Ronald T Ackermann

Biographic Data

ID5534043
NAMERonald T Ackermann
GIVEN NAMESRonald T
FAMILY NAMEAckermann
SIGNATUREACKERMANN R T
AFFILIATIONSIndiana University – Purdue University Indianapolis
ORCID0000-0002-4006-0070
VERIFIEDYes
TOTAL WORKS9
TOTAL CITATIONS3
WORKS AS AUTHOR9
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2004
LATEST PUBLICATION YEAR2026
H-INDEX1

  • Comparing Predictive Power of Area-Level Socioeconomic Status Indices Across Health Outcomes and Geographic Levels

    Francesco Maria Rossi, Lorenzo Franchi et al.ARTICLEMedical Care2026References: 39

    BACKGROUND: Many researchers want to control for both individual-level demographic/health variables and area-level socioeconomic status (area-SES) when studying health outcomes. However, comparative assessments of area-SES indices across geographic levels and a range of health outcomes are scarce. OBJECTIVES: Compare predictive power for 3 commonly used area-SES indices: the Graham Social Deprivation Index (SDI), the Area Deprivation Index (ADI),…

  • A Randomized Comparative Effectiveness Trial for Preventing Type 2 Diabetes

    Ronald T Ackermann, David T Liss et al.ARTICLEAmerican Journal of Public Health2015Cited by: 3References: 31

    Objectives. We evaluated the weight loss effectiveness of a YMCA model for the Diabetes Prevention Program (DPP) lifestyle intervention. Methods. Between July 2008 and November 2010, we individually randomized 509 overweight or obese, low-income, nondiabetic adults with elevated blood glucose in Indianapolis, Indiana, to receive standard care plus brief lifestyle counseling or be offered a group-based YMCA adaptation of the DPP (YDPP). Primary ou…

  • Perspectives on Prevention of Type 2 Diabetes After Gestational Diabetes

    Open AccessJoyce W Tang, Krys E Foster et al.ARTICLEMaternal and Child Health Journal2014

  • Impact of diagnosis of diabetes on health-related quality of life among high risk individuals

    Open AccessDavid G Marrero, Qing Pan et al.ARTICLEQuality of Life Research2013

  • Identifying Risk Factors for Racial Disparities in Diabetes Outcomes

    O Kenrik Duru, Robert B Gerzoff et al.ARTICLEMedical Care2009References: 29

    BACKGROUND: Versus whites, blacks with diabetes have poorer control of hemoglobin A1c (HbA1c), higher systolic blood pressure (SBP), and higher low-density lipoprotein (LDL) cholesterol as well as higher rates of morbidity and microvascular complications. OBJECTIVE: To examine whether several mutable risk factors were more strongly associated with poor control of multiple intermediate outcomes among blacks with diabetes than among similar whites.…

  • The Indiana Chronic Disease Management Program′s Impact on Medicaid Claims

    Barry P Katz, Ann M Holmes et al.ARTICLEMedical Care2009References: 12

    BACKGROUND: : Disease management programs have grown in popularity over the past decade as a strategy to curb escalating healthcare costs for persons with chronic diseases. OBJECTIVES: : To evaluate the effect of the Indiana Chronic Disease Management Program (ICDMP) on the longitudinal changes in Medicaid claims statewide. RESEARCH DESIGN: : Phased implementation of a chronic disease management program in 3 regions of the state. Fourteen repeate…

  • Understanding the Gap Between Good Processes of Diabetes Care and Poor Intermediate Outcomes

    Joe V Selby, Bix E Swain et al.ARTICLEMedical Care2007References: 44

    BACKGROUND: Performance of diabetes clinical care processes has improved recently, but control of hemoglobin A1c (A1c) and other vascular disease risk factors has improved more slowly. OBJECTIVES: To identify patient factors associated with control of vascular disease risk factors among diabetes patients receiving recommended care processes. POPULATION: Managed care enrollees who participated in the TRIAD (Translating Research into Action for Dia…

  • Indiana Chronic Disease Management Program Risk Stratification Analysis

    Jingjin Li, Ann M Holmes et al.ARTICLEMedical Care2005References: 8

    OBJECTIVE: The objective of this study was to compare the ability of risk stratification models derived from administrative data to classify groups of patients for enrollment in a tailored chronic disease management program. SUBJECTS: This study included 19,548 Medicaid patients with chronic heart failure or diabetes in the Indiana Medicaid data warehouse during 2001 and 2002. MEASURES: To predict costs (total claims paid) in FY 2002, we consider…

  • Good Diabetes Care

    Ronald T Ackermann, Paris Roach et al.ARTICLEMedical Care2004References: 10

    Ackermann, Ronald T. MD, MPH; Roach, Paris MD; Marrero, David G. PhD Author Information