Nonprofit Chain Research Articles

Evolution of the home health care market: The expansion and quality performance of multi-agency chains.

To examine the growth and evolution of the home health agency (HHA) market and to compare quality performance across HHA ownership categories. Agency characteristics were extracted from Medicare cost reports and Provider of Services file. Quality of care and patient characteristics were extracted from Quality of Patient Care Star Ratings and HHA Public Use File. Agency- and state-level analyses were conducted to describe HHA market trends. Patient characteristics and quality measures were compared across ownership categories of interest. All Medicare-certified HHAs in operation, 2005-2018. Over the study period, the HHA sector grew substantially, increasing from 7899 to 10818 agencies, and chain-owned HHAs doubled in number from 903 (11.4% of all agencies) to 1841 (17.0%). In 2018, across agency types, for-profit nonchain agencies were the largest category both in the number of agencies (67.8%) and the number of Medicare enrollees served (40.7%). Additionally, for-profit nonchain agencies grew most in total number, from 4293 (54.3%) to 7337 (67.8%), while for-profit chain agencies grew most in the number of Medicare enrollees served, from 439998 (12.9%) to 1082385 (28.3%). Regarding patient composition, for-profit nonchain agencies served the highest proportion of dual eligible beneficiaries (42.2%) and African-Americans (27.9%) among all agency types. Regarding quality performance, a higher star rating is significantly (P<.01) associated with chain agency status. Moreover, chain HHAs performed better on self-reported process measures, and risk-adjusted self-reported outcome measures; however, they performed worse on risk-adjusted claims-based outcome measures. These results were similar across for-profit and nonprofit chain agencies. Chains play a growing role in the home health sector. Substantial differences in geographic distribution, patient composition, and quality performance were observed between chain- and nonchain HHAs. Examining the growth and performance of multi-agency chains can help inform quality reporting and monitoring, assess payment adequacy, and facilitate greater transparency and accountability within the HHA marketplace.

The Determinants and Variation of Nursing Home Private-Pay Prices: Organizational and Market Structure.

Nursing home (NH) care is arguably the most significant financial risk faced by the elderly without long-term care insurance or Medicaid coverage. Annual out-of-pocket expenditures for NH care can easily exceed $70,000. However, our understanding of private-pay prices is limited by data availability. Utilizing a unique data set on NH prices from 2005 through 2010 across eight states, we find that NH price growth has consistently outpaced growth in consumer and medical care prices. After adjusting for geographical and facility differences, for-profit chains charge the lowest prices, independently operated for-profit and nonprofit NHs have similar prices, and nonprofit chains charge the highest prices. Adjusted prices are also likely to be higher when NHs have higher occupancy rates and markets are more concentrated. The significant differences in price across organizational and market structures suggest private-pay prices can be an important factor when evaluating and comparing the value of NH care.

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.

Global Non-Profit Chains and the Challenges of Development Aid Contracting

AbstractThis paper employs Oliver Williamson’s transaction cost approach to assess contracting. We find that donor contracting with global non-profit chains is conducive to NPO opportunism due to the asset specificity of the contracts, infrequent contracting, and the uncertainty of outcomes. These risks are further exacerbated by the weak enforcement mechanisms available in many developing countries. Williamson’s framework predicts that these risks would tempt donors to resort to the muscular approach, where they would exercise maximum control over the non-profit chain. Although competition would be a safeguard against the muscular approach, the donor landscape suffers from collusion and is monopsonistic. Our analysis suggests that while the current contracting and oversight arrangements might serve the donor procedural objective to exercise control in a sector marked by information asymmetries, these arrangements can undermine the primary objective of donors, namely responsiveness to beneficiaries, and ultimately, improved beneficiary welfare. We illustrate our conceptual analysis with short case studies of three Ugandan NPOs.

Do Nursing Home Chain Size and Proprietary Status Affect Experiences With Care?

