Medical Decision Making RSS feed -- OnlineFirst Articles

Mapping the Modified Rankin Scale (mRS) Measurement into the Generic EuroQol (EQ-5D) Health Outcome

Mon, 26 Oct 2009 15:03:54 PDT

Background. Mapping disease-specific instruments into generic health outcomes or utility values is an expanding field of interest in health economics. This article constructs an algorithm to translate the modified Rankin scale (mRS) into EQ-5D utility values. Methods. mRS and EQ-5D information was derived from stroke or transient ischemic attack (TIA) patients identified as part of the Oxford Vascular study (OXVASC). Ordinary least squares (OLS) regression was used to predict UK EQ-5D tariffs from mRS scores. An alternative method, using multinomial logistic regression with a Monte Carlo simulation approach (MLogit) to predict responses to each EQ-5D question, was also explored. The performance ofthe models was compared according to the magnitude of their predicted-to-actual mean EQ-5D tariffdifference, their mean absolute and mean squared errors (MAE and MSE), and associated 95% confidence intervals (CIs). Out-of-sample validation was carried out in a subset of coronary disease and peripheral vascular disease (PVD) patients also identified as part of OXVASC but not used in the original estimation. Results. The OLS and MLogit yielded similar MAE and MSE in the internal and external validation data sets. Both approaches also underestimated the uncertainty around the actual mean EQ-5D tariff producing tighter 95% CIs in both data sets. Conclusions. The choice of algorithm will be dependent on the study aim. Individuals outside the United Kingdom may find it more useful to use the multinomial results, which can be used with different country-specific tariff valuations. However, these algorithms should not replace prospective collection ofutility data.

Bayesian Hierarchical Models for Cost-Effectiveness Analyses that Use Data from Cluster Randomized Trials

Grieve, R., Nixon, R., Thompson, S. G. — Mon, 26 Oct 2009 15:03:54 PDT

Cost-effectiveness analyses (CEA) may be undertaken alongside cluster randomized trials (CRTs) where randomization is at the level of the cluster (for example, the hospital or primary care provider) rather than the individual. Costs (and outcomes) within clusters may be correlated so that the assumption made by standard bivariate regression models, that observations are independent, is incorrect. This study develops a flexible modeling framework to acknowledge the clustering in CEA that use CRTs. The authors extend previous Bayesian bivariate models for CEA of multicenter trials to recognize the specific form of clustering in CRTs. They develop new Bayesian hierarchical models (BHMs) that allow mean costs and outcomes, and also variances, to differ across clusters. They illustrate how each model can be applied using data from a large (1732 cases, 70 primary care providers) CRT evaluating alternative interventions for reducing postnatal depression. The analyses compare cost-effectiveness estimates from BHMs with standard bivariate regression models that ignore the data hierarchy. The BHMs show high levels of cost heterogeneity across clusters (intracluster correlation coefficient, 0.17). Compared with standard regression models, the BHMs yield substantially increased uncertainty surrounding the cost-effectiveness estimates, and altered point estimates. The authors conclude that ignoring clustering can lead to incorrect inferences. The BHMs that they present offer a flexible modeling framework that can be applied more generally to CEA that use CRTs.

Comparison of 5 Health-Related Quality-of-Life Indexes Using Item Response Theory Analysis

Fryback, D. G., Palta, M., Cherepanov, D., Bolt, D., Kim, J.-S. — Tue, 20 Oct 2009 15:23:10 PDT

Background. Five health-related quality-of-life (HRQoL) indexes—EQ-5D, HUI2, HUI3, QWB-SA, and SF-6D—are each used to assign community-based utility scores to health states, although these scores differ. Objective. The authors transform these indexes to a common scale to understand their interrelationships. Methods. Datawerefromthe National Health Measurement Study, a telephone survey of 3844 US adults. The 5 indexes were analyzed using item response theory analysis to estimate scores on an underlying construct of summary health, . Unidimensionality was evaluated using nonlinear principal components analysis. Index scores were plotted against the estimated scores on the common underlying construct. In addition, scores on the Health and Activities Limitation Index (HALex), the Centers for Disease Control and Prevention Healthy Days questions, and self-rated health on a 5-category scale ranging from excellent to poor were plotted. Results. SF-6D and QWB-SA are nearly linear across the range of but with a shallow slope; EQ-5D, HUI2, and HUI3 are linear with a steep slope from low (poor health) into midrange of , then approximately linear with a less steep slope for higher (health just below to well above average), although the inflection points differ by index. Conclusion. Simple linear functions may serve as crosswalks among these indexes only for lower health states, albeit with low precision. Ceiling effects make crosswalks among most of the indexes ill specified above a certain level of health. Although each index measures generic health on a utility scale, these indexes are not identical but are relatively simply, if imprecisely, related.

Changes of Heart: The Switch-Value Method for Assessing Value Uncertainty

John, L. K., Fischhoff, B. — Wed, 14 Oct 2009 09:35:19 PDT

Background. Medical choices often evoke great value uncertainty, as patients face difficult, unfamiliar tradeoffs. Those seeking to aid such choices must be able to assess patients’ ability to reduce that uncertainty, to reach stable, informed choices. Objective. The authors demonstrate a new method for evaluating how well people have articulated their preferences for difficult health decisions. The method uses 2 evaluative criteria. One is internal consistency, across formally equivalent ways of posing a choice. The 2nd is compliance with principles of prospect theory, indicating sufficient task mastery to respond in predictable ways. Method. Subjects considered a hypothetical choice between noncurative surgery and palliative care, posed by a brain tumor. The choice options were characterized on 6 outcomes (e.g., pain, life expectancy, treatment risk), using a drug facts box display. After making an initial choice, subjects indicated their willingness to switch, given plausible changes in the outcomes. These changes involved either gains (improvements) in the unchosen option or losses (worsening) in the chosen one. A 2 x 2mixed design manipulated focal change (gains v. losses) within subjects and change order between subjects. Results. In this demonstration, subjects’ preferences were generally consistent 1) with one another: with similar percentages willing to switch for gains and losses, and 2) with prospect theory, requiring larger gains than losses, to make those switches. Conclusion. Informed consent requires understanding decisions well enough to articulate coherent references. The authors’ method allows assessing individuals’ success in doing so.

Uncertainty Assessment of Input Parameters for Economic Evaluation: Gauss's Error Propagation, an Alternative to Established Methods

Stollenwerk, B., Stock, S., Siebert, U., Lauterbach, K. W., Holle, R. — Thu, 08 Oct 2009 08:10:18 PDT

In decision modeling for health economic evaluation, bootstrapping and the Cholesky decomposition method are frequently used to assess parameter uncertainty and to support probabilistic sensitivity analysis. An alternative, Gauss’s error propagation law, is rarely known but may be useful in some settings. Bootstrapping, the Cholesky decomposition method, and the error propagation law were compared regarding standard deviation estimates of a hypothetic parameter, which was derived from a regression model fitted to simulated data. Furthermore, to demonstrate its value, the error propagation law was applied to German administrative claims data. All 3 methods yielded almost identical estimates of the standard deviation of the target parameter. The error propagation law was much faster than the other 2 alternatives. Furthermore, it succeeded the claims data example, a case in which the established methods failed. In conclusion, the error propagation law is a useful extension of parameter uncertainty assessment.

