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The differences between network medicine and network care you need to know

Network thinking is gaining ground in healthcare. And rightly so, because network-based care has proven to be effective in coping with the rising demand for care and the costs thereof.

However, this popularity seems to have a downside; a wild growth of synonyms for networked care has emerged: network medicine, integrated care, 1.5-line care, substitution of care, care in the right place, sensible care, etc. The so-called “Bullshit Bingo”. You might say, “What difference does it make, in the end it all comes down to the same thing?”. Unfortunately, it is not that simple. Besides being confusing to use ten terms for the same thing, some terms have completely different meanings. Network medicine, for example. In this blog, we explain the difference between network medicine and network care.

Figure 1: The land of the blind

Better care for the land of the blind Essenburgh Training & Consulting

The difference between network medicine and network care

It is not only the Federation of Medical Specialists (FMS) and the KNMG that use network medicine as a synonym for networked care. In March of this year, Medisch Contact also ran a headline stating that Minister Bruins wants to make network medicine – read network care – possible. The term network medicine is not often used correctly in the Netherlands, but it is in neighbouring countries. And since we do not live on an island, it is advisable to use the correct definitions as well. Because if different stakeholders use the terms network care and network medicine interchangeably, this leads to miscommunication. This means there is an unnecessarily high risk of cooperation failing, while good cooperation is precisely what underpins network care.

What is network medicine?

Network medicine is about identifying, preventing and treating diseases. This is done with the help of network analyses. For example, biological networks are used to determine the interaction between proteins. The relationships between diseases and biological factors are mapped with disease networks. And social networks and transportation networks are used to model the spread of disease in populations. Network medicine is thus a biomedical science that deciphers complex, biological networks to improve medical interventions.

What is network care ?

Network care is a coordinated way in which a group of care providers work together to improve the health outcomes of a (sub) population. The care providers are prepared to bear the risk of whether or not quality and costs of care are achieved. Network care is about cooperation between patients and care providers, between care providers and between care organisations. In network care, models and analyses can be used to decipher complex social networks in order to analyze and improve collaboration.

Network medicine and networked care are therefore completely different disciplines. Table 1 briefly lists the concrete differences.

Table 1: Difference between Network Medicine & Network Care

Better care Characteristics Network medicine vs. Network care Essenburgh Training & Advice

In fact, you could say that network medicine and networked care are the extremes of a spectrum with the human being at its centre (see figure 1). The left-hand side of the figure shows the field of network medicine (biological networks) and the right-hand side the field of network care (social networks). Networks of cells (consisting of molecules with genetic material) form the individual and networks of individuals form social networks.

Figure 2: Network medicine vs. Network Care

Better care Network medicine vs. network care Essenburgh Training & Advice

Common basis: System biology

Network medicine and networked care both have their origins in systems biology. The principle is that the whole is greater than the sum of its parts. To take the human body as an example, it consists – in very simple terms – of organs, which in turn consist of tissues made up of cells containing the genetic material. Tissues are not amorphous masses, but dynamic populations of unique cells. The “average” cell does not exist, even within a population of cells of the same cell type. To map the whole, the coordinated integration of all cell types must be understood. This can only be achieved with new technologies in a multidisciplinary approach: a collaboration between biologists, chemists, computer scientists, engineers, mathematicians, physicists and doctors. In this way, the complex interaction patterns in the human body are increasingly being mapped out (see Figure 3).

Figure 3: System biology

Better Care System Biology Essenburgh Training & Consulting

Also in network network care and network medicine dthe average patient doesn’t. In clinical trials with large groups of patients, such as in network medicine, the characteristics of each patient are taken into account. These patient-to-patient vibeslink stratification called. This stratification can also be found in network care. In order to provide efficient and good quality care, we stratify patients into high, increased and low riskgroups. And can bpsychological problems are best solved in a multidisciplinary environment, the same applies to network care. Ea chronic patient with comorbidity soon has to deal with ten care and assistance providers all of whom their own role and responsibility have in the care process. If they work together in a coordinated way, this increases the accessibility, quality and efficiency of care as well as patient satisfaction.

Analyse your care network

The human body is thus a complex, biological network of many small parts that perform certain functions in cooperation with each other. And a healthcare system is a complex, social network made up of people, teams, departments and organizations that work together. In recent years we have come to realize that biological and social networks are not random, but rely on organizational interaction principles. This makes it possible to use models to analyse mutual interactions and optimise interventions. For example, by means of an ‘organizational network analysis’. Network analysis can be used to map all relationships between people and organisations. After all, a relationship that is there or not can make a big difference. To make this more concrete: if you have to turn on a switch to light a lamp on a power line, you have to work together within organizations to achieve results. By analysing your network, you get a picture of how your organisation functions and you can make targeted adjustments where necessary.

Evidence based policy…

Network thinking is the key to healthcare in the 21st century, but to give it a chance of success, we need to deal with it in an unambiguous way. Let’s stop creating confusion by using the wrong terms, like network medicine. The only thing we’ll achieve with that is noise on the line. And let us then use network analyses to provide further scientific underpinning for the added value of network care. In this respect, we can take a leaf out of network medicine’s book, where scientific research forms the foundation. On to evidence-based policy making for terms such as 1.5-line care, substitution of care, care in the right place, sensible care, etc!

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I research the added value of healthcare innovations and the steps needed to achieve better health, better care and lower costs. For this I connect science with practice.

Through thorough research, I determine how organizations perform in realizing value-driven care. With this knowledge I help build future-proof healthcare organizations and networks.

Healthcare networks that work: the key to better outcomes

Integrated care is seen as the solution to improve the accessibility, quality, patient satisfaction and efficiency of care. Network care is therefore not an end in itself, but a means to realize value-driven care, also known as value-based healthcare or triple aim. In this e-book, you will read what a healthcare network is and we will identify the barriers and solution directions for practice. Based on the Rainbow Model and (inter)national best practices.