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Dive into the research topics where Joseph W. Thompson is active.

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Featured researches published by Joseph W. Thompson.


The New England Journal of Medicine | 2009

The Public Health and Economic Benefits of Taxing Sugar-Sweetened Beverages

Kelly D. Brownell; Thomas Farley; Walter C. Willett; Barry M. Popkin; Frank J. Chaloupka; Joseph W. Thompson; David S. Ludwig

Consumption of sugar-sweetened beverages has increased in recent decades; evidence suggests that consumption of these beverages contributes to obesity and adverse health outcomes. The authors discuss the potential public health and economic benefits of taxing sugar-sweetened beverages.


Medical Care | 2002

Using telephone interviews to reduce nonresponse bias to mail surveys of health plan members.

Floyd J. Fowler; Patricia M. Gallagher; Vickie L. Stringfellow; Alan M. Zaslavsky; Joseph W. Thompson; Paul D. Cleary

Objective. To assess the nonresponse bias associated with mail-survey returns and the potential for telephone interviews with nonrespondents to reduce that bias. Methods. A mail survey about health care experiences was conducted with samples of 800 members in each of four health plans. Subsequent attempts were made to interview nonrespondents by telephone. Results. Response rates for the mail surveys averaged 46%; the telephone effort raised the average to 66%. On 17 of 19 measures of health status or need and use of health services, mail respondents were in poorer health and needed more services than interviewed nonrespondents. Thirteen of 36 reports and ratings of health care also differed significantly between the two groups. Based on administrative data, telephone interviews of mail nonrespondents improved the demographic representativeness of the responding samples. Adjusting mail returns to sample population characteristics could not replicate the dual-mode results. Conclusions. Returns to mail surveys are likely to be related to survey content and hence are potentially biased. Nonresponse to phone surveys is less directly related to survey content. Telephone interviews with mail nonrespondents not only increase response rates but also can produce less biased samples than mail-only protocols.


Medical Care | 2000

Impact of sociodemographic case mix on the HEDIS measures of health plan quality.

Alan M. Zaslavsky; John N. Hochheimer; Eric C. Schneider; Paul D. Cleary; Joshua J. Seidman; Elizabeth A. McGlynn; Joseph W. Thompson; Cary Sennett; Arnold M. Epstein

Background.The widely used Health Plan Employer Data and Information Set (HEDIS) measures may be affected by differences among plans in sociodemographic characteristics of members. Objective.The objective of this study was to estimate effects of geographically linked patient sociodemographic characteristics on differential performance within and among plans on HEDIS measures. Research Design.Using logistic regression, we modeled associations between age, sex, and residential area characteristics of health plan members and results on HEDIS measures. We then calculated the impact of adjusting for these associations on plan-level measures. Subjects.This study included 92,232 commercially insured members with individual-level HEDIS data and an additional 20,615 members whose geographic distribution was provided. Measures.This study used 7 measures of screening and preventive services. Results.Performance was negatively associated with percent receiving public assistance in the local area (6 of 7 measures), percent black (5 measures), and percent Hispanic (2 measures) and positively associated with percent college educated (6 measures), percent urban (2 measures), and percent Asian (1 measure) after controlling for plan and product type. These effects were generally consistent across plans. When measures were adjusted for these characteristics, rates for most plans changed by less than 5 percentage points. The largest change in the difference between plans ranged from 1.5% for retinal exams for people with diabetes to 20.2% for immunization of adolescents. Conclusions.Performance on quality indicators for individual members is associated with sociodemographic context. Adjustment has little impact on the measured performance of most plans but a substantial impact on a few. Further study with more plans is required to determine the appropriateness and feasibility of adjustment.


