The impact of dentition status and barriers to dental care services on perceived oral health of medicare beneficiaries.

OBJECTIVE: To examine the association among barriers to dental care services, dentition groups, and self-reported oral health status for Medicare beneficiaries. METHODS: We used data from the 2017 to 2018 National Health and Nutrition Examination Survey (NHANES), which included participants aged ≥65 years who were enrolled in Medicare and had completed the oral health exam. We created a dentition group variable using the detailed dental examination data to account for the presence of natural, replaced, removable, or missing teeth. Through bivariate and logistic analyses, we explored the relationship between barriers to receiving dental care services, dentition groups, and reported oral and general health statuses, along with other control variables. RESULTS: For the total Medicare population as well as in the four subgroup analyses, we showed that those with barriers to dental care services were more likely to report fair or poor oral health status. Those who were edentulous, had complete dentures, or had less than a full mouth of teeth had greater barriers and worse oral and general health than did those with all-natural teeth. Among those who reported fair or poor general health, those with less than a full mouth of teeth showed similar levels of barriers to dental care services and worse perceived oral health than did those without any teeth. CONCLUSIONS: Helping the 65 years and older population retain their teeth in good condition will improve their overall health. Investment in oral hygiene and health for the current and future Medicare populations could improve their overall health.

A Latent Class Approach to Modeling Trajectories of Health Care Cost in Pediatric Cystic Fibrosis.

Introduction. Estimating costs of medical care attributable to treatments over time is difficult due to costs that cannot be explained solely by observed risk factors. Unobserved risk factors cannot be accounted for using standard econometric techniques, potentially leading to imprecise prediction. The goal of this work is to describe methodology to account for latent variables in the prediction of longitudinal costs. Methods. Latent class growth mixture models (LCGMMs) predict class membership using observed risk factors and class-specific distributions of costs over time. Our motivating example models cost of care for children with cystic fibrosis from birth to age 17. We compare a generalized linear mixed model (GLMM) with LCGMMs. Both models use the same covariates and distribution to predict average costs by combinations of observed risk factors. We adopt a Bayesian estimation approach to both models and compare results using the deviance information criterion (DIC). Results. The 3-class LCGMM model has a lower DIC than the GLMM. The LCGMM latent classes include a low-cost group where costs increase slowly over time, a medium-cost group with initial higher costs than the low-cost group and with more rapidly increasing costs at older ages, and a high-cost group with a U-shaped trajectory. The risk profile-specific mixtures of classes are used to predict costs over time. The LCGMM model shows more delineation of costs by age by risk profile and with less uncertainty than the GLMM model. Conclusions. The LCGMM approach creates flexible prediction models when using longitudinal cost data. The Bayesian estimation approach to LCGMM presented fits well into cost-effectiveness modeling where the estimated trajectories and class membership can be used for prediction.

Innovative assessment of inpatient and pulmonary drug costs for children with cystic fibrosis.

BACKGROUND: Previous estimates of the cost of care for pediatric Cystic fibrosis (CF) showed wide variation, without specific summary of pulmonary drug costs. METHODS: Enrolled CF children from the Wisconsin newborn screening trial were evaluated quarterly per protocol. Assessments systematically included all treatments, hospitalizations, and nutritional and pulmonary outcomes. Direct medical costs from hospital billing and medical records from 1989 to 2010 were used to describe costs by age-ranges and subgroups throughout follow-up. Outpatient drugs were separated by category (pulmonary/otherwise). Inpatient and drug costs were examined by clinical risk factors (presence of meconium ileus, pancreatic insufficiency, and expected severity of genetic mutations). RESULTS: Seventy-three children were followed for an average of 12.9 years with an average annual total cost of care of $24,768. Outpatient drug costs (53%) and hospitalizations (32%) represented the majority of costs. Drug costs were 48% for pulmonary indications and 52% for non-pulmonary. Pulmonary drug costs for children taking dornase were 54% of their drug costs while pulmonary drug costs were only 31% for children not taking dornase. Significant differences in frequency of inpatient stays existed for children with pancreatic insufficiency. Substantial differences in treatment costs exist as children age and by clinical risk factor. CONCLUSION: This study provides more accurate longitudinal estimates of CF care costs throughout childhood and shows that increasing age, pancreatic insufficiency, use of dornase, and hospitalizations are key determinants of cost. These estimates can be included in evaluations of the cost-effectiveness of new, highly expensive treatments being introduced for any CF population. Pediatr Pulmonol. 2016;51:1295-1303. © 2016 Wiley Periodicals, Inc.

