to compare facility and individual characteristics across the three groups and logistic regression to model the probability of nursing home trial participation. In the high-dose trial, 4476 (29%) of the 15,502 nursing homes in the target population were eligible for the trial, of which 818 (18%) were randomized. Of the 1,361,122 residents, 91,179 (6.7%) were residents of randomized facilities, 463,703 (34.0%) of eligible non-randomized facilities, and 806,205 (59.3%) of ineligible facilities. In the METRICaL trial, 160 (59%) of the 270 nursing homes in the target population were eligible for the trial, of which 80 (50%) were randomized. Of the 20,262 residents, 973 (34.4%) were residents of randomized facilities, 7431 (36.7%) of eligible non-randomized facilities, and 5858 (28.9%) of ineligible facilities. In the high-dose trial, randomized facilities differed from eligible non-randomized and ineligible facilities by the number of beds (132.5 vs 145.9 and 91.9, respectively), for-profit status (91.8% vs 66.8% and 68.8%), belonging to a nursing home chain (85.8% vs 49.9% and 54.7%), and presence of a special care unit (19.8% vs 25.9% and 14.4%). In the METRICaL trial randomized facilities differed from eligible non-randomized and ineligible facilities by the number of beds (103.7 vs 110.5 and 67.0), resource-poor status (4.6% vs 10.0% and 18.8%), and presence of a special care unit (26.3% vs 33.8% and 10.9%). In both trials, the characteristics of residents in randomized facilities were similar across the three groups. In both trials, facility-level characteristics of randomized nursing homes differed considerably from those of eligible non-randomized and ineligible facilities, while there was little difference in resident-level characteristics across the three groups. Investigators should assess the characteristics of clusters that participate in cluster randomized trials, not just the individuals within the clusters, when examining the applicability of trial results beyond participating clusters.

Encouraging Improvements to Opioid and Substance Use Disorder Care Quality in Nursing Homes

Encouraging Improvements to Opioid and Substance Use Disorder Care Quality in Nursing Homes

JOB CHARACTERISTICS ASSOCIATED WITH INTENT TO QUIT AMONG NURSING HOME EMPLOYEES AND MANAGERS

Abstract High turnover and recruitment challenges of nursing home employees and managers is an ongoing concern. This study’s objective was to examine intent to quit among all staff and assess the roles of job characteristics and job satisfaction. Employees and managers within one nursing home chain working in direct patient care or nursing were compared. Data came from the Work, Family, Health Network 18-month follow-up survey in 2012 (Total = 1,000, Managers = 101, Employees = 899). A cumulative logit model controlling for demographics was estimated for lower intent to quit. Herzberg’s Two-Factor Theory of Work Motivation guided the study. Employees scored significantly lower on family-supportive supervisor behaviors (FSSBs), schedule control (SC), and decision authority (DA) than managers. Employees and managers did not differ on job satisfaction, intent to quit, or job demands. Satisfied workers had 5.88 times greater odds of lower intent to quit compared to workers who were neutral or disagreed (p < .0001). DA (OR=0.29) and SC (OR=0.19) were related to higher intent to quit. In contrast, FSSBs (OR = 1.45), safety compliance (OR=1.41), and the combination of high DA with high SC (OR = 1.4) were related to lower intent to quit. Among nursing home staff, lower intent to quit may be achieved through improving job satisfaction, safety culture, the quality of supervision, and job enrichment through more schedule control and decision-making power. It is also imperative to develop strategies to retain those with more education through further research.

Job Characteristics Associated With Intent to Quit Among Nursing Home Employees and Managers.

