C. Specify the Assessment Problem

One of the most important aspects of an HTA is to specify clearly the problem(s) or question(s) to be addressed; this will affect all subsequent aspects of the assessment. An assessment group should have an explicit understanding of the purpose of the assessment and who the intended users of the assessment are. This understanding might not be established at the outset of the assessment; it may take more probing, discussion and clarification.

The intended users or target audiences of an assessment should affect the content, presentation, and dissemination of results of the HTA. Clinicians, patients, politicians, researchers, hospital managers, company executives, and others have different interests and levels of expertise. They tend to have varying concerns about the effects or impacts of health technologies (health outcomes, costs, social and political effects, etc.). They also have different needs regarding the scientific or technical level of reports, the presentation of evidence and findings, and the format (e.g., length and appearance) of reports.

When the assessment problem and intended users have been specified, they should be reviewed by the requesting agency or sponsors of the HTA. The review of the problem by the assessment program may have clarified or focused the problem in a way that differs from the original request. This clarification may prompt a reconsideration or restatement of the problem before the assessment proceeds.

1. Problem Elements

There is no single correct way to state an assessment problem. The elements typically include specifying most or all of the following:

• Health problem of interest
• Patient population (including subgroups as appropriate)
• Technology of interest
• Comparator(s)
• Setting of care
• Provider/clinician delivering the intervention(s)
• Properties, impacts, or outcomes
• Timeframe, duration, or follow-up period
• Timeframe, duration, or follow-up period
• Study design or type of evidence/data to be included in the HTA
• Target audiences for the HTA findings

One commonly used framework is known as PICOTS (sometimes only PICO or PICOT): Population, Intervention(s), Comparator(s), Outcome(s), Timing, and Study design (Counsell 1997). This framework can be used for describing individual studies or HTAs that might examine evidence from multiple studies. For example, a basic specification of one assessment problem would be the following. (This example uses some characteristics of a particular RCT [Stewart 2005].)

• Population: males and females age 55-75 years with mild hypertension, i.e., diastolic blood pressure 85-99 mm Hg, systolic blood pressure 130-159 mm Hg; no other serious health problems
• Intervention: standardized, moderate exercise program (aerobic and resistance training)
• Comparator: usual physical routine and diet
• Outcomes: changes in: general and abdominal obesity, systolic blood pressure, diastolic blood pressure, aerobic fitness, aortic stiffness (measured as aortofemoral pulse-wave velocity)
• Timing: 6-24 months
• Study design: randomized controlled trials

2. Analytic Frameworks for Presenting HTA Problems

A useful graphical means of presenting an assessment problem is an “analytic framework,” sometimes known as a “causal pathway.” Analytic frameworks depict direct and indirect relationships between interventions and outcomes. Although often used to present clinical interventions for health problems, they can be used as well for other types of interventions in health care.

Analytic frameworks provide clarity and explicitness in defining the key questions to be addressed in an HTA, and draw attention to important relationships for which evidence may be lacking. They can be useful tools to formulate or narrow the focus of an assessment problem. For a clinical problem, an analytic framework typically includes a patient population, one or more alternative interventions, intermediate outcomes (e.g., biological markers), health outcomes, and other elements as appropriate. In instances where a topic involves a single intervention for narrowly defined indications and outcomes, these frameworks can be relatively straightforward. However, given the considerable breadth and complexity of some HTA topics, which may cover multiple interventions for broadly defined health problem (e.g., screening, diagnosis, and treatment of osteoporosis in various population subgroups), analytic frameworks can be detailed.

An example of an analytic framework of the impact of a diagnostic test on health outcomes is shown in Box VI-4. In particular, this framework presents a series of key questions intended to determine whether testing for a particular genotype in adults with depression entering treatment with selective serotonin reuptake inhibitors (SSRIs) will have an impact on health outcomes. The framework includes an overarching key question about the impact of the test on outcomes, as well as a series of linked key questions about the accuracy of the test; its ability to predict metabolism of SSRIs, efficacy of SSRIs, and risk of adverse drug reactions; the test’s impact on treatment decisions; and the ultimate impact on health outcomes.

Box VI-4. Analytic Framework: CYP450 Genotype Testing for Selective Serotonin Reuptake Inhibitors

The numbers above correspond to the following key questions:

1. Overarching question: Does testing for cytochrome P450 (CYP450) polymorphisms in adults entering selective serotonin reuptake inhibitor (SSRI) treatment for nonpsychotic depression lead to improvement in outcomes, or are testing results useful in medical, personal, or public health decision-making?
2. What is the analytic validity of tests that identify key CYP450 polymorphisms?
3. Clinical validity: a: How well do particular CYP450 genotypes predict metabolism of particular SSRIs? b: How well does CYP450 testing predict drug efficacy? c: Do factors such as race/ethnicity, diet, or other medications, affect these associations?
4. Clinical utility: a: Does CYP450 testing influence depression management decisions by patients and providers in ways that could improve or worsen outcomes? b: Does the identification of the CYP450 genotypes in adults entering SSRI treatment for nonpsychotic depression lead to improved clinical outcomes compared to not testing? c: Are the testing results useful in medical, personal, or public health decision-making?
5. What are the harms associated with testing for CYP450 polymorphisms and subsequent management options?

Source: Teutsch SM, Bradley LA, Palomaki GE, et al. The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) initiative: methods of the EGAPP Working Group. Genet Med. 2009;11(1):3-14.