US-Based Drug Cost Parameter Estimation for Economic Evaluations.

INTRODUCTION: In the United States, more than 10% of national health expenditures are for prescription drugs. Assessing drug costs in US economic evaluation studies is not consistent, as the true acquisition cost of a drug is not known by decision modelers. Current US practice focuses on identifying one reasonable drug cost and imposing some distributional assumption to assess uncertainty. METHODS: We propose a set of Rules based on current pharmacy practice that account for the heterogeneity of drug product costs. The set of products derived from our Rules, and their associated costs, form an empirical distribution that can be used for more realistic sensitivity analyses and create transparency in drug cost parameter computation. The Rules specify an algorithmic process to select clinically equivalent drug products that reduce pill burden, use an appropriate package size, and assume uniform weighting of substitutable products. Three diverse examples show derived empirical distributions and are compared with previously reported cost estimates. RESULTS: The shapes of the empirical distributions among the 3 drugs differ dramatically, including multiple modes and different variation. Previously published estimates differed from the means of the empirical distributions. Published ranges for sensitivity analyses did not cover the ranges of the empirical distributions. In one example using lisinopril, the empirical mean cost of substitutable products was $444 (range = $23-$953) as compared with a published estimate of $305 (range = $51-$523). CONCLUSIONS: Our Rules create a simple and transparent approach to creating cost estimates of drug products and assessing their variability. The approach is easily modified to include a subset of, or different weighting for, substitutable products. The derived empirical distribution is easily incorporated into 1-way or probabilistic sensitivity analyses.

Rapid increase in breast magnetic resonance imaging use: trends from 2000 to 2011.

IMPORTANCE: Breast magnetic resonance imaging (MRI) is highly sensitive for detecting breast cancer. Low specificity, cost, and little evidence regarding mortality benefits, however, limit recommendations for its use to high-risk women. How breast MRI is actually used in community settings is unknown. OBJECTIVE: To describe breast MRI trends and indications in a community setting. DESIGN, SETTING, AND PARTICIPANTS: Retrospective cohort study at a not-for-profit health plan and multispecialty group medical practice in New England of 10,518 women aged 20 years and older enrolled in the health plan for at least 1 year who had at least 1 breast MRI between January 1, 2000, and December 31, 2011. MAIN OUTCOMES AND MEASURES: Breast MRI counts were obtained from claims data. Clinical indication (screening, diagnostic evaluation, staging or treatment, or surveillance) was determined using a prediction model developed from electronic medical records on a subset of participants. Breast cancer risk status was assessed using claims data and, for the subset, also through electronic medical record review. RESULTS; Breast MRI use increased more than 20-fold from 6.5 per 10,000 women in 2000 to 130.7 per 10,000 in 2009. Use then declined and stabilized to 104.8 per 10,000 by 2011. Screening and surveillance, rare indications in 2000, together accounted for 57.6% of MRI use by 2011; 30.1% had a claims-documented personal history and 51.7% a family history of breast cancer, whereas 3.5% of women had a documented genetic mutation. In the subset of women with electronic medical records who received screening or surveillance MRIs, only 21.0% had evidence of meeting American Cancer Society (ACS) criteria for breast MRI. Conversely, only 48.4% of women with documented deleterious genetic mutations received breast MRI screening. CONCLUSIONS AND RELEVANCE: Breast MRI use increased steeply over 10 years and then stabilized, especially for screening and surveillance among women with family or personal history of breast cancer; most women receiving screening and surveillance breast MRIs lacked documented evidence of meeting ACS criteria, and many women with mutations were not screened. Efforts are needed to ensure that breast MRI use and documentation are focused on those women who will benefit most.

