Technological Imperative

Technological Imperative in Health Care Spending

The technological imperative describes a pull towards doing whatever medicine can technically do, with the question of whether the extra benefit justifies the extra cost asked late or not at all. In health economics it is offered as one behavioural explanation, alongside insurance and rising incomes, for why new technology accounts for a large share of the long-run growth in health spending. It matters because a technology that is worth funding for some patients tends to spread to patients for whom it is not, and once in routine use it is hard to withdraw. Health technology assessment, cost-effectiveness thresholds and disinvestment programmes are the usual counterweights.

Origins of the term in economics and ethics

The phrase is associated with the health economist Victor Fuchs and his book Who Shall Live?. Bhargava, citing the 2011 edition, summarises Fuchs's meaning as a tendency to take action whatever the cost, even if it offers only a hint of utility. The same commentary lists factors that an Office of Technology Assessment case study on intensive care units linked to a treatment imperative, among them a focus on high technology, a moral climate that errs on the side of more treatment, defensive medicine and a payment environment that encouraged procedure-oriented care.

HTA researchers and ethicists use the term in a related sense. Hofmann's 2002 review in the International Journal of Technology Assessment in Health Care found many descriptions and explanations of the technological imperative in the literature and concluded that there is no technological imperative in the sense of one that reduces responsibility for actions. Bélisle-Pipon and colleagues, writing on artificial intelligence in HTA, describe it as the pressure to use a new technology just because it exists, perceived as superior to conventional practice despite the risks.

How the imperative feeds spending growth

Fuchs, writing on Medicare in 2000 without using the term, set out why new technology tends to raise spending. He reported that real per capita health spending for each age and sex group over 65 had grown by more than 4.0 per cent a year, and that most of this growth reflected more and better care associated with the introduction and diffusion of new technology. He noted that some innovations reduce expenditure, but argued that even when the first expectation is a saving, the long-run effect is usually higher spending, for four reasons.

1. New applications. Uses are found that were not foreseen when the technology was introduced.
2. Wider patient groups. As physicians gain experience, the technology becomes medically appropriate for older and sicker patients.
3. Screening and diagnosis. False positives lead to spending on patients who gain nothing, and more sensitive tests find more patients to treat.
4. Diffusion beyond the trials. Wide use outside selected trial settings can bring more expensive complications.

Fuchs judged much more problematic the services with positive expected benefit but a value lower than their expected cost. He argued that widespread third-party payment without supply controls leads economic theory to predict exactly that outcome, and that because technological change is partly endogenous, more generous insurance coverage fuels the development and diffusion of new drugs and procedures. On this account, the moral hazard in health insurance that lowers the price a patient faces also speeds the spread of new technology.

Empirical work supports the role of technology while disputing its exact size. Okunade and Murthy tested what they called the Newhouse conjecture, that technological change is a major escalator of health care expenditure, on United States data for 1960 to 1997 and found support for it. Chernew concluded that the evidence overwhelmingly points to the diffusion of new medical technology as the primary driver of inflation-adjusted per capita spending growth over past decades. Smith, Newhouse and Freeland estimated that medical technology explains 27 to 48 per cent of United States health spending growth since 1960, a smaller share than earlier estimates, and stressed that technology expands with rising incomes and more generous insurance rather than independently of them. These studies measure technology-driven growth as a whole. None isolates the share due to the imperative itself, which is a behavioural explanation for part of that growth.

Links with induced demand, defensive medicine and payment

Three nearby mechanisms push in the same direction. Supplier-induced demand arises when providers use their information advantage to raise use beyond what an informed patient would choose. Fee-for-service payment rewards each extra test or procedure. Defensive medicine adds tests and imaging to protect the clinician against litigation.

Studdert and colleagues surveyed physicians in six high-liability specialties in Pennsylvania in 2003. Of the 824 who responded, 93 per cent reported practising defensive medicine, and among those who described their most recent defensive act, 43 per cent reported using imaging technology in clinically unnecessary circumstances. Mello and colleagues estimated annual United States medical liability system costs, including defensive medicine, at 55.6 billion USD in 2008 dollars, or 2.4 per cent of total health care spending. The Studdert figures show liability pressure attaching to imaging, and neither study measures the technological imperative as such.

Worked example with one technology and three risk groups

All numbers in this example are illustrative. A new diagnostic technology costs an extra 1,200 GBP per patient. Its expected QALY gain falls as use spreads from high-risk to lower-risk patients. The payer uses an illustrative cost-effectiveness threshold of 20,000 GBP per QALY and compares groups by net monetary benefit.

$$\mathrm{NMB} = \lambda \, \Delta Q - \Delta C$$

where $\lambda$ is the threshold in GBP per QALY, $\Delta Q$ is the incremental QALYs per patient and $\Delta C$ is the incremental cost per patient in GBP.

Step 1 (high-risk group). With H, M and L denoting the three risk groups, the ICER is $\mathrm{ICER}_{H} = 1{,}200 / 0.10 = 12{,}000$ GBP per QALY and $\mathrm{NMB}_{H} = 0.10 \times 20{,}000 - 1{,}200 = 800$ GBP per patient, so use in this group is worth funding at the threshold.

