Showing papers in "Medical Care in 2006"
TL;DR: A nested hierarchy of hypotheses is tested that addresses the cross-group invariance of the instrument's psychometric properties, including configural, metric (or pattern), strong (or scalar), and strict factorial invariance.
Abstract: Comparative public health research makes wide use of self-report instruments. For example, research identifying and explaining health disparities across demographic strata may seek to understand the health effects of patient attitudes or private behaviors. Such personal attributes are difficult or impossible to observe directly and are often best measured by self-reports. Defensible use of self-reports in quantitative comparative research requires not only that the measured constructs have the same meaning across groups, but also that group comparisons of sample estimates (eg, means and variances) reflect true group differences and are not contaminated by group-specific attributes that are unrelated to the construct of interest. Evidence for these desirable properties of measurement instruments can be established within the confirmatory factor analysis (CFA) framework; a nested hierarchy of hypotheses is tested that addresses the cross-group invariance of the instrument's psychometric properties. By name, these hypotheses include configural, metric (or pattern), strong (or scalar), and strict factorial invariance. The CFA model and each of these hypotheses are described in nontechnical language. A worked example and technical appendices are included.
728 citations
TL;DR: The purpose of this essay is to review the definitions and assumptions associated with factorial invariance, placing this formulation in the context of bias, fairness, and equity.
Abstract: Background:Analysis of subgroups such as different ethnic, language, or education groups selected from among a parent population is common in health disparities research. One goal of such analyses is to examine measurement equivalence, which includes both qualitative review of the meaning of items a
572 citations
TL;DR: The Internet-based CDSMP proved effective in improving health statutes by 1 year and is a viable alternative to the small-group Chronic Disease Self Management Program.
Abstract: Background:The small-group Chronic Disease Self-Management Program (CDSMP) has proven effective in changing health-related behaviors and improving health statuses. An Internet-based CDSMP was developed to reach additional chronic-disease patients.Objectives:We sought to determine the efficacy of the
471 citations
TL;DR: Effective ART regimens have substantially improved survival and have increased the lifetime cost of HIV-related medical care in the U.S.
Abstract: Objective:We sought to project the lifetime cost of medical care for human immunodefiency virus (HIV)-infected adults using current antiretroviral therapy (ART) standards.Methods:Medical visits and hospitalizations for any reason were from the HIV Research Network, a consortium of high-volume HIV pr
431 citations
TL;DR: The assumptions and concepts underlying CTT are discussed, including item and scale characteristics that derive from CTT as well as types of reliability and validity.
Abstract: Classical test theory (CTT) comprises a set of concepts and methods that provide a basis for many of the measurement tools currently used in health research. The assumptions and concepts underlying CTT are discussed. These include item and scale characteristics that derive from CTT as well as types of reliability and validity. Procedures commonly used in the development of scales under CTT are summarized, including factor analysis and the creation of scale scores. The advantages and disadvantages of CTT, its use across populations, and its continued use in the face of more recent measurement models are also discussed.
424 citations
TL;DR: The transition to ICD-10 has occurred with no loss of data quality, with data showing a high level of reliability and adherence to coding standards, and administrative data can provide highly reliable population-based estimates of hospitalization rates.
Abstract: Objectives:The International Classification of Disease, 10th Revision (ICD-10) was introduced worldwide beginning in the late 1990s. Because there have been no published data on the quality of coding using ICD-10, the aim of our analysis is to assess the quality of ICD-10 coding in routinely collect
355 citations
TL;DR: Interventions that included team change as a QI strategy were associated with the largest reductions in blood pressure outcomes and a focus on hypertension by someone in addition to the patient's physician was associated with substantial improvement.
Abstract: Background:Care remains suboptimal for many patients with hypertension.Purpose:The purpose of this study was to assess the effectiveness of quality improvement (QI) strategies in lowering blood pressure.Data Sources:MEDLINE, Cochrane databases, and article bibliographies were searched for this study
310 citations
TL;DR: VACS has assembled a rich, in-depth, and representative sample of veterans in care with and without HIV infection to conduct longitudinal analyses of questions concerning the association between alcohol use and related comorbid and AIDS-defining conditions.