In 2012, over half of nursing homes were operated by corporate chains. Facilities owned by the largest for-profit chains were reported to have lower quality of care. However, it is unknown how nursing home chain ownerships are related with experiences of care. To study the relationship between nursing home chain characteristics (chain size and profit status) with patients' family member reported ratings on experiences with care. Maryland nursing home care experience reports, the Online Survey, Certification, And Reporting (OSCAR) files, and Area Resource Files are used. Our sample consists of all nongovernmental nursing homes in Maryland from 2007 to 2010. Consumer ratings were reported for: overall care; recommendation of the facility; staff performance; care provided; food and meals; physical environment; and autonomy and personal rights. We identified chain characteristics from OSCAR, and estimated multivariate random effect linear models to test the effects of chain ownership on care experience ratings. Independent nonprofit nursing homes have the highest overall rating score of 8.9, followed by 8.6 for facilities in small nonprofit chains, and 8.5 for independent for-profit facilities. Facilities in small, medium, and large for-profit chains have even lower overall ratings of 8.2, 7.9, and 8.0, respectively. We find similar patterns of differences in terms of recommendation rate, and important areas such as staff communication and quality of care. Evidence suggests that Maryland nursing homes affiliated with large-for-profit and medium-for-profit chains had lower ratings of family reported experience with care.

Dialysis Chains and Placement on the Waiting List for a Cadaveric Kidney Transplant

The proliferation of multi-unit for-profit dialysis chains in the ESRD industry has raised concerns for patient quality of care including access to renal transplantation therapy (RTT). The effect of dialysis facility chain status on RTT is unknown. Data from the United States Renal Data System were used to identify 4,465 dialysis facilities and 56,714 dialysis patients who started hemodialysis in 2006. Patients were followed from initiation of hemodialysis in 2006 to placement on the renal transplant waiting list or to December 31, 2009. The role of dialysis facility chain status (affiliation, size, and ownership) on placement on the renal transplant waiting list was evaluated by multi-level mixed-effect regression models that account for clustering within facilities. Patients from for-profit chain facilities, compared to nonprofit chain facilities, were 13% (95% CI 0.77-0.98) less likely to be waitlisted. In contrast, among nonchains, facility ownership did not influence likelihood of being waitlisted. There was also a marginally significant difference in waiting list placement by chain size: large chains compared with mid or small chains were 8% (95% CI 0.84-1.00) less likely to place patients on the waiting list. After adjustment for patient and facility characteristics, dialysis facility chain affiliation (chain-affiliated or not) was not found to be independently associated with the likelihood of placement on the transplant waitlist. Dialysis chain affiliation expands previously observed ownership-related differences in placement on the waiting list. For-profit ownership of dialysis chain facilities appears to be a significant impediment to access to renal transplants.

Patient Care Staffing Levels and Facility Characteristics in US Hemodialysis Facilities

Higher numbers of registered nurses (RNs) per patient have been associated with improved patient outcomes in acute-care facilities. Variation in and associations of patient care staffing levels and hemodialysis facility characteristics have not been examined previously. Cross-sectional study using Poisson regression to examine associations between patient care staffing levels and hemodialysis facility characteristics. 4,800 US hemodialysis facilities in the 2009 Centers for Medicare & Medicaid (CMS) End-Stage Renal Disease Annual Facility Survey (CMS-2744 form). Facility characteristics, including profit status, freestanding status, chain affiliation, and geographic region, adjusted for facility size, capacity, functional type, and urbanicity. Patient care staffing levels, including ratios of RNs, licensed practical nurses (LPNs), patient care technicians (PCTs), composite staff (RN + LPN + PCT), social workers, and dietitians to in-center hemodialysis patients. After adjusting for background facility characteristics, ratios of RNs and LPNs to patients were 35% (P < 0.001) and 42% (P < 0.001) lower, respectively, but the PCT to patient ratio was 16% (P < 0.001) higher in for-profit than nonprofit facilities (rate ratios of 0.65 [95% CI, 0.63-0.68], 0.58 [95% CI, 0.51-0.65], and 1.16 [95% CI, 1.12-1.19], respectively). Regionally, compared to the Northeast, the adjusted RN to patient ratio was 14% (P < 0.001) lower in the Midwest, 25% (P < 0.001) lower in the South, and 18% (P < 0.001) lower in the West. Even after additional adjustments, the large for-profit chains had significantly lower RN and LPN to patient ratios than the largest nonprofit chain, but a significantly higher PCT to patient ratio. Overall composite staffing levels also were lower in for-profit and chain-affiliated facilities. The patterns hold when hospital-based units were excluded. Nursing hours were not available. Two part-time staff were counted as one full-time equivalent, which may not always be accurate. The significant variation in patient care staffing levels and its associations with facility characteristics warrants inclusion in future large-scale hemodialysis outcomes studies. End-stage renal disease networks and hemodialysis facilities should attend to quality assurance and performance improvement initiatives that maximize licensed nurse staffing levels in hemodialysis facilities.