High turnover and recruitment challenges of nursing home employees and managers are an ongoing concern. This study's objective was to examine intent to quit among all staff and assess the roles of job characteristics and job satisfaction. Employees and managers within one nursing home chain working in direct patient care or nursing were compared. Data came from the Work, Family, Health Network 18-month follow-up survey in 2012 (total = 1,000, managers = 101, employees = 899). A cumulative logit model controlling for demographics was estimated for intent to quit. Herzberg's Two-Factor Theory of Work Motivation guided the study. Employees scored significantly lower on family-supportive supervisor behaviors (FSSBs), schedule control, and decision authority than managers. Employees and managers did not differ on job satisfaction, intent to quit, or job demands. Satisfied workers had an 83% decrease in the odds of reporting an intent to quit compared to workers who were neutral or disagreed (odds ratio [OR] = 0.17, p < .0001). Decision authority (OR = 3.49) and schedule control (OR = 5.18) were independently related to greater odds of reporting an intent to quit. In contrast, FSSBs (OR = 0.69), safety compliance (OR = 0.71), and the combination of high decision authority with high schedule control (OR = 0.72) were related to lower odds of reporting an intent to quit. Among nursing home staff, lower intent to quit may be achieved through improving job satisfaction, the quality of supervision, safety culture, and job enrichment through more schedule control and decision-making power.

Service Chains’ Operational Strategies: Standardization or Customization? Evidence from the Nursing Home Industry

Problem definition: We investigate how the degree of standardization (DoS) across service chain-belonging units impacts units’ performance outcomes. We study this question in the nursing home industry, focusing on the DoS in three operational dimensions—customer mix, service offering, and service delivery—and its impact on three nursing home outcomes: financial performance, clinical outcome, and resident welfare. Academic/practical relevance: All service chains must decide how unique or standardized each of their units should be, but it is unclear how this decision affects units’ performance outcomes. We assess standardization strategies in multiple operational dimensions in chain-belonging nursing homes and their impact on important operational outcomes, and generalize our findings to other service industries. Methodology: We use a panel data set covering 11 years (2005–2015) of comprehensive measurements of all nursing homes in the United States. We estimate the relationship between the DoS and important nursing home outcomes using fixed-effect models with instrumental variables and clustered standard errors. Results: We find that chain-belonging nursing homes that (1) customize service delivery and standardize customer mix relative to the chain norm tend to experience improved financial performance; (2) standardize customer mix tend to experience improved clinical outcome; and (3) customize service delivery tend to experience enhanced resident welfare. Managerial implications: To our knowledge, this study is the first systematic multidimensional assessment of multiunit service firms’ standardization strategies from a chain perspective. Our results guide nursing home chains in their (1) strategies of within-chain standardization, and (2) investment decisions in acquiring new properties. Our results also provide broader managerial insights for service chains’ standardization strategies and merging and acquisition activities. Supplemental Material: The e-companion is available at https://doi.org/10.1287/msom.2022.1111 .

Financial and Quality Metrics of A Large, Publicly Traded U.S. Nursing Home Chain in the Age of Covid-19.

Nursing homes faced serious challenges with large COVID-19 resident infection rates and deaths during the pandemic. This descriptive case study examined the structure, operations, strategies, care outcomes, and owners of The Ensign Group Inc. the second largest U.S. for-profit chain, between 2007 and 2021. Ensign, as a holding company, has a complex organizational structure that uses more than 430 corporate entities to manage its 228 nursing homes and senior living facilities. With mostly Medicare and Medicaid revenues and favorable government COVID-19 relief, Ensign grew rapidly, even during the pandemic, to $2.5 billion (all amounts in U.S. Dollars) in revenues with a market capitalization of $4.5 billion and strong profits and financial metrics in 2020 to 2021. The company used real estate purchasing, debt financing, and spin-off companies, and tax arbitrage to optimize shareholder value. Before and during the pandemic, its 198 nursing homes had low registered nurse and total nurse staffing levels and regulatory violations with below-average ratings, and they had high COVID-19 infection rates during the pandemic. Ensign's small board, executives, and institutional investors protected and enhanced shareholder interests rather than ensuring that its nursing homes met professional standards and regulatory requirements.

Lessons for deprescribing from a nonessential medication hold policy in US nursing homes.

