Faculty Bibliography

OBJECTIVE: HIV mutation accumulation has great implications for pharmacoeconomics and clinical care, yet scarcity of data has hindered its representation in decision analytic models. Our objective is to determine the accuracy with which mutation accumulation and other unmeasured parameters could be estimated during model calibration. METHODS: We used a second-order Monte Carlo simulation of HIV natural history that had been calibrated by varying two unmeasured parameters (mutation accrual rate and probability of adherence) to minimize differences between estimated and observed clinical outcomes (time to treatment failure and survival). We compared these estimated values first with only those results that had been already published at the time of model calibration, and second including results that were published after model calibration. RESULTS: The value for mutation accrual rate assigned during calibration was 0.014 mutations per month for antiretroviral-naive patients, at the lower bound of the results for nine heterogeneous studies published at the time of calibration (pooled 95% confidence interval [CI] 0.014-0.039 mutations per month). In contrast, this estimate accurately anticipated results from 11 larger and more homogeneous studies published after calibration (pooled 95% CI for antiretroviral-naive patients, 0.012-0.015 mutations per month). The value for probability of adherence assigned during calibration (75%) was also within the range of published results (pooled 95% CI 62-76%). CONCLUSION: Estimates for unobserved parameters derived during model calibration were not only within the range of clinical observations, but anticipated with accuracy clinical results that were not yet available. It may be feasible to use models to estimate unobserved parameters

As the financial burden of cost sharing continues to rise, patients increasingly avoid necessary care, thereby contributing to the high morbidity and mortality of the U.S. population compared with that of other developed countries. The rationale for cost sharing is often based on the moral hazard argument, which states that individuals may overuse care if they do not share in its costs. We evaluate this argument in detail, using it to distinguish between appropriate and inappropriate settings for cost sharing. Cost sharing may be appropriate when health services are of low value (low ratio of benefits to costs), whereas it is inappropriate when health services are of high value (high ratio of benefits to costs). In practice, cost sharing is rarely linked to value, and therefore much of the cost sharing that currently occurs is inappropriate and harmful. Cost-effectiveness analysis is an objective method to estimate the value of health services and may be a way to systematically evaluate whether cost-sharing policies are appropriate. Systematic efforts to discourage inappropriate cost sharing may improve public health

Alcohol consumption is associated with decreased antiretroviral adherence, and decreased adherence results in poorer outcomes. However the magnitude of alcohol's impact on survival is unknown. Our objective was to use a calibrated and validated simulation of HIV disease to estimate the impact of alcohol on survival. We incorporated clinical data describing the temporal and dose-response relationships between alcohol consumption and adherence in a large observational cohort (N=2,702). Individuals were categorized as nondrinkers (no alcohol consumption), hazardous drinkers (consume > or =5 standard drinks on drinking days), and nonhazardous drinkers (consume <5 standard drinks on drinking days). Our results showed that nonhazardous alcohol consumption decreased survival by more than 1 year if the frequency of consumption was once per week or greater, and by 3.3 years (from 21.7 years to 18.4 years) with daily consumption. Hazardous alcohol consumption decreased overall survival by more than 3 years if frequency of consumption was once per week or greater, and by 6.4 years (From 16.1 years to 9.7 years) with daily consumption. Our results suggest that alcohol is an underappreciated yet modifiable risk factor for poor survival among individuals with HIV

The present study prospectively investigated the association between family life stress and insomnia symptoms among 115 undergraduates, ages 17-22 years. Participants completed the following questionnaires at 2 study time points, spaced 3 weeks apart: the Insomnia Severity Index, the Negative Life Events Questionnaire (NLEQ), and the Beck Depression Inventory. First, family life stress at baseline was hypothesized to predict elevated insomnia symptoms 3 weeks later, above and beyond depressive symptoms. Second, compared with academic stressors, negative family and social life events were expected to best predict increased insomnia. Regression analyses were conducted to test study predictions. Hypotheses were partially supported. Family life stress was significantly associated with increased insomnia symptomatology, even after controlling for depression. Results also revealed that negative family life events, together with academic stress, predicted the highest levels of insomnia

Our objective was to illustrate the effects of using stricter standards for the quality of evidence used in decision analytic modeling. We created a simple 10-parameter probabilistic Markov model to estimate the cost-effectiveness of directly observed therapy (DOT) for individuals with newly diagnosed HIV infection. We evaluated quality of evidence on the basis of U.S. Preventive Services Task Force methods, which specified 3 separate domains: study design, internal validity, and external validity. We varied the evidence criteria for each of these domains individually and collectively. We used published research as a source of data only if the quality of the research met specified criteria; otherwise, we specified the parameter by randomly choosing a number from a range within which every number has the same probability of being selected (a uniform distribution). When we did not eliminate poor-quality evidence, DOT improved health 99% of the time and cost less than 100,000 dollars per additional quality-adjusted life-year (QALY) 85% of the time. The confidence ellipse was extremely narrow, suggesting high precision. When we used the most rigorous standards of evidence, we could use fewer than one fifth of the data sources, and DOT improved health only 49% of the time and cost less than 100,000 dollars per additional QALY only 4% of the time. The confidence ellipse became much larger, showing that the results were less precise. We conclude that the results of decision modeling may vary dramatically depending on the stringency of the criteria for selecting evidence to use in the model

