Personalised healthcare and population healthcare

Personalised or individualised healthcare and population healthcare are two sides of one coin. It follows that those responsible for developing population healthcare cannot ignore the individual.

The first reason we cannot separate the individual from the population is that everyone involved in managing health services has an ethical duty to think of the individual. This principle was first enunciated in 1789 by Jeremy Bentham in his classic book An Introduction to the Principles of Morals and Legislation, in which he wrote ‘It is in vain to talk of the interests of the community without understanding what is the interest of the individual’.¹ The second reason is that the value for each individual changes just like the value for the population as the investment in a service increases so people who make decisions about populations, for example to increase investment in a particular service change the nature of the clinical decisions made by individual clinicians and patients too.

In Explorations in Quality Assessment and Monitoring,² Donabedian described not only the concept of structure, process and outcome but also his ‘unifying model of benefit, risk and cost’. The power of this model is that it quantifies for the first time the relationship between resources invested in healthcare and the amount of value obtained from that level of investment. Donabedian showed that as healthcare resources are increased, benefit increases initially, but the increase then flattens off, illustrating what some people have called the law of diminishing returns. Importantly – and this is often overlooked – the amount of harm done does not diminish as resources invested. For each unit increase in resource, there is a unit increase in the number of people treated and consequently a unit increase in the amount of harm done. In fact, there may be a progressive increase in the amount of harm done if, with each unit increase in the availability of care, patients who are less fit and more at risk of harm are covered by the service.

It is important to emphasise that the harm described in Donabedian’s model is not the result of medical errors or safety problems. Rather, harm occurs in all health services, even those that are of the highest quality, as an inevitable consequence of the risks associated with the act of interventions such as X-rays, drugs and anaesthetics.

As a consequence, there may come a point at which the investment of additional resources will lead to a reduction in the net benefit, calculated by subtracting the harm from the benefit, and there comes a point beyond which additional investment reduces the value derived from the resources. He called this the point of optimality (Figure 1).

Figure 1.

The changing relationship between benefit, harm and value as resources increase to a point beyond which there is no increase in value.

There is another equally important reason why personalised care has to be considered to be the flip side of population healthcare. That is, as the value changes for the population as a whole, for example when more resources are put into a particular service such as cataract replacement or chemotherapy, the level of need of the average individual patient treated changes as less severely affected patients are deemed to be eligible. Thus, the clinical decision also changes as the investment of resources increase with a different balance of benefit and harm, as shown in Figure 2.

Figure 2.

The changing relationship of the magnitude of possible benefit and harm for the individual patient as resources increase.

Figure 2 also illustrates how two different communities of practice describe the changing relationship with different languages.³ To clinicians the decisions and interventions range from ‘necessary’ to ‘futile’, with ‘appropriate’ and ‘inappropriate’ in between. To people responsible for populations, the language is different, from ‘higher value’ at one extreme through ‘lower value’, ‘no value’, all the way to ‘negative value’, where the service does more harm than good.

Thus, as we increase the amount of healthcare resources given to the population, we reduce the value to the population as a whole. We also affect the potential value to the individual with the balance of benefit to harm for each individual offered treatment changing to become a less attractive option. For this reason the clinical decision, although evidence-based, also has to be value-based.

Patient-centred care, individualised, personalised and precision medicine

There is much debate about the meaning of these terms but agreement is emerging.

Patient-centred care

The best definition of patient-centred care is that given by Don Berwick:

Others have struggled to find a proper definition of patient-centeredness. These useful maxims that I have encountered are these: 1. “The needs of the patient come first.” 2. “Nothing about me without me.” 3. “Every patient is the only patient.” My proposed definition of “patient-centred care” is this: “The experience (to the extent the informed, individual patient desires it) of transparency, individualization, recognition, respect, dignity, and choice in all matters, without exception, related to one’s person, circumstances, and relationships in health care.⁴

Many services would of course claim that they are delivering patient-centred care and always have done. However, the belief that you are delivering patient-centred care does not ensure that it is actually delivered. Evidence suggests that many, if not most, services need a significant change in culture and new systems to ensure that patient-centred care is delivered.