At the height of the COVID-19 pandemic, a large nursing home chain implemented a policy to temporarily hold potentially unnecessary medications. We describe rates of held and discontinued medications after a temporary hold policy of potentially unnecessary or nonessential medications. This retrospective cohort study uses electronic health record (EHR) data on 3247 residents of 64 nursing homes operated by a multistate long-term care provider. Medications were documented in the electronic medication administration record. Overall medication held and discontinued incidences are reported. Hierarchical Bayesian modeling is used to determine individual probabilities for medication discontinuation within each facility. In total, 3247 residents had 5297 nonessential medications held. Multivitamins were most likely to be held, followed by histamine-2 receptor antagonists, antihistamines, and statins. At the end of the hold policy, 2897 of 5297 (54%) were permanently discontinued, including probiotics (73%), histamine-2 receptor antagonists (66%), antihistamines (64%), and statins (45%). Demographics, cognitive and functional impairment were similar between residents with medications who were discontinued versus continued. For most medications, more than 50% of the variance in whether medications were discontinued was explained by facility rather than resident-level factors. A temporary medication hold policy implemented during the CoVID-19 pandemic led to the deprescribing of a plurality of 'nonessential' medications. This type of organization-wide initiative may be an effective mechanism for altering future prescribing behaviors to reduce the use of unnecessary medications.

Observations of Polypharmacy and Interactions on Varying COVID-19 Medication Regimens in Nursing Home Residents

Around 800,000 preventable medication-related errors occur yearly in nursing homes (NHs). With NHs susceptible to medication errors, COVID-19 can potentially increase their occurrence. No evidence-based regimen exists for COVID-19, yet different “cocktails” are prescribed at NHs as prophylaxis or treatment for COVID-19. Little is known regarding long-term consequences of such regimens, including increased pill burden, stable disease exacerbation, or adverse drug reactions. While preventing COVID-19 spread and decreasing mortality are important, doing so safely and effectively should be a priority. Pharmacists can play a pivotal role even with little information available regarding this issue. Student pharmacists performed a retrospective review of medication profiles of individuals living in a single nursing home chain who had an ICD-10 code for COVID-19 (U07.1) contained within their electronic health record from March 1to September 20, 2020. Medications started specifically for COVID-19 were collected, as were the number of scheduled medications +/-14 and +/-30 days from the COVID-19 diagnosis date. Drug interactions were screened via Lexi-Comp if new medications were started for COVID-19 and significant drug-disease interactions were based on clinical skills of the candidate and a review by the geriatrics-focused preceptor. Across 31 facilities, 759 patients were diagnosed with COVID-19. Out of 759 patients, 322 (42.4%) were treated pharmacologically following diagnosis. Interventions included antibiotics, antiplatelets, anticoagulants, nutritional supplements, and other medications. There were 164 patients (21.6%) prescribed antibiotics, 64 (8.4%) anticoagulants, 36 (4.7%) aspirin, 1 (0.1%) clopidogrel, 21 (2.8%) hydroxychloroquine, 124 (16.3%) corticosteroids, and 312 (41.4%) supplements. Nearly 1 in 5 individuals (n=148) were exposed to dangerous drug-drug interactions, with potential for increased bleeding risk and QTc prolongation the most common possible outcomes. Important drug-disease interactions were found in 221 patients with the most common being use of dexamethasone in diabetic patients. The average number of medications added for COVID-19 was 2.8 (range 1-10). The average increase in medications 30 days post-infection was 2.15 (range 1-13); however, 135 patients had fewer medications post-COVID-19, and 214 had no change. While anticoagulants and antibiotics typically did not persist long past infection resolution largely due to stop dates, supplements continued on profiles 30 days after diagnosis. Pharmacists have a vital role in recommendations of evidence-based medication regimens, as well as ensuring proper monitoring parameters are employed. Making certain stop dates are used can also greatly improve patient care and avoid unnecessary polypharmacy. Pharmacists should ensure when medications are being used for a COVID-19 infection, the indication is properly stated, as this will assist with classification of these individuals in other large database studies.

