Agent relationships and information asymmetries in public health

The agent relationship and information asymmetry are two features of healthcare economics – but how do they apply to public health policy around processed foods?

Why is health different to other goods?

Arrow’s 1963 seminal paper helped lay the foundations for health economics as a discipline. The Nobel-winning economist talks about what makes healthcare different to other types of market goods. Two of the principal things are agent relationship – that a clinician often makes choices on behalf of a patient (Arrow calls them a “controlling agent”); and information asymmetry – that a clinician knows more than the patient (“informational inequality”). Whereas if someone is buying a new car, they make their own choices, and they might read up on the extensive information available so that they are reasonably knowledgeable about what to buy. These two factors have evolved and possibly diminished over time, especially among highly educated people in developed countries; people often have more choice over their treatment options, and some people have become ‘expert patients‘. Patients may no longer believe that the Götter in Weiß (Gods dressed in white) always know best.

Agent relationship and information asymmetry are features of healthcare economics but they also apply to public health economics. But where people accept clinicians as having more knowledge or acting as their agent, people don’t always accept advice on food from public health policy makers in the same way. People may think, “well I know how to buy a bottle of beer, or a can of coke, or a pizza”, and may not see any potential information asymmetry. Some of it might be ‘akrasia’ – they know that food is unhealthy, but they eat it anyway because it is delicious! However, few people may be aware that poor diet and obesity are the biggest risk factors for ill health and mortality in England.

People might ask “why should a nanny state agent make my food or drink decisions for me?” Of course, this is ignoring the fact that processed food companies might be making those decisions, and reinforcing them using huge marketing budgets. Consumers see government influences but they don’t always see the other information asymmetry and agent relationship; the latent power structures that drive their behaviours – from the food, drinks, alcohol industry, etc. Unsustainable food systems that promote obesity and poor health might be an example of market failure or a tragedy of the commons. The English food system has not moved on enough from post-world war 2 rationing, where food security was the major concern; it still has an objective to maximise calorie supply across the population, rather than maximise population health.

Some of the big UK misselling scandals like mortgage PPI are asymmetries. You could argue that processed foods (junk food high in salt, sugar and saturated fats) might be missold because producers try to misrepresent the true mix of ingredients – for example, many advertisements for processed foods try to misrepresent their products by showing lots of fresh fruit and vegetables. Even though processed foods might have ingredients listed, people have an information asymmetry (or at least, a deficit around information processing) around truly understanding the amount of hidden salt and sugars, because they may assume that the preparation process is similar to a familiar home cooked method. In the US there have been several lawsuits from consumers alleging that companies have misled them by promoting products as being wholesome and natural when they are in fact loaded with added sugars.

The agent relationship and information asymmetry as applied to food policy and health.

How acceptable are public health policies?

A 2012 UK poll carried out by YouGov, funded by the Adam Smith Institute (a right wing free market think tank), found that 22% of people in England thought that the government should tell people what to eat and drink, and 44% thought the government should not. Does this indicate a lack of respect for public health as a specialism? But telling people what to eat and drink is not the same as enacting structural policies to improve foods. Research has shown that interventions like reducing salt in processed foods in the UK or added sugar labelling in the US could be very cost effective. There has been some progress with US and UK programmes like the sugary drinks industry levy, which now has a good level of public support. But voluntary initiatives like the UK sugar reduction programme have been less effective, which may be because they are weakly enforced, and not ambitious enough.

A recent UK study used another YouGov survey to assess the public acceptability of behavioural ‘nudge’ interventions around tobacco, alcohol, and high-calorie snack foods. It compared four types of nudges: labelling (adding graphic warning labels to products); size (reducing pack size of snacks, serving size for alcohol, and number of cigarettes in packets for tobacco); tax (increasing the price to consumers); and availability (banning sales from corner shops). This study found that labelling was the most acceptable policy, then size, tax, and availability. It found that targeting tobacco use was more acceptable than targeting alcohol or food. Acceptability was lower in people who participated in the relevant behaviour regularly, i.e. smokers, heavy drinkers, frequent snackers.

What should public health experts do?

