ICU triage: a challenge and an opportunity

In a well-publicized snapshot of the challenge of ICU triage, Chang and colleagues wrote:

Critical care services can be life-saving, but many patients admitted to intensive care units (ICUs) are too sick or, conversely, not sick enough to benefit. Intensive care unit overutilization can produce more costly and invasive care without improving outcomes.

Emphasis added. Hyder provides an interesting critique to which Chang and Shapiro respond. In this post, I shall consider over-utilization by those “not sick enough to benefit”: 23.4% of the 808 patients admitted to the UCLA Medical Center in the study by Chang et al. This over-utilization provides both a challenge and a win-win opportunity (better outcomes at lower cost) if we can meet the challenge.

In a forward-looking vision, which some may regard as optimistic, Anesi et al wrote:

In the year 2050 we will unambiguously reimburse healthcare based on value, and so there is good reason to suspect that we will have targeted and reduced many services that provide little or no benefit to patients…

It can be argued that ICU over-utilization, on average, provides no overall benefit, while significantly increasing costs. Gooch and Kahn observed that US spending on critical care represents nearly 3% of GDP, while:

In contrast, the United Kingdom spends only 0.1% of its gross domestic product on critical care services, with no evidence of worse patient outcomes and similar life expectancies as in the United States. Although there are many differences between these 2 countries, one significant difference is intensive care unit (ICU) bed supply. The United States has 25 ICU beds per 100 000 people, as compared with 5 per 100 000 in the United Kingdom. As a result, ICU case-mix differs substantially. In the United Kingdom, the majority of ICU patients are at high risk for death, whereas in the United States, many patients are admitted to the ICU for observation.

As observed by Halpern, these differences come at a significant cost in the US:

The number of intensive care unit (ICU) beds in the United States has continued to increase over the last 3 decades, as have ICU utilization rates and costs, and this despite the lack of any federal, regional, or critical care society mandates to justify these increases. Some experts believe that the increase in the number of ICU beds has led to inappropriate use of these beds by patients who are either too healthy or too sick to benefit from intensive care. This may in part explain the stable national ICU occupancy rate of approximately 68% between 1985 and 2010 and suggests that ICU utilization has simply risen to meet the increased number of beds.

Emphasis added. I shall consider here only ICU usage by patients too healthy to benefit. Although the economics behind reducing ICU over-utilization by “those not sick enough to benefit” appears simple, the underlying cause is in fact likely complex.

icu-costs-fig-1

This one appears easy: lower costs and potentially better outcomes

At the same time, I recall several caveats, well known to health economists, but important in planning and communication:

  1. We expect ICUs to be available when needed, including for emergencies and disasters,
  2. ICUs have high fixed costs,
  3. Decision-making is critical: incremental costs of adding capacity become fixed costs in the future.

Chris Sampson recently reviewed a study aimed at overconsumption or misconsumption (a consequence of over-utilization). The authors of that paper suggest that “cultural change might be required to achieve significant shifts in clinical behaviour.” Chris laments that this study did not ‘dig deeper’; here we aim to dig deeper in one specific area: ICU triage for patients “not sick enough to benefit.” More questions than answers at this stage, but hopefully the questions will ultimately lead to answers.

I begin by stepping back: economic decisions frequently involve compromises in allocating scarce resources. Decisions in health economics are frequently no different. How scarce are ICU resources? What happens if they are less scarce? What are the costs? Increasing availability can frequently lead to increased utilization, a phenomenon called “demand elasticity”. For example, increasing expressway/motorway capacity “can lead to increased traffic as new drivers seize the opportunity to travel on the larger road”, and thus no reduction in travel time. Gooch and Kahn further note that:

The presence of demand elasticity in decisions regarding ICU care has major implications for health care delivery and financing. Primarily, this indicates it is possible to reduce the costs of US hospital care by constraining ICU bed supply, perhaps through certificate of need laws or other legislation.

I offer a highly simplified sketch of how ICU over-utilization by those “not sick enough to benefit” is one driver of a vicious cycle in ICU cost growth.

icu-costs-fig-2

ICU over-utilization by patients “not sick enough to benefit” as a driver for ICU demand elasticity

Who (if anyone) is at fault for this ICU vicious cycle? Chang and Shapiro offer one suggestion:

For medical conditions where ICU care is frequently provided, but may not always be necessary, institutions that utilize ICUs more frequently are more likely to perform invasive procedures and have higher costs but have no improvement in hospital mortality. Hospitals had similar ICU utilization patterns across the 4 medical conditions, suggesting that systematic institutional factors may influence decisions to potentially overutilize ICU care.

