| Literature DB >> 23807855 |
Corinna Sorenson1, Michael Drummond, Beena Bhuiyan Khan.
Abstract
Health care spending has risen steadily in most countries, becoming a concern for decision-makers worldwide. Commentators often point to new medical technology as the key driver for burgeoning expenditures. This paper critically appraises this conjecture, based on an analysis of the existing literature, with the aim of offering a more detailed and considered analysis of this relationship. Several databases were searched to identify relevant literature. Various categories of studies (eg, multivariate and cost-effectiveness analyses) were included to cover different perspectives, methodological approaches, and issues regarding the link between medical technology and costs. Selected articles were reviewed and relevant information was extracted into a standardized template and analyzed for key cross-cutting themes, ie, impact of technology on costs, factors influencing this relationship, and methodological challenges in measuring such linkages. A total of 86 studies were reviewed. The analysis suggests that the relationship between medical technology and spending is complex and often conflicting. Findings were frequently contingent on varying factors, such as the availability of other interventions, patient population, and the methodological approach employed. Moreover, the impact of technology on costs differed across technologies, in that some (eg, cancer drugs, invasive medical devices) had significant financial implications, while others were cost-neutral or cost-saving. In light of these issues, we argue that decision-makers and other commentators should extend their focus beyond costs solely to include consideration of whether medical technology results in better value in health care and broader socioeconomic benefits.Entities:
Keywords: costs; health expenditure; health policy; medical technology
Year: 2013 PMID: 23807855 PMCID: PMC3686328 DOI: 10.2147/CEOR.S39634
Source DB: PubMed Journal: Clinicoecon Outcomes Res ISSN: 1178-6981
Figure 1Total expenditure on health as a percentage of gross domestic product (GDP) (1980–2009).
Notes: *All data from 1980 except for Czech Republic (1990), Hungary (1991), Italy (1998), Poland (1990), and Slovenia (1995); **all data from 2009, except for Portugal (2008).
OECD Health Data 2011.1
Types of studies included in the review
| General and descriptive analyses | Generally provide an in depth analysis of the main variables or factors affecting health expenditures. Some of these studies take a broad approach examining a range of variables, while others focus on a particular issue, such as medical technology, on spending. Furthermore, studies vary in whether they examine national-level expenditures or take a narrower approach by assessing hospital spending. Most of these studies are qualitative. |
| Policy analyses | Evaluate the impact of different policy interventions (eg, managed care, changes to hospital organization or services) and their impact on health expenditures, as well as on mediating factors, such as technology diffusion. Other policy studies consider the implications of high expenditures associated with a particular cost driver (eg, aging, technological advancement). Analyses can be either qualitative or quantitative in nature. |
| Literature reviews | Assess the current literature on the impact of a particular factor or a broad array of factors on health expenditures. This category includes systematic reviews and general literature reviews. |
| Econometric analyses | Typically entails multivariate studies, which examine multiple variables and their effects (and interrelationships) on health expenditures. These studies employ three methodological approaches most frequently, including the “residual” approach, the “proxy” approach, and case studies of specific technologies. The residual approach measures the impact of certain demographic and economic factors (eg, population aging) known to affect health expenditures and then attributes the unexplained portion of spending growth to medical technology. The proxy approach is an indirect method, which employs a measurable proxy indicator for technological change (eg, spending on research and development, time, patents) to explain health care spending trends. The case study approach examines how a specific technology and the associated changes in clinical practice affect spending on specific types of patients, conditions, or settings. |
| Cost-effectiveness analyses | Assess the cost and clinical benefits of a given technology. Such studies seek to ascertain the value for money of a particular intervention. This approach often entails combining clinical benefit with quality of life in a single generic measure of health gain, the quality-adjusted life year, in a cost-utility analysis. |
| Cost impact studies | Evaluate the impact of specific technologies or policies on costs, either at one point in time or over time. |
Characteristics of the reviewed literature
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| General/descriptive analysis | 12 | 1980–1985 | 1 |
| Policy analysis | 8 | 1986–1990 | 2 |
| Literature review | 4 | 1991–1995 | 5 |
| Multivariate analysis | 21 | 1996–2000 | 12 |
| Cost-effectiveness analysis | 34 | 2001–2005 | 37 |
| Cost impact study | 7 | 2006–2010 | 29 |
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| General health technology | 27 | US | 45 |
| Specific medical devices | 41 | Europe | 21 |
| Specific drugs | 3 | OECD | 5 |
| Combination of specific drugs, devices, and/or services | 7 | Canada | 5 |
| Other | 8 | Other | 10 |
Notes:
Articles that focused on cost containment policy effects and general economic trends;
articles that did not focus on any one country, or did not specify.
Contributions of selected factors to growth in health care spending
| Life expectancy/aging | ∼9% | 15% | 2% | 6%–7% | 2% | 2% | |
| Administrative costs | 15% | 3%–10% | 13% | ||||
| Changes in financing | 10% | 4%–5% | 10% | 10% | |||
| Personal income growth | 9%–20% | 11%–18% | 14%–18% | 5% | <23% | ||
| Health care prices | 18% | 11%–22% | 19% | ||||
| Technology | ∼65% | 50%–75% | 25% | 38%–62% | 70%–75% | 49% | >65% |
Notes:
Not estimated;
included aging, but also “front page treatments” (ie, media coverage drives demand for expensive treatment), increased preventive and diagnostic activity, and consumers moving away from less expensive managed care products;
included government mandates (including new mandated benefits) and federal and state regulatory requirements.