Abstract: The Veterans Aging Cohort Study (VACS) is a longitudinal, prospective multisite observational study of human immunodeficiency virus (HIV) infected and uninfected patients seen in Veterans Administration Medical Center (VAMC) infectious disease and general medical clinics. VACS includes the earlier 3 and 5 site studies (VACS 3 and VACS 5) as well as the ongoing 8 site study. All patients included have provided written consent. It is focused on the role of alcohol use, abuse, and dependence on HIV infection in the larger context of aging, comorbid disease, and long-term antiretroviral treatment. VACS is funded by the National Institute on Alcohol Abuse and Alcoholism at the National Institutes of Health and is in its 7th year (Fig. 1).
FIGURE 1
Veterans Aging Cohort Studies Timeline.
Begun in 1999 as a 3-site study of 881 veterans with HIV infection (Fig. 1, VACS 3), VACS expanded to 5 sites (VACS 5) and added HIV-uninfected age–race–site group matched veteran comparators in 2001 with support from National Institute on Aging and National Institute for Mental Health. VACS 3 and VACS 5 were focused on comorbidity and behaviors that we hypothesized would affect outcomes in HIV. Major strengths of these studies were the predominance of black and or Latino/a (approximately 70–80% of all VACS samples) and their older age (median age ~50 years). The combination of older individuals and racial and ethnic diversity allowed us to begin to understand how comorbidity and behavior impact outcomes as individuals of different racial and ethnic backgrounds age with HIV infection.
As part of these early studies, we included the Alcohol Use Disorders Identification Test (AUDIT), a self-completed screening measure for hazardous alcohol use.1 Using this measure, we were impressed by the prevalence of hazardous drinking and applied to National Institutes of Health for funds to support further work in this area. VACS initially received 5 years of funding from the National Institute on Alcohol Abuse and Alcoholism in September of 2001 to study the association of alcohol with patient outcomes among those with and without HIV infection. Additional funding in 2002 and 2003 allowed VACS to expand to 8 sites and to plan and initiate full-scale blood and DNA banking. A renewal application for 5 more years of funding support is currently under review.
VACS and the virtual cohort (described in a separate report in this supplement) are built on the substantial infrastructure in place within the VA Healthcare System with direct access to all electronic medical records (EMRs) and administrative data (Fig. 2). These data has been supplemented with patient and provider surveys, in-depth telephone interviews, blood and DNA banking, neuropsychiatric testing, and patient and provider focus groups. The availability of multiple sources of data has allowed us to conduct extensive validation studies of EMR and administrative data sources.
FIGURE 2
Data sources available in VACS.
Our short-term objective is to compare differences in outcomes associated with alcohol use, comorbid conditions, and treatment toxicity in veterans with and without HIV disease. Because alcohol use is common among those with HIV infection, the role of alcohol is a major focus. Our long-term objective is to use these data and the EMR to design and implement effective interventions to improve outcomes among patients with HIV infection. These interventions will include computer-supported assessment of individualized risk and preferences, which will in turn inform intervention prioritization, including motivational interviewing and cognitive behavioral therapy. This report summarizes the history, design, data sources, and data elements used in the VACS.
305 citations
TL;DR: It is demonstrated that dissatisfied physicians were 2 to 3 times more likely to leave medicine than satisfied physicians, and these findings have implications for physician manpower projections and quality of care.
Abstract: Background:During the past decade, a confluence of forces has changed the practice of medicine in unprecedented ways. Anecdotal reports suggest that, in response, some physicians are leaving the practice of medicine or retiring earlier than they otherwise would have.Objective:We sought to examine ho
288 citations
TL;DR: Good concordance was found between survey and medical records overall, but there was substantial variation within and across domains, and quality ratings are likely to vary in differing directions, depending on the data source used.