Variation in tumor natural history contributes to racial disparities in breast cancer stage at diagnosis.

Black women tend to be diagnosed with breast cancer at a more advanced stage than whites and subsequently experience elevated breast cancer mortality. We sought to determine whether there are racial differences in tumor natural history that contribute to these disparities. We used the University of Wisconsin Breast Cancer Simulation Model, a validated member of the National Cancer Institute's Cancer Intervention and Surveillance Modeling Network, to evaluate the contribution of racial differences in tumor natural history to observed disparities in breast cancer incidence. We fit eight natural history parameters in race-specific models by calibrating to the observed race- and stage-specific 1975-2000 U.S. incidence rates, while accounting for known racial variation in population structure, underlying risk of breast cancer, screening mammography utilization, and mortality from other causes. The best fit models indicated that a number of natural history parameters must vary between blacks and whites to reproduce the observed stage-specific incidence patterns. The mean of the tumor growth rate parameter was 63.6 % higher for blacks than whites (0.18, SE 0.04 vs. 0.11, SE 0.02). The fraction of tumors considered highly aggressive based on their tendency to metastasize at a small size was 2.2 times greater among blacks than whites (0.41, SE 0.009 vs. 0.019, SE 0.008). Based on our simulation model, breast tumors in blacks grow faster and are more likely to metastasize earlier than tumors in whites. These differences suggest that targeted prevention and detection strategies that go beyond equalizing access to mammography may be needed to eliminate breast cancer disparities.

Derivation of background mortality by smoking and obesity in cancer simulation models.

BACKGROUND: Simulation models designed to evaluate cancer prevention strategies make assumptions on background mortality-the competing risk of death from causes other than the cancer being studied. Researchers often use the U.S. life tables and assume homogeneous other-cause mortality rates. However, this can lead to bias because common risk factors such as smoking and obesity also predispose individuals for deaths from other causes such as cardiovascular disease. METHODS: We obtained calendar year-, age-, and sex-specific other-cause mortality rates by removing deaths due to a specific cancer from U.S. all-cause life tables. Prevalence across 12 risk factor groups (3 smoking [never, past, and current smoker] and 4 body mass index [BMI] categories [<25, 25-30, 30-35, 35+ kg/m(2)]) were estimated from national surveys (National Health and Nutrition Examination Surveys [NHANES] 1971-2004). Using NHANES linked mortality data, we estimated hazard ratios for death by BMI/smoking using a Poisson regression model. Finally, we combined these results to create 12 sets of BMI and smoking-specific other-cause life tables for U.S. adults aged 40 years and older that can be used in simulation models of lung, colorectal, or breast cancer. RESULTS: We found substantial differences in background mortality when accounting for BMI and smoking. Ignoring the heterogeneity in background mortality in cancer simulation models can lead to underestimation of competing risk of deaths for higher-risk individuals (e.g., male, 60-year old, white obese smokers) by as high as 45%. CONCLUSION: Not properly accounting for competing risks of death may introduce bias when using simulation modeling to evaluate population health strategies for prevention, screening, or treatment. Further research is warranted on how these biases may affect cancer-screening strategies targeted at high-risk individuals.

Chapter 3: Cohort life tables by smoking status, removing lung cancer as a cause of death.

The purpose of this study was to develop life tables by smoking status removing lung cancer as a cause of death. These life tables are inputs to studies that compare the effectiveness of lung cancer treatments or interventions, and provide a way to quantify time until death from causes other than lung cancer. The study combined actuarial and statistical smoothing methods, as well as data from multiple sources, to develop separate life tables by smoking status, birth cohort, by single year of age, and by sex. For current smokers, separate life tables by smoking quintiles were developed based on the average number of cigarettes smoked per day by birth cohort. The end product is the creation of six non-lung-cancer life tables for males and six tables for females: five current smoker quintiles and one for never smokers. Tables for former smokers are linear combinations of the appropriate table based on the current smoker quintile before quitting smoking and the never smoker probabilities, plus added covariates for the smoking quit age and time since quitting.

