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Pediatric Clinics of North America - CIPERJ

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DECISION ANALYSIS IN PEDIATRIC HEMATOLOGY<br />

291<br />

Fig. 2. Basic structure and components <strong>of</strong> a Markov model, using the example <strong>of</strong> a patient who<br />

has DVT who can be treated with anticoagulant #1 or #2. Four possible Markov, or health,<br />

states are included.<br />

Usually, the exact probabilities cannot be estimated with certainty. Therefore,<br />

the values that estimate the probabilities best are used in the original,<br />

or base-case, analysis. In sensitivity analysis (discussed later), each probability<br />

is varied over an estimated range. A rigorous literature search is performed<br />

using a hierarchy <strong>of</strong> sources (case series / large cohort studies / prospective<br />

randomized trials / systematic reviews), and the quality and applicability <strong>of</strong><br />

each source should be determined [10]. Probabilities must be assigned to each<br />

branch emanating from a chance node, and for each chance node, the sum <strong>of</strong><br />

the probabilities must be equal to 1. In some cases there may be insufficient<br />

data in the medical literature to inform every chance node in a decision<br />

analysis model. Investigators then may turn to expert or personal opinion<br />

to generate a probability estimate. Although these estimates certainly can<br />

be rigorously tested later in sensitivity analysis, the need to use them does<br />

decrease the validity <strong>of</strong> the technique.<br />

Once the optimal strategy is identified in a decision analysis study, costs<br />

can be added to the model to understand the cost-effectiveness or costutility<br />

<strong>of</strong> that strategy compared with others. When performing a cost-effectiveness<br />

analysis, an investigator should capture all health care use costs<br />

and the productivity loss <strong>of</strong> patients’ caregivers [11]. It also is important<br />

to differentiate cost data from charge data. Actual cost data always are preferred<br />

in decision analysis models, as charge data can be arbitrary and <strong>of</strong>ten<br />

depend highly on a third-party payer or treatment setting. A popular source<br />

for medication costs is the Drug Topics Red Book, an annual reference reporting<br />

the average wholesale price <strong>of</strong> prescription and over-the-counter<br />

medications [12]. In the United States, Medicare and Medicaid reimbursement<br />

data <strong>of</strong>ten are considered the best estimate <strong>of</strong> health care costs. Average<br />

hospitalization costs can be derived from Medicare and Medicaid

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