Individualised care

One of the earliest uses of the emphasis on individualisation was in the definitions of evidence-based medicine. Although accused of developing ‘cookbook medicine’, the originatiors of evidence-based medicine emphasised the need to relate the evidence to the unique clinical condition and value to the individual patient:

Evidence-based medicine is the conscientious, explicit, and judicious use of current best evidence in making decisions about the care of individual patients. The practice of evidence-based medicine means integrating individual clinical expertise with the best available external clinical evidence from systematic research. By individual clinical expertise we mean the proficiency and judgment that individual clinicians acquire through clinical experience and clinical practice. Increased expertise is reflected in many ways, but especially in more effective and efficient diagnosis and in the more thoughtful identification and compassionate use of individual patients’ predicaments, rights, and preferences in making clinical decisions about their care.⁵

Many within evidence-based medicine are moving beyond the focus on promoting the need for randomised trials and systematic reviews to emphasising the need to apply population evidence to individuals.⁶

Personalised medicine

Personalised medicine is, of course, what has been practised, or should have been practised, since we first became thoughtful about the nature of the consultation and the clinical decision. This is best expressed in the book by Peter Rothwell titled Treating Indviduals: From Randomised Trials to Personalised Medicine in which he explains that

This book focuses on the two key questions that are most frequently asked by clinicians about applying the results of randomised controlled trials and systematic reviews to decisions about their individual patients. Is the evidence relevant to my clinical practice? How can I judge whether the probability of benefit from treatment in my current patient is likely to differ substantially from the average probability of benefit reported in the relevant trial or systematic review?⁷

This emphasises the need to relate the evidence derived from the studies of groups of populations, often artificially designed in that the people in the research have only one condition such as heart failure, whereas most people with heart failure have two or other three conditions. The clinician’s job is therefore to relate this evidence to the unique clinical condition of the patient and to create a context in which the patient can be allowed to reflect on their values, the values they attach to different options that may occur, both good and bad, and the value they place on risk-taking or risk avoidance.

This model was relevant before the development of genomic medicine and was, and is, used for decisions such as ‘Should I have a knee replacement now or wait for another year or two?’, although some authors use the term ‘personalised medicine’ as though it had only arrived following the development of genomic knowledge but increasingly the term that is applied is precision medicine.

Precision medicine

Precision medicine may be defined as personalised medicine in which the clinician and patient have to take into account genomic information, both during the process of diagnosis – molecular genetics – and in the choice of drug therapy most likely to be effective – pharmacogenomics, for example

We define precision medicine as the provision of care for diseases that can be precisely diagnosed, whose causes are understood, and which consequently can be treated with rules-based therapies that are predictably effective.⁸

So these three much-used and misused terms do relate to one another:

Promoting personalised decision-making

There has been a large amount of work done on clinical decision-making in the last decade. As is often the case, different academics have produced a different term to describe their perspective on decision-making; however, there is general agreement that decision-making should be shared and the definition of shared decision-making which summarises the key points is

Shared decision-making recognizes the complex tradeoffs that patients must make in the choice of medical care, and addresses the ethical requirement to fully inform patients about the risks and benefits of treatments as well as the need to ensure that patients’ values and preferences play a prominent role in medical decision-making.⁹

There is also now general agreement that decision-making should be evidence-based but a new term that has emerged in the last 10 years is that decision-making should be preference-based and preference-sensitive which ‘involves making value trade-offs between benefits and harms that should depend on informed patient choice’.¹⁰

Furthermore, there is evidence that many professionals do not think about this aspect of decision-making leading to three authors led by Al Mulley to coin the term ‘The Silent Misdiagnosis’.¹¹ By this, they meant that although the clinician of the clinical diagnosis is correct, prostate cancer for example, the clinician had failed to identify, or even to think about trying to identify, the patient’s preferences about different types of outcomes. There is also research showing that not all professionals are able to identify correctly the patient’s preferred type of decision-making. One consequence is that they treat all patients in the same way and to the same degree, assuming, for example, that all elderly people want a paternalistic style of decision-making.

On the basis of this research, it is obvious that it is insufficient to just provide decision aids. Considerable work has been done with both patients and clinicians to help them adapt to the new paradigm and this is one of the key functions of population healthcare.

Activating patients

There has been much concern about patients for example about their inability to understand complex information. However, research is encouraging, showing that many patients can understand probabilities when it is presented using evidence-based methods and that even previous educational entertainment is not a valid predictor of inability to understand probabilities. The important step to take is to assume that patients are confident provided they are given the right information expressed in the right way and to ensure they get that information where and when they need it. The term ‘patient activation’ is now used implying a range of measures to increase the active participation of patients in decision-making care.

In some ways clinicians present the greater challenge. First, many clinicians feel they know all about probabilities and their communication even though there is evidence that they do not. In addition, clinicians may have to unlearn things that they have held to be true for many years, for example it is helpful to patients to present information as percentages.¹²

Supporting shared decision-making

One simple way of engaging with clinicians is to tell them that it is clear that they have insufficient time to give all the information that they want within the time allocated for consultations. This also provides a face-saving excuse to clinicians who might be difficult to change and who can simply be encouraged to support decision aids provided as a supplement and complement to face-to-face consultations.