Organizational and Market Dynamics Associated with Usable, Accessible Health Information Exchange for Skilled Nursing Facilities

Information discontinuity between hospitals and skilled nursing facilities (SNFs) is a critical barrier to safe and effective transitions. To engage effectively in information sharing, SNFs need structural health information exchange (HIE) capabilities but also HIE design and workflows that result in electronic information actually being accessible and usable at the point of care.We use nationally representative SNF data to identify key facility characteristics, and characteristics of the facility’s top hospital referral partner, that are associated with likelihood of SNFs having access to electronic information sharing tools. Controlling for those capabilities, we then assess the extent to which those same characteristics influence the extent to which the SNF reports usable information received electronically that is actually available at the point of care.We conducted pooled, cross‐sectional survey data analyses. We identified our sample of SNFs through the Office of the National Coordinator SNF Health IT Survey (2016‐2017). From this survey, we generated our SNF HIE capability metric (ability to electronically query for or receive patient information from outside sources) as well as our key study outcome—whether SNFs report usable electronic information from outside sources available at the point of care. Organizational SNF characteristics were pulled from the SK&amp;A Nursing Home datafile as well as the CMS Nursing Home Public Use file.We matched each SNF to the hospital responsible for sending the highest percent of their referrals using Medicare referral pattern data and used these same data to calculate a measure of SNF referral relationship concentration. We then, for each partner hospital, used the American Hospital Association (AHA) IT Supplement to identify general and SNF‐specific HIE capabilities. We use linear probability models to estimate the association between relevant organizational characteristics (of the SNF and partner hospital) and both HIE outcomes: (1) SNF HIE capabilities and (2) SNF self‐reported availability of usable and accessible outside information at the point of care (controlling for HIE capabilities).Nationally representative sample of skilled nursing facilities (N = 1,189).Controlling for the presence of an EHR, SNFs are more likely to electronically query for or receive information from outside sources if they are large (+10.3%, top tertile compared to bottom; P = .004), if they are part of a large chain (+11.7%, member of 70+ nursing home chain, compared to standalone; P = .001), and if their partnering hospital reports having a health information portal (+7.5%; P = .049).Adjusting for SNF HIE capabilities, SNFs have a higher probability of usable electronic information available at the point of care if their top partner hospital reports participation in a community HIO (+7.6%; P = .018).Hospital information portals increase SNF access to HIE infrastructure, but community‐level HIOs increase the likelihood that SNFs actually have accessible, usable electronic information from hospitals at the point of care.Community HIOs appear to play a critical role in SNFs having usable, timely access to outside sources of health information. HIOs have significant opportunity to bolster their value proposition through greater engagement with SNFs and other postacute providers on supporting their informational needs and transitional care processes with hospitals.Office of the National Coordinator for Health IT.

Supporting the Medical Director: An Opportunity for Physicians, NPs, and PAs

Supporting the Medical Director: An Opportunity for Physicians, NPs, and PAs

Service Chains' Operational Strategies: Standardization or Customization? Evidence from the Nursing Home Industry

Problem definition: We investigate how the Degree of Standardization (DoS) across service chain-belonging units impacts units' performance outcomes. We study this question in the nursing home industry. More specifically, we study the DoS in three operational dimensions: customer mix, service offering, and service delivery, and its impact on three nursing home outcomes: financial performance, clinical outcome, and resident welfare. Academic/practical relevance: All service chains must decide how unique or standardized each of their units should be, but it is unclear how this decision affects units' performance outcomes. We assess standardization strategies in multiple operational dimensions in chain-belonging nursing homes and their impact on important operational outcomes, and generalize our findings to other service industries. Methodology: We use a panel data set covering eleven years (2005 – 2015) of comprehensive measurements of all nursing homes in the U.S. We estimate the relationships between the DoS and important nursing home outcomes using fixed effect models with instrumental variables and clustered standard errors. Results: We find that nursing home chains need to (1) customize service delivery and standardize customer mix across units to improve financial performance; (2) standardize customer mix to improve clinical outcome; and (3) customize service delivery to enhance resident welfare. Managerial implications: To our knowledge, this study is the first systematic multi-dimensional assessment of multi-unit service firms' standardization strategies from a chain perspective. Our results guide nursing home chains in their (1) strategies of within-chain standardization, and (2) investment decisions in acquiring new properties. Our results also provide broader managerial insights for service chains' standardization strategies and merging and acquisition activities.

Let’s Talk: Communication in the Nursing Home

Let’s Talk: Communication in the Nursing Home

The Impact of Chain Standardization on Nursing Home Staffing.