Capacity Constraints and Cost-Effectiveness: A Discrete Event Simulation for Drug-Eluting Stents

Beate, J., Pfeiffer, K. P., Engelbert, T., Tarride, J.-E., Goeree, R. — Tue, 06 Oct 2009 11:34:08 PDT

Background. Waiting times for access to care, for example, for diagnostic imaging or surgery, are a highly relevant issue in health care. Waiting or deferred treatment caused by limited resource capacities can affect treatment success, quality of life, and costs. However, when treatment alternatives are compared in economic models, often unrestricted availability of resources is assumed, and dynamic changes in waiting lines remain unconsidered. The objective of this study was to evaluate the impact of potential realworld capacity restrictions and implied waiting lines on cost-effectiveness results and additional model outcomes. Methods. A case study of drug-eluting and bare-metal stent treatment illustrates the effect of hypothetical capacity limitations of daily stenting procedures. Therefore, a decisionanalytic model which allows for explicitly defined resource capacities and dynamic waiting lines was built using discrete event simulation. Cost-effectiveness, utilization, waiting time, and budgetary impact of alternative treatment scenarios are analyzed under the assumption of limited and unlimited resource capacities. Results. The compared treatment allocation scenarios in the case study demonstrate that the additional cost for waiting increases the average treatment cost per patient. The different scenarios have different impacts on waiting lines because of the number of repeated interventions. Additionally, this effect leads to changes in cost-effectiveness results for the hypothetical capacity limit. Explicitly modeled capacities allow for further analysis of capacity utilization, waiting lines, and budgetary impact. Conclusion. Our model shows that neglected limited capacities can cause wrong costeffectiveness results. Therefore, capacities should be explicitly included in decision-analytic models if there is evidence of scarcity. Key words: health economic evaluation; cost-effectiveness analysis; modeling technology; discrete event simulation; capacities; limited resources. (Med DecisMaking 20XX;XX:xx–xx)

A Discrete Event Simulation Model to Evaluate Operational Performance of a Colonoscopy Suite

Tue, 22 Sep 2009 14:00:07 PDT

Background and Aims. Colorectal cancer, a leading cause of cancer death, is preventable with colonoscopic screening. Colonoscopy cost is high, and optimizing resource utilization for colonoscopy is important. This study's aim is to evaluate resource allocation for optimal use of facilities for colonoscopy screening. Method. The authors used data from a computerized colonoscopy database to develop a discrete event simulation model of a colonoscopy suite. Operational configurations were compared by varying the number of endoscopists, procedure rooms, the patient arrival times, and procedure room turnaround time. Performance measures included the number of patients served during the clinic day and utilization of key resources. Further analysis included considering patient waiting time tradeoffs as well as the sensitivity of the system to procedure room turnaround time. Results. The maximum number of patients served is linearly related to the number of procedure rooms in the colonoscopy suite, with a fixed room to endoscopist ratio. Utilization of intake and recovery resources becomes more efficient as the number of procedure rooms increases, indicating the potential benefits of large colonoscopy suites. Procedure room turnaround time has a significant influence on patient throughput, procedure room utilization, and endoscopist utilization for varying ratios between 1:1 and 2:1 rooms per endoscopist. Finally, changes in the patient arrival schedule can reduce patient waiting time while not requiring a longer clinic day. Conclusions. Suite managers should keep a procedure room to endoscopist ratio between 1:1 and 2:1 while considering the utilization of related key resources as a decision factor as well. The sensitivity of the system to processes such as turnaround time should be evaluated before improvement efforts are made. Key words: colorectal cancer; colonoscopy; discrete event; simulation. (Med DecisMaking XXXX;XX:xx–x)

The Adoption of Cost-Effectiveness Acceptability Curves in Cost-Utility Analyses

Meckley, L. M., Greenberg, D., Cohen, J. T., Neumann, P. J. — Tue, 22 Sep 2009 14:00:08 PDT

Background.Cost-effectiveness acceptability curves (CEACs) plot the probability that one health intervention is more cost-effective than alternatives, as a function of societal willingness to pay for additional units of health (e.g., lifeyears or quality-adjusted life-years gained). Objectives. To quantify the adoption of CEACs in published cost-utility analyses (CUAs), and to identify factors associated with CEAC use. Methods. Data from the Tufts Medical Center Cost-Effectiveness Analysis Registry (www.cearegistry.org), a database with detailed information on approximately 1,400 CUAs published in the peer reviewed literature through 2006, was analyzed. The registry includes data on study origin, study methodology, reporting of results, whether CEACs were presented, and a subjective quality score. Univariate and multivariate logistic regression analyses were used to identify factors predicting CEAC use, from their introduction in 1994 through 2006. Results. Approximately 15% of CUAs published since 1994 present a CEAC. The use of CEACs has increased rapidly in recent years, from 2.1% of published CUAs in 2001 to 32.6% in 2006 (P > 0:0001). The most significant predictors of CEAC use were study quality (odds ratio [OR]: 2.26; 95% confidence interval [CI]: 1.80, 2.85), recent publication (OR: 1.99; 95% CI: 1.73, 2.29), and whether studies pertain to the UK (OR: 5.66; 95% CI: 3.67, 8.72) or Sweden (OR: 3.76; 95% CI: 1.67, 8.44). Conclusions. CEAC use is increasing in the published cost-effectiveness literature, especially in UK-based studies. Key words: cost-utility analysis (CUA); quality-adjusted life year (QALY); cost-effectiveness acceptability curve (CEAC); uncertainty analysis. (Med Decis Making XXXX;XX:xx–xx)

Patient Time Requirements for Anticoagulation Therapy with Warfarin

Jonas, D. E., Bryant Shilliday, B., Laundon, W. R., Pignone, M. — Tue, 22 Sep 2009 14:00:07 PDT