American Journal of Preventive Medicine | 2000

Measuring immunization coverage

Gerry Fairbrother; Gary L. Freed; Joseph W. Thompson

OBJECTIVE Information about immunization coverage comes from five major sources: the National Immunization Survey, the National Health Interview Survey, retrospective school-entry surveys, the Health Plan Employer Data and Information Set (HEDIS) measures reported by managed care plans, and assessments performed on clinics and private practices. In this article, we describe the methodology of the major surveys, discuss technical and policy issues in measuring immunization coverage, and identify issues that must be addressed to harmonize immunization rates calculated from different sources. METHODS AND TOPICS We describe the (1) design and methodology of the five major sources of immunization coverage assessments, (2) issues and controversies in measuring immunization coverage, and (3) preliminary efforts to harmonize calculation of immunization coverage. Technical and policy issues involve dose and interval requirements, which vaccines are included in the series-completion calculations, and who is excluded from each method of calculation. CONCLUSIONS The purpose of measuring up-to-date immunization coverage determines the way that it is measured. The tension between measuring immunization coverage to monitor population protection against disease and measuring immunization coverage to determine how well the health care delivery system is working leads to different ways of selecting a sample and reporting coverage. These differences create confusion for the public policymakers who try to identify problems and to set priorities for immunization efforts. Although some unavoidable differences may occur because of differences in purpose of the measurement, greater harmonization is possible.


Medical Care | 2000

Tracking clinical preventive service use: a comparison of the health plan employer data and information set with the behavioral risk factor surveillance system.

Sharon A. Bloom; Jeffrey R. Harris; Betsy L. Thompson; Faruque Ahmed; Joseph W. Thompson

BACKGROUND There is a need for meaningful and accurate ways of tracking preventive service delivery among different sectors of the US population. OBJECTIVES To compare methodologies of and clinical preventive service use estimates obtained from 2 data sets: the Health Plan Employer Data and Information Set (HEDIS 3.0) and the Behavioral Risk Factor Surveillance System (BRFSS). METHODS HEDIS used a combination of mailed-survey, administrative, and medical-record data to measure preventive service use among commercial enrollees of 320 HMOs in 42 states during 1996. BRFSS data are from insured respondents (excluding those reporting Medicare or Medicaid coverage) to a random-digit-dialed telephone survey conducted in the same 42 states during 1996. RESULTS The median state-specific mammography, Papanicolaou smear, and retinal examination rates reported by HEDIS were consistently and substantially lower than those reported by BRFSS. For mammography, the median HEDIS rate was 72.4%, compared with 81.1% for BRFSS. For Papanicolaou smear and retinal examinations, HEDIS rates were 72.7% and 40.8%, respectively, compared with 91.2% and 61.6% for BRFSS. The median state rates of advice to quit smoking reported by HEDIS were similar to those for BRFSS: 62.1% versus 62.2%, respectively. For each measure, the absolute difference between HEDIS and BRFSS rates varied substantially both within a state and between states. CONCLUSIONS It does not appear that the BRFSS and HEDIS data can be compared directly to accurately track progress toward national preventive health objectives. This study highlights some of the problems with comparing these data and possible means for addressing the discrepancies.


Drug Safety | 1993

Adverse effects of newer cephalosporins. An update.

Joseph W. Thompson; Richard F. Jacobs

Summarywhile classifications into generations according to antimicrobial activity has helped clinicians incorporate the increasing number of cephalosporins into their pharmacological repertoire, adverse effects among the different agents fail to follow similar categories. In general, cephalosporins are fairly well tolerated antibiotics, and toxicity has been limited to specific agents. Subtle differences in chemical structure and pharmacokinetics can influence the potential for adverse effects. The route of administration may result in minor adverse reactions, including thrombophlebitis and pain. The most common adverse effects of cephalosporins are allergic reactions, occurring in 0.9 to 3.2% of patients. Cephalosporins have very rarely been associated with haematological toxicity (less than 1% of patients), but specific agents have been associated with neutropenia, hypoprothrombinaemia, haemolytic anaemia, and problems with platelet production and function. Other reactions include localised gastrointestinal disturbances, hepatotoxicity (e.g. biliary sludging), nephrotoxicity and mild central nervous system effects. The cephalosporins are generally well tolerated in the paediatric population. Very few interactions have been observed between cephalosporins and other drugs, largely because cephalosporins do not affect the microsomal P450 hepatic enzyme system. While cephalosporins are considered to be relatively ‘safe’ drugs, the introduction of newer members warrants continued careful observation for reporting of adverse drug reactions.


JAMA Pediatrics | 2009

Poor performance of body mass index as a marker for hypercholesterolemia in children and adolescents.