Radiology faculty compliance with recommended health guidelines: comparison with residents.

RATIONALE AND OBJECTIVES: The aims of this study were to determine diagnostic radiology faculty members' compliance with recommended health guidelines for physical activity, body weight, diet, and related health indicators and to compare faculty members' compliance with that of radiology residents. MATERIALS AND METHODS: A request to complete an online health survey was electronically sent to members of the Association of University Radiologists in September 2008. Results were compared to those from a similar survey completed by radiology residents in May and June 2007. Frequency counts and Fisher's exact tests were used to summarize results and to determine statistically significant relationships. RESULTS: The sample consisted of 193 of 801 members of the Association of University Radiologists (24%). A greater percentage of faculty members than residents complied with recommendations for physical activity (52% vs 37%, P < .001) and the consumption of vegetables (67% vs 52%, P < .001), saturated fat (51% vs 37%, P < .001), and sodium (53% vs 37%, P < .001). A greater percentage of faculty members felt that they got enough sleep (51% vs 38%, P = .002) and did not think about stress on most days (39% vs 26%, P = .001). Most faculty members (59%) worked 51 to 60 hours a week, whereas most residents (59%) worked > 60 hours, and greater work hours were correlated with less resident physical activity (P = .017). More female than male faculty members (78% vs 57%, P = .010) and residents (83% vs 62%, P < .001) had body mass indexes < 25 kg/m(2). CONCLUSION: A substantial percentage of faculty members were out of compliance with federal health guidelines, although less so than residents in many categories. Comments from both groups suggest a possible benefit from modifications to the work environment.

Use and employer costs of a pharmacotherapy smoking-cessation treatment benefit.

BACKGROUND: Employers cite a lack of information on the cost of insurance coverage for smoking-cessation treatment as a barrier to its provision. This study describes the use of a new insurance benefit for smoking-cessation pharmacotherapy, and its pharmaceutical costs to a large public employer between 2001 and 2003. METHODS: Annual enrollment and pharmaceutical claims data were collected from the health plans that contracted with the Wisconsin Department of Employee Trust Funds (ETF). State employees, retirees, and adult dependents who obtained health insurance through the ETF constituted our sample, approximately 150,000/year. Pharmacotherapy benefit use was defined as a paid claim for one of four U.S. Food and Drug Administration-approved smoking-cessation medications. Pharmaceutical cost was defined as the ingredient cost (+) dispensing fee (-) member copayment. Analyses included estimation of the proportion of smokers who used the benefit each year and across 3 years, the average annual cost per user, and the per member per month (PMPM) pharmaceutical cost to the employer. Data were collected from 2001 to 2004 and analyzed in 2005-2006. RESULTS: Annual benefit use among smokers ranged from 6% to 7% with a 3-year rate of approximately 17%. The PMPM cost of the covered pharmacotherapy was approximately 0.13 dollars. CONCLUSIONS: The cost to employers of providing insurance coverage for smoking-cessation pharmacotherapy to their employees is low. By informing insurance purchasing decisions, these results may facilitate the adoption of such coverage, with the goal of ultimately reducing the proportion of employees who smoke.

Competing risks to breast cancer mortality.

BACKGROUND: Simulation models analyzing the impact of treatment interventions and screening on the level of breast cancer mortality require an input of mortality from causes other than breast cancer, or competing risks. METHODS: This chapter presents an actuarial method of creating cohort life tables using published data that removes breast cancer as a cause of death. RESULTS: Mortality from causes other than breast cancer as a percentage of all-cause mortality is smallest for women in their forties and fifties, as small as 85% of the all-cause rate, although the level and percentage of the impact varies by birth cohort. CONCLUSION: This method produces life tables by birth cohort and by age that are easily included as a common input by the various CISNET modeling groups to predict mortality from other causes. Attention to removing breast cancer mortality from all-cause mortality is worthwhile, because breast cancer mortality can be as high as 15% at some ages.