Background. Most patients receiving warfarin are managed in outpatient office settings or anticoagulation clinics that require frequent visits for monitoring. Objective. To measure the amount and value of time required of patients for chronic anticoagulation therapy with warfarin. Design/Participants. Prospective observation of a cohort of adult patients treated at a university-based anticoagulation program. Measurements. Participants completed a questionnaire and a prospective diary of the time required for 1 visit to the anticoagulation clinic, including travel, waiting, and the clinic visit. The authors reviewed subjects' medical records to obtain additional information, including the frequency of visits to the anticoagulation clinic. They used the human capital method to estimate the value of time. Results. Eighty-five subjects completed the study. The mean (median) total time per visit was 147 minutes (123). Subjects averaged 15 visits per year (14) and spent 39.0 hours (29.3) per year on their visits. Other anticoagulation-related activities, such as communication with providers, pharmacy trips, and extra time preparing food, added an average of 52.7 hours (19.0) per year. The mean annual value of patient time spent traveling, waiting, and attending anticoagulation visits was $707 (median $591). The mean annual value when also including other anticoagulation-related activities was $1799 (median $1132). Conclusions. The time required of patients for anticoagulation visits was considerable, averaging approximately 2.5 hours per visit and almost 40 hours per year. Methods for reducing patient time requirements, such as home-based testing, could reduce costs for patients, employers, and companions. Key words: anticoagulation; warfarin; time; human capital method; health economics. (Med Decis Making XXXX;XX:xx–xx)

Does One Size Fit All? Investigating Heterogeneity in Men's Preferences for Benign Prostatic Hyperplasia Treatment Using Mixed Logit Analysis

Eberth, B., Watson, V., Ryan, M., Hughes, J., Barnett, G. — Fri, 04 Sep 2009 10:36:05 PDT

Background. Most studies of bilateral arm training (BAT) did not employ a randomized controlled trial design and involved very limited functional training tasks.Objective. Compare the effects of BAT with control intervention (CI) on motor control and motor performance of the upper extremity and also functional gains in patients with chronic stroke. Methods. This 2-group randomized controlled trial with pretreatment and posttreatment measures enrolled 33 stroke patients (mean age = 53.85 years) 6 to 67 months after onset of a first stroke. They received either a BAT program concentrating on both upper extremities moving simultaneously in functional tasks by symmetric patterns or CI (control treatment) for 2 hours on weekdays for 3 weeks. Outcome measures included kinematic analyses assessing motor control strategies for unilateral and bimanual reaching and clinical measures involving the Fugl-Meyer Assessment (FMA) of motor-impairment severity and the Functional Independence Measure (FIM) and the Motor Activity Log (MAL) evaluating functional ability. Results. After treatment, the BAT group showed better temporal and spatial efficiency during unilateral and bilateral tasks and less online error correction only during the bilateral task than the control group.The BAT group showed a significantly greater improvement in the FMA than the control group but not in the FIM and MAL. Conclusions. Relative to CI, BAT improved the spatiotemporal control of the affected arm in both bilateral and unilateral tasks, decreased online corrections to perform bilateral tasks,and reduced motor impairment.These findings support the use of BAT to improve motor control and motor function of the affected upper limb in stroke patients.

Are Providers More Likely to Contribute to Healthcare Disparities Under High Levels of Cognitive Load? How Features of the Healthcare Setting May Lead to Biases in Medical Decision Making

Burgess, D. J. — Wed, 02 Sep 2009 14:11:29 PDT

Systematic reviews of healthcare disparities suggest that clinicians’ diagnostic and therapeutic decision making varies by clinically irrelevant characteristics, such as patient race, and that this variation may contribute to healthcare disparities. However, there is little understanding of the particular features of the healthcare setting under which clinicians are most likely to be inappropriately influenced by these characteristics. This study delineates several hypotheses to stimulate future research in this area. It is posited that healthcare settings in which providers experience high levels of cognitive load will increase the likelihood of racial disparities via 2 pathways. First, providers who experience higher levels of cognitive load are hypothesized to make poorer medical decisions and provide poorer care for all patients, due to lower levels of controlled processing (H1). Second, under greater levels of cognitive load, it is hypothesized that healthcare providers’ medical decisions and interpersonal behaviors will be more likely to be influenced by racial stereotypes, leading to poorer processes and outcomes of care for racial minority patients (H2). It is further hypothesized that certain characteristics of healthcare settings will result in higher levels of cognitive load experienced by providers (H3). Finally, it is hypothesized that minority patients will be disproportionately likely to be treated in healthcare settings in which providers experience greater levels of cognitive load (H4a), which will result in racial disparities due to lower levels of controlled processing by providers (H4b) and the influence of racial stereotypes (H4c).The study concludes with implications for research and practice that flow from this framework.

Can Female Adolescents Tell Whether They Will Test Positive for Chlamydia Infection?

Bruine de Bruin, W., Downs, J. S., Murray, P., Fischhoff, B. — Tue, 25 Aug 2009 13:26:48 PDT

Objectives. Having better predictors of chlamydia infection may improve health care providers’ decisions about when to provide testing for Chlamydia trachomatis (Ct). Adolescents’ probability judgments of significant life events in the next year and by age 20 y have shown promising validity, being significantly correlated with subsequent self-reports of having experienced these events. Here, the authors examine whether female adolescents’ probability judgments of having chlamydia were correlated with the objective outcome of a Ct polymerase chain reaction assay. Methods. Three hundred sexually active female adolescents were recruited from urban health care clinics in Pittsburgh. They assessed ‘‘the percent chance that you have chlamydia right now,’’ then answered questions about their demographic background and sexual history. Subsequently, the authors tested for Ct infection using a self-administered introital swab. Results. Adolescents’ probability judgments of having chlamydia ‘‘right now’’ were correlated with whether they tested positive for Ct infection, even after controlling for demographic variables and sexual history. This result held when probability judgments were dichotomized in terms of whether adolescents had assigned a zero or nonzero probability. Adolescents’ mean probability judgment was less than their infection rate, indicating that, on average, they underestimated their actual risk. Conclusions. Adolescents can tell whether they are at increased risk for chlamydia but may need better information about its absolute magnitude. Eliciting adolescents’ probability judgments of having chlamydia can add value to clinical decision making.

An Equivalent Relative Utility Metric for Evaluating Screening Mammography

Abbey, C. K., Eckstein, M. P., Boone, J. M. — Tue, 25 Aug 2009 13:26:46 PDT

Comparative studies of performance in screening mammography are often ambiguous. A new method will frequently show a higher sensitivity or detection rate than an existing standard with a concomitant increase in false positives or recalls. The authors propose an equivalent relative utility (ERU) metric based on signal detection theory to quantify screening performance in such comparisons. The metric is defined as the relative utility, as defined in classical signal detection theory, needed to make 2 systems equivalent. ERU avoids the problem of requiring a predefined putative relative utility, which has limited application of utility theory in receiver operating characteristic analysis. The metric can be readily estimated from recall and detection rates commonly reported in comparative clinical studies. An important practical advantage of ERU is that in prevalence matched populations, the measure can be estimated without an independent estimate of disease prevalence. Thus estimating ERU does not require a study with long-term follow-up to find cases of missed disease. The approach is applicable to any comparative screening study that reports results in terms of recall and detection rates, although the authors focus exclusively on screening mammography in this work. They derive the ERU from the definition of utility given in classical treatments of signal detection theory. They also investigate reasonable values of relative utility in screening mammography for use in interpreting ERU using data from a large clinical study. As examples of application of ERU, they reanalyze 2 recently published reports using recall and detection rates in screening mammography.