Joyce M. Lee; Achamyeleh Gebremariam; Paula Card-Higginson; Jennifer L. Shaw; Joseph W. Thompson; Matthew M. Davis

OBJECTIVE To evaluate the test performance of specific body mass index (BMI) percentile cutoffs for detecting children/adolescents with hypercholesterolemia. DESIGN Cross-sectional analysis. SETTING National Health and Nutrition Examination Survey 1999-2004. PARTICIPANTS Population-based sample of children (aged 3-18 years) with nonfasting total cholesterol (TC) and high-density lipoprotein (HDL) cholesterol levels and adolescents (aged 12-18 years) with fasting low-density lipoprotein (LDL) cholesterol and triglyceride (TG) levels. MAIN OUTCOME MEASURES Individuals were classified as having hypercholesterolemia if they had a TC level greater than 200 mg/dL, HDL cholesterol level less than 35 mg/dL, LDL cholesterol level greater than 130 mg/dL, or TG level greater than 150 mg/dL, and sensitivity, specificity, and likelihood ratios were calculated for specific BMI percentiles. Receiver operating characteristic curves were constructed and area under the curve (AUC) was calculated. RESULTS Receiver operating characteristic curves using BMI percentiles to predict abnormal levels of TC and LDL cholesterol had AUC values (0.60 for TC level and 0.63 for LDL cholesterol level) that were less than the threshold of acceptable discrimination (between 0.7-0.8). Body mass index percentiles provided better discrimination for detecting children with abnormal HDL cholesterol and TG levels, with AUC values approaching levels of acceptable discrimination (0.69 and 0.72, respectively), although there are no specific guidelines regarding management of children with these abnormalities. CONCLUSIONS According to the American Academy of Pediatrics guidelines, abnormal levels of LDL cholesterol are used to determine which children require nutritional and pharmacologic therapy. Because BMI percentiles did not adequately identify children and adolescents with abnormal TC and LDL cholesterol levels, the new recommendations for targeted screening of obese children and adolescents may require further consideration.


Obstetrics & Gynecology | 1998

Cost-Effectiveness of Mandatory Compared With Voluntary Screening for Human Immunodeficiency Virus in Pregnancy ☆

Evan R. Myers; Joseph W. Thompson; Kit Simpson

Objective To determine the cost-effectiveness of mandatory screening for human immunodeficiency virus (HIV) in pregnancy compared with that of voluntary screening under varying assumptions about patient behavior. Methods Using a health care system perspective, a decision-analysis model was constructed to estimate the outcomes and costs of the two strategies. Average and incremental cost-effectiveness ratios were calculated for each strategy. Sensitivity analyses were performed to test the effects of different values on the results of the simulation. In particular, we examined the potential effects of changes in patient behavior resulting from mandatory screening on our estimates of cost-effectiveness. Results At a prevalence of 170 per 100,000, average costs per case prevented were


American Journal of Preventive Medicine | 2003

Health plan quality-of-care information is undermined by voluntary reporting

Joseph W. Thompson; Sathiska D. Pinidiya; Kevin W. Ryan; Elizabeth D McKinley; Shannon Alston; James E. Bost; Jessica Briefer French; Pippa Simpson

255,158 and


American Journal of Preventive Medicine | 2009

Self-Reported Health Risks Linked to Health Plan Cost and Age Group

Rhonda K. Hill; Joseph W. Thompson; Jennifer L. Shaw; Sathiska D. Pinidiya; Paula Card-Higginson

367,998 for mandatory and voluntary screening, respectively. The incremental cost-effectiveness of mandatory compared with voluntary screening was

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Kevin W. Ryan

University of Arkansas for Medical Sciences

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Paula Card-Higginson

University of Arkansas for Medical Sciences

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James E. Bost

University of Pittsburgh

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Richard F. Jacobs

University of Arkansas for Medical Sciences

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Sathiska D. Pinidiya

University of Arkansas for Medical Sciences

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Shirley Tyson

University of Arkansas for Medical Sciences

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Jennifer L. Shaw

University of Arkansas for Medical Sciences

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Cary Sennett

National Committee for Quality Assurance

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Elizabeth D McKinley

Case Western Reserve University

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