OBJECTIVES: Determining the relationship between antiretroviral adherence and resistance accumulation is important for the design and evaluation of adherence interventions. Our objective was to explain heterogeneity observed in this relationship. METHODS: We first conducted a systematic review to locate published reports describing the relationship between adherence and resistance. We then used a validated computer simulation to simulate the patient populations in these reports, exploring the impact of changes in individual patient characteristics (age, CD4, viral load, prior antiretroviral experience) on the shape of the adherence-resistance (A-R) curve. RESULTS: The search identified 493 titles, of which 3 contained relevant primary data and 2 had sufficient follow-up for inclusion (HOMER and REACH cohorts). When simulating HOMER, the A-R curve had a high peak with a greatly increased hazard ratio (HR) of accumulating mutations at partial compared to complete adherence (simulation, HR 2.9; HOMER, HR 2.7). When simulating REACH, the A-R curve had a shallow peak with a slightly increased hazard of accumulating mutations at partial adherence (simulation, HR 1.2; REACH, HR 1.4). This heterogeneity was primarily attributable to differences in antiretroviral experience between the cohorts. CONCLUSIONS: Our computer simulation was able to explain much of the heterogeneity in observed A-R curves

BACKGROUND: Studies have established that physiologic instability and services mismatching precede adverse events in hospitalized patients. In response to these considerations, the concept of a Rapid Response System (RRS) has emerged. The responding team is commonly known as a medical emergency team (MET), rapid response team (RRT), or critical care outreach (CCO). Studies show that an RRS may improve outcome, but questions remain regarding the benefit, design elements, and advisability of implementing a MET system. METHODS: In June 2005 an International Conference on Medical Emergency Teams (ICMET) included experts in patient safety, hospital medicine, critical care medicine, and METs. Seven of 25 had no experience with an RRS, and the remainder had experience with one of the three major forms of RRS. After preconference telephone and e-mail conversations by the panelists in which questions to be discussed were characterized, literature reviewed, and preliminary answers created, the panelists convened for 2 days to create a consensus document. Four major content areas were addressed: What is a MET response? Is there a MET syndrome? What are barriers to METS? How should outcome be measured? Panelists considered whether all hospitals should implement an RRS. RESULTS: Patients needing an RRS intervention are suddenly critically ill and have a mismatch of resources to needs. Hospitals should implement an RRS, which consists of four elements: an afferent, 'crisis detection' and 'response triggering' mechanism; an efferent, predetermined rapid response team; a governance/administrative structure to supply and organize resources; and a mechanism to evaluate crisis antecedents and promote hospital process improvement to prevent future events

BACKGROUND: Male veterans represent a large population at risk for acquiring or transmitting human immunodeficiency virus (HIV) infection. We sought to determine the prevalence of risky sexual behavior among veterans with and without HIV infection and to assess the relationship of intoxication before intercourse and other measures of drug and alcohol use to risky sexual behavior in this population. METHODS: We analyzed baseline data on 1009 HIV-positive (mean age 49 years) and 710 HIV-negative male veterans (mean age 55 years) who were participating in the Veterans Aging Cohort 5-Site Study (VACS 5). Participants completed a written questionnaire that included measures of alcohol and drug use and risky sexual behavior. RESULTS: Compared with HIV-negative veterans, HIV-positive veterans were more likely to report 5 or more sexual partners in the past year (14% vs. 4%, P < 0.01), less likely to report not using a condom at last intercourse (25% vs. 75%, P < 0.01), and similarly likely to report having 2 or more partners and inconsistent condom use (10% vs. 10%). Among sexually active HIV-positive veterans, intoxication before intercourse was significantly associated with having 5 or more sexual partners in the past year (odds ratio [OR] 1.8, 95% confidence interval [CI] 1.1-2.8), inconsistent condom use (OR 1.8, 95% CI 1.2-2.7), and the combined measure of 2 or more partners and inconsistent condom use (OR 1.8, 95% CI 1.1-3.0). Intoxication before intercourse was not significantly associated with these behaviors in HIV-negative veterans, although similar trends were noted. CONCLUSION: Risky sexual behavior was common among male veterans attending outpatient clinics and is more common among HIV-positive veterans who use alcohol and drugs in sexual situations. Asking HIV-positive men a single question about intoxication before intercourse could help to identify men at increased risk of engaging in risky sexual behavior, and specific advice to avoid intoxication in sexual situations could help to reduce risky sexual behavior

The authors discuss techniques for Monte Carlo (MC) cohort simulations that reduce the number of simulation replications required to achieve a given degree of precision for various output measures. Known as variance reduction techniques, they are often used in industrial engineering and operations research models, but they are seldom used in medical models. However, most MC cohort simulations are well suited to the implementation of these techniques. The authors discuss the cost of implementation versus the benefit of reduced replications