Standardization in production is common in multientity chain organizations. Although chains are prominent in the nursing home sector, standardization in care has not been studied. One way nursing home chains may standardize is by controlling the level and mix of staffing in member homes. To examine the extent to which standardization occurred in staffing, its relative presence across different types of chains, and whether facilities became more standardized following acquisition by a chain. We estimated predictors of the difference between facility and chain staffing using Generalized Estimating Equations with 2000-2010 data. This study included nursing homes nationally, excluding hospital-based homes and homes in Alaska, Hawaii, and the District of Columbia. Chain ownership was coded from text identifying chain names. Two nurse staffing measures were used: staff hours per resident day and staff mix. Very large for-profit chain nursing homes and large nonprofits had less variation in staff hours per resident day (P<0.001) but greater variation in staffing mix (P<0.001) compared with the chain average nationally. Large for-profit chains and medium nonprofit chains had greater dispersion on staff hours per resident day (P<0.001), while large nonprofit chains had greater dispersion in staffing mix (P<0.001). The difference between facility and chain staffing decreased over time. The largest chains (for-profit and nonprofit) had less staffing variation compared with national standards, suggesting they were best at implementing corporate practices. Following ownership changes, staffing converged towards chain averages over time, suggesting standardization takes time to implement.

Failure to Meet Nurse Staffing Standards: A Litigation Case Study of a Large US Nursing Home Chain.

Large for-profit nursing home chains in the United States have generally reported low nurse staffing levels. This historical case study examined a class action litigation case regarding staffing levels, resident rights, and quality outcomes in 12 Arkansas nursing homes owned by a large for-profit chain. The questions were as follows: (1) How did the residents’ care needs compare with actual nurse staffing levels? (2) How did the staffing levels compare with federal and state nurse staffing requirements and professional staffing standards? (3) Did the facilities comply with state and federal residents’ rights and quality of care requirements? The findings showed staffing levels marginally above state minimum standards, staffing shortages that violated state standards, staffing levels not adjusted for resident acuity, and shortages that resulted in omitted care. Staffing levels were lower than needed according to nursing directors, lower than average facilities in the state, and lower than professional standards. The findings showed many resident grievances regarding basic care and residents’ rights, clinical measures of poor quality, and state deficiencies. A large settlement was agreed on to compensate the residents. The case shows that chain’s management, as well as the regulatory system, failed to ensure adequate staffing levels that took into account regulatory requirements and professional standards and resulted in violations of residents’ rights, health, safety, and well-being.

Nursing Home Chain Affiliation and Its Impact on Specialty Service Designation for Alzheimer Disease.

Specialty care units (SCUs) in nursing homes (NHs) grew in popularity during the 1990s to attract residents while national policies and treatment paradigms changed. Alzheimer disease has consistently been the dominant form of SCU. This study explored the extent to which chain affiliation, which is common among NHs, affected SCU bed designation. Using data from the Online Survey Certification and Reporting (OSCAR) from 1996 through 2010 with 207 431 NH-year observations, we described trends and compared chain-affiliated NHs with independent NHs. Designation of beds for Alzheimer disease SCUs grew from 1996 to 2003 and then declined. At the peak, 19.6% of all NHs had at least one Alzheimer disease SCU bed. In general, chain affiliation promoted Alzheimer disease SCU bed designation across time, chain size, and NH profit status. During the period of largest growth from 1996 to 2003, the likelihood of designation of Alzheimer disease SCU beds was 1.55 percentage points higher among for-profit NHs affiliated with large chains than independent for-profit NHs (P < .001) and remained 1.28 percentage points higher from 2004 to 2010. However, chain-affiliated NHs generally had a lower percentage of residents with dementia than independent NHs. For example, although for-profit NHs affiliated with large chains had more Alzheimer disease SCU beds, they had nearly 3% fewer residents with dementia than independent NHs (P < .001). We conclude that organizational decisions to designate beds for Alzheimer disease SCUs may be related to marketing strategies to attract residents since adoption of Alzheimer disease SCUs has fluctuated over time, but did not appear driven by demand.

