Journal:Big data and public health systems: Issues and opportunities

Full article title	Big data and public health systems: Issues and opportunities
Journal	International Journal of Interactive Multimedia and Artificial Intelligence
Author(s)	Rojas de la Escalera, David; Carnicero Giménez de Azcárate, Javier
Author affiliation(s)	Sistemas Avanzados de Tecnología, Health Service of Nararre
Primary contact	Email: javier dot carnicero dot gimenez at cfnavarra dot es
Year published	2018
Volume and issue	4 (7)
Page(s)	53–59
DOI	10.9781/ijimai.2017.03.008
ISSN	1989-1660
Distribution license	Creative Commons Attribution 3.0 Unported
Website	http://www.ijimai.org/journal/node/1629
Download	http://www.ijimai.org/journal/sites/default/files/files/2017/03/ijimai_4_7_8_pdf_16011.pdf (PDF)

Abstract

In recent years, the need for changing the current model of European public health systems has been repeatedly addressed, in order to ensure their sustainability. Following this line, information technology (IT) has always been referred to as one of the key instruments for enhancing the information management processes of healthcare organizations, thus contributing to the improvement and evolution of health systems. On the IT field, big data solutions are expected to play a main role, since they are designed for handling huge amounts of information in a fast and efficient way, allowing users to make important decisions quickly. This article reviews the main features of the European public health system model and the corresponding healthcare and management-related information systems, the challenges that these health systems are currently facing, and the possible contributions of big data solutions to this field. To that end, the authors share their professional experience on the Spanish public health system and review the existing literature related to this topic.

Keywords: big data, health system, healthcare organizations, health information systems, epidemiological surveillance, strategic planning

Introduction

The health system

According to the World Health Organization (WHO), “a health system consists of all organizations, people and actions whose primary intent is to promote, restore or maintain health. This includes efforts to influence determinants of health as well as more direct health-improving activities. A health system is therefore more than the pyramid of publicly owned facilities that deliver personal health services.” Furthermore, every health system performs the following set of basic functions:

• delivering health services to individuals and to populations
• creating resources
• providing stewardship
• financing the system

The center of any health system must be the first of these functions, since healthcare constitutes the paramount goal and therefore the reason for the existence of the health system itself. Around it, other functions are organized, essential for ensuring healthcare delivery and public health. Among these, the following must be remarked upon:

• epidemiological surveillance, which comprises the collection and analysis of large volumes of data directly or indirectly related to people’s health, so as to detect or prevent possible health problems regarding public health
• planning and overseeing the management of the health system, which allows healthcare organizations to set out their strategic goals, allocate the necessary resources, assess the degree of compliance of these goals and apply corrective measures if required
• clinical research, focused on generating knowledge and applying it to the development of new diagnostic and therapeutic techniques
• education and teaching, in order to train new professionals and keep the practicing ones appropriately updated and competent

The health cluster or ecosystem

From a structural point of view, a health system is neither an isolated nor homogeneous entity, but rather it comprehends or relates to entities of diverse nature, both public and private, with interests of their own, as well as shared interests. This ensemble is known as health cluster or ecosystem, and among its components the following must be pointed out:

• central or federal government and regional or local authorities
• healthcare services, conceived as organizations responsible for the management of a determined healthcare network
• hospitals
• primary care centers
• emergency services
• pharmacies
• convalescent centers
• health professionals acting as external providers to the health system
• public health services
• insurance companies, mutual societies, and other entities which finance healthcare
• schools for the education and training of doctors, nurses, and other health professionals
• research centers
• professional associations and colleges
• foundations and learned societies
• stakeholders, such as patients associations
• pharmaceutical and other health technology industries

Challenges faced by the health system

For decades, the public health systems of European countries, created following the end of World War II, have been frequently mentioned as a reference model to be followed, especially in those aspects regarding coverage, quality of service, and contribution to the welfare of society. However, the scene in which these systems arose has suffered a series of major changes, being the most important the following ones:

• the aging of the population, with a continuous increment of chronic and degenerative diseases
• the financial crisis, which causes important budget cuts in the public funds meant to finance the health systems activities, and makes it more difficult—or even impossible—for the citizens to compensate these cuts with out-of-pocket expenses
• the creation of new techniques and drugs, more effective but also more expensive, mainly due to the necessity to compensate the research costs caused by their development
• the increasing demands of the citizens, who require more and better healthcare services in a setting that seeks patient empowerment and promotion of personalized medicine

As a token of the first two determinants, aging of the population and public budget cuts, the Spanish case is addressed below. Table I shows the progress of these two indicators during the period between 2003 and 2014.

