Regenstrief Institute

About: Regenstrief Institute is a nonprofit organization based out in Indianapolis, Indiana, United States. It is known for research contribution in the topics: Health care & Population. The organization has 742 authors who have published 2042 publications receiving 96966 citations.

APOE ε4 and the risk for Alzheimer disease and cognitive decline in African Americans and Yoruba.

Abstract: Background: There is little information on the association of the APOEe4 allele and AD risk in African populations. In previous analyses from the Indianapolis-Ibadan dementia project, we have reported that APOE e4 increased the risk for Alzheimer's disease (AD) in African Americans but not in Yoruba. This study represents a replication of this earlier work using enriched cohorts and extending the analysis to include cognitive decline. Methods: In this longitudinal study of two community dwelling cohorts of elderly Yoruba and African Americans, APOE genotyping was conducted from blood samples taken on or before 2001 (1,871 African Americans & 2,200 Yoruba). Mean follow up time was 8.5 years for African Americans and 8.8 years for Yoruba. The effects of heterozygosity or homozygosity of e4 and of the possession of e4 on time to incident AD and on cognitive decline were determined using Cox's proportional hazards regression and mixed effects models. Results: After adjusting for covariates, one or two copies of the APOE e4 allele were significant risk factors for incident AD (p < 0.0001) and cognitive decline in the African-American population (p < 0001). In the Yoruba, only homozygosity for APOE e4 was a significant risk factor for AD (p = 0.0002) but not for cognitive decline (p = 0.2346), however, possession of an e4 allele was significant for both incident AD (p = 0.0489) and cognitive decline (p = 0.0425). Conclusions: In this large longitudinal comparative study, APOE e4 had a significant, but weaker, effect on incident AD and on cognitive decline in Yoruba than in African Americans. The reasons for these differences remain unclear.

