Construct validity assesses how effectively something measures what it is supposed to measure. For example, how well does the quality-of-life instrument NEI-VFQ-25 [30] for ocular diseases actually measure the quality of life associated with neovascular macular degeneration?

Risk Reduction

The two variants of risk reduction are absolute risk reduction and relative risk reduction [24]. They produce very different outcomes and are often confused.

Absolute risk reduction (ARR) is defined as [(Control event rate)—(treatment event rate)]. For example, if an intervention reduces the incidence of blindness in a cohort of 100 treated people from 10% to 5%, the ARR=10%−5%=5%, or a 5% reduction in blindness among the entire cohort.

Number needed to treat. The ratio of 1.0/ARR is the number of patients needed to treat to obtain a therapeutic benefit in one person. For the blindness intervention, the ARR=1.0/5%=20, meaning that 20 people must be treated with the intervention to prevent one outcome of blindness.

Relative risk reduction. Relative risk reduction (RRR) is defined as the [Control Event Rate (CER) − Treatment Event Rate (TER)]/Control Event Rate (CER). Thus, the RRR for the above blindness intervention is (10 − 5%)/10% = 50%. The RRR essentially illustrates the reduction in an event that occurs among the people who would have definitely become blind without therapy.

The type of risk reduction is critically important for patient counseling. Some clinicians present the RRR, suggesting that treatment reduces the incidence of blindness by 50%, which is true for those who would have otherwise become blind. Patients should know, however, that among all patients treated, the intervention reduces the incidence of blindness from 10% to 5%.

Pharmacoeconomic Analysis

Healthcare economic instruments, or pharmacoeconomic instruments for purposes herein, occur in four basic variants. In the order of increasing

complexity, these include: (1) cost-minimization analysis, (2) cost-benefit analysis, (3) costeffectiveness analysis, and (4) cost-utility analysis [23]. An understanding of the different forms of analysis is important for clinicians, especially since H.R.3590, the Patient Protection and Affordable Care Act [31] of 2010 funded the Patient-Centered Outcomes Research Institute. While established primarily for promoting comparative effectiveness standards, the center will most assuredly promote and regulate the costeffectiveness arena as well.

A description of each of the healthcare economic instruments follows.

Cost-Minimization Analysis

A cost-minimization analysis assesses the cost of two identical interventions to ascertain which is less expensive. Unfortunately, cost-minimization analysis often suffers from the dilemma that it compares two different interventions that may seem similar, but are not. For example, while two VEGF inhibitors for the treatment of neovascular, age-related macular degeneration (AMD) may have similar visual outcomes, the associated adverse events, and the incidences of these events, may be very different. This form of analysis is therefore used infrequently today.

An example of a simplistic cost-minimization analysis is one that compares cataract surgery in a hospital outpatient setting versus an ambulatory surgical center setting, using the same technique in each location. Here, the same intervention is undertaken in a different setting and the cost is compared to ascertain which is least expensive.

Cost-Benefit Analysis

A cost-benefit analysis assesses the dollars expended for an intervention with those gained from that intervention. As an example, let us assume that ranibizumab therapy for neovascular AMD has direct medical cost of $10,000/year. The treatment may considerably decrease the human burden of disease, but the primary factor here is the overall cost expended versus the cost

Quality-of-Life Instruments, Function-Based

Many instruments have been utilized to assess the quality of life associated with a health state (one disease alone or with comorbidities). Generic instruments, including the Medical Outcomes Short-Form-36 (SF-36) [36], the Sickness Impact Profile (SIP) [37], and the Quality of Well-Being Scale [38], are theoretically applicable to interventions across multiple specialties. Among the specialty-specific instruments are the VF-14 [39] and the NEI-25 [30], both used to assess ophthalmic quality of life. In general, the generic medical instruments are not applicable to ophthalmic diseases and the ophthalmic instruments are not applicable across medical health states [23]. All of these tests primarily measure the function (physical, social, psychological, pain-associated, and so forth) associated with a given health state [23].

