Using claims data to predict dependency in activities of daily living as a proxy for frailty

Estimating drug effectiveness and safety among older adults in population-based studies using administrative health care claims can be hampered by unmeasured confounding as a result of frailty. A claims-based algorithm that identifies patients likely to be dependent, a proxy for frailty, may improve confounding control. Our objective was to develop an algorithm to predict dependency in activities of daily living (ADL) in a sample of Medicare beneficiaries. Methods: Community-dwelling respondents to the 2006 Medicare Current Beneficiary Survey, >65years old, with Medicare Part A, B, home health, and hospice claims were included. ADL dependency was defined as needing help with bathing, eating, walking, dressing, toileting, or transferring. Potential predictors were demographics, International Classification of Diseases, Ninth Revision Clinical Modification diagnosis/procedure and durable medical equipment codes for frailty-associated conditions. Multivariable logistic regression was used to predict ADL dependency. Cox models estimated hazard ratios for death as a function of observed and predicted ADL dependency. Results: Of 6391 respondents, 57% were female, 88% white, and 38% were ≥80. The prevalence of ADL dependency was 9.5%. Strong predictors of ADL dependency were charges for a home hospital bed (OR=5.44, 95%CI=3.28-9.03) and wheelchair (OR=3.91, 95%CI=2.78-5.51). The c-statistic of the final model was 0.845. Model-predicted ADL dependency of 20% or greater was associated with a hazard ratio for death of 3.19 (95%CI: 2.78, 3.68). Conclusions: An algorithm for predicting ADL dependency using health care claims was developed to measure some aspects of frailty. Accounting for variation in frailty among older adults could lead to more valid conclusions about treatment use, safety, and effectiveness

The coalition for conservation genetics: Working across organizations to build capacity and achieve change in policy and practice

Abstract The Coalition for Conservation Genetics (CCG) brings together four eminent organizations with the shared goal of improving the integration of genetic information into conservation policy and practice. We provide a historical context of conservation genetics as a field and reflect on current barriers to conserving genetic diversity, highlighting the need for collaboration across traditional divides, international partnerships, and coordinated advocacy. We then introduce the CCG and illustrate through examples how a coalition approach can leverage complementary expertise and improve the organizational impact at multiple levels. The CCG has proven particularly successful at implementing large synthesis-type projects, training early-career scientists, and advising policy makers. Achievements to date highlight the potential for the CCG to make effective contributions to practical conservation policy and management that no one “parent” organization could achieve on its own. Finally, we reflect on the lessons learned through forming the CCG, and our vision for the future