Abstract: Background: The validity of quality of care assessments relies upon data quality, yet little is known about the relative completeness and validity of data sources for evaluating the quality of care. Objectives: We evaluated concordance between ambulatory medical record and patient survey data. Levels of concordance, variations by type of item, sources of disagreement between data sources, and implications for quality of care assessment efforts are discussed. Design and Subjects: This was an observational study that included 1270 patients sampled from 39 West Coast medical organizations with at least 1 of the following: diabetes, ischemic heart disease, asthma or chronic obstructive pulmonary disease, or low back pain. Measures: Items from both data sources were grouped into 4 conceptual domains: diagnosis, clinical services delivered, counseling and referral, and medication use. We present total agreement, kappa, sensitivity, and specificity at the item and domain-levels and for all items combined. Results: We found good concordance between survey and medical records overall, but there was substantial variation within and across domains. The worst concordance was in the counseling and referrals domain, the best in the medication use domain. Patients were able to report with good sensitivity on memorable items. Conclusions: Quality ratings are likely to vary in differing directions, depending on the data source used. The most appropriate data source for analyses of components of and overall quality of care must be considered in light of study objectives and resources. We recommend data collection from multiple sources to most accurately portray the patient and provider experience of medical care.
282 citations
TL;DR: The ordinal logistic regression approach to DIF detection, when combined with IRT ability estimates, provides a reasonable alternative for Dif detection.
Abstract: Introduction:We present an ordinal logistic regression model for identification of items with differential item functioning (DIF) and apply this model to a Mini-Mental State Examination (MMSE) dataset. We employ item response theory ability estimation in our models. Three nested ordinal logistic reg
TL;DR: Adjusted rates of potentially avoidable readmissions are scientifically sound enough to warrant their inclusion in hospital quality surveillance.
Abstract: Background:The hospital readmission rate has been proposed as an important outcome indicator computable from routine statistics. However, most commonly used measures raise conceptual issues.Objectives:We sought to evaluate the usefulness of the computerized algorithm for identifying avoidable readmi
TL;DR: Through this work, it has become clear that differences in raw scores of different groups cannot be used to infer group differences in theoretical attributes unless the test scores accord with a particular set of model invariance restrictions.
Abstract: question whether observed differences in psychometric test scores can be attributed to differences in the properties that such tests measure is relevant in many research domains; examples include the proper interpretation of differences in intelligence test scores across different generations of people,1 gender differences in affectivity,2 and crosscultural differences in personality. This question also has generated some of the most conspicuous controversies in the social and life sciences, where the highest temperature in the many heated discussions around the topic has, without a doubt, been reached in the debate on IQ-score differences between ethnic groups in the United States.4'5 Such debates are often unproductive because of a lack of unambiguous characterizations of concepts like "biased," "incomparable," and "culture-fair." Terms are easily coined, as is illustrated by Johnson's6 count of no less than 55 types of measurement equivalence; however, it is often less easy to spell out their meaning in terms of their empirical consequences. However, without at least some degree of precision in one's conception of a term like "equivalence," it is difficult to have a scientifically productive debate, or even to agree on what aspects of empirical data are relevant for answering the questions involved. It is for this reason that the establishment of concepts like measurement invariance and bias in an unambigous, formal framework with testable consequences7"9 represents a theoretical development of great importance. Through this work, it has become clear that differences in raw scores (eg, IQ-scores) of different groups (eg, blacks and whites) cannot be used to infer group differences in theoretical attributes (eg, general intelligence) unless the test scores accord with a particular set of model invariance restrictions. Namely, the same attribute must relate to the same set of observations in the same way in each group. Statistically, this means that the mathematical function that relates latent variables to the observations must be the same in each of the groups involved in the comparison.7'8 This idea has become known as the requirement of measurement invariance. The theoretical definitions of measurement invariance and bias are very general, and apply to different models, such as item response theory (IRT) and factor models, in roughly the same way.10'11 This does not hold for the empirical methods available for testing measurement invariance. In the past decades, psychometricians working on measurement invariance have produced many different statistical techniques to assess differential item functioning (DIF). These techniques usually employ different statistical assumptions, for instance, regarding the form of the relation between latent and observed variables and the shape of the population distribution on the latent variable, and employ different modeling strategies as well as selection criteria for flagging items as biased. For this reason, it is difficult to assess the consequences of choosing a particular technique; moreover, it is not always clear to what extent the choice of technique makes a difference with respect to the diagnosis of meaurement invariance and bias in applied situations. For this reason, the articles on DIF collected here (by Crane et al;12 Dorans and Kulick;13 Jones;14 Morales, Flowers, Gutierrez, Kleinman, and Teresi;15 Edelen Orlando et al16) represent a useful project in the application of bias detection methods. Each set of authors analyzes the Mini-Mental State Examination (MMSE) for measurement invariance using the same data, albeit with different methods. Together, the articles provide a
TL;DR: In the HAART era, HIV-related codes are sufficient for identifying HIV-infected subjects from administrative data when patients with a single outpatient code are excluded.
