Health Technologies as a Cost-Driver in Canada
Abstract
This report describes our estimation of the effects of technological change (TC) on health care (HC) expenditures in Canada during the period 1996-2008. We focus on the effect of TC on overall nominal expenditures, as well as the effects of TC on prescription drug expenditure and all other (non-drug) HC expenditure. Estimation is complicated by the fact that it is not possible to directly estimate the “stock” of health technology in the non-drug sector without very detailed data on the myriad forms of diagnostic, therapeutic, preventative and palliative healthcare used today. Health technology involves drugs, medical equipment, devices and other tangible items as well as procedures, techniques and other forms of “know how”. As such, health technology is exceedingly heterogeneous and not directly comparable. The same problems bedevil direct estimation of expenditures on health technology. Because we cannot directly measure the “stock” of health technology, we need to estimate the effect of health TC on HC spending indirectly. We estimate this as the component of health care spending growth that remains after subtracting the growth in health care spending due to population growth, inflation, demographic change and other readily quantifiable cost drivers. This technique is known as the “residual” approach. A defect of the residual approach is that it is possible that time-varying factors other than TC are absorbed in the residual. To implement this, we estimated regression models of prescription drug spending and non-drug spending using province-year level data obtained from the Canadian Institute for Health Information (CIHI). These models allowed us to directly estimate the role of standard cost drivers (i.e. population growth, inflation, demographic change, income) and a residual component, which was modelled as a set of year specific indicator variables. The estimates of these year indicators on spending, known as “year effects”, capture the changes over time in the “residual” expenditures that are common to all provinces. We supplemented this regression-based analysis with an accounting-based analysis, in which we used estimates of the effect of standard cost drivers produced by others. Our regression models suggest that TC explains 45% of the growth in prescription drug spending and 37% of the growth in other (non-drug) healthcare spending over the period 1996-2008. Non-drug spending accounts for the majority of total HC spending; thus we estimate that TC explains 38% of the growth in total HC spending over the period. TC in the prescription drug and non-drug sectors is estimated to have increased HC spending by $5 billion and $23 billion, respectively, over the period 1996-2008. Our accounting-based estimates are less precise. They suggest that TC explains between 27 – 49% of total real per capita HC costs over the period 1996-2008, depending on the income elasticity used and ones assumptions regarding the level of excess medical price inflation. This uncertainty likely reflects the fact that time-varying factors other than TC are absorbed in the residual. Nevertheless, our regression models did appear to be valid. The growth in the year effects was highly correlated with observed measures of TC, 3 spending on MRIs, CT scans and other diagnostic imaging performed in Canadian hospitals since 1998. Moreover, the 38% estimate is very close to an independent estimate for Canada for the period 1975-2000, and an estimate for Australia over the period 1992-93 to 2002-03. The estimate of the impact of TC on prescription drug spending is consistent with estimates produced by the Patented Medicine Prices Review Board. We conclude that TC in the non-drug sector is financially significant, and it is thus worthwhile to assess value for money spent on new technologies. We recommend that CIHI track spending on new procedures in both the inpatient and ambulatory care sectors. This can be done using their existing data holdings, and would help prioritize the technologies that are subject to economic appraisal.