Comparative Effectiveness Research-Part 1: Searching for Value
Owing to the recent senatorial election results in Massachusetts, anticipated health care reform agendas for the United States are undergoing change again as the electorate and Congress struggle with a burgeoning health care system.
Owing to the recent senatorial election results in Massachusetts, anticipated health care reform agendas for the United States are undergoing change again as the electorate and Congress struggle with a burgeoning health care system. Among those areas still being defined in the context of health care reform is comparative effectiveness research (CER). Conflicted economic priorities and desired levels of clinical outcomes in the marketplace along with increasingly complicated science have created a potentially unique opportunity for CER.
To understand the growing interest in CER, it is important to appreciate the evolution for payment of health care services in the US health care system as well as the shift in those who determine the value of a product or service. Before the availability of health care insurance, patients determined the who, what, and when of health care services to be provided. They also determined the payment or relative value of those services.
The advent of health insurance for hospital and some physician care services began in the mid-20th century. By the latter portion of the century, health insurance had evolved rapidly to cover additional aspects of health care, such as prescription drugs.
This expansion in coverage was accompanied by a shift in decision making from the patient to the insurance provider. First, decisions around payment and service discounts transitioned from the patient or employer. Eventually, insurers began influencing patient access to services through the use of contracted networks.
Hospital formularies in the 1950s had focused on product safety and an adequate supply of medication, but the role of the P&T committees changed as enrollment in MCOs rose along with spiraling increases in medication costs. This led to the use of formularies to leverage discounts and rebates from manufacturers. As a result, P&T committees began using a variety of management tactics to control costs and promote the rational use of medications; this also led to benefit management outsourcing.1 All of these efforts continued the shift of health care decision making away from the patient and into the hands of a third party.
The use of health outcomes data for therapeutics and formulary decisions has resulted from the expanding role of P&T committees along with increasing economically driven decision making in managed care. MCOs as well as other insurers rely on pharmacoeconomic data and models to control rising costs and increased use. This information helps determine the value of a product when making formulary decisions.2 This strategy also allows third-party payers of patient care services to ensure spending on proven medical treatments as part of their fiduciary responsibilities under their insurance or management services contract.
Roots of CER
The typical goal for CER is to target health care spending on proven medical treatments that are effective in defined, real-world populations. Comparative effectiveness can be determined through the use of many research methods, including randomized trials, systematic reviews, database analyses, and prospective observational studies.3 The origins for these methods emerged from organized health care systems that lie in health-related economic analyses, pharmacoeconomics, and health technology assessment.
Among the various types of health economic analyses applied to pharmaceutical products are 5 major models: cost benefit, cost utility, cost-effectiveness, cost minimization, and cost avoidance.4 These models can provide a comparison of cost and consequences related to the use of drug products or services, but they require a decision-making context or framework that can balance opposing forces regarding rising health care expenditures.
Health technology assessment (HTA) has been commonly used for medical services, devices, and diagnostics by both private and public sector payer agencies to determine coverage based on a collected body of evidence. The HTA framework includes 5 steps:
• Scanning the market during preapproval stages of emerging products.
• Selecting topical areas of interest based on new market-approved products.
• Assessing and gathering evidence on the new product.
• Appraising the evidence and using a decision-making committee to make recommendations on coverage.
• Deciding whether to reimburse for or to cover the product.
Public sector producers of HTA include the Veterans Administration, the Agency for Healthcare Research and Quality, and the Department of Defense. Private sector producers of HTA include Hayes, Inc; the ECRI Institute; the Center for Medical Technology Policy; and th
e Blue Cross Blue Shield Technology Evaluation Center. Health plans and PBMs may use in-house expertise to produce HTA, purchase those insights from the available private commercial sources, and obtain public domain information. The Centers for Medicaid & Medicare Services typically reviews publicly available CER and budgetary data on medications but not proprietary manufacturer data.
Public Sector as Payer
Through programs such as Medicaid, Medicare, and armed services or Veterans programs, the public sector has emerged as the second largest payer for health care services in the United States. As a result of program growth and an aging population, the public sector agencies adapted many of the private insurance techniques for determining plan administration, operational policies, and computer technologies. Resulting similarities among private and public sector programs have now evolved for the management of health care dollars along with the decision making on behalf of the patient to determine the value of services covered under the various programs. Today, increasing economic pressures on public sector programs have resulted in significant health management advances and cost management tactics used by public sector managers. These have included robust information technology capabilities and computerized medical record systems as well as targeted use of HTA with aggressive outsourcing of management services to control program cost inflation factors.
Health reform efforts began in the past decade, which led to the American Recovery and Reinvestment Act of 2008 and initiated a process to develop CER through a federal board of experts. Planned CER efforts promise to assist marketplace stakeholders-consumers, clinicians, purchasers, and policy makers-to make better informed decisions that will improve health care at both the individual and population levels.5 However, because of the diverse and large number of stakeholders represented, along with their segmented interests, the Institute of Medicine created a list of 100 priorities for CER across a range of medical treatments, procedures, and tests (Table). Examples of those priorities include atrial fibrillation, hearing loss, dementia, and dental caries.5
Editor’s note: Look for the second part of this article, “Comparative Effectiveness Research-Part 2: The Impact on Decision Making,” in the next issue of Drug Benefit Trends. We will explore the reemergence of private sector benefit plans and MCOs as well as the potential applications of CER in health care services decision making in this decade.
References:
References
1. Balu S, O’Connor P, Vogenberg FR. Contemporary issues affecting P&T committees, part 1: the evolution. P&T. 2004;29:709-711.
2. Balu S, O’Connor P, Vogenberg FR. Contemporary issues affecting P&T committees, part 2: beyond managed care. P&T. 2004;29:780-783.
3. Vogenberg FR. Comparative effectiveness research: valuable insight or government intrusion? P&T. 2009;34:684-685.
4. Vogenberg FR, Sica JM. Managing Pharmacy Benefits. 2nd ed. Brookfield, WI: International Foundation of Employee Benefit Plans; 2006.
5. Institute of Medicine. Initial national priorities for comparative effectiveness research. Washington, DC. National Academies Press. June 30, 2009. http://www.iom.edu/~/media/Files/Report%20Files/2009/ComparativeEffectivenessResearchPriorities/Stand%20Alone%20List%20of%20100% 20CER%20Priorities%20-%20for%20web.ashx. Accessed November 6, 2009.
