Medicare payment changes and nursing home quality: effects on long-stay residents

The Balanced Budget Act of 1997 dramatically changed the way that Medicare pays skilled nursing facilities, providing a natural experiment in nursing home behavior. Medicare payment policy (directed at short-stay residents) may have affected outcomes for long-stay, chronic-care residents if services for these residents were subsidized through cost-shifting prior to implementation of Medicare prospective payment for nursing homes. We link changes in both the form and level of Medicare payment at the facility level with changes in resident-level quality, as represented by pressure sores and urinary tract infections in Minimum Data Set (MDS) assessments. Results show that long-stay residents experienced increased adverse outcomes with the elimination of Medicare cost reimbursement.     

Finding a useful conceptual basis for enhancing the quality of life of nursing home residents

In this article it is depicted that before nursing home staff can effectively contribute to optimising the quality of life (QOL) of nursing home residents, it has to be clear what exactly QOL is and how it can be enhanced. The aim is to identify a QOL framework that provides tools for optimising QOL and can form the basis for the development of guidelines for QOL enhancement. For that purpose, a framework should meet three basic criteria: (1) it should be based on assumptions about comprehensive QOL of human beings in general; (2) it should clearly describe the contribution of each dimension to QOL and identify relationships between the dimensions; (3) it should take individual preferences into account. After the criteria are defined, frameworks identified from a literature search are discussed and evaluated according to these criteria. The most suitable framework appears to be the QOL framework of the theory of Social Production Functions. The implications of this framework in understanding the QOL of nursing home residents are described and recommendations for further research are discussed.     

OBRA 1987 and the quality of nursing home care

Because minimum government standards for quality regulate only part of the market failure, they may have unintended effects. We present a general theory of how government regulation of quality of care may affect different market segments, and test the hypotheses for the nursing home market. OBRA 1987 was a sweeping government reform to improve the quality of nursing home care. We study how the effect of OBRA on the quality of nursing home care, measured by resident outcomes, varied with nursing home profitability. Using a semi-parametric method to control for the endogenous effects of regulation, we found that this landmark legislation had a negative effect on the quality of care in less profitable nursing homes, but improved the quality in more profitable nursing homes during the initial period after OBRA. But, this legislation had no statistically significant effect in the later period when the regulation was weakly enforced. JEL Classification I18 . I11     

Strategic orientation and nursing home response to public reporting of quality measures: an application of the miles and snow typology

OBJECTIVE: To assess whether differences in strategic orientation of nursing homes as identified by the Miles and Snow typology are associated with differences in their response to the publication of quality measures on the Nursing Home Compare website. DATA SOURCES: Administrator survey of a national 10 percent random sample (1,502 nursing homes) of all facilities included in the first publication of the Nursing Home Compare report conducted in May-June 2004; 724 responded, yielding a response rate of 48.2 percent. STUDY DESIGN: The dependent variables are dichotomous, indicating whether or not action was taken and the type of action taken. Four indicator variables were created for each of the four strategic types: Defender, Analyzer, Prospector, and Reactor. Other variables were included in the seven logistic regression models to control for factors other than strategic type that could influence nursing home response to public disclosure of their quality of care. DATA COLLECTION/EXTRACTION METHODS: Survey data were merged with data on quality measures and organizational characteristics from the first report (November 2002). PRINCIPAL FINDINGS: About 43 percent of surveyed administrators self-typed as Defenders, followed by Analyzers (33 percent), and Prospectors (19 percent). The least self-selected strategic type was the Reactor (6.6 percent). In general, results of the regression models indicate differences in response to quality measure publication by strategic type, with Prospectors and Analyzers more likely, and Reactors less likely, to respond than Defenders. CONCLUSIONS: While almost a third of administrators took no action at all, our results indicate that whether, when, and how nursing homes reacted to publication of federally reported quality measures is associated with strategic orientation.     

