KEY PRESCRIPTION DRIVERS

Key Prescription Drivers For Long Term Prescription Drugs By Physician In Private Practice



Key Prescription Drivers For Long Term Prescription Drugs By Physician In Private Practice

Chapter 4

Medicaid is a federally funded national health assistance program in the United States that provides health-care coverage to individuals and families with low incomes and disabilities. At about $34 billion, prescription drugs formed 13% of the total Medicaid expenditures in 2003 and were growing at an annual rate of 15%—almost 3 times the growth rate of total health expenditures and States have put various administrative and policy measures in place with varying degrees of strictness to control such growth. (D. Rowland, 2005, 65-78)

The most commonly adopted administrative measures include formularies or preferred drug lists (PDLs), prior authorization (PA), drug utilization reviews, fail-first or step therapy requirements, quantity limits, generic substitution, and cost sharing. As a common practice, states often attempt to replicate successes with such interventions from other states which are considered similar based on geographic proximity, demographic distribution, or economic standing. However, studies of formulary restrictions have come up with mixed results in terms of their effectiveness in containing prescription drug and other expenditure.3 A recent survey observed that despite state budget-driven cost-containment initiatives, Medicaid spending in the 2004 fiscal year grew by 9.5%, faster than other state programs. Drug costs have been found to be among the major drivers of such an increase. (D. Rowland, 2005, 65-78)

One of the reasons offered for the unpredictability in outcomes of cost-containment interventions is that Medicaid is not essentially uniform across the nation, and that there are actually 56 different Medicaid programs—one for each state, territory, and the District of Columbia.5 It is possible that such diversity causes variations in the outcomes of interventions when replications are attempted from one state or program to another. Studies in this area have attempted to explain Medicaid costs and to identify potential determinants of spending in the Medicaid system. Some studies have examined demographic determinants. Johnshrud and Lawson6 found tenable relationships between demographic characteristics, and previous and subsequent prescription costs, prescription utilization, and deviation in prescription costs among Medicaid nursing home residents in Texas. Ash et al7 presented a multiple-condition diagnostic cost group modeling framework which used demographic data like individual health status and the disease burden of populations, along with diagnosis data to predict future levels of resource need. Their model demonstrated the highest explanatory power in a Medicaid population owing to several reasons cited by the authors, including the distribution of the cost variable that had a less extreme upper tail, and the predictability of expenditures in medically defined groups like pregnant women, children, and the disabled. Fortess et al8 identified links between specific characteristics of patients, physicians, and treatment settings, and associated changes in utilization of essential medications in a chronically ill, elderly population following New Hampshire Medicaid's 3- prescription monthly reimbursement limit. They found that patients with multiple chronic illnesses, especially along with mental illnesses, were the most at risk of reduced access ...