This paper presents the problem of small outcomes compared to the investment in large scale IT projects. Focus was given in the application of big data in health sector, where the new element, enhancing the problem, comes from the incorporation of new forms of patient generated data. Proposed were processes aiming on the one hand to underline that apart of the importance of patients' involvement, also important is the involvement of all the other stakeholders. This will both make data collection easier and better, and turn data into actionable information. Finally concrete interventions in the direction of Big Data usage in Health sector are here proposed, which will help in enabling new operating and business models.
In many sectors, when implementing large scale IT projects, the outcomes seem small compared to the investments. It makes no difference in the health care sector. Medical professionals claim that with the currently used IT systems they are wasting their time, as they are hard to use and even more they interfere their interactions with patients. In addition, healthcare institutions get more losses than gains, as they have to deal with many issues when integrating new IT systems into their operations. Finally, any efforts in the direction of persuading health institutions to share information continue to lag, due to communication and compatibility issues, and legal limitations, resulting in data being useless for the public health policy-making.
Getting an inside look of the problem we may see that the currently used
IT systems focus majorly on electronic registers, which can improve billing and
reimbursement procedures [
However, we see some industries use technology better than others do, and
labor productivity statistics reflect that. In the case of U.S., we see that the health
care has been growing faster, as an industry, than the overall economy. However,
since the number of health care workers has been rapidly increasing, and the use
of information technology has lagged, productivity growth has been minimal [
The idea of this paper is to explore, whether big data can help in the direction of improving IT systems, and their use in the health sector, so they can better serve the medical professionals and more specific the public health policy makers. Even more to propose proper interventions, which can contribute in overcoming the current obstacles, and in introducing new business and operation models, including multidisciplinary knowledge and teams.
However, let us first define the use of big data in the health care sector. Until
now, the focus is on public health policy-making, clinical trials and research, and
health services provision improvement. The data used for the purpose are
electronic health records (EHRs), electronic patient reported outcomes (ePROs),
genomics and imaging data. There are many examples of successfully implemented
systems, but all of them are related to concrete institutions and deal with concrete
medical cases [
Supporting the above, we may see [
The difference comes since until recently data like EHRs, and ePROSs were included. The new element comes from the incorporation of new forms of patient generated data. These forms include both physiological but also psychometric data. Data collected real-time, and directly through sensor devices or data generated online, as patients’ comments or posts in social networking tools online. We see mobile technologies and sensor devices facilitating the development of new models supporting online methods of health monitoring. The focus is on recording and analyzing big volumes of physiological and psychometric data, now directly collected from patients.
However, although we see many successful projects, applying different
technologies in healthcare in analyzing Big Data, there is a lag between those projects
and their real application in clinical practice. We have promising results in
clinical research, as data-driven hypothesis generation and testing, or as identification
of relationships and results based on heterogeneous data sets of genomic or
environmental data and patient health records [
The aim of this paper was to review the Big Data and data-driven systems and tools targeting patients, doctors and public health policy makers as their immediate beneficiaries, and identify actions focused on how Big Data actually can help to improve the effectiveness of those tools and systems used for the promotion of health in primary and secondary healthcare.
Having in mind the above, both as example of best practices, but also as divided opinion of the medical professionals, and health policy decision makers, regarding the effectiveness of big data in health care, we propose to get one level below and try to define the operations. Having the operations defined we may further propose interventions on a per-process basis.
The scope of the proposed processes is on the one hand to underline that apart of the importance of patients’ involvement, it is also important the involvement of all the other stakeholders. They are all part of the big data value chain in medicine and public health policy-making. We need to include from the medical professionals to the public health policy-makers, but also IT and data specialists, the public administration, etc.
The European Commission (EC), Directorate-General for Health and Food
Safety, Directorate B — Health systems, medical products and innovation, Unit
B.3 — Cross-border Healthcare, e-Health [
The scope of the actionable plan is to provide with suggestions to the public health policy makers on how to: • utilize the strengths and exploit the opportunities of Big Data for Public
Health without compromising privacy or safety of citizens; • use Big Data in Health not as a goal in itself, but as a tool to reach certain purposes that benefit the patient and the public; • protect current ethical standards and not let be compromised for potential benefits of Big Data; and • include as more as possible stakeholders in the implementation of the proposed recommendations and in the production of future recommendations on Big Data in Health.
Concrete interventions in the direction of Big Data usage in Health sector
are here proposed. They are formulated as recommendations in different aspects,
which will enable new business models. The following list summarizes the
interventions:
1. raise awareness: aiming in the development and the implementation of a
communication strategy, which would help increasing the added value of Big Data
in Health and encouraging a positive attitude towards Big Data in Health.
2. provide education and training: focus on the human capital and increase the
workforce capabilities in utilizing the Big Data potential in Health. There is a
huge need for increasing the digital literacy of the healthcare professionals.
3. secure the data sources: the quality and safety of the existing data sources
is the first priority, but also the need of expansion, and identification of new
data sources. An excellent example in this direction must be mentioned the
experience, and best practice of the act on secondary use of health and social
care data. This act opens up new possibilities and streamlines usage health
and social care data. On March 13th 2019, after almost four years of
preparatory work, the Finnish Parliament approved the Act on the Secondary Use of
Health and Social Data [
The problem of small outcomes compared to the investment in large scale IT projects was presented as it appears in many sectors. Especially in the application of big data in health sector, the new element enhancing the problem comes from the incorporation of new forms of patient generated data. These forms include both physiological but also psychometric data. Data collected real-time, and directly through sensor devices or data generated online, as patients’ comments or posts in social networking tools online. Proposed were processes aiming on the one hand to underline that apart of the importance of patients’ involvement, it is also important the involvement of all the other stakeholders. This will both make data collection easier and better, and turn data into actionable information. Finally concrete interventions in the direction of Big Data usage in Health sector are here proposed, which will help in enabling new operating and business models.
This paper is prepared with the support of GloBIG: cloud integration model platform with hybrid massive parallelism and its application for analysis and automated semantic enrichment of large collections of heterogeneous data contract number: DN 02/9-17.12.2016г., and the scientific project, under the National Scientific Program “е-Health in Bulgaria”, contract number: D01-200/16.11.2018