Perhaps public health experts need to do more to enhance their reputation with the public. But when they are competing with a partnership between right wing think tanks, the media and politicians, all funded by big food, tobacco and alcohol, it is difficult for public health experts to get their message out. Perhaps it falls to celebrities and TV chefs like Jamie Oliver and Hugh Fearnley-Whittingstall to push for healthy (and often more sustainable) food policy, or fiscal measures to internalise the externalities around unhealthy foods. The food industry falls back on saying that obesity is complex, exercise is important as well as diet, and more research is needed. They are right that obesity is complex, but there is enough evidence to act. There is good evidence for an ‘equity effectiveness hierarchy‘ where policy-level interventions are more effective at a population level, and more likely to reduce inequalities between rich and poor, than individual, agentic interventions. This means that individual education and promoting exercise may not be as effective as national policy interventions around food.

The answer to these issues may be in doing more to reduce information asymmetries by educating the public about what is in processed food, starting with schools. At the same time understanding that industries are not benevolent; they have an agent relationship in deciding what is in the foods that arrive at our tables, and the main objectives for their shareholders are that food is cheap, palatable, and with a long shelf life. Healthy comes lower on the list of priorities. Government action is needed to set standards for foods or make unhealthy foods more expensive and harder to buy on impulse, and restrict marketing, as previously done with other harmful commodities such as tobacco.

In conclusion, there are hidden agent relationships and information asymmetries around public health policies, for instance around healthy food and drinks. Public health can potentially learn from economic instruments that have been used in other industries to mitigate information asymmetries and agent relationships. If Government and the food industry had shared incentives to create a healthier population then good things might happen. I would be curious to know what others think about this!

Thesis Thursday: Logan Trenaman

On the third Thursday of every month, we speak to a recent graduate about their thesis and their studies. This month’s guest is Dr Logan Trenaman who has a PhD from the University of British Columbia. If you would like to suggest a candidate for an upcoming Thesis Thursday, get in touch.

Title
Economic evaluation of interventions to support shared decision-making: an extension of the valuation framework
Supervisors
Nick Bansback, Stirling Bryan
Repository link
http://hdl.handle.net/2429/66769

What is shared decision-making?

Shared decision-making is a process whereby patients and health care providers work together to make decisions. For most health care decisions, where there is no ‘best’ option, the most appropriate course of action depends on the clinical evidence and the patient’s informed preferences. In effect, shared decision-making is about reducing information asymmetry, by allowing providers to inform patients about the potential benefits and harms of alternative tests or treatments, and patients to express their preferences to their provider. The goal is to reach agreement on the most appropriate decision for that patient.

My thesis focused on individuals with advanced osteoarthritis who were considering whether to undergo total hip or knee replacement, or use non-surgical treatments such as pain medication, exercise, or mobility aids. Joint replacement alleviates pain and improves mobility for most patients, however, as many as 20-30% of recipients have reported insignificant improvement in symptoms and/or dissatisfaction with results. Shared decision-making can help ensure that those considering joint replacement are aware of alternative treatments and have realistic expectations about the potential benefits and harms of each option.

There are different types of interventions available to help support shared decision-making, some of which target the patient (e.g. patient decision aids) and some of which target providers (e.g. skills training). My thesis focused on a randomized controlled trial that evaluated a pre-consultation patient decision aid, which generated a summary report for the surgeon that outlined the patient’s knowledge, values, and preferences.

How can the use of decision aids influence health care costs?

The use of patient decision aids can impact health care costs in several ways. Some patient decision aids, such as those evaluated in my thesis, are designed for use by patients in preparation for a consultation where a treatment decision is made. Others are designed to be used during the consultation with the provider. There is some evidence that decision aids may increase up-front costs, by increasing the length of consultations, requiring investments to integrate decision aids into routine care, or train clinicians. These interventions may impact downstream costs by influencing treatment decision-making. For example, the Cochrane review of patient decision aids found that, across 18 studies in major elective surgery, those exposed to decision aids were less likely to choose surgery compared to those in usual care (RR: 0.86, 95% CI: 0.75 to 1.00).