Emphasis added. I note that demand elasticity is not in itself bad; it must simply be recognized, controlled and used appropriately. As part of a discussion in print on the role of cost considerations in medical decisions, Du and Kahn write:

Although we argue that costs should not be factored into medical decision-making in the ICU, this does not mean that we should not strive toward healthcare cost reduction in other ways. One strategy is to devise systems of care that prevent unnecessary or unwanted ICU admissions—given the small amount of ICU care that is due to discretionary spending, the only real way to reduce ICU costs is to prevent ICU admissions in the first place.

Du and Kahn also argue for careful cost-effectiveness analyses, such as that supported by NICE in the UK:

These programs limit use of treatments that are not cost-effective, taking cost decisions out of the hands of physicians and putting them where they belong: in the hands of society at large… We will achieve real ICU savings only by encouraging a society committed to system-based reforms.

Emphasis added. One can debate “taking cost decisions out of the hands of physicians”, though Guidet & Beale‘s and Capuzzo & Rhodes‘s argument for more physician awareness of cost might provide a good intermediate position in this debate.

Finally, increasing ICU supply (that is, ICU beds) in response to well-conceived increases in ICU demand is not in itself bad; ICU supply must be able to respond to demands imposed by disasters or other emergencies. We need to seek out novel ways to provide this capacity without incurring potentially unnecessary fixed costs, perhaps from region-wide stockpiling of supplies and equipment, and region-wide pools of on-call physicians and other ICU personnel. In summary, current health-related literature offers a wide-ranging discussion of the growing costs of intensive care; in my opinion: more questions than answers at this stage, but hopefully the questions will ultimately lead to answers.

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Alastair Canaway’s journal round-up for 20th February 2017

Every Monday our authors provide a round-up of some of the most recently published peer reviewed articles from the field. We don’t cover everything, or even what’s most important – just a few papers that have interested the author. Visit our Resources page for links to more journals or follow the HealthEconBot. If you’d like to write one of our weekly journal round-ups, get in touch.

The estimation and inclusion of presenteeism costs in applied economic evaluation: a systematic review. Value in Health Published 30th January 2017

Presenteeism is one of those issues that you hear about from time to time, but rarely see addressed within economic evaluations. For those who haven’t come across it before, presenteeism refers to being at work, but not working at full capacity, for example, due to your health limiting your ability to work. The literature suggests that given presenteeism can have large associated costs which could significantly impact economic evaluations, it should be considered. These impacts are rarely captured in practice. This paper sought to identify studies where presenteeism costs were included, examined how valuation was approached and the degree of impact of including presenteeism on costs. The review included cost of illness studies as well as economic evaluations, just 28 papers had attempted to capture the costs of presenteeism, these were in a wide variety of disease areas. A range of methods was used, across all studies, presenteeism costs accounted for 52% (range from 19%-85%) of the total costs relating to the intervention and disease. This is a vast proportion and significantly outweighed absenteeism costs. Presenteeism is clearly a significant issue, yet widely ignored within economic evaluation. This in part may be due to the health and social care perspective advised within the NICE reference case and compounded by the lack of guidance in how to measure and value productivity costs. Should an economic evaluation pursue a societal perspective, the findings suggest that capturing and valuing presenteeism costs should be a priority.

Priority to end of life treatments? Views of the public in the Netherlands. Value in Health Published 5th January 2017

Everybody dies, and thus, end of life care is probably something that we should all have at least a passing interest in. The end of life context is an incredibly tricky research area with methodological pitfalls at every turn. End of life care is often seen as ‘different’ to other care, and this is reflected in NICE having supplementary guidance for the appraisal of end of life interventions. Similarly, in the Netherlands, treatments that do not meet typical cost per QALY thresholds may be provided should public support be sufficient. There, however, is a dearth of such evidence, and this paper sought to elucidate this issue using the novel Q methodology. Three primary viewpoints emerged: 1) Access to healthcare as a human right – all have equal rights regardless of setting, that is, nobody is more important. Viewpoint one appeared to reject the notion of scarce resources when it comes to health: ‘you can’t put a price on life’. 2) The second group focussed on providing the ‘right’ care for those with terminal illness and emphasised that quality of life should be respected and unnecessary care at end of life should be avoided. This second group did not place great importance on cost-effectiveness but did acknowledge that costly treatments at end of life might not be the best use of money. 3) Finally, the third group felt there should be a focus on care which is effective and efficient, that is, those treatments which generate the most health should be prioritised. There was a consensus across all three groups that the ultimate goal of the health system is to generate the greatest overall health benefit for the population. This rejects the notion that priority should be given to those at end of life and the study concludes that across the three groups there was minimal support for the possibility of the terminally ill being treated with priority.

