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Health services research methods

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136 papers 25 to 100 followers Drug and device development, pivotal clinical trials, post-market studies, quasi experimental research methods, registry trials , methods to reduce bias in analysis , trial / study design issues
By Jamie Jarmul Md / PhD student at UNC - Chapel Hill, PhD in Health Policy and Management
Deborah J Cohen, Bijal A Balasubramanian, Leah Gordon, Miguel Marino, Sarah Ono, Leif I Solberg, Benjamin F Crabtree, Kurt C Stange, Melinda Davis, William L Miller, Laura J Damschroder, K John McConnell, John Creswell
BACKGROUND: The Agency for Healthcare Research and Quality (AHRQ) launched the EvidenceNOW Initiative to rapidly disseminate and implement evidence-based cardiovascular disease (CVD) preventive care in smaller primary care practices. AHRQ funded eight grantees (seven regional Cooperatives and one independent national evaluation) to participate in EvidenceNOW. The national evaluation examines quality improvement efforts and outcomes for more than 1500 small primary care practices (restricted to those with fewer than ten physicians per clinic)...
2016: Implementation Science: IS
Hanna Choi, Jeongeun Kim, Ahjung Byun
This study was conducted on verifying whether variables such as prior health related behaviors, health literacy, interpersonal influence, perceived ease of use and usefulness of health information, and behavioral intention could predict actual health promoting behaviors of consumers using health information with mobile in the future. The research model was based on Technology Acceptance Model. Data were collected from 199 mobile health information seekers. Participants' actual health promoting behaviors were checked after 3 months from pre-data collection...
2016: Studies in Health Technology and Informatics
Rachel Grob, Mark Schlesinger, Andrew M Parker, Dale Shaller, Lacey Rose Barre, Steven C Martino, Melissa L Finucane, Lise Rybowski, Jennifer L Cerully
OBJECTIVE: To design a methodology for rigorously eliciting narratives about patients' experiences with clinical care that is potentially useful for public reporting and quality improvement. DATA SOURCES/STUDY SETTING: Two rounds of experimental data (N = 48 each) collected in 2013-2014, using a nationally representative Internet panel. STUDY DESIGN: Our study (1) articulates and operationalizes criteria for assessing narrative elicitation protocols; (2) establishes a "gold standard" for assessment of such protocols; and (3) creates and tests a protocol for narratives about outpatient treatment experiences...
June 2016: Health Services Research
Krysta Johnson-Martinez, Rebecca Wheeler, Carolyn Clevenger, Anne Tomolo
No abstract text is available yet for this article.
September 2016: American Journal of Medical Quality: the Official Journal of the American College of Medical Quality
Hannah T Neprash, Jacob Wallace, Michael E Chernew, J Michael McWilliams
OBJECTIVE: To compare methods of price measurement in health care markets. DATA SOURCES: Truven Health Analytics MarketScan commercial claims. STUDY DESIGN: We constructed medical prices indices using three approaches: (1) a "sentinel" service approach based on a single common service in a specific clinical domain, (2) a market basket approach, and (3) a spending decomposition approach. We constructed indices at the Metropolitan Statistical Area level and estimated correlations between and within them...
December 2015: Health Services Research
Sara Geneletti, Aidan G O'Keeffe, Linda D Sharples, Sylvia Richardson, Gianluca Baio
The regression discontinuity (RD) design is a quasi-experimental design that estimates the causal effects of a treatment by exploiting naturally occurring treatment rules. It can be applied in any context where a particular treatment or intervention is administered according to a pre-specified rule linked to a continuous variable. Such thresholds are common in primary care drug prescription where the RD design can be used to estimate the causal effect of medication in the general population. Such results can then be contrasted to those obtained from randomised controlled trials (RCTs) and inform prescription policy and guidelines based on a more realistic and less expensive context...
