Medical Decision Making http://mdm.sagepub.com
Highlights of This Issue Med Decis Making 2007; 27; 345 DOI: 10.1177/0272989X070270040101 The online version of this article can be found at: http://mdm.sagepub.com
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HIGHLIGHTS OF THIS ISSUE
HEALTH CARE DISPARITIES
Medicaid, Medicare, and the Michigan Tumor Registry: A Linkage Strategy Cathy J. Bradley, PhD, Charles W. Given, PhD, Zhehui Luo, PhD, Caralee Roberts, PhD, Glenn Copeland, Beth A. Virnig, PhD
Reducing disparities is at the forefront of the nation’s health care agenda. The disparities literature calls for a data infrastructure that can track progress toward reducing differences in health outcomes due to race and income. Bradley and colleagues describe a strategy for linking Medicaid, Medicare, and Tumor Registry data for the purposes of studying disparities in cancer diagnosis, quality of care, and survival. They create an expansive data set reflecting the Medicare and Medicaid medical service use and outcomes for a cohort of Michigan individuals aged 65 years and older diagnosed with cancer, and they show how others can create similar data sets in their states. This data set serves as a cornerstone of a health outcomes data infrastructure. The methodology described may serve as a model for other researchers seeking to create a similar data set in their state.
DECISION MAKING IN THE DESIGN OF PHARMACEUTICAL TRIALS
The Decision to Conduct a Head-to-Head Comparative Trial: A Game-Theoretic Analysis Edward C. Mansley, PhD, Elamin H. Elbasha, PhD, Steven M. Teutsch, MD, MPH, Marc L. Berger, MD
The Medicare Modernization Act calls on the Agency for Healthcare Research and Quality to conduct research related to the comparative effectiveness of health care items and services, including prescription drugs. This reinforces earlier calls for head-to-head comparative trials of clinically relevant treatment alternatives. Using a game-theoretic model, Mansley and colleagues explore a pharmaceutical company’s decision to conduct such trials. The model suggests that an important factor affecting this decision is the potential loss in market share and profits following a result of inferiority or comparability. This hidden cost is higher for the market leader than the market follower, making it less likely that the leader will choose to conduct a trial. The model also suggests that in a full-information environment, it will never be the case that both firms choose to conduct such a trial. Furthermore, if market shares and the probability of proving superiority are similar for both firms, it is quite possible that neither firm will choose to conduct a trial. Finally, the results indicate that incentives to offset the direct cost of a trial can prevent a no-trial equilibrium, even when both firms face the possibility of an inferior outcome.
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HIGHLIGHTS OF THIS ISSUE
Improving the Decision to Pursue a Phase 3 Clinical Trial by Adjusting for Patient-Specific Factors in Evaluating Phase 2 Treatment Efficacy Data Glenn Heller, PhD, Michael W. Kattan, PhD, Howard I. Scher, MD
The authors propose a model-based approach for analyzing the results of a phase 2 trial that addresses the question of whether the current treatment provides a clinically significant improvement over prior treatments in the population. The proposed test statistic computes the difference between the observed outcome of the current treatment and the predicted outcome based on a model of the historical data. If the model provides an accurate description of the data, then use of this method should improve the decision whether to proceed to a phase 3 clinical trial.
JUDGMENT AND DECISION MAKING
Relative Influence of Antibiotic Therapy Attributes on Physician Choice in Treating Acute Uncomplicated Pyelonephritis Jessina C. McGregor, PhD, Anthony D. Harris, MD, MPH, Jon P. Furuno, PhD, Douglas D. Bradham, DrPh, Eli N. Perencevich, MD, MS
Reducing excess duration of antibiotic therapy is a strategy for limiting the spread of antibiotic resistance, but altering physician practice to accomplish this requires knowledge of the factors that influence physician antibiotic choice. In a conjoint analysis survey and proportional hazards regression of predictors of choice of antibiotic, McGregor and colleagues found that physicians were willing to accept increases in treatment failure to reduce the number of days of diarrhea, a common side effect. They suggest that efforts to encourage physicians to choose shorter treatment durations should emphasize reduced treatment-associated side effects.
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HIGHLIGHTS OF THIS ISSUE
UTILITIES AND PREFERENCES
Quantification of Health States with Rank-Based Nonmetric Multidimensional Scaling Paul F. M. Krabbe, PhD, Joshua A. Salomon, PhD, Christopher J. L. Murray, MD, PhD
Using data from a representative sample (n = 212) of the Dutch population, Krabbe and colleagues introduce an indirect method for valuing health states that may offer an attractive alternative to direct elicitation. The method is based on ordinal data collection techniques combined with scaling models. The rank-based values explain 98% of the variance in the visual analog scale values.
Extrinsic Goals and Time Tradeoff
Abnormal Outcomes Following Cervical Cancer Screening: Event Duration and Health Utility Loss Ralph P. Insinga, PhD, Andrew G. Glass, MD, Evan R. Myers, MD, MPH, Brenda B. Rush, RN
In this study, Insinga and colleagues assess the health and psychosocial burdens associated with follow-up for abnormal Papanicolaou test results. They use administrative and cytopathology data for women to calculate the time each woman spent with various cytologic and histologic diagnoses, then combine this information with utility weights to estimate the total loss of quality-adjusted life-years per episode of care. They find that for women with a false-positive result (n = 722), the average duration of follow-up is 10 months. Total quality-adjusted life-year losses per episode of care are estimated to be 0.11 for all 3 grades of cervical intraepithelial neoplasia and 0.04 for a false-positive Papanicolaou test result.
