Limitations and Probable Outcomes in Affecting Change in Society

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Of 70 cost-effectiveness evaluations submitted to the Australian Pharmaceutical Benefits Advisory Committee between December 1995 and June 1997, only 17 were based exclusively on direct evidence from randomized clinical trials, 24 were based only on models, and 29 used a combination of direct experimental evidence and modeling (personal communication: Mitchell A, Australian Pharmaceutical Benefits Advisory Committee). Likewise, several model-based studies submitted to the Canadian Coordinating Council of Health Technology Assessment (CCOHTA) led to coverage recommendations, including a decision to cover the drug omeprazole to treat gastro-esophageal reflux disease (personal communication: Otten N, formerly with CCOHTA).

In managed care, the role of models and economic evaluations in general, remains uncertain, but decisions to cover or not to cover such technologies as enhanced cervical cytology screening and BRCA gene testing in various health-maintenance organizations appear to have been guided in part by models (personal communication: Eddy D, MD, Ph.D., consultant). The role of models in influencing the formulation of important clinical practice guidelines is clear. That model suggested that the incremental value of annual screening after following negative screens was negligible and that less frequent screening, such as every three years, was cost-effective.

Similarly, an analysis based on the Coronary Heart Disease (CHD) Policy Model, was cited by the Second Adult Treatment Panel of the National Cholesterol Education Program to support its recommendation actively endorsing treatment of mildly elevated low-density lipoprotein (LDL) levels in persons with a history of heart disease. This recommendation was made even before direct evidence from clinical trials confirmed that drug-mediated lipid lowering reduced the risk of CHD mortality and non-fatal events by approximately the degree predicted by the model.

Strengths of Health Care Policy

As Jacobs, et. al. 2006 states, “The pursuit of efficiency has become a central objective of policy makers within most health systems. Health care amounts to a sizeable proportion of gross domestic product. Policy makers need to be assured that such expenditures are in line with citizens preferences, particularly when many sources of finance, such as tax revenues, are under severe pressure. On the supply side, health technologies are changing rapidly and the pressures to introduce modern technologies are often desirable, even when there is uncertainty about cost-effectiveness. On the demand side, aging populations pose challenges for the design of health system and expectations are becoming ever more challenging.”

The international explosion of interest in measuring the inputs, activities, and outcomes of health care systems can be attributed to heightened concerns with the cost of health care, increased demands for public accountability and improved capabilities for measuring performance. Broadly speaking, the policy makers notion of effectiveness can be thought of as the extent to which objectives are achieved about the resource consumed. There might also be some consideration of external circumstances that affect the ability of the system to meet its aims. The potential customers or measures of efficiency include government, regulations, health care purchasers, health care providers and the public.

Governments have an interest in measuring the efficiency of their health institutions. In all developed countries, public finance of one sort or another is the single most important source of health system funding to national and local governments.

In conclusion, it is therefore not surprising to find that methodologies that offer insights into efficiency have attracted the interest of policymakers. Moreover, in most industrialized countries, a significant element of the health care sector is provided by non-market organizations. A clear need for instruments that offer insights into performance is modern technology. With the escalating of health care cost and the increased public pressure to ensure expenditure on the health system is a great concern. A distinct role in promoting public safety regulation requires the development of measures of comparative performance to set a level playing field for providers, a task to which efficiency models are in principle well suited.

Finally, there is an increasing demand for offering the reliable public information about the performance of its national and local health system and individual providers.

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Reference

- Barlow, D. H. (1996). Health care policy, psychotherapy research, and the future of psychotherapy. American Psychologist, 51(10), 1050.

- Jacobs, R., Smith, P. C., & Street, A. (2006). Measuring efficiency in health care: analytic techniques and health policy. Cambridge University Press.

- Jacobs, R., Smith, P. C., & Street, A. (2006). Measuring efficiency in health care: analytic techniques and health policy. Cambridge University Press.

- Porter, M. E. (2010). What is value in health care? New England Journal of Medicine, 363(26), 2477-2481

- Reeves, S., Zwarenstein, M., Goldman, J., Barr, H., Freeth, D., Hammick, M., & Koppel, I. (2008). Interprofessional education: effects on professional practice and health care outcomes. Cochrane Database Syst Rev, 1(1).

- Reeves, S., Zwarenstein, M., Goldman, J., Barr, H., Freeth, D., Hammick, M., & Koppel, I. (2008). Interprofessional education: effects on professional practice and health care outcomes. Cochrane Database Syst Rev, 1(1).

- Weinstein, M. C., Toy, E. L., Sandberg, E. A., Neumann, P. J., Evans, J. S., Kuntz, K. M., ... & Hammitt, J. K. (2001). Modeling for health care and other policy decisions: uses, roles, and validity. The value in Health, 4(5), 348-361.

- Weinstein, M. C., Toy, E. L., Sandberg, E. A., Neumann, P. J., Evans, J. S., Kuntz, K. M., ... & Hammitt, J. K. (2001). Modeling for health care and other policy decisions: uses, roles, and validity. The value in Health, 4(5), 348-361.