July 10, 2015: Statistics in Medicine
Scott D Ramsey, Richard J Willke, Henry Glick, Shelby D Reed, Federico Augustovski, Bengt Jonsson, Andrew Briggs, Sean D Sullivan
Clinical trials evaluating medicines, medical devices, and procedures now commonly assess the economic value of these interventions. The growing number of prospective clinical/economic trials reflects both widespread interest in economic information for new technologies and the regulatory and reimbursement requirements of many countries that now consider evidence of economic value along with clinical efficacy. As decision makers increasingly demand evidence of economic value for health care interventions, conducting high-quality economic analyses alongside clinical studies is desirable because they broaden the scope of information available on a particular intervention, and can efficiently provide timely information with high internal and, when designed and analyzed properly, reasonable external validity...
March 2015: Value in Health: the Journal of the International Society for Pharmacoeconomics and Outcomes Research
Xiaomin Wan, Liubao Peng, Yuanjian Li
BACKGROUND: In general, the individual patient-level data (IPD) collected in clinical trials are not available to independent researchers to conduct economic evaluations; researchers only have access to published survival curves and summary statistics. Thus, methods that use published survival curves and summary statistics to reproduce statistics for economic evaluations are essential. Four methods have been identified: two traditional methods 1) least squares method, 2) graphical method; and two recently proposed methods by 3) Hoyle and Henley, 4) Guyot et al...
2015: PloS One
Michal Horný, Jake R Morgan, Vanessa L Merker
OBJECTIVE: To quantify changes in private insurance payments for and utilization of abdominal/pelvic computed tomography scans (CTs) after 2011 changes in CPT coding and Medicare reimbursement rates, which were designed to reduce costs stemming from misvalued procedures. DATA SOURCES: TruvenHealth Analytics MarketScan Commercial Claims and Encounters database. STUDY DESIGN: We used difference-in-differences models to compare combined CTs of the abdomen/pelvis to CTs of the abdomen or pelvis only...
December 2015: Health Services Research
Robert Weech-Maldonado, Marc N Elliott, John L Adams, Amelia M Haviland, David J Klein, Katrin Hambarsoomian, Carol Edwards, Jacob W Dembosky, Sarah Gaillot
OBJECTIVE: To examine how similar racial/ethnic disparities in clinical quality (Healthcare Effectiveness Data and Information Set [HEDIS]) and patient experience (Consumer Assessment of Healthcare Providers and Systems [CAHPS]) measures are for different measures within Medicare Advantage (MA) plans. DATA SOURCES/STUDY SETTING: 5.7 million/492,495 MA beneficiaries with 2008-2009 HEDIS/CAHPS data. STUDY DESIGN: Binomial (HEDIS) and linear (CAHPS) hierarchical mixed models generated contract estimates for HEDIS/CAHPS measures for Hispanics, blacks, Asian-Pacific Islanders, and whites...
December 2015: Health Services Research
Robert W Grundmeier, Lihai Song, Mark J Ramos, Alexander G Fiks, Marc N Elliott, Allen Fremont, Wilson Pace, Richard C Wasserman, Russell Localio
OBJECTIVE: To assess the utility of imputing race/ethnicity using U.S. Census race/ethnicity, residential address, and surname information compared to standard missing data methods in a pediatric cohort. DATA SOURCES/STUDY SETTING: Electronic health record data from 30 pediatric practices with known race/ethnicity. STUDY DESIGN: In a simulation experiment, we constructed dichotomous and continuous outcomes with pre-specified associations with known race/ethnicity...
August 2015: Health Services Research
Linnea A Polgreen, Elizabeth A Cook, John M Brooks, Yuexin Tang, Philip M Polgreen
BACKGROUND: Investigators have attributed protective effects of statins against pneumonia and other infections. However, these reports are based on observational data where treatments are not assigned randomly. We aimed to determine if the protective effects of statins against pneumonia are due to nonrandom treatment assignment. METHODS: We built a cohort consisting of 124 695 Medicare beneficiaries diagnosed with an acute myocardial infarction (AMI) for which we had complete claims data...
