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Arbor Research Collaborative for Health’s staff of clinicians, biostatisticians, and data managers conducts multidisciplinary studies in epidemiology and public health with the goal of improving patient outcomes. Our findings have led to better care for patients with chronic diseases and organ failure.
Arbor Research

Transforming Data into Knowledge Minimize/Maximize

We conduct the research behind important and difficult questions of health care policy, including allocation of scarce organs for transplantation and clinical practice opportunities to improve care for dialysis patients. Arbor Research is committed to improving patient lives through research. Large-scale prospective studies, original data collection, and analysis of existing databases are among the approaches we apply. Our analysts contribute at every step in these investigations, from study design and detailed biostatistical analysis to the identification of research implications for health care practice and policy. Close ties between Arbor Research and biostatisticians and clinicians at the University of Michigan bolster our ability to perform rigorous research.

Sharing Knowledge with Decisionmakers, Practitioners, and the Public Minimize/Maximize

Our research is directed toward practical outcomes, knowing how to ask the right questions to achieve useful evidence-based answers. Applied study of patient-level data can result in improved policy and practice; Arbor Research manages all the steps in this process, from study design to publication of results. Since 1997, we have published over 100 articles in peer-reviewed medical journals, addressing key matters of health care policy and clinical practice. Our investigators and analysts have contributed to the development of informed public policy by providing detailed research to federal agencies, medical societies and clinicians around the world.

Excellence in Data Management and Analysis Minimize/Maximize

Amassing and managing large data sets is at the heart of our work, through original data collection and integration of existing health databases. Sometimes the most valuable databases are geared toward function rather than research. Arbor Research has considerable experience adapting such databases, ranging from transplant waiting lists to Medicare billing data, for statistical outcomes research. When developing questionnaires, our clinicians and statisticians collaborate to ensure that data collection will be feasible, informative, and powerful. We work with both electronic and paper-based data collection systems, gathering information from a wide range of health care sources: doctors, technicians, nurses, insurers, and patients themselves. Arbor Research has created a flexible yet consistent online data entry platform that may be used in multiple languages and cultures. We also work extensively with national Medicare data and other private and public databases. Such integration can validate a study, increase its sample size, and enhance its statistical power.

Recent Publications and News

New President Appointed for Arbor Research
Robert M. Merion, M.D. succeeds Friedrich K. Port, M.D. M.S, as the third president of the Arbor Research Collaborative for Health, the organization’s Board of Directors announced in March.
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DOPPS Vascular Access Mortality Paper Published
Facility-based analyses diminish treatment-by-indication bias and suggest that less catheter and graft use improves patient survival.
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DOPPS Vitamin D Survival Advantage Paper Published
The association between vitamin D and mortality among DOPPS participants is assessed using standard regression and marginal structural models with an expanded set of covariates, as well as by instrumental variable models to account for potential bias due to unmeasured confounders. Based on route of vitamin D administration, no difference in mortality is observed.
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DOPPS Practice-Related Risk Score (PRS) Paper Published
The PRS assesses modifiable hemodialysis practices that are linked to improved patient survival.
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SRTR Re-Weighting The Model For End-Stage Liver Disease Score Components Paper Published
To determine whether the previously established weights assigned to the three components of the existing MELD formula optimally predict mortality risk, SRTR data for the liver waiting list was examined. A time-dependent analysis predicted waiting list mortality risk more accurately than a model based only on the MELD score at listing.
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SRTR Immunosuppression and Hepatitis C Paper Published
In kidney recipients with HCV-positive serology, the use of antibody induction did not negatively affect patient survival and the use of mycophenolate mofetil as part of maintenance immunosuppression was associated with better patient survival.
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Recent Publications and News



Arbor Research
Collaborative for Health


315 W. Huron St.
Suite 360
Ann Arbor, MI 48103
USA
Tel: +1 (734) 665-4108
Fax: +1 (734) 665-2103

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