This was observed in the trial-based economic evaluation which constituted the first chapter of my thesis. This analysis found that decision aids were highly cost-effective, largely due to a smaller proportion of patients undergoing joint replacement. Of course, this conclusion could change over time. One of the challenges of previous cost-effectiveness analysis (CEA) of patient decision aids has been a lack of long-term follow-up. Patients who choose not to have surgery over the short-term may go on to have surgery later. To look at the longer-term impact of decision aids, the third chapter of my thesis linked trial participants to administrative data with an average of 7-years follow-up. I found that, from a resource use perspective, the conclusion was the same as observed during the trial: fewer patients exposed to decision aids had undergone surgery, resulting in lower costs.

What is it about shared decision-making that patients value?

On the whole, the evidence suggests that patients value being informed, listened to, and offered the opportunity to participate in decision-making (should they wish!). To better understand how much shared decision-making is valued, I performed a systematic review of discrete choice experiments (DCEs) that had valued elements of shared decision-making. This review found that survey respondents (primarily patients) were willing to wait longer, pay, and in some cases willing to accept poorer health outcomes for greater shared decision-making.

It is important to consider preference heterogeneity in this context. The last chapter of my PhD performed a DCE to value shared decision-making in the context of advanced knee osteoarthritis. The DCE included three attributes: waiting time, health outcomes, and shared decision-making. The latent class analysis found four distinct subgroups of patients. Two groups were balanced, and traded between all attributes, while one group had a strong preference for shared decision-making, and another had a strong preference for better health outcomes. One important finding from this analysis was that having a strong preference for shared decision-making was not associated with demographic or clinical characteristics. This highlights the importance of each clinical encounter in determining the appropriate level of shared decision-making for each patient.

Is it meaningful to estimate the cost-per-QALY of shared decision-making interventions?

One of the challenges of my thesis was grappling with the potential conflict between the objectives of CEA using QALYs (maximizing health) and shared decision-making interventions (improved decision-making). Importantly, encouraging shared decision-making may result in patients choosing alternatives that do not maximize QALYs. For example, informed patients may choose to delay or forego elective surgery due to potential risks, despite it providing more QALYs (on average).

In cases where a CEA finds that shared decision-making interventions result in poorer health outcomes at lower cost, I think this is perfectly acceptable (provided patients are making informed choices). However, it becomes more complicated when shared decision-making interventions increase costs, result in poorer health outcomes, but provide other, non-health benefits such as informing patients or involving them in treatment decisions. In such cases, decision-makers need to consider whether it is justified to allocate scarce health care resources to encourage shared decision-making when it requires sacrificing health outcomes elsewhere. The latter part of my thesis tried to inform this trade-off, by valuing the non-health benefits of shared decision-making which would not otherwise be captured in a CEA that uses QALYs.

How should the valuation framework be extended, and is this likely to indicate different decisions?

I extended the valuation framework by attempting to value non-health benefits of shared decision-making. I followed guidelines from the Canadian Agency for Drugs and Technologies in Health, which state that “the value of non-health effects should be based on being traded off against health” and that societal preferences be used for this valuation. Requiring non-health benefits to be valued relative to health reflects the opportunity cost of allocating resources toward these outcomes. While these guidelines do not specifically state how to do so, I chose to value shared decision-making relative to life-years using a chained (or two-stage) valuation approach so that they could be incorporated within the QALY.

Ultimately, I found that the value of the process of shared decision-making was small, however, this may have an impact on cost-effectiveness. The reasons for this are twofold. First, there are few cases where shared decision-making interventions improve health outcomes. A 2018 sub-analysis of the Cochrane review of patient decision aids found little evidence that they impact health-related quality of life. Secondly, the up-front cost of implementing shared decision-making interventions may be small. Thus, in cases where shared decision-making interventions require a small investment but provide no health benefit, the non-health value of shared decision-making may impact cost-effectiveness. One recent example from Dr Victoria Brennan found that incorporating process utility associated with improved consultation quality, resulting from a new online assessment tool, increased the probability that the intervention was cost-effective from 35% to 60%.

Sam Watson’s journal round-up for 30th October 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.

