Pharmacoeconomics Journal

The clinical value of every drug is defined by its efficacy, tolerability and safety. With many drugs now on the market, healthcare providers have a choice of optimal therapy from a pharmacoeconomic standpoint. Four main types of pharmacoeconomic analysis are used:

• cost-minimization analysis (or cost-of-illness analysis);
• cost-effectiveness analysis;
• cost-utility analysis;
• cost-benefit analysis.

An acceptable cost-to-effectiveness and/or cost-to-utility ratio has become a requirement in some countries for inclusion of drugs in state-subsidized formularies.

Some analyses are carried out via prospective clinical trials in control groups. Subjects are randomly assigned to treatment groups and followed over time. Such studies can be double-blind. The end-point and the methods of analysis are defined at the study-planning stage.

Use of medical services in naturalistic conditions is monitored over a pre-fixed period. Naturalistic conditions are important for outcomes research. In classic trials visit frequency, procedure counts and treatment options are driven by the protocol. Outcomes research in naturalistic settings measures use of medical services without being driven by the research methods, since patients visit medical facilities according to their established practice. Collecting data for prospective trials in naturalistic settings can pose new challenges for researchers.

Retrospective clinical research — analyzing data from already completed studies — is much more common. A typical example is selecting and evaluating information on patients who received the treatment of interest. Two patient groups are formed based on results of two different treatments. Depending on the study goal, doctor-visit data and other medical-services data are analyzed. Such studies are performed within organized healthcare systems and require longitudinal clinical data.

Longitudinal studies may be randomized or non-randomized and follow patients over long periods. The figure shows the types of pharmacoeconomic analysis (see also Table 1).

Figure. Common types of pharmacoeconomic analysis

Table 1. Types of outcomes research

COST-MINIMIZATION ANALYSIS (CMA)

CMA is used to determine the lower cost between two or more treatments with known or assumed equivalent clinical effectiveness. All medical-service categories associated with each treatment are included and their costs determined.

Formulas:

CMA = DC₁ − DC₂

or

CMA = (DC₁ + IC₁) − (DC₂ + IC₂),

where CMA = cost difference; DC₁ = direct cost of treatment 1; IC₁ = indirect cost of treatment 1; DC₂ and IC₂ — same for treatment 2.

Example. The CMA criterion can be used, for example, to compare two effective lipid-lowering drugs. Outcome data are collected for two groups each receiving one drug. If one drug causes more adverse events, patients may need extra visits to medical facilities — associated costs, including additional diagnostic tests, will inevitably raise the cost of that drug’s treatment. The CMA criterion factors in the retail price of each drug.

A study assessing a treatment’s costs without comparison to any other is called a cost-of-illness analysis. A study of all direct and indirect costs of treating a patient with a specific disease, independent of the treatment method, is called disease-specific cost analysis — information helpful for a pharma company starting development of a drug for that indication.

COST-EFFECTIVENESS ANALYSIS (CEA)

CEA is the most familiar and possibly most useful outcomes-research type. Total costs of all medical services tied to different treatments are compared with their clinical effects. CEA builds on CMA and adds effectiveness as well as cost — helping identify treatments that may be more expensive but are balanced by higher clinical effect.

Formula: CEA = (DC + IC)/Ef, where Ef = effectiveness (relative number of cured patients).

Example. Two drugs for urinary incontinence can be selected for comparison. The main end-point is maintaining a certain quality of life, assessed by a standard scheme using validated measures including patient-reported outcomes. Another end-point is the full cost of care — doctor visits, lab tests, surgery, other treatments.

If treatment costs are similar but one group visits surgeons more often than the other, the effectiveness results will differ. One alternative may be more expensive yet more cost-effective. Cost-effectiveness is not necessarily cost saving.

Effectiveness units usually reflect the drug’s indications. Common outcome measures include mortality reduction, hospital discharge in viable/working condition and life-years after treatment. For chronic non-fatal disease the system is less objective — quality-of-life measures are useful. Work continues on improving standardized quality-of-life measures.

