Well-being Data And Tools

Well-being consists of multiple parts. Each of us have our own definition for well being and factors that are affecting it. When it comes to our well-being, we also tend to value different things related to it.

Generally speaking one might say that things like health, environment, social relationships and the ability to do the things that are important to a person, are all parts of well-being. Today there are multiple tools for monitoring well-being, which are becoming increasingly popular.

In this post we will discuss big data, open data and myData in relation to well-being data and data management. The article addresses the use of data in well-being services and everyday life, but also the challenges and threats data management systems can have. For this article our team got help from an Master’s student in Xamk, physiotherapist Saija Hyvönen.

Well-being Data

To produce well-being data we need to collect it. This can be done differently, depending on things like the registrar and the facility. In Finland for instance, well-being data is currently collected in various registers. These registers have been in use for a long time already, and the data collected has been used in research and product development for years and years.

But what is data? It is digitally recorded information (symbols, marks) that machines can read. With the help of this data we are able to create documents, databases, transcripts of hearing and audio recordings. Basically, data is just raw material and by processing it, we can create meaningful information that we can use in various ways.

Data is being analyzed and utilized in different levels of organization and processes. With the help of data we can get answers to questions such as

  • What has happened
  • Why something is happening
  • What should be done to make something happen

“In my work as a physiotherapist I collect data from the customer visits. Will the customer book a new appointment or not? If they don’t book another appointment, is it because their issue got resolved already on the first visit? I also collect data about customer satisfaction. This I do by a simple but effective questionnaire that the customer can fill after the visit. With the collected data I can see the quality of my treatments and also make changes for the future” Saija Hyvönen says.

Well-being Information In Finland Now And In The Future

The health and well-being data collected from citizens and the data collected by social services, the use of health and well-being data from the population and the use of health services and quality of the information available to citizens, social and health service providers and the public system, research institutions and businesses.

In Finland, however, the situation has long been that well-being data collected on individuals, such as patient and lifestyle data, is scattered in different systems and difficult to use. (Parikka et al. 2020, 10).

“In my own work as a physiotherapist, I find it challenging that when my clients come to my practice, I rarely get complete medical records on them, which could have a big impact on the course of treatment and speed up the initial assessment. For example, the information may be in my own file, in two different private hospital health records and as a multiple envelope during a visit. In addition, the client may still show the data measured by the smartwatch, which, depending on the device and measurement method, may either be useful or not” says Saija.

According to Tuomisto (2015), the patient himself will in future become an important information provider and may provide the doctor with, for example, exercise data collected by the mobile phone, which should enable an assessment of its relevance to health. On the other hand, patients will be able to make more thorough self-assessments and comparisons online and offer their own diagnosis and treatment recommendations to the doctor (and physiotherapist). The role of the doctor is changing from expert authority to coach.

“The problem I see in the work of physiotherapists is that, as self-diagnosis becomes more and more common, clients increasingly come to the doctor’s office with a ready-made diagnosis that they have worked out themselves, but this is not necessarily the case” Saija says and continues:

“This is a collision course with the first treatment session, when the client’s perception of the condition in question may be completely changed and the course of treatment may be different from what had been anticipated. It may seem strange, but some people may be disappointed when a sore shoulder is treated with rehabilitation rather than being put on the operating table.”

Three Different Types of Data

High-quality data is an extremely important raw material for research and innovation. In the future, access to data and the ability to use and combine it creatively will be key to developing new business models and effective governance. (Parikka et al. 2020, 1.)

In the future, people will have even better ways to manage and promote their own health as applications, data and genetic technologies develop. It is estimated that by 2030, an AI-enhanced platform economy and new data-driven services will account for at best 30% of the Finnish economy. (Parikka et al. 2020, 1.)

Big Data

Big data describes data volumes that are so large and diverse that they require technologies and practices that differ from traditional data processing to store and process them. (Sutinen 2016, 11.) Big data includes, for example, log data from websites or social media usage data, which are constantly growing and changing. We constantly leave a trace when we use the internet and getting rid of it can be challenging, usually impossible.

There are three commonly recognised characteristics for identifying Big Data. These characteristics, which distinguish big data from ordinary data, are:

  • volume,
  • velocity, and
  • variety.