Organizational Status of Dialysis Facilities and Patient Outcome: Does Higher Injectable Medication Use Mediate Increased Mortality?

Examine the mediating effect of injectable drugs in the relationship between dialysis facility organizational status and patient mortality. Medicare dialysis population. Data from the U.S. Renal Data System (USRDS) were used to identify 3,884 freestanding dialysis facilities and 37,942 Medicare patients incident to end-stage renal disease (ESRD) in 2006. The role of injectable medications was evaluated during a 2-year follow-up period by mediational analyses using mixed-effect regression models. USRDS data were matched with Dialysis Facility Report data from Centers for Medicare and Medicaid Services (CMS) and census data. There was a strong association found between organizational status and use of injectable drugs. Large for-profit chains used significantly higher injectable medications compared with nonprofit chains and independent facilities. However, the relationship between facility organizational status and patient mortality was not found to be mediated through the higher use of injectable drugs. Large for-profit chain facilities administered higher IV epoetin, iron, and vitamin D dosages, but this did not result in improved survival. Given the associated costs and lack of a survival benefit, the overuse of injectable medications among the U.S. dialysis patients will likely end under the recent bundling of injectable medications without jeopardizing patient outcomes.

Do Resource Utilization and Clinical Measures Still Vary Across Dialysis Chains After Controlling for the Local Practices of Facilities and Physicians?

Because of adverse survival effects, anemia management and financial incentives to increase doses of erythropoiesis-stimulating agents (ESAs) have been controversial. Prior studies showed more aggressive anemia management in dialysis facilities owned by for-profit chains, but have been criticized for not accounting for practices of individual physicians and facilities. To improve understanding of how dialysis practices and resource utilization are influenced by physicians, facilities, and chains. Mixed models with chain fixed effects and facility and physician random effects. Medicare hemodialysis patients in 2004. A total of 234,158 patients, 3995 facilities, 4838 physicians, and 7 chain classifications were included. Spending per session for dialysis-related services billed separately from the dialysis treatment and for ESAs. Achievement of hematocrit (HCT) and urea reduction ratio (URR) targets. Of the 4 largest for-profit chains, 3 had higher resource use than independents, with differences up to $17.92 higher ESA/session. Utilization was positively associated with achieving target HCT. Despite incurring lower costs, patients treated by a large nonprofit chain were as likely as patients of independents to achieve the HCT target. The largest chains were more likely than independents to achieve the URR target. Substantial variation occurred across physicians and facilities, and adjustment for chain only modestly decreased this variation. Chains' methods of influencing practices were not directly observed. Chains appear to have the ability to implement protocols that shift practices, but not the ability to substantially reduce local variation. Assertions that chain effects found by earlier studies were spurious are not supported.

Cut to the Bone? Hospital Takeovers and Nurse Employment Contracts

The authors examine changes in the wages, employment, and effort of nurses in California hospitals following takeovers by large chains in the 1990s. The market for nurses has been described as a classic monopsony, so that one might expect increases in firm market power to be associated with declines in wages. However, a basic contracting model predicts effects on effort rather than on wages, which is what this analysis finds: nurses experienced few declines in wages following takeovers, but did see increases in the number of patients per nurse, the measure of effort used here. The authors show that their results are also consistent with an extended version of the monopsony model that considers effort and allows for revenue shifts following a takeover. Finally, they find that these changes were similar in the largest for-profit and non-profit chains, suggesting that market forces are more important than institutional form.

Cut to the Bone? Hospital Takeovers and Nurse Employment Contracts

This paper uses data from the 1990s to examine changes in the wages, employment, and effort of nurses in California hospitals following takeovers by large chains. The market for nurses has been described as a classic monopsony, so that one might expect increases in firm market power to be associated with declines in wages. However, we show that if one extends the monopsony model to consider effort, or if we apply a basic contracting model to the data, then we would expect to see effects on effort rather than on wages. This prediction is bourne out by the data nurses see few declines in wages following takeovers, but see increases in the number of patients per nurse, our measure of effort. We also find that these changes are similar in the largest for-profit and non-profit chains, suggesting that market forces are more more important than institutional form.