CEA has serious theoretical promise but practical limits. Prospective studies can be expensive and time-consuming. For chronic disease, follow-up must last until treatment ends — which may take years. Selecting comparison groups with tight matching criteria is hard. Costs of monitoring a comparison group may be reduced if reliable prior CMA data exist, but a retrospective comparison group may weaken the study’s conclusions.

CEA is a strong drug-evaluation method but has two main drawbacks: 1) being one-dimensional, it cannot compare different interventions that had different effects on health; 2) while identifying the most effective path, it does not reveal social utility.

COST-UTILITY ANALYSIS (CUA)

When a medical intervention produces multi-dimensional results, economists developed the cost-utility approach to integrate measurements of different effects onto one scale.

CUA is a type of cost-effectiveness research that converts the clinical outcome into utility — defined as a patient preference. QALY (Quality-Adjusted Life-Years) is the widely used measure, characterizing treatment by forecasting the quantity and quality of expected survival.

Formulas: CUA = ((DC₁+IC₁) − (DC₂+IC₂)) / (Ut₁ − Ut₂) or CUA = (DC+IC)/Ut.

Example. For bladder cancer in situ two drugs have shown survival benefit: A — 2 years, B — 4 years. But B’s pain syndrome reduces the patient’s ability to work or spend free time actively, lowering quality of life. Some patients may choose A — preferring shorter but higher-quality life.

Thus emphasis is on clinical effectiveness and drug utility.

COST-BENEFIT ANALYSIS (CBA)

CBA compensates the second drawback of CEA — inability to assess a drug’s social value — by expressing clinical results in monetary terms. Direct treatment costs can then be compared with the monetary value of the effect. The logic is appealing but difficult: how to express a saved life or added life-years in dollars? For this and other reasons CBA is rarely used.

Example. Costs of a new hypertension treatment were calculated. Mortality reduction in the treated group vs. untreated was observed. For CBA the life extension had to be expressed in dollars and compared with treatment costs.

The research perspective shapes the study design. Pharmacoeconomic studies should be organized around the upcoming decision. Studies are usually done for marketing purposes, yet payment decisions are made by different participants — patients, individual physicians, state healthcare bodies, third-party insurance, healthcare providers. The study design and its cost estimate must match the goals of the group expected to use the results.

Types of costs. Two cost categories are counted: direct and indirect. Examples in Table 2. Direct costs reflect spending on medical and non-medical goods and services. Indirect costs do not require explicit spending but have an economic component.

Table 2. Cost categories in outcomes research

• Direct medical costs: hospitalization; drugs; lab tests; imaging; physician visits; home medical care; pharmacy preparation costs; services and supplies used by clinic staff.
• Direct non-medical costs (disease-related): food; transport; accommodation; protective clothing and materials.
• Indirect costs (with an economic component): lost productivity; reduced income; productivity lost during illness and restored by treatment; premature death.

Societal economic perspective. Public-health agencies and other government bodies care about disease- or treatment-related costs and their impact on quality of life. In such studies all direct and indirect costs must be counted.

For flexibility it is important to separate non-medical from medical costs — though both belong to the societal perspective, as even indirect costs affect society through taxes and lost productivity.

Payer perspective. Public and private insurers pay for treatments. They focus on direct medical costs. Non-medical direct costs matter only if insurance covers them. Health-service organizations and other healthcare providers are insurers. They take on the payer-perspective share arising from direct medical costs.

State insurance programs care about long-term treatment costs — today’s high cost may decline over life and deliver economic benefit later.

In the US, HMO members typically change plans every 2 years, limiting the HMOs’ interest in investing in expensive treatments to save money later.

Provider perspective. Private-practice physicians traditionally do not care about treatment costs, especially with privately insured patients. From their perspective, what matters is the quality-of-life impact on the patient. Some institutions — health-service organizations and public-health physicians — value both perspectives equally since they both organize care and deliver services.

Patient perspective. Overall quality of life is most important to the patient, especially with insurance or public coverage. Economically the patient cares most about out-of-pocket costs — usually direct non-medical costs — and indirect personal costs. Where the patient can choose, they will likely prefer the best quality-of-life option regardless of cost.