Assessing nursing home care quality through Bayesian networks

This article demonstrates how Bayesian networks can be employed as a tool to assess the quality of care in nursing homes. For the data sets analyzed, the proposed model performs comparably to existing quantitative assessment models. In addition, a Bayesian network approach offers several uniques advantages. The structure and parameters of a Bayesian network provide rich insight into the multidimensional aspects of the quality of care. Bayesian networks can be used as a guide in implementing limited resources by identifying information that would be most relevant to an assessment. Finally, Bayesian networks provide a straightforward framework for integrating nursing home care quality research that is conducted in various locations and for various purposes.     

The influence of staffing characteristics on quality of care in nursing homes

OBJECTIVE: The influence staffing levels, turnover, worker stability, and agency staff had on quality of care in nursing homes was examined. DATA SOURCES/STUDY SETTING: Staffing characteristics came from a survey of nursing homes (N=1,071) conducted in 2003. The staffing characteristics were collected for Nurse Aides, Licensed Practical Nurses, and Registered Nurses. Fourteen quality indicators came from the Nursing Home Compare website report card and nursing home organizational characteristics came from the Online Survey, Certification, and Recording system. STUDY DESIGN: One index of quality (the outcome) was created by combining the 14 quality indicators using exploratory factor analysis. We used regression analyses to assess the effect of the four staffing characteristics for each of the three types of nursing staff on this quality index in addition to individual analyses for each of the 14 quality indicators. The effect of organizational characteristics as well as the markets in which they operated on outcomes was examined. We examined a number of different model specifications. PRINCIPAL FINDINGS: Quality of care was influenced, to some degree, by all of these staffing characteristics. However, the estimated interaction effects indicated that achieving higher quality was dependent on having more than one favorable staffing characteristic--the effect of quality was larger than the sum of the independent effects of each favorable staffing characteristic. CONCLUSIONS: Our results indicate that staff characteristics such as turnover, staffing levels, worker stability, and agency staff should be addressed simultaneously to improve the quality of nursing homes.     

Nursing home spending patterns in the 1990s: the role of nursing home competition and excess demand

OBJECTIVE: To examine nursing home expenditures on clinical, hotel, and administrative activities during the 1990s and to determine the association between nursing home competition and excess demand on expenditures. DATA SOURCES/STUDY SETTING: Secondary data sources for 1991, 1996, and 1999 for 500 free-standing nursing homes in New York State. STUDY DESIGN: A retrospective statistical analysis of nursing homes' expenditures. The dependent variables were clinical, hotel, and administrative costs in each year. Independent variables included outputs (inpatient and outpatient), wages, ownership, New York City location, and measures of competition and excess demand. DATA COLLECTION/EXTRACTION METHOD: Variables were constructed from annual financial reports submitted by the nursing homes, the Patient Review Instrument and Medicare enrollment data. PRINCIPAL FINDINGS: Clinical and administrative costs have increased over the decade, while hotel expenditures have declined. Increased competition was associated with higher clinical and administrative costs while excess demand was associated with lower clinical and hotel expenditures. CONCLUSIONS: Nursing home expenditures are sensitive to competition and excess demand conditions. Policies that influence competition in nursing home markets are therefore likely to have an impact on expenditures as well.     

Detecting systematic discrepancies in nursing home assessments of residents

Medicare and Medicaid reimbursement received by nursing homes are linked to the care needs of residents in a facility. Thus, a facility may have an incentive to overestimate the care needs of residents. To evaluate this, a sample of nursing homes in Ohio was selected, and independent assessors were sent to sampled facilities, and the rating of residents by the independent assessor was compared to a similar rating by the staff at nursing homes. We first evaluated whether the independent assessors were homogeneous with respect to agreement with nursing facility assessors using a permutation test procedure. Since there was evidence of heterogeneity among the independent assessors, we evaluated agreement between the independent nurse and facility assessors separately for each independent nurse. Responses were collapsed into three categories: independent assessor was lower, equal or greater than the facility assessor. Under a null hypothesis that lower and greater categories were equally probable, the maximum likelihood estimate of the vector of probabilities corresponding to these categories was constructed for each independent assessor. The P-value for detecting a difference between independent and facility assessors was calculated for each facility by summing the multinomial probabilities of obtaining a result at least as extreme as observed in the direction of the “lower” category being more probable. Five of the 39 facilities had P-value < 0.10 with three of the low P-value facilities occurring in reviews by one of the independent assessors. We believe that there is not evidence of systematic differences between the facility assessors and independent assessors although a caveat associated with this statement is the power of this assessment procedure is strongly linked to number of cases reviewed per facility along with the size of the effect expected. We believe this provides a screening mechanism to identify facilities where additional samples are warranted.     