Nursing Effort and Quality of Care for Nursing Home Residents

Abstract: Poor-quality nursing home care is a persistent concern. Efforts to address this concern have included stronger regulation, stricter educational standards, and expanded consumer information. Another proposed strategy is to increase nursing home direct care staffing levels under the assumption that many nursing homes have insufficient staff resources to deliver good-quality care. The evidence to support the relationship between staffing and quality deserves closer examination. Although the majority of studies (described here) have shown a positive relationship between at least one staffing variable and one quality variable, these same studies have found that there are no significant relationships between other staffing and quality variables. Most studies examining the relationship between nurse staffing and quality have used facility-level staffing data from the Centers for Medicare & Medicaid Services (CMS) Online Survey, Certification and Reporting (OSCAR) database (Akinci & Krolikowski, 2005; Bostick, 2004; Castle, 2002; Cherry, 1991; Harrington, Zimmerman, Karon, Robinson, & Beutel, 2000; Jette, Warren, & Wirtalla, 2004; Mosely & Jones, 2003; Spector & Takada, 1991; Stevenson, 2005; Weech-Maldanado, Meret-Hanke, Neff, & Mor, 2004; Zhang & Grabowski, 2004; S. Zimmerman, Gruber-Baldini, Hebel, Sloane, & Magaziner, 2002). The inconsistency in facility reporting of OSCAR staffing data has raised questions about their reliability (CMS, 2001a). Other studies have used administrative data such as Medicaid cost reports (Anderson, Hsieh, & Su, 1998; Bates-Jensen, Schnelle, Alessi, Al-Samarrai, & Levy-Storms, 2004; CMS, 2001b; Munroe, 1990; Nyman, 1988; Rantz et al., 2004; Schnelle et al., 2004), which typically cover a long time period (e.g., 12 months) and, thus, may be insensitive to variation in staffing over time. Also, none of the previous studies have had unit-level measures of staffing. Quality measures in previous studies have varied greatly and have included such variables as care deficiencies cited by nursing home surveyors (Akinci & Krolikowski, 2005; Castle, 2002; Harrington et al., 2000; Mosely & Jones, 2003; Munroe, 1990), care processes (e.g., use of restraints and catheters; Graber & Sloane, 1995; Phillips et al., 1996; Schnelle et al., 2004; Sullivan-Marx, Strumpf, Evans, Baumgarten, & Maislin, 1999; Svarstad & Mount, 2001; Weech-Maldanado et al., 2004), and health or functional outcomes (e.g., weight loss, pressure ulcers, or functional decline; Anderson et al., 1998; Bliesmer, Smayling, Kane, & Shannon, 1998; Bostick, 2004; CMS, 2001b; Cohen & Spector, 1996; Horn, Buerhaus, Bergstrom, & Smout, 2005; Jette et al., 2004; Weech-Maldanado et al., 2004; S. Zimmerman et al., 2002). The validity of survey data as quality indicators has been challenged because of differences in the way surveyors investigate and cite deficiencies within and between states (CMS, 2001c). Studies using Minimum Data Set (MDS) or other resident-level data have lacked common definitions of processes or outcomes (Bostick, 2004; CMS, 2001b; Horn et al., 2005; Weech-Maldanado et al., 2004; Zhang & Grabowski, 2004). In addition, endogeneity between measures of staffing and quality makes causal inference problematic, particularly for process measures for which staffing level both influences and is influenced by the types of care being provided to residents. Another threat to causal inference is spuriousness, whereby higher staffing and higher quality, although correlated, may result from a third factor. For example, facilities committed to better care may hire more staff and manage them more effectively. Researchers have found staff skill mix (i.e., proportion registered nurse [RN], licensed practical nurse [LPN], nursing assistant, or other staff types) to be an important factor in quality. The majority of studies have pointed to the importance of licensed nurse time, particularly RN time (Akinci & Krolikowski, 2005; Anderson et al., 1998; Bliesmer et al., 1998; Bostick, 2004; Castle, 2002; Cherry, 1991; Cohen & Spector, 1996; Harrington et al., 2000; Horn et al., 2005; Munroe, 1990; Spector & Takada, 1991; Weech-Maldanado et al., 2004; S. Zimmerman et al., 2002). Fewer studies have found unlicensed staff time to be significant (Akinci & Krolikowski, 2005; Bostick, 2004; Graber & Sloane, 1995; Harrington et al., 2000; Schnelle et al., 2004). A number of studies have found that licensed practical/vocational nurse time either was not significantly related to quality (Castle, 2002; Harrington et al., 2000) or had a negative relationship (Bostick, 2004; Horn et al., 2005; Sullivan-Marx et al., 1999; Zhang & Grabowski, 2004; S. Zimmerman et al., 2002). All previous studies have examined quality and staffing relationships at the facility or nursing unit level. Yet effects of staffing are relevant at two levels— the overall staffing resources available on the unit (RN, LPN, or aide hours per resident day [HPRD]) and the amount of care provided to each resident. Available staffing constrains the amount of care a resident can receive, but the allocation of care across residents on a unit is also influenced by clinical decisions, management practices, physical environment, and other factors that are difficult to observe. In the end, it is the time spent by staff with an individual resident that should have the greatest effect on care quality. Ours is the first study to measure the time spent by different staff types with individual residents and to employ multilevel modeling to examine simultaneously the effects of unit staffing and care received by individual residents on quality measures.

Association Between Prescribing of Anticholinergic Medications and Incident Delirium: A Cohort Study

Abstract: Objectives: To describe the association between anticholinergic medications and incident delirium in hospitalized older adults with cognitive impairment and to test the hypothesis that anticholinergic medications would increase the risk of incident delirium. Design: Observational cohort study. Setting: Urban public hospital in Indianapolis, Indiana. Participants: One hundred forty-seven participants aged 65 and older with cognitive impairment who screened negative for delirium at the time of admission to a general medical ward. Measurements: Cognitive function at the time of admission was assessed using the Short Portable Mental Status Questionnaire (SPMSQ). Anticholinergic medication orders between the time of admission and the final delirium assessment were evaluated. Anticholinergic medication orders were identified using the Anticholinergic Cognitive Burden Scale. Delirium was assessed using the Confusion Assessment Method. Results: Fifty-seven percent of the cohort received at least one order for possible anticholinergic medications, and 28% received at least one order for definite anticholinergic medications. The incident rate for delirium was 22% of the entire cohort. After adjusting for age, sex, race, baseline SPMSQ score, and Charlson Comorbidity Index, the odds ratio (OR) for developing delirium in those with orders for possible anticholinergic medications was 0.33 (95% confidence interval (CI) = 0.10�1.03). The OR for developing delirium among those with orders for definite anticholinergic medications was 0.43 (95% CI = 0.11�1.63). Conclusion: The results did not support the hypothesis that prescription of anticholinergic medications increases the risk of incident delirium in hospitalized older adults with cognitive impairment. This relationship needs to be established using prospective study designs with medication dispensing data to improve the performance of predictive models of delirium.