Eliciting Population Preferences for Mass Colorectal Cancer Screening Organization

Nayaradou, M., Berchi, C., Dejardin, O., Launoy, G. — Wed, 19 Aug 2009 17:36:05 PDT

Introduction. The implementation of mass colorectal cancer (CRC) screening is a public health priority. Population participation is fundamental for the success of CRC screening as for any cancer screening program. The preferences of the population may influence their likelihood of participation. Objectives. The authors sought to elicit population preferences for CRC screening test characteristics to improve the design of CRC screening campaigns. Methods. A discrete choice experiment was used. Questionnaires were compiled with a set of pairs of hypothetical CRC screening scenarios. The survey was conducted by mail from June 2006 to October 2006 on a representative sample of 2000 inhabitants, aged 50 to 74 years from the northwest of France, who were randomly selected from electoral lists. Questionnaires were sent to 2000 individuals, each of whom made 3 or 4 discrete choices between hypothetical tests that differed in 7 attributes: how screening is offered, process, sensitivity, rate of unnecessary colonoscopy, expected mortality reduction, method of screening test result transmission, and cost. Results. Complete responses were received from 656 individuals (32.8%). The attributes that influenced population preferences included expected mortality reduction, sensitivity, cost, and process. Participants from high social classes were particularly influenced by sensitivity. Conclusions. The results demonstrate that the discrete choice experiment provides information on patient preferences for CRC screening: improving screening program effectiveness, for instance, by improving test sensitivity (the most valued attribute) would increase satisfaction among the general population with regard to CRC screening programs. Additional studies are required to study how patient preferences actually affect adherence to regular screening programs.

The Challenge of Shared Decision Making Among Patients With Lower Literacy: A Framework for Research and Development

McCaffery, K. J., Smith, S. K., Wolf, M. — Wed, 19 Aug 2009 17:36:06 PDT

There have been major advances in techniques to increase patient involvement in health decisions with the benefits of greater involvement and shared decision making now widely recognized. However, there has been little attention in the development of tools and strategies to support patient participation among adults with lower literacy, a group with poor health knowledge, limited involvement in health decisions, and poor health outcomes. The authors put forward a framework to consider the different stages of shared health decision making and the tasks and skills required to achieve each stage. They consider where current research exists in the decision making literature and where more is needed if adults with limited literacy are to be better engaged in shared decision making in health care.

Markov Processes for the Prediction of Aircraft Noise Effects on Sleep

Basner, M., Siebert, U. — Fri, 14 Aug 2009 12:40:02 PDT

Background. Aircraft noise disturbs sleep and impairs recuperation. Authorities plan to expand Frankfurt airport. Objective. To quantitatively assess the effects of a traffic curfew (11 PM to 5 AM) at Frankfurt Airport on sleep structure. Design. Experimental sleep study; polysomnography for 13 consecutive nights. Setting. Sleep laboratory. Subjects. 128 healthy subjects, mean age (SD) 38 (13) years, range 19 to 65, 59% female. Intervention. Exposure to aircraft noise via loudspeakers. Measurements. A 6state Markov state transition sleep model was used to simulate 3 noise scenarios with first-order Monte Carlo simulations: 1) 2005 traffic at Frankfurt Airport, 2) as simulation 1 but flights between 11 PM and 5 AM cancelled, and 3) as simulation 2, with flights between 11 PM and 5 AM from simulation 1 rescheduled to periods before 11 PM and after 5 AM. Probabilities for transitions between sleep stages were estimated with autoregressive multinomial logistic regression. Results. Compared to a night without curfew, models indicate small improvements in sleep structure in nights with curfew, even if all traffic is rescheduled to periods before and after the curfew period. For those who go to bed before 10:30 PM or after 1 AM, this benefit is likely to be offset by the expected increase of air traffic during late evening and early morning hours. Limitations. Limited ecologic validity due to laboratory setting and subject sample. Conclusions. According to the decision analysis, it is unlikely that the proposed curfew at Frankfurt Airport substantially benefits sleep structure. Extensions of the model could be used to evaluate or propose alternative air traffic regulation strategies for Frankfurt Airport.

The Relative Ability of Different Propensity Score Methods to Balance Measured Covariates Between Treated and Untreated Subjects in Observational Studies

Austin, P. C. — Fri, 14 Aug 2009 12:40:02 PDT

The propensity score is a balancing score: conditional on the propensity score, treated and untreated subjects have the same distribution of observed baseline characteristics. Four methods of using the propensity score have been described in the literature: stratification on the propensity score, propensity score matching, inverse probability of treatment weighting using the propensity score, and covariate adjustment using the propensity score. However, the relative ability of these methods to reduce systematic differences between treated and untreated subjects has not been examined. The authors used an empirical case study and Monte Carlo simulations to examine the relative ability of the 4 methods to balance baseline covariates between treated and untreated subjects. They used standardized differences in the propensity score matched sample and in the weighted sample. For stratification on the propensity score, within-quintile standardized differences were computed comparing the distribution of baseline covariates between treated and untreated subjects within the same quintile of the propensity score. These quintile-specific standardized differences were then averaged across the quintiles. For covariate adjustment, the authors used the weighted conditional standardized absolute difference to compare balance between treated and untreated subjects. In both the empirical case study and in the Monte Carlo simulations, they found that matching on the propensity score and weighting using the inverse probability of treatment eliminated a greater degree of the systematic differences between treated and untreated subjects compared with the other 2 methods. In the Monte Carlo simulations, propensity score matching tended to have either comparable or marginally superior performance compared with propensity-score weighting.

Increasing the Detection and Response to Adherence Problems with Cardiovascular Medication in Primary Care through Computerized Drug Management Systems: A Randomized Controlled Trial

Wed, 12 Aug 2009 13:58:43 PDT

Background. Adherence with antihypertensive and lipid-lowering therapy is poor, resulting in an almost 2-fold increase in hospitalization. Treatment side effects, cost, and complexity are common reasons for nonadherence, and physicians are often unaware of these potentially modifiable problems. Objective. To determine if a cardiovascular medication tracking and nonadherence alert system, incorporated into a computerized health record system, would increase drug profile review by primary care physicians, increase the likelihood of therapy change, and improve adherence with antihypertensive and lipid-lowering drugs. Methods. There were 2293 primary care patients prescribed lipid-lowering or antihypertensive drugs who were randomized to the adherence tracking and alert system or active medication list alone to determine if the intervention increased drug profile review, changes in cardiovascular drug treatment, and refill adherence in the first 6 months. An intention to treat analysis was conducted using generalized estimating equations to account for clustering within physician. Results. Overall, medication adherence was below 80% for 36.3% of patients using lipid-lowering drugs and 40.8% of patients using antihypertensives at the start of the trial. There was a significant increase in drug profile review in the intervention compared to the control group (44.5% v. 35.5%; P < 0:001), a nonsignificant increase in drug discontinuations due to side effects (2.3% v. 2.0%; P = 0:61), and a reduction in therapy increases (28.5% v. 29.1%; P = 0:86). There was no significant change in refill adherence after 6 months of follow-up. Conclusion. An adherence tracking and alert system increases drug review but not therapy changes or adherence in prevalent users of cardiovascular drug treatment. Targeting incident users where adverse treatment effects are more common and combining adherence tracking and alert tools with motivational interventions provided by multidisciplinary primary care teams may improve the effectiveness of the intervention.