Marjon van der Pol, PhD, Alan Shiell, PhD
The authors evaluate the hypothesis that the extrinsic goal of seeing one’s children through to maturity will affect the value 30 recent mothers placed on different health states as measured by the time tradeoff method. They find that parenthood affects how many years of life one will trade for better health but not whether one will trade in the 1st place. This conclusion became apparent only when the quantitative time tradeoff data were combined with information from interviews with the mothers. Although some women suggested that the goal of seeing their children through to maturity had motivated their responses to the time tradeoff, the interviews paint a more complicated and nuanced picture of what drives a person’s responses to health valuation surveys.
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HIGHLIGHTS OF THIS ISSUE
RISK ASSESSMENT
Does Concordance with Guideline Triage Recommendations Affect Clinical Care of Patients with Possible Acute Coronary Syndrome? David A. Katz, MD, MSc, Jeffery Dawson, ScD, Joni R. Beshansky, RN, MPH, Peter S. Rahko, MD, Tom P. Aufderheide, MD, Mark Bogner, MD, Hocine Tighouart, MS, Harry P. Selker, MD, MSPH
More than 5 million people present to U.S. emergency departments annually for evaluation of chest pain and other symptoms suggestive of acute coronary syndrome (ACS). There remain fundamental questions concerning the safety and utility of guidelines for triage of emergency department patients with symptoms of possible ACS. Katz and colleagues assess whether discharge of low-risk patients and admission of intermediate- to high-risk patients to a monitored bed improves follow-up care and 30-day mortality. They analyze data from 7466 adults who presented with symptoms of possible ACS during the period from 1993 to 2001. They find that discharge to home from the emergency department is not associated with a higher risk of death and does not increase the need for emergency care or hospitalization during followup in low-risk patients. They also find, however, that 1.7% of discharged low-risk patients have confirmed ACS. In intermediate- to high-risk patients, admission to a monitored bed is not associated with a lower risk of death, but it significantly reduces the need for emergency department revisits. This analysis supports recommendations to discharge low-risk emergency department patients with symptoms of possible ACS but demonstrates the need for special precautions (e.g., arranging timely follow-up in the clinic or performing additional diagnostic studies in the emergency department or in the hospital). It also confirms the benefit of admitting emergency department patients with intermediate- to high-risk characteristics to a monitored bed.
A Cautionary Note on Data Sources for Evidence-Based Clinical Decisions: Warfarin and Stroke Prevention Richard Thomson, MD, Martin Eccles, MD, Ruth Wood, MSc, David J. Chinn, PhD
In this article, Thomson and colleagues show that community-based cohorts give lower stroke risk estimates than those calculated with prediction equations that have been incorporated into commonly used practice guidelines. Using communityderived risks would lead to fewer patients’ being treated with warfarin than guidance derived from randomized trials. This raises the debate about appropriate sources of data for risk assessment to support risk communication and effective clinical decisions.
METHODOLOGY
Calculating Partial Expected Value of Perfect Information via Monte Carlo Sampling Algorithms Alan Brennan, MSc, Samer Kharroubi, PhD, Anthony O’Hagan, PhD, Jim Chilcott, MSc
Partial expected value of perfect information calculations can quantify the value of learning about particular subsets of uncertain parameters in decision models. In this article, Brennan and colleagues study the limitations of alternative computational approaches and set out several remaining areas for methodological development.
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HIGHLIGHTS OF THIS ISSUE
Cost-Effectiveness Analysis Using Data from Multinational Trials: The Use of Bivariate Hierarchical Modeling Andrea Manca, PhD, Paul C. Lambert, PhD, Marc Sculpher, PhD, Nigel Rice, PhD
In multinational trials, differences in clinical practice, patient case mix, and the unit costs of health care resources may account for differences in the results among countries. Standard analytical approaches to cost-effectiveness analysis (CEA) ignore the presence of between-country variability in the results of multinational trials. To correct this problem, Manca and colleagues advocate the use of Bayesian bivariate hierarchical modeling to analyze multinational costeffectiveness data. Using data from a CEA based on a large, multinational, randomized controlled trial, the authors illustrate how the proposed methods facilitate a more accurate estimation of the overall and country-specific incremental cost-effectiveness results compared to standard analysis. Country-specific results can then be used to assess the variability by location of the study conclusions while controlling for differences in country-specific and patient-specific characteristics.
A Critique and Impact Analysis of Decision Modeling Assumptions Jonathan Karnon, PhD, Alan Brennan, MSc, Ron Akehurst, Hon MFPHM
Karnon and colleagues criticize a previously published (2002) cost-effectiveness analysis of clopidogrel, aspirin, or both for secondary prevention of coronary disease. They argue that although the article has significant flaws, it has met widely accepted guidelines for the practice of pharmacoeconomic analyses. The authors call for further development and stricter application of guidelines for the conduct of economic evaluations.
In an editorial, Christopher McCabe argues that recent guidelines for conducting pharmacoeconomic analyses are sufficient to address the issues raised in Karnon and colleagues’ article. A response from Gaspoz, the first author of the 2002 costeffectiveness analysis, will appear in a forthcoming issue of Medical Decision Making.
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