Table 3. Economic-perspective information

• Society / Public-health programs — all short-term direct and indirect costs; all long-term direct and indirect costs; impact on quality of life.
• Payers / Private insurer / Government program / Health organizations — direct short-term costs.
• Providers / Private-practice physician / Health organizations — impact on quality of life; direct short-term costs (medical care).
• Patient — impact on quality of life; direct and indirect costs paid in cash.

Pharmacoeconomic research during clinical development. Two options: (1) collect outcomes data within the traditional clinical-trial system, (2) collect them independently. Pros and cons of simultaneous pharmacoeconomic and clinical research:

Pros:

• More efficient to gather data on subjects already enrolled;
• Parallel-group design possible;
• Efficacy/safety data can be compared directly with economic and quality-of-life data from patients;
• Quality-of-life measures likely more reliable if subjects are randomized.

Cons:

• Hard to assess medical-service effectiveness outside naturalistic conditions; protocol-driven visits distort the picture of real care and hence cost;
• Researchers resist collecting extra data perceived as irrelevant;
• Many trials may be too short to assess long-term quality-of-life impact; extending them would delay drug development. Solution: continue collecting economic data after clinical data collection ends.

Modeling draws on economics and behavioral psychology to predict real-world outcomes. You can accumulate information from which a pharmacoeconomic specialist can model summary measures with real economic meaning. Modeling is more credible when grounded in initial data. Local authorities and healthcare agencies differ in how much they accept modeling. The pharmacoeconomic specialist will know how much modeling can help for a given country or an international study.

Study results attract more attention than the research activity itself. This partly reflects low awareness, but also the following negative factors: pharmacoeconomic research can be very expensive; it can last years if long-term outcomes are assessed; no one has definitively established which information payers, healthcare bodies and pricing agencies will treat as decisive; no broadly accepted model for evaluating such research yet exists; expensive long studies are risky when results are unpredictable; the field is still evolving and full mutual understanding is rare.

Using pharmacoeconomic data in project planning. An organization conducting pharmacoeconomic research must be well equipped — with specialized teams helping project managers plan and run the research. As needs and opportunities for the new product are identified, bring in the right specialists and consultants. The economic aspects of the product’s use should be considered during development.

The economics of using a new product should be analyzed at the earliest planning stage of clinical development and marketing. If cost-of-use data for the indication are missing, a dedicated clinical study should be run. If economic benefits are not known, consider modeling and probabilistic forecasting before the full-scale study. Cost-of-treatment data (all costs analysis) can help forecast cost levels that will support market launch.

Applications of pharmacoeconomic results:

• Promoting a more promising drug vs. those in practice;
• Supporting hospitals, public-health institutions and healthcare organizations in formulary decisions;
• Providing purchasers and organizations with pricing data;
• Setting acceptable prices in countries with pricing authorities.

After identifying viable applications for the results, consult the pharmacoeconomic specialist who performed the analysis. Economic end-points can be less objective than clinical efficacy end-points. A skilled expert will distinguish studies with negligible effect from those with solid positive results. Pharmacoeconomic specialists know the robust economic criteria and can design an analysis that meets the trial’s objectives.

New regulatory trends. Governments, together with local pharma, are developing economic-evaluation guidelines for manufacturers. Despite differences in pricing and reimbursement processes, these guidelines share common features. The most important sign of interest is submitting economic data to justify reimbursement claims. For pharma it has become routine to submit not only safety, efficacy and quality data but also cost data. Economic drug analysis has become more widespread.

Economic-evaluation guidelines can serve different goals. In Australia pharma companies must provide an economic evaluation when applying for reimbursement. Guidelines can be used to apply methodological and ethical standards in drug-economic evaluation — removing the need for formal pressure. The government benefits from the guidelines because they can be used to contain drug spending or allocate budgets for best value. Supporting a more efficient reimbursed-prescription system further justifies such guidelines. Economic evaluation is also needed to form a national state-subsidized drug reference list.

Guidelines requiring CEA results to be provided after safety, efficacy and quality have been established may act as a barrier. Manufacturers may object to the extra cost and documentation, but the guidelines set standards for the use of economic criteria and clarify subsidy decisions. In competitive markets economic evaluation can be an important marketing tool. Industry may therefore support their development, but making them mandatory should not be inevitable.