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Digital Health, Healthcare, mHealth, Wearables
There’s no denying that the popularity of wearables is gaining momentum. However, manufacturers are aiming to go beyond being mere fitness gadgets and a technological trend to becoming accepted as valued medical devices utilized by the healthcare sector. It’s a new beginning of Wearables in Healthcare. keep reading

Digital Health, Healthcare, Internet Of Things IoT, mHealth
The use of Internet of Things in Healthcare is going to be revolutionary in the next years. IoT is now pretty much in everything we touch in our modern lives, technology is now a common denominator in most of everybody’s life. IoT is seeing by many sceptics and conservatives as a buzz word, however we truly believe that IoT is more than that.
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Digital Health, Healthcare, Internet Of Things IoT, mHealth
It’s relevant to understand the state of the healthcare industry. For this reason, Siemens Healthineers asked Harvard Business Analytics Services to survey healthcare professionals (decision makers, influencers and managers) to gain insight into key industry trends. The survey garnered 613 respondents of which 85% worked in healthcare, the remaining 15% comprised consultants with clients from the healthcare industry. keep reading

Big Data, Digital Health, Healthcare, Innovation, Internet Of Things IoT
Technology is changing healthcare, Artificial Intelligence will change healthcare in few years. Data in general equals too many possibilities, data organised and specific equals fewer and far more accurate options. Over the past decades, many new ways of collecting and storing health data have been implemented in our healthcare system, this of course highly valuable. However, without any method for interlinking or combining, this data is of no use.  how artificial intelligence is changing healthcare The amount of stored patient data has increased with 700% between 2010 and 2015, 91% of that data is unstructured. This data resides outside of an organised database such as lab records or electronic health records, making it impossible for payers, care providers and patients to tap into its potential. However, if we would be able to tap into this data we could accelerate healthcare transformation, making it more efficient and cost-effective.  Therefore, Artificial intelligence (AI) is seen as the solution to the problem. With its capability to draw “intelligence” from the vast amounts of raw data, located in different sources, it has healthcare executives worldwide supporting it. Globally, 63% of healthcare executives are already investing in AI technologies and 74% are planning to do so as well. AI healthcare A PwC study found that healthcare is most likely to derive some of the biggest gains through AI. It would increase productivity, enhance the quality and give the space to the increased consumption. The possibilities would be endless, especially with regards to diagnostics. It could for example:
  • “help detect small variations within patients’ health data and comparing variations among similar patients
  • identify potential pandemics early and tracking the incidence of diseases to help prevent and contain their spread
  • enhance imaging diagnostics in radiology and pathology.”– (Brian Williams, 2017)
Some of these AI powered diagnostic tools but also preventive tools are already seen in the market. Although not yet wide spread it does display the potential of AI driven devices in healthcare. Examples are smartphones connected to a device which can make Electrocardiograms (ECG) and give results instantly or online services which can diagnose skins, rashes and moles on the basis of a digital photo. Imagine, in the near future patients would not have to see a doctor to diagnose them or give them advice, AI driven devices can take over that role and doctors would just have to verify saving immense amounts of time and costs. “According to HRI’s 2015 clinician survey, 42% of US doctors say they are willing to prescribe medications based on the results of consumer-operated diagnostic technologies.”– (Brian Williams, 2017) But how do health consumers feel about being treated by their smartphone rather than by an actual doctor. A recent study of 12.000 people across 12 countries states that the majority is willing to substitute the care given by human clinicians by care given by AI digital health or ehealth robots. Ai-enabled healthcare Thus, AI can safe vast amounts of cost and increase efficiency throughout our healthcare system. Moreover, healthcare executives, clinicians and patients are all willing to try and are seeing its potential. Does this mean that AI is our health future? Yes, I think it is inevitable. Studies are already predicting that the AI market is in for massive growth. Between 2014 and 2021 a 40% increase in the market of AI in healthcare is expected, growing from $633.8 million to $6.66 billion.  However, while the potential is surely there, there are still many unknowns and issues to be solved before our health AI future can reach its full potential. New systems and business models will need to be implemented and large investments are needed to make everything happen. I think the below sums it all up…  “The road toward the vision of a self-serve, consumer-directed, personalized healthcare delivery model powered by artificial intelligence will likely be repeatedly disrupted by unexpected stops and starts. But, to more and more clinicians and technologists on the leading edge of healthcare IT development, it’s just a matter of time.” – (Brian Williams, 2017) And that it is, we will need to work hard, but our AI healthcare future is soon to be there!  This article is based upon the following post:  Are you planning to innovate in healthcare? We can help you implementing the latest technologies and eHealth Innovation Methodologies in your Healthcare business. Contact us