In terms of volume, big data deals with data that cannot be measured in terabytes or petabytes. Big data operates at a scale where non-traditional storage and analysis methods are required to analyse and store the data. Speed refers to the speed at which new data is created and the time it takes to be able to analyse the data. (Sutinen 2016, 11.)

A good example of Big Data is the use of social media data. Social social media can be used to track users’ interests, which can be used to influence, for example, targeted marketing.

There may be concern about how much data is available on one’s own online behaviour and targeted ads appear in front of the eyes. Every day, social media presents online services, courses and products related to health and well-being.

Mass data is becoming more and more common and more and more data is becoming freely available. In Finland, mass data is used in areas such as molecular biology and public health, making use of datasets related to these topics, especially from a Finnish perspective.

There are several important datasets in our country that are not yet being used effectively. Mass data has already provided significant benefits, particularly in understanding cellular phenomena, but the public health and individual choice benefits are only beginning to emerge. (Tuomisto, J. 2015.) Data and evidence can be used to better improve welfare services, bring clarity to decision-making and meet the need for services.

Open Data

Open data is information in digital format that is freely available to anyone for any use, as long as the original source is acknowledged. (Avoindata.fi 2021.)

The Avoindata.fi website lists three things to consider with regard to open data:

  1. The data must be discoverable and accessible on the Internet in its entirety and free of charge in a usable and editable format.
  2. It is freely viewable, downloadable, copyable, modifiable, sharable and accessible by anyone for any lawful activity without any economic, legal, technical, social or practical constraints.
  3. Its terms of use and licenses guarantee the data producer the right to be duly identified, if he so wishes, and the user certainty as to the origin of the data. There are no other conditions restricting use.

For example, THL is constantly producing a lot of open data related to well-being data. THL makes the data it produces and collects openly available and promotes the widespread use of social and health data resources. The data published as open data does not contain personal data or other confidential information. When data is opened, all direct identifying information is removed (THL 2021.)

“The importance of open data in the development of welfare services will certainly increase in the future. The importance of information and data will become more important and health services will rely more and more on researched data and look at the big picture in the light of numbers. Both open data and mass data will contribute to quality data management, making statistics and research more and more part of the future of health services.” Saija points out.

Read also: Best data collecting tools

MyData

MyData is the principle of personal data management and processing, whereby people must be able to manage, access and share the personal data collected about them. If a person does not have the possibility to make use of personal data collected about him or her by someone else, it cannot be called MyData. (Poikola et al. 2018, 5.)

MyData (also omadata) refers on the one hand to human-centered models of personal data management and use that give people the right to their own data, and on the other hand to personal data managed according to such models. The idea is that people themselves can access, manage and pass on data collected about them, such as shopping, mobility, financial or health data.

People-centric data management creates interoperability and minimizes the creation of service locks as data platforms evolve. It reconciles individual rights and high data protection standards with the promotion of data accessibility and business. MyData is a phenomenon, model and future scenario in international development, around which technology and business are gathering momentum. (Poikola et al. 2018, 4.)

Biochipping

As mentioned earlier, people who measure themselves want to acquire information about themselves that will enable them to make decisions about themselves and improve their performance.

The ease and relative affordability of collecting self-reported data has led to a situation where many people are already tracking their activities at some level, for example through a smartphone or smart watch. (Koivunen 2014, 12.)

People already spend much of their time with technology, and it is now an inner curiosity and problem-solving drive to use technology to measure individual or other life-related characteristics. This purposeful monitoring of one’s own activities is known worldwide as self-tracking and these individuals are called self-trackers. In Finland, the term is biohacking and people who do biohacking are called biohackers. (Koivunen 2014, 12.)

“The disadvantage of biohacking is that the more you test, the more you find. It is not always possible for the person to judge whether the findings are necessarily a reason for further action. For example, taking an MRI scan of the back and finding a small bulge or insignificant abrasion may make a person more ill than they really are, because they have data about the finding in their own body.”, Saija says and adds:

“Excessive health monitoring can also cause stress and fear, even anxiety. In my opinion, technological tools and applications that come onto the market should have some form of control and accountability and their use should be based on researched data, or qualitatively good technologies/applications should be given a separate ‘researched good’ label. There are many different sources of health information, but the average consumer may not understand the need to pay attention to the reliability of the information sources.”