Conditional cash transfers: the case of Progresa/OportunidadesJournal of Economic Literature [RePEc] Published September 2017

The Progresa/Oportunidades programme was instigated in Mexico in 1995. The main innovation of the programme was a series of cash payments conditional on various human capital investments in children, such as regular school attendance and health check-ups. Beginning principally in rural areas, it expanded to urban areas in 2000-1. Excitingly for researchers, randomised implementation of the programme was built into its rollout, permitting evaluation of its effectiveness. Given it was the first such programme in a low- or middle-income country to do this, there has been a considerable amount of analysis and literature published on the topic. This article provides an in-depth review of this literature – incorporating over one hundred articles from economics and health journals. I’ll just focus on the health-related aspects of the review rather than education, labour market, or nutrition outcomes, but they’re also worth a look. The article provides a simple theoretical model about the effects of conditional cash transfers to start with and suggests that they have both a price effect, through reducing the shadow wage of time in activities other than those to which the payment is targeted, and an income effect, by increasing total income. The latter effect is ambiguous in its direction. For health, a large number of outcomes including child mortality and height, behavioural problems, obesity, and depression have all been assessed. For the most part  this has been through health modules applied to a subsample of people in surveys, which may limit the conclusions one can make for reasons such as attrition in the samples of treated and control households. Generally, the programme has demonstrated positive health effects (of varying magnitudes) in both the short and medium terms. Health care utilisation increased and with it there was a reduction in self-reported illness, behavioural problems, and obesity. However, positive effects are not reported universally. For example, one study reported an increase in child height in the short term, but in the medium term little change was reported in height-for-age z-scores in another study, which may suggest children catch-up in their growth. Nevertheless, it seems as though the programme succeeded in its aims, although there remains the question of its cost-benefit ratio and whether these ends could have been achieved more cost-effectively by other means. There is also the political question about the paternalism of the programme. While some political issues are covered, such as the perception of the programme as a vehicle for buying votes, and strategies for mitigating these issues, the issue of its acceptability to poor Mexicans is not well covered.

Health‐care quality and information failure: evidence from Nigeria. Health Economics [PubMedPublished 23rd October 2017

When we conceive of health care quality we often think of preventable harm to patients. Higher quality institutions make fewer errors such as incorrect diagnoses, mistakes with medication, or surgical gaffes. However, determining when an error has been made is difficult and quality is often poorly correlated with typical measures of performance like standardised mortality ratios. Evaluating quality is harder still in resource-poor settings where there are no routine data for evaluation and often an absence of patient records. Patients may also have less knowledge about what constitutes quality care. This may provide an environment for low-quality providers to remain in business as patients do not discriminate on the basis of quality. Patient satisfaction is another important aspect of quality, but not necessarily related to more ‘technical’ aspects of quality. For example, a patient may feel that they’ve not had to wait long and been treated respectfully even if they have been, unbeknownst to them, misdiagnosed and given the wrong medication. This article looks at data from Nigeria to examine whether measures of patient satisfaction are correlated with technical quality such as diagnostic accuracy and medicines availability. In brief, they report that there is little variation in patient satisfaction reports, which may be due to some reporting bias, and that diagnostic accuracy was correlated with satisfaction but other markers of quality were not. Importantly though, the measures of technical quality did little to explain the overall variation in patient satisfaction.

State intimate partner violence-related firearm laws and intimate partner homicide rates in the United States, 1991 to 2015. Annals of Internal Medicine [PubMedPublished 17th October 2017

Gun violence in the United States is a major health issue. Other major causes of death and injury attract significant financial investment and policy responses. However, the political nature of firearms in the US limit any such response. Indeed, a 1996 law passed by Congress forbade the CDC “to advocate or promote gun control”, which a succession of CDC directors has interpreted as meaning no federally funded research into gun violence at all. As such, for such a serious cause of death and disability, there is disproportionately little research. This article (not federally funded, of course) examines the impact of gun control legislation on inter-partner violence (IPV). Given the large proportion of inter-partner homicides (IPH) carried out with a gun, persons convicted of IPV felonies and, since 1996, misdemeanours are prohibited from possessing a firearm. However, there is variation in states about whether those convicted of an IPV crime have to surrender a weapon already in their possession. This article examines whether states that enacted ‘relinquishment’ laws that force IPV criminals to surrender their weapons reduced the rate of IPHs. They use state-level panel data and a negative binomial fixed effects model and find that relinquishment laws reduced the risk of IPHs by around 10% and firearm-related IPH by around 15%.

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