Abstract: Background:The VA's integrated electronic medical record makes it possible to create a “virtual” cohort of veterans with and without HIV infection to monitor trends in utilization, toxicity, and outcomes.Objectives:We sought to develop a virtual cohort of HIV-infected veterans by adapting an existin
TL;DR: Physicians who identify themselves as more religious and more spiritual, particularly those who are Protestants, are significantly more likely to endorse and report each of the different ways of addressing R/S in the clinical encounter.
Abstract: Context:Controversy exists regarding whether and how physicians should address religion/spirituality (R/S) with patients.Objective:This study examines the relationship between physicians’ religious characteristics and their attitudes and self-reported behaviors regarding R/S in the clinical encounte
TL;DR: Researchers and policymakers may need to broaden the scope of factors they consider as barriers to access if the goal of eliminating disparities in health care is to be achieved.
Abstract: Objectives:The substantial racial and ethnic disparities in access to and use of health services are well documented A number of studies highlight factors such as health insurance coverage and socioeconomic differences that explain some of the differences between groups, but much remains unexplaine
TL;DR: The results show that not only the disease itself, but also psychosocial and work-related factors affect the magnitude of the costs of arthritis, which are substantial.
Abstract: Objective:The objective of this study was to assess the cost attributable to lost productivity from arthritis and the association between the degree of loss and demographic, disease-related, occupational, and psychosocial variables for people.Methods:In a prospective study, 383 employed individuals
TL;DR: Depressed patients with higher ratings of involvement in medical decisions have a higher probability of receiving guideline-concordant care and improving their symptoms over an 18-month period.
Abstract: Background:Depression is undertreated in primary care settings. Little research investigates the impact of patient involvement in decisions on guideline-concordant treatment and depression outcomes.Objective:The objective of this study was to determine whether patient involvement in decision-making
TL;DR: Although some comorbidity measures demonstrate minor advantages over others, each is fairly robust in predicting both chemotherapy receipt and noncancer death.
Abstract: Administrative claims data are used frequently in health services research and policy to examine patient health status and the quality and cost of care. Comorbid illness has a significant impact on these and other outcomes, and several measures of comorbidity have been developed for use in studies based on administrative claims.1–8 Claims-based measures of comorbidity are of particular importance to cancer care researchers, who increasingly use population-based cancer registry data linked with administrative claims (eg, Surveillance, Epidemiology, and End Results [SEER]-Medicare files) to examine such issues as racial or geographic disparities in receipt of recommended treatments or the association between treatment and survival.9–12 Adjustment for comorbidity is essential in these observational studies because baseline differences in health status between groups (eg, racial and ethnic groups, those with and without treatment) may modulate differences found in study outcomes.
