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Biomedical subjects

Jason Roy

Publications and source records attributed to Jason Roy.

7 recordsLinked to original sources
PubMed2003

Inter-rater reliability of nursing home quality indicators in the U.S.

BACKGROUND: In the US, Quality Indicators (QI's) profiling and comparing the performance of hospitals, health plans, nursing homes and physicians are routinely published for consumer review. We report the results of the largest study of inter-rater reliability done on nursing home assessments which generate the data used to derive publicly reported nursing home quality indicators. METHODS: We sampled nursing homes in 6 states, selecting up to 30 residents per facility who were observed and assessed by research nurses on 100 clinical assessment elements contained in the Minimum Data Set (MDS) and compared these with the most recent assessment in the record done by facility nurses. Kappa statistics were generated for all data items and derived for 22 QI's over the entire sample and for each facility. Finally, facilities with many QI's with poor Kappa levels were compared to those with many QI's with excellent Kappa levels on selected characteristics. RESULTS: A total of 462 facilities in 6 states were approached and 219 agreed to participate, yielding a response rate of 47.4%. A total of 5758 residents were included in the inter-rater reliability analyses, around 27.5 per facility. Patients resembled the traditional nursing home resident, only 43.9% were continent of urine and only 25.2% were rated as likely to be discharged within the next 30 days. Results of resident level comparative analyses reveal high inter-rater reliability levels (most items >.75). Using the research nurses as the "gold standard", we compared composite quality indicators based on their ratings with those based on facility nurses. All but two QI's have adequate Kappa levels and 4 QI's have average Kappa values in excess of.80. We found that 16% of participating facilities performed poorly (Kappa <.4) on more than 6 of the 22 QI's while 18% of facilities performed well (Kappa >.75) on 12 or more QI's. No facility characteristics were related to reliability of the data on which Qis are based. CONCLUSION: While a few QI's being used for public reporting have limited reliability as measured in US nursing homes today, the vast majority of QI's are measured reliably across the majority of nursing facilities. Although information about the average facility is reliable, how the public can identify those facilities whose data can be trusted and whose cannot remains a challenge.

Aged↗
PubMed2003

Clinical and organizational factors associated with feeding tube use among nursing home residents with advanced cognitive impairment.

CONTEXT: Empiric data and expert opinion suggest that use of feeding tubes is not beneficial for older persons with advanced dementia. Previous research has shown a 10-fold variation in this practice across the United States. OBJECTIVE: To identify the facility and resident characteristics associated with feeding tube use among US nursing homes residents with severe cognitive impairment. DESIGN, SETTING, AND PARTICIPANTS: Cross-sectional study of all residents with advanced cognitive impairment who had Minimum Data Set assessments within 60 days of April 1, 1999, (N = 186,835) and who resided in Medicare- or Medicaid-certified US nursing homes. Main Outcomes Measures Facility and resident characteristics described in the 1999 On-line Survey Certification of Automated Records and the 1999 Minimum Data Set. Multivariate analysis using generalized estimating equations determined the facility and resident factors independently associated with feeding tube use. RESULTS: Thirty-four percent of residents with advanced cognitive impairment had feeding tubes (N = 63,101). Resident characteristics associated with a greater likelihood of feeding tube use included younger age, nonwhite race, male sex, divorced marital status, lack of advance directives, a recent decline in functional status, and no diagnosis of Alzheimer disease. Controlling for these patient factors, residents living in facilities that were for profit (adjusted odds ratio [OR], 1.09; 95% confidence interval [CI], 1.06-1.12); located in an urban area (OR, 1.14; 95% CI, 1.11-1.16); having more than 100 beds (OR, 1.04; 95% CI, 1.01-1.07); and lacking a special dementia care unit (OR, 1.11; 95% CI, 1.07-1.15) had a higher likelihood of having a feeding tube. Additionally, feeding tube use was more likely among residents living in facilities that had a smaller proportion of residents with do-not-resuscitate orders, had a higher prevalence of nonwhite residents, and lacked a nurse practitioner or physician assistant on staff. CONCLUSIONS: More than one third of severely cognitively impaired residents in US nursing homes have feeding tubes. Feeding tube use is independently associated with both the residents' clinical characteristics and the nursing homes' fiscal, organizational, and demographic features.

Advance Directives↗
PubMed2003

Scaled marginal models for multiple continuous outcomes.