Methodological issues surrounding the use of baseline health-related quality of life data to inform trial-based economic evaluations of interventions within emergency and critical care settings: a systematic literature review. PharmacoEconomics [PubMed] Published 6th January 2017

Catchy title. Conducting research within emergency and critical settings presents a number of unique challenges. For the health economist seeking to conduct a trial based economic evaluation, one such issue relates to the calculation of QALYs. To calculate QALYs within a trial, baseline and follow-up data are required. For obvious reasons – severe and acute injuries/illness, unplanned admission – collecting baseline data on those entering emergency and critical care is problematic. Even when patients are conscious, there are ethical issues surrounding collecting baseline data in this setting, the example used relates to somebody being conscious after cardiac arrest, is it appropriate to be getting them to complete HRQL questionnaires? Probably not. Various methods have been used to circumnavigate this issue; this paper sought to systematically review the methods that have been used and provide guidance for future studies. Just 19 studies made it through screening, thus highlighting the difficulty of research in this context. Just one study prospectively collected baseline HRQL data, and this was restricted to patients in a non-life threatening state. Four different strategies were adopted in the remaining papers. Eight studies adopted a fixed health utility for all participants at baseline, four used only the available data, that is, from the first time point where HRQL was measured. One asked patients to retrospectively recall their baseline state, whilst one other used Delphi methods to derive EQ-5D states from experts. The paper examines the implications and limitations of adopting each of these strategies. The key finding seems to relate to whether or not the trial arms are balanced with respect to HRQL at baseline. This obviously isn’t observed, the authors suggest trial covariates should instead be used to explore this, and adjustments made where applicable. If, and that’s a big if, trial arms are balanced, then all of the four methods suggested should give similar answers. It seems the key here is the randomisation, however, even the best randomisation techniques do not always lead to balanced arms and there is no guarantee of baseline balance. The authors conclude trials should aim to make an initial assessment of HRQL at the earliest opportunity and that further research is required to thoroughly examine how the different approaches will impact cost-effectiveness results.

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Chris Sampson’s journal round-up for 6th February 2017

Every Monday our authors provide a round-up of some of the most recently published peer reviewed articles from the field. We don’t cover everything, or even what’s most important – just a few papers that have interested the author. Visit our Resources page for links to more journals or follow the HealthEconBot. If you’d like to write one of our weekly journal round-ups, get in touch.

A review of NICE methods and processes across health technology assessment programmes: why the differences and what is the impact? Applied Health Economics and Health Policy [PubMed] Published 27th January 2017

Depending on the type of technology under consideration, NICE adopts a variety of different approaches in coming up with their recommendations. Different approaches might result in different decisions, which could undermine allocative efficiency. This study explores this possibility. Data were extracted from the manuals and websites for 5 programmes, under the themes of ‘remit and scope’, ‘process of assessment’, ‘methods of evaluation’ and ‘appraisal of evidence’. Semi-structured interviews were conducted with 5 people with expertise in each of the 5 programmes. Results are presented in a series of tables – one for each theme – outlining the essential characteristics of the 5 programmes. In their discussion, the authors then go on to consider how the identified differences might impact on efficiency from either a ‘utilitarian’ health-maximisation perspective or NICE’s egalitarian aim of ensuring adequate levels of health care. Not all programmes deliver recommendations with mandatory funding status, and it is only the ones that do that have a formal appeals process. Allowing for local rulings on funding could be good or bad news for efficiency, depending on the capacity of local decision makers to conduct economic evaluations (so that means probably bad news). At the same time, regional variation could undermine NICE’s fairness agenda. The evidence considered by the programmes varies, from a narrow focus on clinical and cost-effectiveness to the incorporation of budget impact and wider ethical and social values. Only some of the programmes have reference cases, and those that do are the ones that use cost-per-QALY analysis, which probably isn’t a coincidence. The fact that some programmes use outcomes other than QALYs obviously has the potential to undermine health-maximisation. Most differences or borne of practicality; there’s no point in insisting on a CUA if there is no evidence at all to support one – the appraisal would simply not happen. The very existence of alternative programmes indicates that NICE is not simply concerned with health-maximisation. Additional weight is given to rare conditions, for example. And NICE want to encourage research and innovation. So it’s no surprise that we need to take into account NICE’s egalitarian view to understand the type of efficiency for which it strives.

