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Dive into the research topics where Gerhardt Pohl is active.

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Featured researches published by Gerhardt Pohl.


Current Medical Research and Opinion | 2007

Short-term economic impact of body weight change among patients with type 2 diabetes treated with antidiabetic agents: analysis using claims, laboratory, and medical record data

Andrew P. Yu; Eric Q. Wu; Howard G. Birnbaum; Srinivas Emani; Madeleine Fay; Gerhardt Pohl; Matthew Wintle; Elaine Yang; Alan Oglesby

ABSTRACT Background: Obesity is highly prevalent among patients with type 2 diabetes. Unfortunately, weight gain may also be a consequence of some antidiabetic medications. Although clinical benefits of weight loss have been established, the economic consequence of weight change among patients with type 2 diabetes is unclear. Objectives: The objective was to measure 1‑year total and diabetes-related health care costs associated with weight change during the preceding 6‑month period among type 2 diabetic patients on antidiabetic therapy. Methods: Administrative claims, electronic laboratory data and medical chart information were abstracted for continuously enrolled adults with type 2 diabetes from an health maintenance organization (HMO) for the period from July 1, 1997 through October 31, 2005. To assess the economic impact of weight change, three regression models were applied to estimate the following: (1) the effect of weight change in general (one-slope model); (2) the different effects of weight gain and no weight gain(two-slope model); and (3) the different effects of weight gain and no weight gain (i.e., no change or weight loss) among obese and non-obese patients (four-slope model). Patients included in the study had a baseline weight measurement and a second weight measurement approximately 6 months later. They were also required to be on at least one antidiabetic drug therapy within 1 month around the baseline weight measurement date (index date). Based on the measured weight change, patients were classified into two groups – weight gainers and non-weight gainer. Total health care cost and diabetes-related cost were measured during the 1‑year period following the second weight measurement and were adjusted to 2004 dollars by the medical component of the Consumer Price Index (CPI). Generalized linear models with log link function and gamma distribution were applied to assess the impacts of weight change on the 1‑year total health care cost as well as 1‑year diabetes-related cost. All models controlled for patients’ baseline demographics, comorbidities, body mass index (BMI), glycosylated hemoglobin (HbA1c), and prior resource utilization. Results: The study included 458 patients, of whom 224 (48.9%) experienced minimum weight gain of 1 pound between the two weight measurements. The average 1‑year total health care cost following the second weight measure was


Chemotherapy Research and Practice | 2012

Healthcare Costs and Workloss Burden of Patients with Chemotherapy-Associated Peripheral Neuropathy in Breast, Ovarian, Head and Neck, and Nonsmall Cell Lung Cancer

Crystal Pike; Howard G. Birnbaum; Catherine Muehlenbein; Gerhardt Pohl; Ronald B. Natale

6382 and the diabetes-related cost was


BMC Health Services Research | 2009

A retrospective claims analysis of combination therapy in the treatment of adult attention-deficit/hyperactivity disorder (ADHD)

Gerhardt Pohl; David L. Van Brunt; Wenyu Ye; William W. Stoops; Joseph A. Johnston

2002. The mean total health care cost was


PLOS ONE | 2014

Survival Patterns in United States (US) Medicare Enrollees with Non-CML Myeloproliferative Neoplasms (MPN)

Gregory L Price; Keith L. Davis; Sudeep Karve; Gerhardt Pohl; Richard A. Walgren

7260 for the weight-gainers and


Pharmacotherapy | 2005

Predictors of Selecting Atomoxetine Therapy for Children with Attention-Deficit—Hyperactivity Disorder

David L. Van Brunt; Joseph A. Johnston; Wenyu Ye; Gerhardt Pohl; Pei J. Sun; Kimberly L. Sterling

5541 for the non-weight gainers ( p = 0.046), and the mean diabetes-related cost, respectively, was


BMC Health Services Research | 2014

Comparison of demographics, treatment patterns, health care utilization, and costs among elderly patients with extensive-stage small cell and metastatic non-small cell lung cancers:

Sudeep J Karve; Gregory L Price; Keith L. Davis; Gerhardt Pohl; Emily Nash Smyth; Lee Bowman

2141 and


BMC Women's Health | 2008

Characteristics of patients initiating raloxifene compared to those initiating bisphosphonates

Kathleen A. Foley; Eric S. Meadows; Joseph A. Johnston; Sara Wang; Gerhardt Pohl; Stacey R. Long

1869 ( p = 0.006). Results from the models showed that one percentage point of weight change was positively associated with a 3.1% (


Cancer | 2011

A review and characterization of the various perceptions of quality cancer care

Ann Colosia; Gerson Peltz; Gerhardt Pohl; Esther Liu; Kati Copley‐Merriman; Shahnaz Khan; James A. Kaye

213, p < 0.01) change in total health care cost. When weight gain and no gain were modeled separately, one percentage point of weight loss was associated with a 3.6% (


Journal of Occupational and Environmental Medicine | 2010

Illness-associated productivity costs among women with employer-sponsored insurance and newly diagnosed breast cancer.

Eric S. Meadows; Stephen S. Johnston; Zhun Cao; Kathleen A. Foley; Gerhardt Pohl; Joseph A. Johnston; Scott D. Ramsey

256, p < 0.05) decrease in total health care cost and a 5.8% (


Journal of Osteoporosis | 2011

Factors Associated with Persistence with Teriparatide Therapy: Results from the DANCE Observational Study.

Deborah T. Gold; David L. Weinstein; Gerhardt Pohl; Kelly Krohn; Yi Chen; Eric S. Meadows

131, p < 0.01) decrease in diabetes-related cost. However, one percentage point of weight gain was not associated with significant increase in either total health care or diabetes-related cost. Further, results from the model with interactions between weight change and obesity status revealed that the economic benefit of weight loss was more pronounced in the obese group (BMI ≥ 30). Log likelihood ratio tests showed that the one-slope model for total health care cost and the two-slope model for diabetes-related cost are the appropriate models of choice. Conclusions: Weight loss significantly reduced diabetes-related costs. Controlling for baseline factors in the regression model, the 1‑year total health care cost following 1% weight loss (or gain) was

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Edward J. Stepanski

Rush University Medical Center

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Lee S. Schwartzberg

University of Tennessee Health Science Center

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