by our colleague Ales Bourek
Defining Innovation
Innovation is a term that is easily mis-used, abused and rendered largely meaningless (like ‘quality’) unless we use it in a relatively precise way.
EHFF as part of a small working group examined the concept in great detail in the course of a recent European Commission pilot project.
The definition the group agreed was ‘‘Healthcare innovation….is an effective, novel intervention that entails change which leads to improvement in system performance (the system becomes more efficient or achieves better outcomes or both (value proposition)) following its adoption or implementation.” Rather than separate types of innovation it is best to describe a continuum between day–to-day incremental improvements and paradigm shifting, radical innovations. Innovations need to be seen from a systems perspective; in terms of system preparedness, maturity or capability; a process of innovation.
In judging whether a change is innovative, we suggested examining case examples from the viewpoint of:
The pace of adoption of innovation in healthcare tends to be slow because perceived risk associated with change mitigates against adoption.
Even with proven effectiveness, there is no guarantee that there will be widespread diffusion, for contextual reasons such as organisational readiness or preparedness for change, perceived difficulty in adoption (‘challenging innovation’) or so-called ‘political’ or financial factors.
There is a slow but increasing recognition that design principles are a crucial requirement to effective system transformation. This means bringing expertise from other sources of creativity such as art and design schools to work with technical experts from other fields such as medicine or general management.
Lastly, we are fans of one special guru on transformational change, Prof Shoji Shiba. For an introduction to his work, click across.
eHealth and mHealth
eHealth is a broad term, referring to the use of information and communications technologies in healthcare.
“…an emerging field in the intersection of medical informatics, public health and business, referring to health services and information delivered or enhanced through the Internet and related technologies”.’
Logically, mHealth is a sub-section of this field involving mobile communication devices. Originating with the concept of telemedicine, which had its roots in the early 1900s, health telematics as it developed from the 1950s was at first seen as a means of communicating data such as radiographs to allow remote consultations for example during war conditions or for isolated rural areas.
The massive evolution of communication technology in the wake of the space programmes of the 1960s ushered in the modern era of eHealth.
A brief review of the digitalisation of health
Ales emphasises that both analogue (human) and digital (machine systems) handling of data and information contribute to health service outputs and strategic goals. eHealth tools have enormous transformational capability (current practice in diabetes care a leading example) but, as per the discussion on innovation in the previous section, we would highlight two aspects of human factors, as opposed to technological ones, which can have a crucial influence on the cost and effectiveness of new technology adoption. Firstly, intelligent design, which absolutely requires the earliest engagement of end-users and understanding their needs in the development of new eHealth tools …
(an example is our Berlin project in the Project Archive) and secondly, the enhancement of digital literacy, both for citizens and healthcare professionals, as discussed elsewhere.
Relevant here is the required change in dynamic in healthcare working relationships, discussed in detail in the section on citizen empowerment. An extension of this is the concept of the ePatient which recognises that the digitally literate patient presents a real challenge for the healthcare professional, partly because the former’s expectations of the latter will be different, but also because their sources of information may not be entirely familiar (e.g. extensive use of social media).
Activities in the field
For the European Commission digital has become a major policy development area and this represents opportunities for even small NGOs like ours to participate.
ECHAlliance (one of our partner organisations) has a large Digital Health Society project which were signed up to and we have a loose working group in the field including experts on our Advisory group (Agnieszka Daval at Phillips Europe, Ales Bourek, member of the EXPH panel, Tobias Gantner of Healthcare Futurists, Daniel Steenstra, expert on disruptive innovation and design) and Charles Lowe of DHACA, Victoria Betton and others among our community.
Other technology
Digitalisation in health has the potential of genuine innovation in health and healthcare, a major lever for change, subject to all the caveats regarding implementation (and time is a major element. In this age of ‘fast forward into the future’ let’s bear in mind the lessons of history, that what starts out as a novel and exciting concept, during the time it takes to be widely adopted, may have become very familiar indeed).
In considering other technologies that might transform aspects of health and healthcare, we point out the significance of ‘shiny new toy syndrome’. The pragmatic rule of thumb for judging what is being hyped as ‘ground-breaking,’ whether application of Blockchain or Quantum Computing or a new pharmaceutical is: ‘does it change the way we do things?’ In other words, that it doesn’t lead to the same kinds of activity as before, simply re-packaged as ‘novel’ because a new bit of technology allows us to do it faster.
Technologies that we think come into the category of ‘ones to watch’ are:
Medical devices
Medical devices including laparoscopy (already proven, but an important case example) and advanced imaging techniques, Genomics and personalised medicine (yet to be fully proven, but with huge potential), VR and robotics in surgery.
Smart devices
for monitoring, diagnostics and prevention (already in use, but with nothing like the level of adoption that those promoting them would have us believe)
AI and Big Data
Algorithms now subtly pervade all aspects of our lives, but machine learning as an adjunct to healthcare practice? Early days. Similarly, the impact of the use of Big Data, although its potential has been demonstrated, remains uncertain (see also our section on knowledge management).
We argue for having measures to allow us to judge whether a new tool, technique or approach will lead to a genuine transformation of what we do, rather than doing ‘the same old’ with new packaging, but there are four other criteria that need to be considered:
cost benefit - justifiable functionality (ethics) - equity - the window for adoption
Until there is the kind of breakthrough envisaged by the promoters of applied disruptive innovation (where a less sophisticated but much, much cheaper version of a technology hits the market) there is the problem that the cost envelope for healthcare in Europe is finite. New tech. is rarely cheap; hence cost/benefit analysis is highly relevant. Justifiable functionality is about whether ‘because we can’ is sufficient as an argument for carrying out heroic surgery, preventing diseases via genetic manipulation etc. Again, cost comes into this but also ethical issues.
Do we really want to live for ever? If we extend life, what quality of life will be achieved?
This is another kind of benefit analysis, including the relative benefit of not engaging in treatment, for some cases. Looking through the lens of ethics and morality, the overlapping dilemma is equity, or rather increasing inequality in health. By and large new technology has the potential to increase health inequality, not decrease it. Finally, the window for adoption refers to system and human factors in the readiness for change. There are many, many examples of innovation and innovative technology that simply arrived at the wrong time – often thirty or more years earlier! Not easy to judge (but commercially of crucial importance).
Futures Thinking
Futures thinking is not about predicting the future or trend analysis.
It is no surprise that futurists recognise the value of complexity science, because accepting non-linear causation and equally the impossibility of predicting what will happen when overlapping systems of different magnitude and speed are interacting (as with climate trends), one must inevitably accept that there are multiple possible futures.
Futurists use a variety of techniques including formal scenario planning (previously used both by the military for strategic planning) and by businesses (to broaden thinking by their strategists), horizon scanning (with or without AI) and other foresight based approaches (for example: third horizons approach). As described in the ‘what we do’ section of this website, our activities are roughly ordered according to the principles of Foresight methodologies (for more background see: Maree Conway – An overview of Foresight Methodologies).
We are keen to maintain contact with and learn from practitioners active in the field such as the London Futurists (David Wood), the Association of Professional Futurists, IFF (Bill Sharpe), Rafael Ramirez’ scenarios team at Said School of Business, Oxford and IFTF (Institute for the Future, California): (honourable mention to Michael Jackson at Shaping Tomorrow).
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