Health services researchers have a choice of comorbidity measures and must decide how best to apply them to their work. The measures themselves have been developed and used with claims from different places of services (eg, inpatient, outpatient) and time frames in relationship to the disease diagnosis (eg, prediagnosis, during treatment or diagnosis hospitalization). Some measures were developed to predict cost and modify payment systems,13–15 others to predict mortality and control for preexisting health status.1–8 A few studies have compared the performance of different measures in predicting mortality, generally concluding that measures incorporating more conditions and data sources are better predictors of mortality. Although some investigators have found no advantage to disease-specific indices, several have suggested creating condition- and/or outcome-specific comorbidity indices. Creating study-specific measures may not be possible, however, and investigators often apply measures in a manner at variance from how they were developed.10,12,16–18
In this study, we identified 4 administrative claims-based measures of comorbidity that have been used frequently in the health services literature to adjust for baseline health status and compared their performance in predicting 2 outcomes of importance to cancer care researchers—receipt of recommended adjuvant chemotherapy and mortality—among stage III colon cancer patients. We chose to study stage III colon cancer patients for several reasons. First, colon cancer is generally a disease of the elderly, who are more likely to have comorbid illness. Second, a 1990 National Institutes of Health Consensus Panel on Colorectal Cancer recommended routine adjuvant chemotherapy for stage III colon cancer, yet the reported rate of adjuvant chemotherapy use among the elderly is only about 55%.19 Because comorbidity may contribute to this low treatment rate, identifying the optimal comorbidity measure is important for analyses examining receipt of recommended treatment. Third, colon cancer patients’ level of comorbid illness could influence survival both through the influence on receipt of recommended treatment and through the association with noncancer death.
This work compares the performance of a wide variety of comorbidity measures in predicting treatment use and mortality, and examines the influence of using different data sources on measure performance. Because one of our measures was developed specifically for colorectal cancer patients, we were able to compare its performance to that of other measures derived from more generalized populations. We hypothesized that a measure that combines multiple data sources with specificity to colorectal cancer patients would be the best predictor of our study outcomes.
TL;DR: The high concordance between prescription claims database and pill counts suggested that the rate with which patients refill their medications usually is consistent with the rate they consume them, and DPIN is not accurate for nondiscrete dosage forms or medications prescribed for “as-required” use.
Abstract: Background:Prescription claims data have been used to estimate refill medication adherence through calculations of cumulative medication acquisition (CMA) and cumulative medication gap (CMG) values. Few studies have assessed the validity of these calculated rates.Objectives:We sought to assess the v
TL;DR: A retrospective study of patients initiating selective serotonin reuptake inhibitor (SSRI) therapy for depression and/or anxiety in a large national managed care database found adherent patients were associated with the lowest yearly medical costs.
Abstract: Objective:The objective of this study was to differentiate between 3 measures of antidepressant adherence with regard to the number of patients deemed adherent to therapy and the association between adherence and resource utilization.Design and Setting:The authors conducted a retrospective study of
TL;DR: An integrated approach to the examination of measurement equivalence, invariance, and DIF is necessary for measurement in an increasingly multi-ethnic society.
Abstract: Background and objectives Reviewed in this article are topics related to the study of invariance and differential item functioning (DIF) that have received relatively little attention in the literature. Several factors influence DIF detection; these include (1) model fit, (2) model assumptions, (3) disability distributions, (4) purification, (5) cutoff values for magnitude measures, and (6) sample and scale size. Methods Approaches to DIF detection are discussed in terms of model assumptions, purification, magnitude and impact, and possible advantages and disadvantages of each method. Conclusions An integrated approach to the examination of measurement equivalence, invariance, and DIF is necessary for measurement in an increasingly multi-ethnic society. Ideally, qualitative analyses should be performed in an iterative fashion to inform about findings of DIF. However, if an already-developed measure is being evaluated, then the steps might be to focus first on dimensional invariance using factor analytic methods, followed by DIF analyses examining both significance and magnitude of DIF, accompanied by formal tests of the impact of DIF. The DIF analytic method selected in the second step might be determined based on the findings summarized in the table presented within this paper.
TL;DR: In contrast to current bariatric studies, which report a 20% in-hospital complication rate, this work finds a significantly higher complication rate over the 6 months after surgery, resulting in costly readmissions and emergency room visits.