Step 2 (medium and low-risk groups). The ICERs are $\mathrm{ICER}_{M} = 1{,}200 / 0.04 = 30{,}000$ and $\mathrm{ICER}_{L} = 1{,}200 / 0.01 = 120{,}000$ GBP per QALY, and net monetary benefit is $\mathrm{NMB}_{M} = 0.04 \times 20{,}000 - 1{,}200 = -400$ and $\mathrm{NMB}_{L} = 0.01 \times 20{,}000 - 1{,}200 = -1{,}000$ GBP per patient.

Step 3 (use for everyone). Total cost is $C = 10{,}000 \times 1{,}200 = 12{,}000{,}000$ GBP and total gain is $Q = 100 + 120 + 60 = 280$ QALYs, an average ICER of $C / Q = 42{,}857$ GBP per QALY. Group NMB sums to $\mathrm{NMB}_{all} = 800{,}000 - 1{,}200{,}000 - 6{,}000{,}000 = -6{,}400{,}000$ GBP.

Step 4 (interpretation). At the threshold, the total cost displaces $C / \lambda = 12{,}000{,}000 / 20{,}000 = 600$ QALYs elsewhere, against 280 gained, a net loss of 320 QALYs, equal to the negative NMB of 6,400,000 GBP divided by the threshold. Restricting use to the high-risk group costs 1,200,000 GBP, gains 100 QALYs and displaces 60, a net gain of 40 QALYs. The imperative to use the technology for everyone who might benefit turns a good investment into a large opportunity cost, and a single average ICER for all users hides the group where the technology earns its place.

Assessment and disinvestment as counterweights

Hofmann rejected the idea that technology removes responsibility from those who develop, assess, implement or use it. In his account, the wider possibilities that technology brings increase responsibility, and technology promotes a moral imperative to proper assessment. Health technology assessment is one institutional form of that response. The 2020 international definition states that HTA can be applied at different points in a technology's lifecycle, from pre-market through to disinvestment, and lists reimbursement decisions including disinvestment among the decisions it informs.

Timing matters because stopping a technology is harder than not starting it. Refolo and colleagues write that with health technologies beginnings count, because there is a technological imperative and reversal and de-implementation are very difficult. Early health technology assessment and budget impact analysis give payers a view before adoption, and the worked example shows why recommendations restricted to subgroups matter as much as yes or no decisions.

For technologies already in use, Elshaug and colleagues proposed reducing existing interventions that offer little or no benefit relative to the cost of their public subsidy, using criteria based on those developed for HTA, and reallocating the funds to more cost-effective care. Fuchs observed that countries with national health insurance typically rely on supply-side constraints to control spending, including limits on the diffusion of high-cost technologies such as magnetic resonance imaging devices and open-heart surgery teams. These approaches are forms of cost containment aimed at the volume and spread of technology rather than at prices.

Boundaries with nearby ideas

The technological imperative is a behaviour or norm, while technology-driven cost growth is the spending outcome it helps to produce, alongside insurance, income growth and genuine health gains. Diffusion of innovation describes how any new practice spreads through adopters, whatever its value. Supplier-induced demand concerns the agency relationship between provider and patient and does not need new technology. The rule of rescue, which McKie and Richardson describe as the imperative people feel to rescue identifiable individuals facing avoidable death, also conflicts with cost-effectiveness analysis, but it centres on the person rescued rather than the device or procedure. Low-value care is the category of services the imperative tends to enlarge.

Limitations and common misreadings

The term is descriptive rather than a measured quantity, and the evidence on technology and spending comes from aggregate studies, such as the time-series analysis of Okunade and Murthy, which cannot separate imperative-driven use from valuable use. Hofmann's review found that the term has many meanings.

1. All new technology is wasteful. Cutler and McClellan estimated that in four of five conditions studied (heart attacks, low-birthweight infants, depression and cataracts) the benefit of technological change was much greater than its cost, with costs and benefits about equal for breast cancer. The concern is adoption without regard to value, not innovation as such.
2. Technology always raises costs. Fuchs noted that some innovations reduce expenditure. The imperative concerns how use expands after introduction.
3. The imperative is inevitable. Hofmann argued that no imperative frees anyone from responsibility for how technology is assessed and used, which is the case for HTA and disinvestment.

Sources

• Fuchs VR. Medicare reform: the larger picture. NBER Working Paper 7504. Cambridge, MA: National Bureau of Economic Research; 2000. https://www.nber.org/papers/w7504
• Bhargava R. Whither orthopaedics today: an introspection. Indian Journal of Orthopaedics. 2017;51(1):14-17. https://doi.org/10.4103/0019-5413.197515
• Hofmann B. Is there a technological imperative in health care? International Journal of Technology Assessment in Health Care. 2002;18(3):675-689. https://doi.org/10.1017/S0266462302000491
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• Refolo P, Duthie K, Hofmann B, Stanak M, Bertelsen N, Bloemen B, et al. Ethical challenges for health technology assessment (HTA) in the evolving evidence landscape. International Journal of Technology Assessment in Health Care. 2024;40(1):e39. https://doi.org/10.1017/S0266462324000394
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