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Patient Centricity

Trust is the basis for a successful patient excellence strategy"

Patient Centricity

Trust is the basis for a successful patient excellence strategy"

Dr. Thomas Kraft, Head of Competence Center Market Excellence at msg industry advisors ag, on the importance of Patient Centricity and the central role of trust for a successful patient excellence strategy.

Customer centricity is one of the central paradigms across all industries today. Which role do these approaches play in healthcare? What constitutes patient centricity? 

Customer orientation is indeed an essential anchor and guiding principle for sustainable market success. At its core, it's about aligning all processes with the well-being of the customer in the best possible way and across the entire physical and digital interaction cycle. These general premises naturally also apply in healthcare. People should be able to have the best possible experiences and engage in their role as patients situationally throughout the treatment process, so that the highest possible patient satisfaction can be achieved at the end, i.e., a high level of satisfaction measured against multiple and complex expectations and reference points.

So much for the structural similarities between patient and customer centricity. So what is so special about it?

It goes without saying that medicine is a very special field. It involves very critical factors up to the patient's own life, which is why the process is characterized by a high level of sensitivity. The most important factor here is trust. Trust is of central importance in terms of customer excellence and customer experience in general. In the relationship with patients throughout the treatment process, it is existential.

Patient centricity is primarily about the relationship between patient and physician. The pressure is concentrated on the physician to ensure that excellence is actually experienced. At the same time, however, there are many other stakeholders – insurance companies, administrations, service providers, the pharmaceutical industry, medical technology manufacturers. They are all united by the goal of patient satisfaction. If these stakeholders work well together, much more can be done toward this goal than is being done today.

Patients do not have the same typical sovereignty of customers. Instead, fears, dependencies, pressure to act and uncertainty characterize the situation. What is the relevance of these conditions?

The initial situations of customers and patients are very different. Customers enter into interaction with suppliers confidently and actively. The job of suppliers is to fulfill customer wishes, whereby the appropriate design of the journey is a means to an end in order to enable positive experiences.

But no one likes going to the doctor or the hospital. People want to get well with as little pain as possible while maintaining personal dignity. These are very basic goals. Physicians are not service suppliers that make wishes come true; the therapies they recommend are not always in accordance with the wishes of patients. Who wants chemotherapy? No one. But the will to survive, to get well, is above everything. And because that's the case, people are willing to go through such valleys. It is obvious that trust plays a paramount role in this. After all, the patient ultimately surrenders autonomy to the physician. If you are not a physician yourself, it's very difficult to assess the medical expert opinion. Physicians are persons of trust. This means that the other stakeholders in the treatment process to not have this trust from the outset. It is therefore necessary for all those who contribute to the well-being of the patient in the healthcare market to work together much more closely and in a more orchestrated manner in order to develop this trust.

What does this central role of trust mean for the pharmaceutical industry?

The pharmaceutical industry does not have its own patients, the patients are the patients of the attending physicians or hospitals. This creates the challenge of making the added value of their work recognizable to patients and as comprehensible as possible. That is the basis for establishing trust. Patients and pharmaceutical companies are currently in a phase of getting to know each other. The industry faces the task of positioning itself as an active and trustworthy partner for patients. If patients trust the pharmaceutical industry, they will be more willing to share highly sensitive health data for medical research and medical trials.

This data is invaluable. This data is everything in the pharmaceutical and therapeutic practice – without it, there is no real progress, no better, no new medication. Patient excellence, then, depends largely on how much you know about patients. Trust is the basis to gain this knowledge.

What approaches are there to build this trust?

What is needed are coordinated actions that link smaller steps, various forms of support for patients, community, relatives. Digital technologies can be very helpful here. For example, more and more people want to know their health status as precisely as possible and manage their health actively and preventively. This also explains the great acceptance of health apps. Pharmaceutical manufacturers, whether on their own or via partnerships, could address this need and provide contents via apps, which are valuable in certain situations.

Plus: With personalized medicine must come personalized information. So it's all about the specific situation: When a person is a patient, their priorities change. Digital services that are unnecessarily complex, require special skills, and do not address the patient's condition are doomed to failure. If you're lying in bed after an operation and can't hold a tablet or process certain information, you need scenarios that are appropriate for these conditions. You have to understand the specific situation, respond to it and enable the best situational experience. Otherwise, you can neither establish acceptance nor trust.

How exactly does the pharmaceutical industry benefit from interaction with patients?

To make it concrete, two topics can be singled out: One is personal healthcare, increasingly individualized medicine. General medications are already so good that in terms of patient benefit, there is a plateau in some areas. This is why we need new examination methods such as gene sequencing and deeper insights into patients' circumstances. Only then can we gain deeper and more precise insights into how an organism responds to certain medication and which interactions and underlying conditions are relevant. If the pharmaceutical industry can access genetic maximum ratings in anonymized and partially anonymized form, it can better advance the development of individual medication.

The second – corresponding – topic is market approvals and reimbursements. New medications must demonstrate an additional benefit in order to be approved and included in insurers' reimbursement programs. Enabling and demonstrating this benefit is becoming more difficult in many areas. The availability of data would lead to the development of medications that achieve significant advances through personalized or targeted procedures for specific patient populations. Patient benefit and industry economic success thus go hand in hand.

More data about patients enables new insights – but also generates additional complexity. What are the implications of this development?

It is ironic that better understanding initially generates rapidly growing complexity. When 1,000 or 10,000 parameters are analyzed and combined, we not only need data but also logics and methods to deal efficiently with this statistical raw material. Plus: The more personalized medication becomes, the less statistical data is available. This is why the way using intensive and trusting collaboration is certainly the right approach. Whether this is the only way or whether other approaches are also possible – that is another question.

That is one side of the complexity. The other is the system in which this data needs to circulate and that is characterized by organizational and technological silos, diversity or competing objectives. Customer centricity and customer excellence only work if everyone is on board. If processes and data are not integrated along the patient journey, we create data cemeteries and data disruptions at every stage of that journey, which can cause key initiatives and innovations to fail due to structural complexity.

AI is already playing a very important role in customer management – at multiple levels. What changes could be added with the popularization of Large Language Models?

Customer interaction could be automated where directly or statically correlated information is combined. The more error-free this works, the sooner this type of interaction will become established. If I, as a patient, am unsure what to do next, these models already help. In medicine, obtaining information is sometimes very complex. AI assistants break down barriers in terms of comprehensibility and availability – while remaining calm and patient. So we are definitively getting closer to the vision of a “digital companion”.

Doesn’t this development also lead to a difficult social discussion?

Yes, and this discussion is absolutely necessary. How does progress pay into our future, how does our understanding of values change? How open to technology must and may we be? How much acceptance is there for certain negative consequences of progress, and how can we avoid social disruptions?

We need to take a step beyond classic medical ethics. Digital ethics shifts the discussion to the question: Is the technology built on ethical foundations, does it make ethically sound decisions, and how can these be verified and controlled?

We are already experiencing comparable discussions around autonomous driving. This involves the question of decision-making responsibility and the decision-making parameters in critical situations. Here, too, social processes must be used to find decision-making calculations that are ethically viable in society. Only then can certain rules and algorithms be derived. But we are already moving to uncharted territory here. In principle, data is the key here as well. For example, we can determine through observation, statistics or experience that in certain situations certain actions were successful or had fewer negative consequences. And then we could attempt to implement corresponding logics in algorithms. The difficulty arises from the enormous variety of the scenarios. This is why we will probably continue to encounter situations in which we cannot resort to formalized procedures.

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Dr. Thomas Kraft