The Wisconsin Breast Cancer Epidemiology Simulation Model.

The Wisconsin Breast Cancer Epidemiology Simulation Model is a discrete-event, stochastic simulation model using a systems-science modeling approach to replicate breast cancer incidence and mortality in the U.S. population from 1975 to 2000. Four interacting processes are modeled over time: (1) natural history of breast cancer, (2) breast cancer detection, (3) breast cancer treatment, and (4) competing cause mortality. These components form a complex interacting system simulating the lives of 2.95 million women (approximately 1/50 the U.S. population) from 1950 to 2000 in 6-month cycles. After a "burn in" of 25 years to stabilize prevalent occult cancers, the model outputs age-specific incidence rates by stage and age-specific mortality rates from 1975 to 2000. The model simulates occult as well as detected disease at the individual level and can be used to address "What if?" questions about effectiveness of screening and treatment protocols, as well as to estimate benefits to women of specific ages and screening histories.

Retrospective cost-effectiveness analysis of screening mammography.

BACKGROUND: Many guidelines recommend screening mammography every 1-2 years for women older than 40 years; more than 70% of women now participate in routine screening. No studies have examined the societal impact of screening practices over the past decade in the United States on costs and quality-adjusted life-years (QALYs). We performed a retrospective cost-effectiveness analysis comparing actual and alternative screening mammography scenarios. METHODS: We used a discrete-event simulation model of breast cancer epidemiology to estimate the costs and the number of QALYs that were associated with observed screening mammography patterns in the United States from 1990 to 2000 for women aged 40 years or older. We also estimated costs and QALYS for no screening and for 64 alternative screening scenarios. Incremental cost-effectiveness ratios were computed. Sensitivity analyses were performed on key parameters. RESULTS: Actual U.S. screening patterns from 1990 to 2000 accrued 947.5 million QALYs and cost $166 billion over the lifetimes of the screened women, resulting in a gain of 1.7 million QALYs for an additional cost of $62.5 billion compared with no screening. Among those polices that were not dominated--i.e., for which no alternative existed that produced more QALYs for lower costs--screening all women aged 40-80 years annually per some U.S. guidelines was the most expensive option, costing $58,000 per additional QALY gained compared with the next most costly alternative, screening all women aged 45-80 years annually. Many alternative screening scenarios generated more QALYs for less cost (with savings up to $6 billion) than actual screening patterns over the study period. Sensitivity analysis showed that conclusions about the cost-effectiveness of screening mammography policies were highly sensitive to small, short-term detrimental effects on quality of life from the screening test itself. CONCLUSIONS: Choosing among the efficient policies to guide current screening recommendations requires consideration of costs to promote participation in screening and measurement of acute quality-of-life effects of mammography.

Cystic fibrosis mutations and genotype-pulmonary phenotype analysis.

BACKGROUND: Although there are more than 1000 mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene, most of them are uncommon and only limited information exists regarding genotype-pulmonary phenotype relationships. METHODS: We determined and classified the CFTR mutations using denaturing high-performance liquid chromatography and developed new, quantitative methods to categorize pulmonary phenotypes. RESULTS: Two novel alleles were discovered, namely G1047R and 1525-2A-->G, which were accompanied by F508del and G551D mutations, respectively. Assessment of numerous options revealed that CF pulmonary phenotype categorization in children cannot be accomplished with clinical or pulmonary function data but is facilitated by longitudinal quantitative chest radiology. It was most useful to categorize pulmonary disease status by evaluating the typical pattern of abnormalities in patients homozygous for the F508del mutation, and then compare patients with minor mutations to this typical CF pulmonary phenotype. By this method, both patients with novel mutations have pulmonary phenotypes typical of F508del homozygotes. However, patients with class IV mutations (e.g., R347P) or with pancreatic sufficiency showed serial chest radiographs that were atypically mild. CONCLUSIONS: Longitudinal quantitative chest radiography provides a new strategy for CF pulmonary phenotype categorization that should be useful for genotype-phenotype delineation in individual patients and in both epidemiologic studies and clinical trials involving groups of children with CF.