In studies that involve multivariate outcomes it is often of interest to test for a common exposure effect. For example, our research is motivated by a study of neurocognitive performance in a cohort of HIV-infected women. The goal is to determine whether highly active antiretroviral therapy affects different aspects of neurocognitive functioning to the same degree and if so, to test for the treatment effect using a more powerful one-degree-of-freedom global test. Since multivariate continuous outcomes are likely to be measured on different scales, such a common exposure effect has not been well defined. We propose the use of a scaled marginal model for testing and estimating this global effect when the outcomes are all continuous. A key feature of the model is that the effect of exposure is represented by a common effect size and hence has a well-understood, practical interpretation. Estimating equations are proposed to estimate the regression coefficients and the outcome-specific scale parameters, where the correct specification of the within-subject correlation is not required. These estimating equations can be solved by repeatedly calling standard generalized estimating equations software such as SAS PROC GENMOD. To test whether the assumption of a common exposure effect is reasonable, we propose the use of an estimating-equation-based score-type test. We study the asymptotic efficiency loss of the proposed estimators, and show that they generally have high efficiency compared to the maximum likelihood estimators. The proposed method is applied to the HIV data.

Antiretroviral Therapy, Highly Active↗
PubMed2003

Modeling longitudinal data with nonignorable dropouts using a latent dropout class model.

In longitudinal studies with dropout, pattern-mixture models form an attractive modeling framework to account for nonignorable missing data. However, pattern-mixture models assume that the components of the mixture distribution are entirely determined by the dropout times. That is, two subjects with the same dropout time have the same distribution for their response with probability one. As that is unlikely to be the case, this assumption made lead to classification error. In addition, if there are certain dropout patterns with very few subjects, which often occurs when the number of observation times is relatively large, pattern-specific parameters may be weakly identified or require identifying restrictions. We propose an alternative approach, which is a latent-class model. The dropout time is assumed to be related to the unobserved (latent) class membership, where the number of classes is less than the number of observed patterns; a regression model for the response is specified conditional on the latent variable. This is a type of shared-parameter model, where the shared "parameter" is discrete. Parameter estimates are obtained using the method of maximum likelihood. Averaging the estimates of the conditional parameters over the distribution of the latent variable yields estimates of the marginal regression parameters. The methodology is illustrated using longitudinal data on depression from a study of HIV in women.

Analysis of Variance↗
PubMed2003

Classification and regression tree analysis in public health: methodological review and comparison with logistic regression.

BACKGROUND: Audience segmentation strategies are of increasing interest to public health professionals who wish to identify easily defined, mutually exclusive population subgroups whose members share similar characteristics that help determine participation in a health-related behavior as a basis for targeted interventions. Classification and regression tree (C&RT) analysis is a nonparametric decision tree methodology that has the ability to efficiently segment populations into meaningful subgroups. However, it is not commonly used in public health. PURPOSE: This study provides a methodological overview of C&RT analysis for persons unfamiliar with the procedure. METHODS AND RESULTS: An example of a C&RT analysis is provided and interpretation of results is discussed. Results are validated with those obtained from a logistic regression model that was created to replicate the C&RT findings. Results obtained from the example C&RT analysis are also compared to those obtained from a common approach to logistic regression, the stepwise selection procedure. Issues to consider when deciding whether to use C&RT are discussed, and situations in which C&RT may and may not be beneficial are described. CONCLUSIONS: C&RT is a promising research tool for the identification of at-risk populations in public health research and outreach.

Decision Trees↗
PubMed2003

Why do drug treatment organizations use contingent staffing arrangements? An analysis of market and social influences.

Contingent staffing arrangements are defined as conditional and transitory work arrangements. In the drug abuse treatment sector, contingent staffing arrangements have the potential to improve treatment if they are used to increase access to needed services. Alternatively, such arrangements could interfere with the development of consistent, long-term client-staff relationships. Unfortunately, little is known about the consequences of or influences on contingent staff arrangements in this sector. The goal of this study is to examine the conditions under which outpatient substance abuse treatment organizations are more likely to use contingent staffing arrangements. Building on previous research on the social organization of health care structures and practices, we develop a conceptual model based in market economics and institutional perspectives to suggest that treatment organizations choose contingent arrangements in response to market conditions and uncertainty, institutional demands, and client needs. Using data from a nationally representative study conducted in 1988, 1990, and 1995, we find limited evidence that drug treatment units use contingent staff in response to market pressures. Labor market and demand uncertainty, however, are systematically associated with greater use of contingent staff. Study results suggest that expectations and norms from the institutional environment, particularly the organizational context of the treatment unit are strong predictors of the use of contingent staff. By considering both market and social influences of contingent staffing, we contribute to a growing body of research on how markets and institutions interact to influence organizational structures and practices in the health care system.

Ambulatory Care Facilities↗