Information Security

Information security is the protection of data, systems, services and communications by administrative, technical and other measures. We now live in a world where almost all information and services must be available 24 hours a day, seven days a week, 365 days a year. Digital security enables the digitalisation and uninterrupted functioning of society as a whole.

Digitalisation in an organization means being able to maintain its operations with controlled risks through guidelines, training and exercises. In the workplace, it is the organization’s management that is responsible for the implementation of the digital security aspects. (Eoppiva.fi, 2021.) Digital collaboration tools might also be needed.

Phone-related Security

“In my own life, I have had to think about information security in relation to my own phone usage, among other things. Behind a single code, or often a fingerprint, on a smartphone, there is a huge amount of sensitive personal data: bank details, emails (work and personal), prestored credit card details on websites, phone numbers/addresses, location histories, permissions given to applications (the ones in small print) and all social media channels. “ Saija says and adds:

“For many people, a mobile phone is a communication tool, a work tool, a hobby tool, a streaming service player, etc., which they carry in their pocket or bag more or less from morning to night. We are very vulnerable if our phones fall into the wrong hands.”

Data Security In the Work Of a Physiotherapist

“In my own work, data security protects a huge amount of data. Every day I deal with a patient information system which contains names, addresses, personal identifiers, telephone numbers and patient records. To access this data I need to know many passwords and sometimes double-check my access to the registry with my phone.” Saija says and continues:

“I have undergone the security training required by my employer, but I feel that it has not been comprehensive enough for me to know what to do in the event of a threat. For example, if I discovered a security breach of a medical record, I would have no idea who to report it to first.”

“When dealing with a large amount of sensitive data, the risks inevitably increase. For my own work, for example, maintaining a patient register is a necessity, not only to maintain personal data but also to protect both the physiotherapist providing the treatment and the patient by means of visit records. “What has not been recorded has not happened” was already taught during my physiotherapy studies.”

Thanks, Saija, for letting our team use your school assignment from your Master’s studies in Xamk as a base for this article and thank you for your valuable insights on the topic! Hope to get to work together in the future as well! – DCT team.

You can follow Saija and her studies (in Finnish) on her Instagram account @fysioterapiaa_ja_hyvinvointia

Sources:

Avoindata.fi. 2021. Mitä on avoin data? www-document. Available at: https://www.avoindata.fi/fi/opas/mita-on-avoin-data [accessed 27 September.2021].

Eoppiva. Digiturvallinen työelämä. 2021. Available at: https://www.eoppiva.fi/kurssit/digiturvallinen-tyoelama/#/ [accessed 28 September 2021].

Koivunen, S. 2014. University of Jyväskylä. Tietojenkäsittelytieteiden laitos. Progradu.  Dataa itsestä – kriittiset tekijät omaa toimintaa mittaavan teknologiapalvelun käyttöönotossa. Available at: https://jyx.jyu.fi/bitstream/handle/123456789/45151/1/URN%3ANBN%3Afi%3Ajyu-201501231171.pdf [accessed 27 September 2021].

Parikka, H., Sinipuro, J., Hämäläinen, H,. Kalliola, M,. Luoma-Kyyny, J., Malkamäki, S. 2020. Huomisen hyvinvointia datasta. Sitra. Available at: https://media.sitra.fi/2018/11/27161423/huomisen-hyvinvointia-datasta.pdf [accessed 27 September 2021].

Poikola, A., Kuikkaniemi, K., Kuittinen, O., Honko, H. & Knuutila, A. 2018. Open Knowledge Finland. Liikenne- ja viestintäministeriö. MyData – johdatus ihmiskeskeiseen henkilötiedon hyödyntämiseen. Available at: https://julkaisut.valtioneuvosto.fi/bitstream/handle/10024/160954/MyData%202018.pdf?sequence=4&isAllowed=y [accessed 27 September 2021].

Sutinen, M. 2016. University of Jyväskylä. Tietojenkäsittelytieteiden laitos. Big data ja analytiikka terveydenhuollossa. Available at: Tuomisto, J. 2015. https://jyx.jyu.fi/bitstream/handle/123456789/51135/URN%3ANBN%3Afi%3Ajyu-201608313919.pdf?sequence=1&isAllowed=y [accessed 22 September 2021].

THL. 2021. Avoin data. Available et: https://thl.fi/fi/tilastot-ja-data/aineistot-ja-palvelut/avoin- data [accessed 14 November 2021].