Assessing the cost of cystic fibrosis diagnosis and treatment.

OBJECTIVES: To extend previous evaluations of costs of cystic fibrosis (CF) diagnosis and examine key issues in assessing the CF cost of care. STUDY DESIGN: Costs for CF newborn screening (NBS) including CF multi-mutation testing are analyzed by using data from the Wisconsin State Laboratory of Hygiene. Electronic data from 2 Wisconsin CF centers are used to illustrate the complexity of analyzing CF health care utilization and costs. RESULTS: The current cost-per-newborn of a CF multi-mutation test is 50% higher than testing for a single mutation. Data collection for the cost-of-care study requires a combination of electronic and manual data collection; modeling of cost data requires consideration of any censoring. Hospitalizations are shown to have a large impact on costs and show high variability at the individual level. Sixty-nine percent of children with meconium ileus had some hospitalization versus 56% of children without meconium ileus. CONCLUSION: A cost-benefit analysis of CF multi-mutation testing is warranted. The study of health care cost data is complex and utilization varies between children. Individual-level modeling of CF costs must include factors contributing to the severity of the disease and allow for consideration of individual-level utilization, such as the number of hospitalizations.

Use of a new comprehensive insurance benefit for smoking-cessation treatment.

INTRODUCTION: Uncertainty about levels of employee use of an insurance benefit for smoking-cessation treatment has presented a barrier to employers considering the adoption of such coverage. This study examined self-reported awareness and use of a new insurance benefit for smoking-cessation treatment among a sample of Wisconsin state employees, retirees, and adult dependents. METHODS: We evaluated the self-reported use of insurance coverage for smoking-cessation treatment during the first 2 years of its availability to the Wisconsin state employee, retiree, and adult dependent population. We conducted analyses of responses to smoking-related questions in 2001 and 2002 cross-sectional surveys of insured state employees, retirees, and adult dependents, weighted to represent this population. RESULTS: In 2002, benefit use among smokers aware of the benefit was 39.6%, and benefit use among smokers unaware of the benefit was 3.5%. Only 27.4% of smokers were aware of the benefit in 2002; use among all smokers was 13.6%. Of all smokers, 30.4% used smoking-cessation treatment medication (over-the-counter or covered) in 2002. Smoking prevalence was 15.6% in 2001 and 13.2% in 2002. CONCLUSION: In an educated employee population, self-reported smoking-cessation treatment benefit use was modest among all smokers during its first 2 years of availability. Benefit awareness was low in this educated population, which may help explain low use rates, particularly given the 30% of all smokers who attempted to quit smoking with the help of smoking-cessation treatment medication. These data provide use-rate estimates for states contemplating adoption of an evidence-based smoking-cessation treatment benefit.

Analysis of the costs of diagnosing cystic fibrosis with a newborn screening program.

OBJECTIVES: To compare the cost of diagnosing cystic fibrosis (CF) through a newborn screening program with the traditional method and to estimate the cost of CF diagnosis if a national newborn screening program is implemented. STUDY DESIGN: Surveys were conducted to determine the annual number of sweat tests in 1991 and in 2000 after implementation of statewide screening. A national survey of sweat test costs was used to estimate the annual expense for diagnosing CF in the United States through newborn screening. RESULTS: Since the introduction of newborn screening for CF, the numbers of sweat tests ordered annually have decreased from 1670 to 804 (including 134 follow-up tests from screening). The current estimated annual cost of Wisconsin CF newborn screening and diagnosis is $4.58 per newborn infant. The estimated annual cost per newly diagnosed CF infant using the traditional method is $4.97 per newborn infant. If no additional sweat tests were ordered outside of the newborn screening program, the estimated annual cost of a Wisconsin CF newborn screening and diagnosis is $2.66 per newborn and $2.47 per newborn for a national CF newborn screening program. CONCLUSIONS: A CF newborn screening program provides a potentially cost-saving alternative to the traditional method of diagnosis of CF.