June 15, 2015: Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America
Tom Loney, Nico J Nagelkerke
The validity of ecological studies in epidemiology for inferring causal relationships has been widely challenged as observed associations could be biased by the Ecological Fallacy. We reconsider the important design components of ecological studies, and discuss the conditions that may lead to spurious associations. Ecological associations are useful and valid when the ecological exposures can be interpreted as Instrumental Variables. A suitable example may be a time series analysis of environmental pollution (e...
2014: Emerging Themes in Epidemiology
Seongho Kim, Elisabeth Heath, Lance Heilbrun
Although the sample size for simple logistic regression can be readily determined using currently available methods, the sample size calculation for multiple logistic regression requires some additional information, such as the coefficient of determination ([Formula: see text]) of a covariate of interest with other covariates, which is often unavailable in practice. The response variable of logistic regression follows a logit-normal distribution which can be generated from a logistic transformation of a normal distribution...
March 4, 2015: Statistical Methods in Medical Research
Ji Lin, Robert H Lyles
We explore the 'reassessment' design in a logistic regression setting, where a second wave of sampling is applied to recover a portion of the missing data on a binary exposure and/or outcome variable. We construct a joint likelihood function based on the original model of interest and a model for the missing data mechanism, with emphasis on non-ignorable missingness. The estimation is carried out by numerical maximization of the joint likelihood function with close approximation of the accompanying Hessian matrix, using sharable programs that take advantage of general optimization routines in standard software...
May 20, 2015: Statistics in Medicine
Signe M Jensen, Christian B Pipper, Christian Ritz
Evaluation of intervention effects on multiple outcomes is a common scenario in clinical studies. In longitudinal studies, such evaluation is a challenge if one wishes to adequately capture simultaneous data behavior. In this situation, a common approach is to analyze each outcome separately. As a result, multiple statistical statements describing the intervention effect need to be reported and an adjustment for multiple testing is necessary. This is typically done by means of the Bonferroni procedure, which does not take into account the correlation between outcomes, thus resulting in overly conservative conclusions...
May 30, 2015: Statistics in Medicine
Ali Mirzazadeh, Mohsen Malekinejad, James G Kahn
OBJECTIVES: Heterogeneity of effect measures in intervention studies undermines the use of evidence to inform policy. Our objective was to develop a comprehensive algorithm to convert all types of effect measures to one standard metric, relative risk reduction (RRR). STUDY DESIGN AND SETTING: This work was conducted to facilitate synthesis of published intervention effects for our epidemic modeling of the health impact of human immunodeficiency virus [HIV testing and counseling (HTC)]...
March 2015: Journal of Clinical Epidemiology
Monique L Anderson, Robert M Califf, Jeremy Sugarman
Cluster randomized trials randomly assign groups of individuals to examine research questions or test interventions and measure their effects on individuals. Recent emphasis on quality improvement, comparative effectiveness, and learning health systems has prompted expanded use of pragmatic cluster randomized trials in routine health-care settings, which in turn poses practical and ethical challenges that current oversight frameworks may not adequately address. The 2012 Ottawa Statement provides a basis for considering many issues related to pragmatic cluster randomized trials but challenges remain, including some arising from the current US research and health-care regulations...
June 2015: Clinical Trials: Journal of the Society for Clinical Trials
Francisco J Diaz, Hung-Wen Yeh, Jose de Leon
Some empirical studies and recent developments in pharmacokinetic theory suggest that statistical random-effects linear models are valuable tools that allow describing simultaneously patient populations as a whole and patients as individuals. This remarkable characteristic indicates that these models may be useful in the development of personalized medicine, which aims at finding treatment regimes that are appropriate for particular patients, not just appropriate for the average patient. In fact, published developments show that random-effects linear models may provide a solid theoretical framework for drug dosage individualization in chronic diseases...
March 2012: Current Pharmacogenomics and Personalized Medicine
Andrea J Apter
No abstract text is available yet for this article.
April 2015: JAMA Pediatrics
2015-02-14 19:22:52
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