Neoliberalism and health care: the case of the Irish nursing home sector

The usefulness of neoliberalism as a theoretical concept in health research has been debated. This paper argues that when the concept of neoliberalism is used precisely and concretely, it provides an important and valid framework to analyse how health systems have been transformed over the last several decades. This claim is illustrated through the case of the Irish nursing home sector, which, over the last 20 years, has been turned upside down: from a mostly public system, it has been restructured into a mostly private, for-profit one. Privatisation, a quintessential neoliberal outcome, is analysed in detail. It was fostered by several neoliberal policies and has benefitted Irish (and to some extent global) economic elites. Tax incentives for private home operators and government budgetary constraints have limited state involvement in service provision and supported the expansion of the private sector. Private home staff are subject to more ‘flexible’ working conditions, which benefits employers. Moreover, the government plans to build new public nursing homes via public–private partnerships, which amount to privatisation. Also, global nursing home chains have begun to enter the Irish market, which offers profitable opportunities to international investors. However, international research shows that quality of care tends to be lower in private homes, due to cost cutting to increase profits.

The Effects of Chains on the Measurement of Competition in the Nursing Home Industry.

Consistently accounting for more than 50% of the nursing homes in the United States, corporate chains have played an important role in the industry for several decades. However, few studies have explicitly considered the role of chains in measuring competition in nursing home markets. In this study, we use a newly developed database tracking common ownership over a period of nearly two decades to compare chain-adjusted and unadjusted measures of competition at the county and 25 km fixed-radius levels and explore how the differences would affect the assessment of local market structure. On average, the chain-adjusted Herfindahl-Hirschman Indexes (HHIs) are about 0.02 higher than the unadjusted HHIs. Each year, about 20% to 22% of the counties would appear more concentrated when recalculating HHIs accounting for common ownership. Evidence suggests that nursing home chains tend to focus more on expanding access to new markets within a state than to increasing market power within a smaller local market.

What Happens to a Nursing Home Chain When Private Equity Takes Over? A Longitudinal Case Study.

We analyzed what happens to a nursing home chain when private equity takes over, with regard to strategy, financial performance, and resident well-being. We conducted a longitudinal (2000-2012) case study of a large nursing home chain that triangulated qualitative and quantitative data from 5 different data sources. Results show that private equity owners continued and reinforced several strategies that were already put in place before the takeover, including a focus on keeping staffing levels low; the new owners added restructuring, rebranding, and investment strategies such as establishing new companies, where the nursing home chain served as an essential “launch customer.”

Marketization in Long-Term Care: A Cross-Country Comparison of Large For-Profit Nursing Home Chains.

This article presents cross-country comparisons of trends in for-profit nursing home chains in Canada, Norway, Sweden, United Kingdom, and the United States. Using public and private industry reports, the study describes ownership, corporate strategies, costs, and quality of the 5 largest for-profit chains in each country. The findings show that large for-profit nursing home chains are increasingly owned by private equity investors, have had many ownership changes over time, and have complex organizational structures. Large for-profit nursing home chains increasingly dominate the market and their strategies include the separation of property from operations, diversification, the expansion to many locations, and the use of tax havens. Generally, the chains have large revenues with high profit margins with some documented quality problems. The lack of adequate public information about the ownership, costs, and quality of services provided by nursing home chains is problematic in all the countries. The marketization of nursing home care poses new challenges to governments in collecting and reporting information to control costs as well as to ensure quality and public accountability.

Cost (In)Efficiency and Institutional Pressures in Nursing Home Chains

Over the past 10 years, merger activities in the private for-profit nursing home industry have been increasing in Europe. In this paper, we investigate chain affiliation’s influence on the performance of lucrative nursing homes. We measure performance using a cost frontier estimated by stochastic analysis on a sample of 370 French for-profit nursing homes. We find that cost efficiency decreases with the number of facilities in a chain. We also identify different external actor types in nursing homes’ institutional environment and test their influence. We show that nursing home chains’ cost efficiency improves when local governments and shareholders exert pressure. Our results are robust to alternative model specifications and another definition of costs. Overall, our findings inform researchers, as well as standards setters, of the relevance of chain affiliation and of the role of institutional pressures regarding cost containment at the nursing home level.