Satisfaction with Care: A Measure of Quality of Care in Prostate Cancer Patients

Jayadevappa, R., Schwartz, J. S., Chhatre, S., Wein, A. J., Malkowicz, S. B. — Wed, 12 Aug 2009 13:58:43 PDT

Background. Patients’ assessment of satisfaction with care, quality of care, and outcomes has become a central issue in patient-centered prostate cancer (PCa) care. We sought to analyze the association between patient-reported satisfaction with care and health-related quality of life (HRQoL) in newly diagnosed PCa patients. Methods. Prospective cohort design was used to recruit 590 newly diagnosed PCa patients from an urban academic hospital and a VA hospital. Participants completed satisfaction with care (CSQ-8) and HRQoL (SF-36 and UCLA-PCI) surveys prior to treatment and at 3, 6, 12, and 24 months’ follow-up. Cross-lagged analysis was used to ascertain the causal direction between satisfaction with care and HRQoL. Propensity scores were used to adjust for potential selection bias between treatment groups. Linear mixed models were used to analyze the association between satisfaction with care, process of care (treatment), and outcomes (generic and prostate-specific HRQoL) after adjusting for covariates. Results. Cross-lagged correlation results are consistent with a cause-effect association between HRQoL and satisfaction with care. After controlling for clinical and demographic covariates, radical prostatectomy (RP) treatment was associated with higher satisfaction with care (odds ratio [OR], 7.9; P = 0:043). Improved generic and prostate-specific HRQoL were associated with higher satisfaction with care, after adjusting for demographic and clinical covariates. Conclusion. Satisfaction with care appears to be associated with process of care and outcomes of care. Assessment of satisfaction with care is useful for evaluating the quality of PCa care. Satisfaction with care is an important arena in cancer outcomes research, whose full potential remains unexploited.

The Association between Individual Time Preferences and Health Maintenance Habits

Bradford, W. D. — Wed, 12 Aug 2009 13:58:42 PDT

Context. Encouraging healthy behaviors, including disease screening, exercise, and tobacco avoidance, has been a significant focus of clinical attention in recent decades. Little is known about the association between individual preferences with respect to time play and preventive health care use and healthy lifestyles. Objective. To determine whether rates of these health behaviors are associated with latent time preferences. Design. Interval regression analysis was used to impute individual level discount rates. The difference in means for the rates of health behaviors were assessed for high vs. low to moderate discounting groups using one-factor probit models. Participants. The 2004 wave of the Health and Retirement Survey included in a time preferences module (1,039 respondents aged 24 to 65 years). Main Outcome Measures. Rates of recent mammograms, breast exams, Pap smears, prostate exams, cholesterol testing, flu shots, and dental visits, and non-smoking status. Results. Respondents in the upper 20th percentile of the distribution have an average imputed annual discount rate of 0.335 (33.5%). High discount rate status is found to have a negative marginal association on the probability that respondents had recent mammogram use (–15.1%; P = 0.001), Pap smear use (–8.3%; P = 0.049), prostate examination use (–20.4%; P = 0.003), dental visits (–24.8%; P = 0.001), cholesterol testing (–12.4%; P = 0.001), flu shot usage (–11.1%; P = 0.005), rates of vigorous exercise (–15.1%; P = 0.001), nonsmoking status (–10.4%; P = 0.001), and undertook all measured health habits (–7%; P = 0.001). Conclusions. Differences in underlying preferences for the present over the future may be a substantial barrier for people’s propensity to adopt healthy lifestyles.

Improving Decision Making at the End of Life with Video Images

Volandes, A. E., Barry, M. J., Chang, Y., Paasche-Orlow, M. K. — Wed, 12 Aug 2009 13:58:42 PDT

Background. Decision making at the end of life is frequently complex and often filled with uncertainty. We hypothesized that people with limited health literacy would have more uncertainty about end-of-life decision making than people with adequate literacy. We also hypothesized that video images would decrease uncertainty. Design. Before and after oral survey. Participants. Subjects presenting to their primary care physicians. Methods. Subjects were asked about their preferences for end-of-life care after they heard a verbal description of advanced dementia and were asked to rate the level of their uncertainty. Subjects then viewed a video of a patient with advanced dementia and were asked again about their preferences and uncertainty. Uncertainty was measured using the Decisional Conflict Scale with score ranges from 3 (high uncertainty)to 15 (no uncertainty). Health literacy was measured using the Rapid Estimate of Adult Literacy in Medicine, and subjects were divided into 3 literacy categories: low (0–45, 6th grade and below), marginal (46– 60, 7th–8th grade), and adequate (61–66, 9th grade and above). Results. A total of 146 patients completed the interview. Prior to the video, the average uncertainty scores for subjects with low, marginal, and adequate health literacy were 10.8, 12.4, and 13.5, respectively (P < 0.0001). After the video, the 3 groups had similar uncertainty about their decisions. The average uncertainty scores for subjects with low, marginal, and adequate health literacy were 13.6, 14.1, and 14.5, respectively (P = 0.046). Conclusions. Subjects with limited health literacy expressed more uncertainty about their preferences for end-of-life care than did subjects with adequate literacy. Our video decision aid improved end-of-life decision making by decreasing uncertainty regarding subjects’ preferences, especially for those with limited literacy.

Sample Size in Obesity Trials: Patient Perspective versus Current Practice

Wed, 12 Aug 2009 13:58:43 PDT

Objective. To evaluate patient opinions on acceptable risks in exchange for a given degree of weight loss and their implications for sample size determination in obesity randomized clinical trials (RCTs). Design. Survey of patients entering RCTs for weight loss in a university-based clinical research setting and power calculations based on their responses. Participants. Men (n = 8) and women (n = 66) between 24 and 73 years of age with body mass indices ranging from 26.8 to 40.5 kg/m². Measurements. Survey responses to questions assessing the added risk of serious adverse events (SAEs) or death one is willing to assume for a given degree of weight loss. Results. For 5% and 10% weight loss against risk for death per se, the mean acceptable risk tended to be about 3.5%, but the median (0.00) and mode (0.00) suggested that for most individuals, only a risk of ≤ 1% would be acceptable. Figures, estimated dropout rates, and base rates of SAEs (including deaths) from recent obesity trials indicate that 1-year 2-group obesity RCTs would need tens of thousands of participants per group to have 80% power to detect risks that are meaningful to patients at the 2-tailed 0.05 a level. Conclusion. Patient education is needed to explain which risks are realistically detectable in RCTs so that patients may provide truly informed consent, or RCT standards should be modified to meet patients’ implicit expectations.