Quality-of-Life Instruments, Preference-Based

Preference-based quality-of-life instruments are essentially synonymous with utility instruments. Utilities, the outcomes, quantify the quality of life associated with a health state. Utility analysis is believed to be more all-encompassing than function-based quality-of-life measures in that it integrates all functions, psychological overlay, caregiver availability, socioeconomic conditions, occupational aspects and virtually every other aspect that comprises quality of life [23, 40]. The time tradeoff methodology has been demonstrated to have good ophthalmic construct validity [41], and correlates most closely with visual acuity in the better seeing eye [41–45].

Pearl

Utility analysis is a preference-based, allencompassing instrument that allows a measure of the quality of life associated with any health state.

Utilities generally vary from 0.00 (death) to 1.00 (normal health, or normal vision, permanently).

The closer a utility is to 1.00, the better the quality of life associated with the health state, while the closer a utility is to 0.00, the poorer the quality of life associated with the health state. As examples, the utility associated with treated systemic arterial hypertension is 0.98, while that associated with a severe stroke is 0.34 [23]. A great advantage of utilities is that they compare health states across all of medicine using the same outcome.

Pearl

Utilities typically vary from 0.00 (death) to 1.00 (normal health, or normal vision in each eye permanently).

A time tradeoff utility is calculated by asking a study participant two questions:

•How long do you expect to live?

•What is the maximum percentage of your remaining time, if any, you would be willing to trade for an intervention that immediately returns your health problem to normal on a permanent basis?

The utility is calculated by subtracting the

proportion of time traded from 1.0. For example, if a person with 20/200 vision in the better seeing eye believes they will live for another 30 years, and is willing to trade 10 of the 30 years in return for a normal vision permanently, their resultant ocular utility is 1.0 − 10/30 = 0.67 [41]. Because patients can prefer to trade time for better health or prefer to trade no time and remain in the same health state, utility analysis is referred to as a preference-based quality-of-life instrument [23].

Utility Acquisition

It is important to note that the researcher who obtains utilities by interview will likely have different results for the same health state compared to the investigator who obtains utilities via mail or some other noninterview format. Participants reveal very personal information when they answer the above questions and, unless the researcher has a good rapport, are

often hesitant to disclose their true preferences to strangers [23].

Utilities associated with visual acuity in the better-seeing eye are shown in Table 10.2 [16, 41, 44], while utilities associated with general medical conditions are shown in Table 10.3 [16]. The ocular utilities are directly comparable with the general medical utilities. Ocular utilities appear to correlate closely with the vision in the betterseeing eye, rather than the underlying cause of visual loss [16, 17, 41–46].

Pearl

Utilities can compare health states across all of medicine. For example, if 20/40 vision in the better-seeing eye is associated with a utility of 0.80 and American College of Rheumatology Global Functional Status Class III osteoarthritis of the hip also is associated with a utility of 0.80, the two entities are associated with similar quality of life.

Utility Gain

The improvement in quality of life conferred by an intervention can be analytically quantified with utility analysis. For example, if the vision in the better-seeing eye improves from 20/800 (utility of 0.52) to 20/25 (utility of 0.87), the gain in utility is (0.87 – 0.52 =) 0.35 [42].

Decision Analysis

Decision analysis is a mathematical instrument that utilizes the weighted averages of utilities to arrive at the most probable utility outcome associated with an intervention (Fig. 10.1). It is often helpful in amalgamating the benefits of a drug with its 40 or 50 adverse events, as well as the incidences of those adverse events, to more effectively demonstrate the overall utility associated with use of the drug (Fig. 10.1). Markov modeling is a useful tool within decision analysis in assessing the risk of a recurrent event, such as the yearly incidence of the occurrence of neovascular AMD in an eye contralateral to one

Table 10.2 Time tradeoff utilities associated with vision in the better-seeing eye [16, 42, 45]

OU both eyes, HM hands motions, LP light perception, NLP no light perception

Table 10.3 Time tradeoff utilities for general medical health states [16]

that has already developed neovascular AMD. The TreeAge program (TreeAge Software, Inc. @ www.treeage.com) is a well-supported, widely used decision analysis program utilized by the current authors.