Use of Long-Term Care Services by Older Persons with Limited English Proficiency.

Older migrants face special difficulties in the access and use of long-term care services and supports (LTSS). Our study was designed to examine how older persons with limited English proficiency (LEP) in two groups of migrants (Spanish or Chinese speaking) interact with the LTSS system. Focus groups were used to elicit information from members of these groups. We discovered Chinese elders were likely to believe that the LTSS services could, if managed properly, meet their needs, while the Spanish speakers were more skeptical. These differences were associated with the presence of trusted intermediaries among the Chinese elders who could represent their interests, while most Spanish speakers did not report having such intermediaries. In this way, trust, or lack of it, was uncovered as the key element defining older adults' interactions with the formal health and social service systems. Findings will be used to develop a modeling method that will allow us to analyze results in a manner that can be extended to use with other migrant groups.

From Personalized Medicine to Personalized Aging Services.

As medical models become more ubiquitous in developing strategies to provide long-term care services and support (LTSS), we need to ask whether these models adequately account for sources of diversity and disadvantage that affect access to and use of services by older adults. Medical models typically focus on categorizing information about the individual in order to clearly define current health status and appropriate treatment. Any individual, however, reflects the sum of their life experiences. Therefore, this medicalization approach can miss key factors in determining health outcomes including social determinants of health. Just as importantly, this approach can miss issues of values, beliefs, and assumptions that older adults can bring into the encounter with service providers. This issue is especially important when dealing with older migrant communities. Beliefs and attitudes shaped in their place of origin, as well as the migration experience, can influence levels of trust and resulting decisions regarding the use of LTSS. We need to integrate an understanding of how these beliefs and attitudes affect decision making into any model designed to improve the lives of older persons.

Accuracy and validation of an automated electronic algorithm to identify patients with atrial fibrillation at risk for stroke.

BACKGROUND: There is no universally accepted algorithm for identifying atrial fibrillation (AF) patients and stroke risk using electronic data for use in performance measures. METHODS: Patients with AF seen in clinic were identified based on International Classification of Diseases, Ninth Revision(ICD-9) codes. CHADS(2) and CHA(2)DS(s)-Vasc scores were derived from a broad, 10-year algorithm using IICD-9 codes dating back 10 years and a restrictive, 1-year algorithm that required a diagnosis within the past year. Accuracy of claims-based AF diagnoses and of each stroke risk classification algorithm were evaluated using chart reviews for 300 patients. These algorithms were applied to assess system-wide anticoagulation rates. RESULTS: Between 6/1/2011, and 5/31/2012, we identified 6,397 patients with AF. Chart reviews confirmed AF or atrial flutter in 95.7%. A 1-year algorithm using CHA(2)DS(2)-Vasc score ≥2 to identify patients at risk for stroke maximized positive predictive value (97.5% [negative predictive value 65.1%]). The PPV of the 10-year algorithm using CHADS(2) was 88.0%; 12% those identified as high-risk had CHADS(2) scores <2. Anticoagulation rates were identical using 1-year and 10-year algorithms for patients with CHADS(2) scores ≥2 (58.5% on anticoagulation) and CHA(2)DS(2)-Vasc scores ≥2 (56.0% on anticoagulation). CONCLUSIONS: Automated methods can be used to identify patients with prevalent AF indicated for anticoagulation but may have misclassification up to 12%, which limits the utility of relying on administrative data alone for quality assessment. Misclassification is minimized by requiring comorbidity diagnoses within the prior year and using a CHA(2)DS(2)-Vasc based algorithm. Despite differences in accuracy between algorithms, system-wide anticoagulation rates assessed were similar regardless of algorithm used.

Building an integrated research/policy planning age-friendly agenda.

This article describes an innovative model for integrating research into a policy and planning agenda aimed to help neighborhoods become more supportive of older adults. Philadelphia Corporation for Aging (PCA) established Age-Friendly Philadelphia (AFP) to catalyze efforts to improve the physical and social environments for seniors. The Research Program at PCA became an important part of this effort by providing multiple types of supports to PCA staff and other stakeholders. Most notably, the research program worked with planners to adopt the United States Environmental Protection Agency's Aging Initiative model for Philadelphia. That model focuses on (1) staying active, connected, and engaged; (2) development and housing; (3) transportation and mobility; and (4) staying healthy. Examples of practice efforts actualized using this research are also presented. By developing a new approach to the way research can support practice initiatives, AFP has been able to increase its effectiveness, and researchers have found better ways to work collaboratively with professionals in policy, planning, and practice. The PCA model should be considered as a framework for similar efforts aimed at creating age-friendly communities.

Is "Walkability" A Useful Concept for Gerontology?

The study tested two hypotheses. 1) In a walkable neighborhood, residents will exercise more, eat healthier, and suffer from less obesity. 2) That relation will be stronger for the elderly. Health was measured by physical activity, number of portions of fruits and vegetables eaten, and BMI. "Walkability" was measured by a set of environmental items that formed three distinct factors. The three health outcomes were related to the three environmental factors. Age was not a significant predictor. While environment does play a significant role in health outcomes the ways that role is expressed and its relation to age is complex.