The term ‘decision aid' is used in many ways and here is one example of its meaning:

Decision aids are evidence-based tools designed to prepare patients to participate in making specific and deliberative choices among healthcare options in ways they prefer. These tools assist decision-making by providing evidence-based information about a health condition, the options for treatment, associated benefits, harms, probabilities and scientific uncertainties. Decision aids help patients recognise the value sensitive nature of the decision and clarify the value they place on the benefits, harms and scientific uncertainties. This can be done by describing the options in enough detail that patients can imagine what it is like to experience the physical, emotional and social effects; and by guiding patients to consider which benefits and harms are most important to them.¹³

Decision aids need to cover:

• factual information about anatomy, physiology and pathology, for example about the gallbladder and gallstones;

• a clear description about the treatment options;

• information about the outcomes, both good and bad in each option;

• description of the probability of a good outcome occurring expressed in absolute terms;

• links to resources such as the patient interviews on the website Webtalkonline;

• provide patients with prompts and reflections from other patients to help them reflect on their own values and how the information given relates to their values.

The new era has arrived, facilitated or perhaps driven by the mobile phone, but health services and professions are behind the pace. They need to move to a new culture in which all data are presented in an evidence-based way, for example using the Fact Box methodology.¹⁴ The new era has been called the era of Sharing Medicine,¹⁵ which demands a empathic care and may capture the spirit better than the term personalised medicine which still implies that the clinician is in charge. In fact, healthcare involves an emphasis on what people do for themselves.

Determining the future role of the clinician

What is emerging in the trends discussed above include a shift in power from clinician to patient, a need to individualise evidence from randomised controlled trials and genetic analysis, while appreciating the need to remember, and sometimes rediscover, empathy.

All forms of individualised medicine (patient-centred, personalised, precision medicine, etc.) share one thing. They all require that practitioners understand the patients’ symptoms, needs and aims. Essentially, empathy is a necessity. As used in trials demonstrating health benefits of empathy, empathy is defined as follows:^16,17

1. understanding another person’s situation, feelings and perspective, recognising the difficulties in putting oneself in another’s shoes;

2. communicating that understanding, checking its accuracy; and

3. acting on that understanding in a helpful way.

This definition is operationalised by encouraging practitioners to enhance how they display empathic behaviours, such as taking time to understand the patient’s history, offering encouragement and giving verbal and non-verbal signs that the patient has been understood.

Not only is empathy required for any form of care that focuses on applying population evidence to individuals, but it can independently enhance important patient outcomes. Trials have shown that such behaviours can reduce pain, anxiety, depression, while improving patient satisfaction.^15–18 For example, Chassany et al.’s¹⁸ empathy training intervention for general practitioners (n = 180) reduced pain in osteoarthritis patients (n = 842) by 1 point out of 10 on a 10-point Visual Analogue Scale (p < 0.0001). Delivering positive messages can also be effective. Benedetti et al.’s trial showed that delivering a positive message can reduce pain by an additional 1 point on a 10-point Visual Analogue Scale (p = 0.001). Improved empathy and expectation management are likely to work by reducing patient anxiety and inducing the body to produce endogenous opiates. These modest benefits are comparable to many pharmaceutical interventions.

It follows from this discussion of empathy that any attempts to apply medicine to individuals must engage with and take into account the growing evidence about empathic care.¹⁹ This takes place in the context of a world in which dramatic changes are taking places as a result of the revolutionary impact of the Internet.

Most attention has been focused on the changing role of the patient, but the more dramatic change may be needed in the role of the clinician and the driver may be technological as well as social with the disruptive technology being not the genome but the Internet or, its ubiquitous manifestation, the smartphone. In Medieval Technology and Social Change, the historian Lynn White Jr emphasised how technology changed culture without anyone appreciating that change is happening.²⁰ The people we call patients now have access to almost all the knowledge that doctors can access, and that which they cannot access, primary research in journals accessible only by subscription, is of relatively little importance because it is so often invalidated.²¹ Furthermore, the person formerly known as the patient has much more time than the clinician. But this is only part of the shift that technology is bringing about. The implications of Artificial Intelligence and cognitive computing are profound and resources like IBM Watson^22,23 are emerging as disruptive technologies with big implications for specialties such as pathology and radiology as well as for specialties that are based on the face-to-face consultations that have changed little since even before the original telephone, never mind the smartphone.

Professions are notoriously slow to change,²⁴ sometimes fatally slow, but radical change is needed. As Bill Gates said ‘the key question for any organization in the digital age is to ask – what is the role of the human being?’ For no group is this more appropriate than the medical profession.

Declarations

Competing Interests

None declared.

Funding

None declared.

Ethical approval

Not applicable.

Guarantor

MG.

Contributorship

MG wrote the first draft and the other authors contributed sections and improved the whole text.

Acknowledgements

None.

Provenance

Not commissioned; editorial review.