Digital Health, Healthcare, Innovation, mHealth
There are some problems related with Digital Health Transformation. It is so normal in our digital age, the focus on technology is highlighting developments and innovations. When modernizing healthcare however, this emphasizes on technology is overshadowing the real centre of where change needs to happen… people. digital health transformation Digital health transformation is by many presumed to be about transferring vast amounts of data and having technology as “ready to go” solution. Healthcare however is a people business, centring around the needs and desires of humans giving and receiving care. This makes that when it comes to making digital health transformation happen, the difficulties do not lie with building the right technology, but with the behaviour changes that need to happen. This makes that first step to successful digital health transformation is to understand the problems of digital health transformation lying underneath.

Understand the problem

This seems very simple but is often harder than you think. For example, when healthcare providers would like the system of patient recording to change from let’s say paper to electronic. It might seem like you have fixed the problem by implementing the newest electronic system that enhances access, with lots of different options and shining innovative attributes. However, when asking  why they want the system changed and what the specific problems are with the current system, you might find out that for care givers a simple system, with fewer options and a user friendly interface is key to perform their jobs effective and efficiently. In that case, your beautiful new system would be far from desired. “It’s about finding the pain points and determining how that translates to the needs of caregivers or patients.” – (Travis Good, 2017)

Make the technology fit into the workflows

After you have a clear understanding of the problem it is key to gain insight into how the technology will fit into the workflow of the healthcare provider. Try looking at the work as an operation project rather than an IT project. This ensures that the technology will be aligned with the strategic initiatives and objectives of the overall department. An example, a project around operating procedures replacing hips and knees. Having an IT perspective we might focus on gathering the data from the electronic health records to improve the inventory levels of replacement joints which boosts the return on investment by sterilizing fewer equipment, reduction in employee costs and other efficiencies. This of course would already help a lot. However, taking an operation project perspective and while speaking with operational people, the director of the OR for example, you might find out that there are additional department goals which could be well implemented in this system. Think about accurate and timely data to help with budgeting or supply chain management.

Standardize your Digital Health Transformation

Healthcare systems are often highly complex and interlinked with various systems and processes. Therefore, to successfully implement digital health, standardization is key. The technology tool itself but also the processes and support systems around it, such as training and compliance need to be interlinked and standardized. This can reduce complexity each time another application is added to the ecosystem and therewith creates system sustainability. When deciding whether or not to add a new technology, standardization should be applied as well. A piece of technology can be highly innovative and change the way care is provided, however the new IT might not be suitable to be built into the existing system. There should be a process in place to understand whether it is a smart long-term investment. The digital health conversation is dominated by technology but most people working outside IT do not know what is possible in this field. This makes that for doctors for example it is hard to formulate what exactly the technology should do. Using the technology such as documentation tools for people to type into, costs them time away with patients. Especially since IT people build the systems without a clear value proposition, healthcare professionals complain since they have all the data but are not using it. For this reason discussions needs to change. More non-technological and subject related experts need to sit around the table. Information need to be gained from the people technology is serving, patients, doctors and nurses. What are they experiencing, what would truly benefit them and how would it fit their needs, desires and ways of working. “In the short term, having more voices around the table won’t necessarily make the process of transformation more efficient. But, in the long-term, broadening beyond a technology discussion will be necessary.”(Travis Good, 2017) If we truly want successful digital health transformation and receive the benefits from such systems, we need to go back to the before the time of the tower of babel and try to speak the same language, understanding each other.   Click here to view the article this post is based upon.