Use of Nomograms for Personalized Decision-Analytic Recommendations

Fu, A. Z., Cantor, S. B., Kattan, M. W. — Fri, 31 Jul 2009 15:32:54 PDT

Objective. A difficulty with applying decision analysis at the bedside is that it generally requires computer software for the calculations, which may render the method impractical. The purpose of this study was to illustrate the feasibility of developing a regression model that approximates the results from a published decision-analytic model for prostate cancer and permits bedside generation of personalized decision-analytic recommendations with a paper nomogram. Methods. The authors used the example of radical prostatectomy v. watchful waiting for patients with early-stage prostate cancer. First, they took a published decision analysis and generated recommendations using simulated data where patient baseline factors and preference scores for health states were systematically varied. Multivariable logistic regression was used to identify the parameters with strong associations with the recommendation. A reduced model was fit that excluded other preference scores except for watchful waiting. They compared the recommended management predictive accuracies from the full v. reduced model at the individual patient level for 63 men from another published study. Discrimination was assessed using receiver operating characteristic (ROC) curve analysis. A nomogram was constructed from the covariates in the reduced model. Results. The reduced logistic regression model predicted the recommendations accurately for the 63 patients, with an area under the ROC curve of 0.92. Discrimination was excellent as demonstrated by histograms. Conclusions. The authors demonstrated that logistic regression modeling allows accurate reproduction of decision-analytic recommendations with simplified calculations, which can be accomplished using a graphic nomogram. This approach should facilitate clinical decision analysis at the bedside.

Patients' Preferences for Treatment of Hepatitis C

Fraenkel, L., Chodkowski, D., Lim, J., Garcia-Tsao, G. — Mon, 27 Jul 2009 15:29:04 PDT

Background. The objective of this study was to ascertain patient preferences for treatment of hepatitis C virus (HCV). Methods. The authors recruited consecutive patients eligible for treatment of HCV and used adaptive conjoint analysis (ACA), a hybrid approach of conjoint analysis that uses both self-explicated ratings and pair-wise comparisons, to elicit preferences for pegylatedinterferon and ribavirin. They examined the association between patient characteristics and treatment preferences using the Mann-Whitney U test and w² statistic for continuous and categorical variables, respectively, and subsequently calculated adjusted odds ratios and 95% confidence intervals using logistic regression. Results. A total of 140 subjects completed the ACA task. The mean (+SD) age of the sample was 51+8 y; 85% were male, and 59% were white. When described as being associated with mild side effects, 67% (n = 94) of subjects preferred treatment for HCV. The percentage of subjects preferring therapy decreased to 51% (n = 72) when it was described as being associated with severe side effects. Preferences for treatment of HCV were stronger among subjects with a higher perceived risk of developing cirrhosis, more severe underlying liver disease, and worse HCV-related quality of life. Subjects having more severe disease placed greater weight on the importance of expected benefits and less on the risk of toxicity compared with those with mild or no fibrosis. Conclusions. Whether to choose treatment for HCV is a difficult decision for many patients. Treatment is usually recommended for those with moderate to severe liver disease, and these results demonstrate that most patients’ preferences are concordant with this practice.

Evaluation of Imputation Methods in Ovarian Tumor Diagnostic Models Using Generalized Linear Models and Support Vector Machines

Dimou, I., Van Calster, B., Van Huffel, S., Timmerman, D., Zervakis, M. — Wed, 15 Jul 2009 15:08:58 PDT

Neglecting missing values in diagnostic models can result in unreliable and suboptimal performance on new data. In this study, the authors imputed missing values for the CA-125 tumor marker in a large data set of ovarian tumors that was used to develop models for predicting malignancy. Four imputation techniques were applied: regression imputation, expectation-maximization, data augmentation, and hotdeck. Models using the imputed data sets were compared with models without CA-125 to investigate the important clinical issue concerning the necessity of CA125 information for diagnostic models and with models using only complete cases to investigate differences between imputation and complete case strategies for missing values. The models are based on Bayesian generalized linear models (GLMs) and Bayesian least squares support vector machines. Results indicate that the use of CA-125 resulted in small, clinically nonsignificant increases in the AUC of diagnostic models. Minor differences between imputation methods were observed, and imputing CA-125 resulted in minor differences in the AUC compared with complete case analysis (CCA). However, GLM parameter estimates of predictor variables often differed between CCA and models based on imputation. The authors conclude that CA-125 is not indispensable in diagnostic models for ovarian tumors and that missing value imputation is preferred over CCA.

A Maximum Likelihood Estimator of a Markov Model for Disease Activity in Crohn's Disease and Ulcerative Colitis for Annually Aggregated Partial Observations

Wed, 15 Jul 2009 15:08:59 PDT

Crohn’s disease (CD) and ulcerative colitis (UC) are chronic inflammatory bowel diseases that have a remitting, relapsing nature. During relapse, they are treated with drugs and surgery. The present study was based on individual data from patients diagnosed with CD or UC at Her-lev University Hospital, Copenhagen, Denmark, during 1991 to 1993. The data were aggregated over calendar years; for each year, the number of relapses and the number of surgical operations were recorded. Our aim was to estimate Markov models for disease activity in CD and UC, in terms of relapse and remission, with a cycle length of 1 month. The purpose of these models was to enable evaluation of interventions that would shorten relapses or postpone future relapses. An exact maximum likelihood estimator was developed that disaggregates the yearly observations into monthly transition probabilities between remission and relapse. These probabilities were allowed to be dependent on the time since start of relapse and on the time since start of remission, respectively. The estimator, initially slow, was successfully optimized to shorten the execution time. The estimated disease activity model for CD fits well to observed data and has good face validity. The disease activity model is less suitable for UC due to its transient nature through the presence of curative surgery.

Dimensions of Design Space: A Decision-Theoretic Approach to Optimal Research Design

Conti, S., Claxton, K. — Wed, 15 Jul 2009 15:08:59 PDT

Bayesian decision theory can be used not only to establish the optimal sample size and its allocation in a single clinical study but also to identify an optimal portfolio of research combining different types of study design. Within a single study, the highest societal payoff to proposed research is achieved when its sample sizes and allocation between available treatment options are chosen to maximize the expected net benefit of sampling (ENBS). Where a number of different types of study informing different parameters in the decision problem could be conducted, the simultaneous estimation of ENBS across all dimensions of the design space is required to identify the optimal sample sizes and allocations within such a research portfolio. This is illustrated through a simple example of a decision model of zanamivir for the treatment of influenza. The possible study designs include: 1) a single trial of all the parameters, 2) a clinical trial providing evidence only on clinical endpoints, 3) an epidemiological study of natural history of disease, and 4) a survey of quality of life. The possible combinations, samples sizes, and allocation between trial arms are evaluated over a range of cost-effectiveness thresholds. The computational challenges are addressed by implementing optimization algorithms to search the ENBS surface more efficiently over such large dimensions.