Economic evaluations alongside efficient study designs using large observational datasets: the PLEASANT trial case study. PharmacoEconomics [PubMed] Published 21st January 2017

One of the worst things about working on trial-based economic evaluations is going to lots of effort to collect lots of data, then finding that at the end of the day you don’t have much to show for it. Nowadays, the health service routinely collects many data for other purposes. There have been proposals to use these data – instead of prospectively collecting data – to conduct clinical trials. This study explores the potential for doing an economic evaluation alongside such a trial. The study uses CPRD data, including diagnostic, clinical and resource use information, for 8,608 trial participants. The intervention was the sending out of a letter in the hope of reducing unscheduled medical contacts due to asthma exacerbation in children starting a new school year. QALYs couldn’t be estimated using the CPRD data, so values were derived from the literature and estimated on the basis of exacerbations indicated by changes in prescriptions or hospitalisations. Note here the potentially artificial correlation between costs and outcomes that this creates, thus somewhat undermining the benefit of some good old bootstrapping. The results suggest the intervention is cost-saving with little impact on QALYs. Lots of sensitivity analyses are conducted, which are interesting in themselves and say something about the concerns around some of the structural assumptions. The authors outline the pros and cons of the approach. It’s an important discussion as it seems that studies like this are going to become increasingly common. Regarding data collection, there’s little doubt that this approach is more efficient, and it should be particularly valuable in the evaluation of public health and service delivery type interventions. The problem is that the study is not able to use individual-level cost and outcome data from the same people, which is what sets a trial-based economic evaluation apart from a model-based study. So for me, this isn’t really a trial-based economic evaluation. Indeed, the analysis incorporates a Markov-type model of exacerbations. It’s a different kind of beast, which incorporates aspects of modelling and aspects of trial-based analysis, along with some unique challenges of its own. There’s a lot more methodological work that needs to be done in this area, but this study demonstrates that it could be fruitful.

“Too much medicine”: insights and explanations from economic theory and research. Social Science & Medicine [PubMed] Published 18th January 2017

Overconsumption of health care represents an inefficient use of resources, and so we wouldn’t recommend it. But is that all we – as economists – have to say on the matter? This study sought to dig a little deeper. A literature search was conducted to establish a working definition of overconsumption. Related notions such as overdiagnosis, overtreatment, overuse, low-value care, overmedicalisation and even ‘pharmaceuticalisation’ all crop up. The authors introduce ‘need’ as a basis for understanding overconsumption; it represents health care that should never be considered as “needed”. A useful distinction is identified between misconsumption – where an individual’s own consumption is detrimental to their own well-being – and overconsumption, which can be understood as having a negative effect on social welfare. Note that in a collectively funded system the two concepts aren’t entirely distinguishable. Misconsumption becomes the focus of the paper, as avoiding harm to patients has been the subject of the “too much medicine” movement. I think this is a shame, and not really consistent with an economist’s usual perspective. The authors go on to discuss issues such as moral hazard, supplier-induced demand, provider payment mechanisms, ‘indication creep’, regret theory, and physicians’ positional consumption, and whether or not such phenomena might lead to individual welfare losses and thus be considered causes of misconsumption. The authors provide a neat diagram showing the various causes of misconsumption on a plane. One dimension represents the extent to which the cause is imperfect knowledge or imperfect agency, and the other the degree to which the cause is at the individual or market level. There’s a big gap in the top right, where market level causes meet imperfect knowledge. This area could have included patent systems, research fraud and dodgy Pharma practices. Or maybe just a portrait of Ben Goldacre for shorthand. There are some warnings about the (limited) extent to which market reforms might address misconsumption, and the proposed remedy for overconsumption is not really an economic one. Rather, a change in culture is prescribed. More research looking at existing treatments rather than technology adoption, and to investigate subgroup effects, is also recommended. The authors further suggest collaboration between health economists and ecological economists.

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