What is the impact of policy differences on nursing home utilization? The cases of Germany and the Netherlands

Though need factors would predict a higher rate of institutional use in Germany, in 2004 the percentage of people over 65 in institutions in the Netherlands was almost double the percentage in Germany. The lower nursing home utilization in Germany coincided with lower out-of-pocket costs, de facto means-testing of social assistance for such care, a lower perceived quality of nursing home, and less acceptance of the nursing home as a main care modality for adults experiencing functional impairments. These factors have developed over time and are consistent with a – relatively – large government responsibility toward care for the elderly and a preference for institutional care over home care in the Netherlands. The policy to encourage older adults to move to elderly homes to decrease the housing shortage after WWII might have had long-lasting effects. This paper points out that a key in the success of a reform is a behavioral change in the system. As there seems to be no single factor to decrease the percentage of older adults in nursing homes, a sequence of policies might be a more promising route.     

Wolves in sheep’s clothing: Is non-profit status used to signal quality?

Why do many firms in the healthcare sector adopt non-profit status? One argument is that non-profit status serves as a signal of quality when consumers are not well informed. A testable implication is that an increase in consumer information may lead to a reduction in the number of non-profits in a market. We test this idea empirically by exploiting an exogenous increase in consumer information in the US nursing home industry. We find that the information shock led to a reduction in the share of non-profit homes, driven by a combination of home closure and sector switching. The lowest quality non-profits were the most likely to exit. Our results have important implications for the effects of reforms to increase consumer provision in a number of public services.     

Development and testing of nursing home quality indicators

In this article, the authors report on the development and testing of a set of indicators of quality of care in nursing homes, using resident-level assessment data. These quality indicators (QIs) have been developed to provide a foundation for both external and internal quality-assurance (QA) and quality-improvement activities. The authors describe the development of the QIs, discuss their nature and characteristics, address the development of a QI-based quality-monitoring system (QMS), report on a pilot test of the QIs and the system, comment on methodological and current QI validation efforts, and conclude by raising further research and development issues.     

Feasibility of quality indicators for the management of geriatric syndromes in nursing home residents

PURPOSE: The assessment and management of dementia, falls and mobility disorders, malnutrition, end-of-life issues, pressure ulcers, and urinary incontinence have been identified as important quality improvement targets for vulnerable elders residing in nursing homes. This study aimed to identify valid and feasible measures of specific care processes associated with improved outcomes for these conditions. METHODS: Nine experts in nursing home (NH) care participated in a modified Delphi process to evaluate potential quality indicators (QIs) for care in NHs. Panelists met and discussed potential indicators before completing confidential ballots rating validity (process associated with improved outcomes), feasibility of measurement (with charts or interviews), feasibility of implementation (given staffing resources in average community NHs), and importance (expected benefit and prevalence in NHs). The NH panel's median votes were used to identify a final set of QIs that were subsequently reviewed by a clinical oversight committee. RESULTS: Sixty-eight geriatric syndrome QIs were identified as valid and important in NH populations. Panelists assessed 12 (18%) of these QIs as having questionable feasibility to implement in average community nursing homes trying to provide quality care. Nine (13%) would not be included in systems assessing quality of care for persons with advanced dementia or poor prognosis. CONCLUSIONS: Steps of care critical to the assessment and management of geriatric syndromes in NHs were identified. Feasibility is an important issue for a significant number of these, indicating that much remains to be done to design systems that efficiently and reliably implement these care processes.