Evaluating the Claim of Enhanced Persistence: The Case of Osteoporosis and Implications for Payers

Kelton, C. M.L., Pasquale, M. K. — Fri, 19 Jun 2009 11:07:10 PDT

Cost-effectiveness analysis (CEA) has been widely used in evaluating treatments for osteoporosis. To study the claim of enhanced persistence, this research determined the effects of persistence (the proportion of individuals who remain on treatment) and efficacy on incremental cost-effectiveness ratios (ICERs) for bisphosphonate treatment relative to no bisphosphonate treatment in the United States. For 2 age groups, 55 to 59 and 75 to 79, the authors relied on published fracture rates and applied them to 1000 postmenopausal osteoporotic patients with bone mineral density (BMD) T score ≤ -2.5 during 3 years of treatment. After developing an algebraic ICER, with effectiveness measured by either quality-adjusted life years (QALYs) gained or number of fractures averted, they determined the effects of persistence and efficacy and then calibrated the model to variable estimates from the literature. For the younger (older) cohort, the cost per fracture averted was $66,606 ($18,256), consistent with a validated Markov simulation model. The effect of a 1 percentage point change in vertebral efficacy was 24 (5) times the effect of a 1 percentage point change in persistence for the younger cohort when QALYs (fractures) were involved. Nonvertebral efficacy had approximately 27 (9) times the effect of persistence. For the older cohort, the ratios were 15 (4.5) and 33 (10) for vertebral and non-vertebral fractures, respectively. In evaluating the claim of enhanced persistence, formulary decision makers need to exercise caution to ensure that efficacy is not compromised. Two drugs would have to be virtually identical in efficacy for better persistence to improve cost-effectiveness.

Nearest-Neighbor and Logistic Regression Analyses of Clinical and Heart Rate Characteristics in the Early Diagnosis of Neonatal Sepsis

Xiao, Y., Griffin, P., Lake, D. E., Moorman, J. R. — Thu, 18 Jun 2009 08:20:19 PDT

Objectives. To test the hypothesis that nearest-neighbor analysis adds to logistic regression in the early diagnosis of late-onset neonatal sepsis. Design. The authors tested methods to make the early diagnosis of neonatal sepsis using continuous physiological monitoring of heart rate characteristics and intermittent measurements of laboratory values. First, the hypothesis that nearest-neighbor analysis makes reasonable predictions about neonatal sepsis with performance comparable to an existing logistic regression model was tested. The most parsimonious model was systematically developed by excluding the least efficacious clinical data. Second, the authors tested the hypothesis that a combined nearest-neighbor and logistic regression model gives an outcome prediction that is more plausible than either model alone. Training and test data sets of heart rate characteristics and laboratory test results over a 4-y period were used to create and test predictive models. Measurements. Nearest-neighbor, regression, and combination models were evaluated for discrimination using receiver-operating characteristic areas and for fit using the Wald statistic. Results. Both nearest-neighbor and regression models using heart rate characteristics and available laboratory test results were significantly associated with imminent sepsis, and each kind of model added independent information to the other. The best predictive strategy employed both kinds of models. Conclusion. The authors propose nearest-neighbor analysis in addition to regression in the early diagnosis of subacute, potentially catastrophic illnesses such as neonatal sepsis, and they recommend it as an approach to the general problem of predicting a clinical event from a multivariable data set.

Estimating Progression Rates for Human Papillomavirus Infection From Epidemiological Data

Jit, M., Gay, N., Soldan, K., Choi, Y. H., Edmunds, W. J. — Fri, 12 Jun 2009 16:05:10 PDT

A Markov model was constructed in order to estimate type-specific rates of cervical lesion progression and regression in women with high-risk human papillomavirus (HPV). The model was fitted to age-and type-specific data regarding the HPV DNA and cytological status of women undergoing cervical screening in a recent screening trial, as well as cervical cancer incidence. It incorporates different assumptions about the way lesions regress, the accuracy of cytological screening, the specificity of HPV DNA testing, and the age-specific prevalence of HPV infection. Combinations of assumptions generate 162 scenarios for squamous cell carcinomas and 54 scenarios for adenocarcinomas. Simulating an unscreened cohort of women infected with high-risk HPV indicates that the probability of an infection continuing to persist and to develop into invasive cancer depends on the length of time it has already persisted. The scenarios and parameter sets that produce the best fit to available epidemiological data provide a basis for modeling the natural history of HPV infection and disease.

The Cost-Effectiveness of an RCT to Establish Whether 5 or 10 Years of Bisphosphonate Treatment Is the Better Duration for Women With a Prior Fracture

Tue, 09 Jun 2009 09:02:04 PDT

Purpose. Five years of bisphosphonate treatment have proven efficacy in reducing fractures. Concerns exist that long-term bisphosphonate treatment may actually result in an increased number of fractures. This study evaluates, in the context of England and Wales, whether it is cost-effective to conduct a randomized controlled trial (RCT) and what sample size may be optimal to estimate the efficacy of bisphosphonates in fracture prevention beyond 5 years. Method. An osteoporosis model was constructed to evaluate the cost-effectiveness of extending bisphosphonate treatment from 5 years to 10 years. Two scenarios were run. The 1st uses long-term efficacy data from published literature, and the 2nd uses distributions elicited from clinical experts. Results of a proposed RCT were simulated. The expected valueofsampleinformation techniquewas appliedto calculate the expected net benefit of sampling from conducting such an RCT at varying levels of participants per arm and to compare this with proposed trial costs. Results. Without further information, the better duration of bisphosphonate treatment was estimated to be 5 years using the published data but 10 years using the elicited expert opinions, although in both cases uncertainty was substantial. The net benefit of sampling was consistently high when between 2000 and 5000 participants per arm were recruited. Conclusions. An RCT to evaluate the long-term efficacy of bisphosphonates in fracture prevention appears to be cost-effective for informing decision making in England and Wales.