Abstract: Objective:Bariatric surgery is one of the fastest growing hospital procedures. Our objective is to examine the safety outcomes and utilization of resources in the 6 months after bariatric surgery using a nationwide, population-based sample.Data/Design:We examine insurance claims for 2522 bariatric s
TL;DR: No evidence of a “safe” level of consumption among those with HIV infection is found, and estimates of disease risk associated with alcohol use based upon ICD-9 Diagnostic Codes appear similar to those based upon chart review.
Abstract: Background:Many people with human immunodeficiency (HIV) infection drink alcohol. We asked whether level of exposure to alcohol is associated with medical disease in a linear or nonlinear manner, whether the association depends upon the proximity of alcohol use, and whether it varies by source used
TL;DR: This commentary outlines an approach that involves the deconstruction of race/ethnicity, which clarifies the independent influences of acculturation, quality of education, socioeconomic class, and racial socialization on outcomes of interest.
Abstract: A crucial issue for health researchers is how to measure health and health-related behaviors across racial/ethnic groups. This commentary outlines an approach that involves the deconstruction of race/ethnicity, which clarifies the independent influences of acculturation, quality of education, socioeconomic class, and racial socialization on outcomes of interest. Research on the influence of these variables on health outcomes in general, and cognitive test performance specifically, is presented. This research indicates that when variables such as quality of education, wealth, and perceived racism are taken into account, the effect of race/ethnicity on health outcomes is greatly reduced. In other words, race/ethnicity serves as a proxy for these more meaningful variables, and explicit measurement of these constructs will improve research of health within majority and minority ethnic groups.
TL;DR: Differences in Papanicolaou (Pap) smear and mammography screening among U.S.-born women and immigrants who are naturalized citizens or remained noncitizens are examined to suggest initiatives to diminish disparities in screening should prioritize improving access to care for noncitizens.
Abstract: Background: Immigrant women are less likely to undergo cancer screening. However, few national studies have examined the role of citizenship status or acculturation. Objective: The objective of this study was to examine differences in Papanicolaou (Pap) smear and mammography screening among U. S.-born women and immigrants who are naturalized citizens or remained noncitizens. Among Latinas, we also determined if acculturation is related to screening after adjusting for covariates. Research Design: The authors conducted a cross-sectional analysis of the Adult Section of the 2000 National Health Interview Survey, a nationally representative sample. Subjects: A total of 18,342 women completed the survey, including 1445 who were not citizens. Measures: For Pap smears, women age 18-65 were appropriately screened if they reported testing within the past 3 years. For mammograms, women age 50-70 were considered appropriately screened if they reported testing within the past 2 years. We determined acculturation using a modified version of the Marin scale. Results: After adjusting for age, education, family income, and marital status, noncitizens remained significantly less likely to report having a mammogram than U. S.-born women (14 percentage point difference; P < 0.01). However, after adjusting for health insurance coverage and a usual source of care, these disparities were markedly attenuated. For Pap smears, after adjusting for sociodemographics and access to care, disparities persisted (11 percentage points, P < 0.01). Among Latinas, differences in Pap smears between noncitizens and the U. S.-born disappeared after further controlling for acculturation. Conclusions: Our study suggests that initiatives to diminish disparities in screening should prioritize improving access to care for noncitizens. Our study also lends support to culturally sensitive interventions aimed at improving Pap smear screening among noncitizens.
TL;DR: The hospital record and Medicare claims are complementary data sources for identifying comorbid conditions andComorbidity is greatly underascertained when derived only from the facesheet of the hospital record.