Price, Performance, and the FDA Approval Process: The Example of Home HIV Testing

Paltiel, A. D., Pollack, H. A. — Fri, 08 May 2009 12:24:21 PDT

The Food and Drug Administration (FDA) is considering approval of an over-the-counter, rapid HIV test for home use. To support its decision, the FDA seeks evidence of the test’s performance. It has asked the manufacturer to conduct field studies of the test’s sensitivity and specificity when employed by untrained users. In this article, the authors argue that additional information should be sought to evaluate the prevalence of undetected HIV in the end-user population. The analytic framework produces the elementary but counterintuitive finding that the performance of the home HIV test— measured in terms of its ability to correctly detect the presence and absence of HIV infection among the people who purchase it—depends critically on the manufacturer’s retail price. This finding has profound implications for the FDA’s approval process. Key words: HIV testing; FDA; predictive value. (Med Decis Making XXXX;XX:xx-xx)

The Language of Prognostication in Intensive Care Units

White, D. B., Engelberg, R. A., Wenrich, M. D., Lo, B., Curtis, J. R. — Wed, 27 Aug 2008 16:06:46 PDT

Rationale. Although misunderstandings about prognosis are common in intensive care units (ICUs), little is known about how physicians actually communicate prognostic information. Objectives. The authors sought to 1) develop a framework to describe the language physicians use to disclose prognosis, 2) determine whether physicians frame prognostic statements as estimates for populations or estimates for individual patients, and 3) determine whether physicians use the recommended "ask-tell-ask" approach when discussing prognosis. Methods. The authors conducted a multicenter, cross-sectional study of 51 audiotaped physician-family conferences about life support decisions in ICUs. They identified each prognostic statement and used grounded theory methods to develop a framework to understand the language physicians use to communicate prognosis. Main Results. Physicians prognosticated in 50 of 51 conferences. When discussing prognosis, physicians used qualitative probability statements in 72% (36/50) of conferences, numeric statements in 20% (10/50), absolute statements in 13% (4/32), and nonprobabilistic statements in 40% (20/50). Physicians exclusively used population-based language in 10% (5/50) of conferences, single-event probability statements in 62% (31/50), and both in 28% (14/ 50). In only 2% (1/50) of conferences did physicians ask whether the family wished to hear prognostic information prior to discussing it, and in only 14% of conferences (7/50) did physicians check to verify that families understood the prognostic information. Conclusions. There is considerable variability in the language used by physicians to disclose prognosis, with only 20% of physicians using quantitative terms. Very few physicians checked whether families understood prognostic information. These findings may provide potential targets for interventions to improve communication about prognosis in ICUs. Key words: intensive care units; prognostication; communication; physicians. (Med Decis Making XXXX;XX:xx–xx)

Modeling HUI2 Health State Preference Data Using a Nonparametric Bayesian Method

Kharroubi, S. A., McCabe, C. — Thu, 12 Jun 2008 15:28:16 PDT

This article reports the application of a recently described approach to modeling health state valuation data and the impact of the respondent characteristics on health state valuations. The approach applies a nonparametric model to estimate a Bayesian Health Utilities Index Mark 2 (HUI2) health state valuation algorithm. The data set is the UK HUI2 valuation study, in which a sample of 51 states defined by the HUI2 was valued by a sample of the UK general population using standard gamble. The article reports the application of the nonparametric model and compares it to the original model estimated using a conventional parametric random effects model. Advantages of the nonparametric model are that it can be used to predict scores in populations with different distributions of characteristics than observed in the survey sample and that it allows for the impact of respondent characteristics to vary by health state. The results suggest an important age effect, with sex having some effect but the remaining covariates having no discernable effect. The article discusses the implications of these results for future applications of the HUI2 and further work in this field. Key words: preference-based health measure; HUI2; covariates; nonparametric Bayesian methods. (Med Decis Making XXXX; XX:xx–xx)

Health Utility Bias: A Systematic Review and Meta-Analytic Evaluation

Doctor, J. N., Bleichrodt, H., Lin, H. J. — Thu, 12 Jun 2008 15:28:17 PDT

Background. A common assertion is that rating scale (RS) values are lower than both standard gamble (SG) and time tradeoff (TTO) values. However, differences among these methods may be due to method specific bias. Although SG and TTOs suffer systematic bias, RS responses are known to depend on the range and frequency of other health states being evaluated. Over many diverse studies this effect is predicted to diminish. Thus, a systematic review and data synthesis of RS-TTO and RS-SG difference scores may better reveal persistent dissimilarities. Purpose. The purpose of this study was to establish through systematic review and meta-analysis the net effect of biases that endure over many studies of utilities. Methods. A total of 2206 RS and TTO and 1318 RS and SG respondents in 27 studies of utilities participated. MEDLINE was searched for data from 1976 to 2004, complemented by a hand search of full-length articles and conference abstracts for 9 journals known to publish utility studies, as well as review of results and additional recommendations by 5 outside experts in the field. Two investigators abstracted the articles. We contacted the investigators of the original if required information was not available. Results. No significant effect for RS and TTO difference scores was observed: effect size (95% confidence interval [CI]) =0.04 (-0.02, 0.09). In contrast, RS scores were significantly lower than SG scores: effect size (95% CI)=-0:23 (-0:28, -0:19). Correcting SG scores for 3 known biases (loss aversion, framing, and probability weighting) eliminated differences between RS and SG scores: effect size (95% CI)=0:01 (-0:03, 0:05). Systematic bias in the RS method may exist but be heretofore unknown. Bias correction formulas were applied to mean not individual utilities. Conclusions. The results of this study do not support the common view that RS values are lower than TTO values, may suggest that TTO biases largely cancel, and support the validity of formulas for correcting SG bias. Key words: utility measurement; rating scale; category scale; time tradeoff; standard gamble. (Med Decis Making XXXX;XX:xx–xx)

Do Decision Biases Predict Bad Decisions? Omission Bias, Naturalness Bias, and Influenza Vaccination

DiBonaventura, M. d., Chapman, G. — Tue, 03 Jun 2008 08:41:40 PDT

Purpose. Numerous studies using hypothetical vignettes have demonstrated decision biases, or deviations from utility theory. Do people who commit biases in questionnaire studies make worse real-world decisions than do less biased people? Methods. Two-hundred and seventy university faculty and staff participated in a questionnaire study in which they reported whether they accepted a free flu vaccine offered at their work place. Flu vaccine acceptance was the measure of real-world decision making. Participants responded to 3 hypothetical scenarios. Two scenarios measured the omission bias and described a vaccine (scenario 1) and a medication (scenario 2) that prevented a negative health outcome, but which could itself cause the negative health outcome. The omission bias is a preference for not vaccinating or medicating even when the vaccine/medication lowers the total risk of the negative outcome. A 3rd scenario measured the naturalness bias by presenting a choice between 2 chemically identical medications, one extracted from a natural herb and the other synthesized in a laboratory. Preference for the natural medication indicated a naturalness bias. Results. The results indicated that a substantial proportion of participants exhibited these biases and participants who exhibited these biases were less likely to accept the flu vaccine. Conclusions. To the extent that declining a free flu vaccine is a worse real-world decision, people who demonstrate the naturalness and omission biases in hypothetical scenarios make worse real-world decisions. Key words: patient decision making; decision aids/tools; detailed methodology; heuristics and biases; judgment and decision psychology; detailed methodology; infectious disease; internal medicine; application areas. (Med Decis Making XXXX;XX:xx–xx)