Abstract: Background Identifying appropriate comorbidity data sources is a key consideration in health services and outcomes research Objective Using cancer patients as an example, we compared comorbid conditions identified: 1) on the discharge facesheet versus full hospital medical record and 2) in the hospital record versus Medicare claims, both precancer diagnosis and associated with a cancer treatment-related index hospitalization Methods We used data from 1995 Surveillance, Epidemiology and End Results patterns of care studies for 1,382 patients Comorbid conditions were ascertained from the hospital record associated with the most definitive cancer treatment and Medicare claims We calculated the prevalence for and assessed concordances among 12 conditions derived from the hospital record facesheet; full hospital record; Medicare claims precancer diagnosis, with and without a rule-out algorithm applied; and Medicare claims associated with an index hospitalization Results The proportion of patients with one or more comorbid conditions varied by data source, from 21% for the facesheet to 85% for prediagnosis Medicare claims without the rule-out algorithm Condition prevalences were substantially lower for the facesheet compared with the full hospital record For prediagnosis Medicare claims, condition prevalences were more than 17 times greater in the absence of an algorithm to screen for rule-out diagnoses Measures assessing concordance between the full hospital record and prediagnosis Medicare claims (rule-out algorithm applied) showed modest agreement Conclusions The hospital record and Medicare claims are complementary data sources for identifying comorbid conditions Comorbidity is greatly underascertained when derived only from the facesheet of the hospital record Investigators using Part B Medicare claims to measure comorbidity should remove conditions that are listed for purposes of generating bills but are not true comorbidities
TL;DR: The dispensing of opiate medications in Medicaid programs increased at almost twice the rate of nonpain-related medications during the 7-year study period, suggesting large, unexplained geographic variation in aggregate use exists.
Abstract: Background: Although studies have documented hospital and surgical service geographic variability, prescription use geographic variability is largely unknown Opiate pain medications are widely used, particularly because the promulgation of clinical guidelines promoting aggressive pain treatment This study describes temporal and interstate variability in aggregate prescription opiate medication use within US Medicaid programs Methods: A dataset of 49 states’ fee-for-service (FFS) Medicaid prescription drug dispensing records from 1996 to 2002 was compiled and used to quantify medication dispensing examining all opiates, controlled release oxycodone, and methadone The defined daily dose (DDD) per 1000 FFS Medicaid adult enrollees per day was calculated for all opiate medication categories A market basket of nonpain prescription medications was constructed for comparison Rates, trends, and the coefficient of variation were determined overall, by year and for each state Results: From 1996 to 2002, overall use of opiate pain medications increased 309% The market basket use increased 170% Total opiate dispensing varied widely from state to state, with a range of 69 to 441 DDD/1000/d in 1996, and 71 to 1650 DDD/1000/d (a 23-fold difference) in 2002 The coefficient of variation was 496 in 2002 Controlled release oxycodone and methadone had a greater rate of increase compared with all opiates Conclusions: The dispensing of opiate medications in Medicaid programs increased at almost twice the rate of nonpain-related medications during the 7-year study period Large, unexplained geographic variation in aggregate use exists The impact of Medicaid cost-containment strategies on utilization and outcomes should be investigated
TL;DR: The articles addressing differential item functioning (DIF) and factorial invariance in this special issue of Medical Care1−9 are uniformly excellent and readers will find that each article makes an important contribution to the measurement literature.
Abstract: The articles addressing differential item functioning (DIF) and factorial invariance in this special issue of Medical Care1–9 are uniformly excellent and readers will find that each article makes an important contribution to the measurement literature. The suggestion to have researchers apply variou
TL;DR: IRT and the likelihood-based model comparison approach comprise a powerful tool for DIF detection that can aid in the development, refinement, and evaluation of measures for use in ethnically diverse populations.
Abstract: Background An important part of examining the adequacy of measures for use in ethnically diverse populations is the evaluation of differential item functioning (DIF) among subpopulations such as those administered the measure in different languages. A number of methods exist for this purpose. Objective The objective of this study was to introduce and demonstrate the identification of DIF using item response theory (IRT) and the likelihood-based model comparison approach. Methods Data come from a sample of community-residing elderly who were part of a dementia case registry. A total of 1578 participants were administered either an English (n = 913) or Spanish (n = 665) version of the 21-item Mini-Mental State Examination. IRT was used to identify language DIF in these items with the likelihood-based model comparison approach. Results : Fourteen of the 21 items exhibited significant DIF according to language of administration. However, because the direction of the identified DIF was not consistent for one language version over the other, the impact at the scale level was negligible. Conclusions IRT and the likelihood-based model comparison approach comprise a powerful tool for DIF detection that can aid in the development, refinement, and evaluation of measures for use in ethnically diverse populations.