Table 1. Demographics and health expenditure in Spain (2003–2014) Sources - demographics: Demographic Information System, Spanish National Statistics Institute (INE); health expenditure date: OECD Health Statistics Year Total population Population 15–64 years Population older than 64 years Dependency ratio Public health expenditure Private health expenditure People % over total M€ % GDP M€ % GDP 2003 42,717,064 29,396,965 7,276,620 17.03% 24.75% 43,158.4 5.37% 17,354.5 2.16% 2004 43,197,684 29,777,965 7,301,009 16.90% 24.52% 46,992.4 5.46% 18,651.1 2.17% 2005 44,108,530 30,511,110 7,332,267 16.62% 24.03% 51,351.5 5.52% 20,094.2 2.16% 2006 44,708,964 30,849,177 7,484,392 16.74% 24.26% 56,662.2 5.62% 21,520.7 2.14% 2007 45,200,737 31,188,079 7,531,826 16.66% 24.15% 61,612.0 5.70% 23,101.9 2.14% 2008 46,157,822 31,869,008 7,632,925 16.54% 23.95% 68,147.1 6.11% 24,392.9 2.19% 2009 46,745,807 32,145,023 7,782,904 16.65% 24.21% 73,035.6 6.77% 23,863.0 2.21% 2010 47,021,031 32,153,527 7,931,164 16.87% 24.67% 72,852.6 6.74% 24,593.7 2.28% 2011 47,190,493 32,082,758 8,093,557 17.15% 25.23% 71,800.0 6.68% 25,510.2 2.38% 2012 47,265,321 31,980,402 8,222,196 17.40% 25.71% 68,262.9 6.47% 26,594.3 2.55% 2013 47,129,783 31,718,285 8,335,861 17.69% 26.28% 65,718.5 6.26% 26,981.3 2.62% 2014 46,771,341 31,281,943 8,442,427 18.05% 26.99% 65,975.7 6.34% 28,558.1 2.74%

These data reveal that the Spanish population has increased from 42.72 to 46.77 million people during the 2003-2014 period, while the percentage of people older than 64 years has risen from 17.03% to 18.05% over total population, and the dependency ratio, which indicates the ratio between population older than 64 years and population between 15 and 64 years old, has risen from 24.75% to 26.99%. On the other hand, public health expenditure in 2003 meant 5.37% GDP, reaching a peak of 6.77% in 2009 and falling to 6.26% in 2013, experiencing a small recovery in 2014, with 6.34% GDP. Regarding private health expenditure, it was at minimums around 2.14%-2.17% GDP but it has risen year after year since the beginning of the financial crisis in 2008, reaching 2.74% GDP in 2014.

All things considered, the impact of all these determinants is so important that the sustainability of this model of public health system has been questioned in recent years.

The transformation of public health systems

Despite the fact that the challenges explained above make clear that a deep transformation of this health system model is needed, and IT is often considered as one of the main facilitators for this change, it is not admissible to think that health systems are going to lose their essential features. Health systems must improve people’s health, from both an individual and a collective point of view, and this final goal will not change in spite of the introduction of new technologies impacting big data.

The patient must always be the center of any health system and, in the same way, health information must always be the center of a health information system, which will be introduced below. The actions of a clinic professional focus on the achievement of specific healthcare goals customized for each one of their patients, improving or maintaining their health status. Besides knowledge, healthcare requires a connected and personalized relationship between the provider and the patient, so that interventions are tailored to the patient’s unique preferences and behavior, as with, for instance, drug adherence. Different people will have different reasons for non-adherence.

On their behalf, health systems managers must seek the compliance of the general goals defined by their organizations. These goals will be the aggregate of the individual goals related to each one of the professionals in their clinical staff. In addition, these managers will also be responsible for the allocation of the necessary resources and the financing of the whole activity in their organizations.

On the whole, health systems must focus their efforts on the creation of value for both the patient and society. To that end, clear goals must be defined that find an appropriate balance between the patient’s personal interests and the collective interest of society. For instance, in the event of a surgical intervention it is mandatory to measure some indicators such as mortality rate, adverse events, time of recovery, care costs, or time for the patients to return to their jobs at full capacity. Nevertheless, it is necessary to also take into account other indicators, maybe more subjective and thus harder to measure, but equally important because of their impact on the patient, such as post-surgery functionality, pain suffered, or the cost of all these factors from a quality-of-life point of view. If health systems are not focused on their patients’ interests and on achieving the corresponding goals, they will hardly be able to change and ensure their sustainability.

This article reviews the main features of the European public health system model and the corresponding healthcare and management-related information systems, the problems and challenges that these health systems are currently facing, and the solutions that big data tools may potentially offer in that respect. To that end, the authors have based this work on their professional experience with the Spanish public health system, an analysis of the scene that the latter is facing in the upcoming years and decades, and a review of the existing literature on big data applied to health.

Big data solutions in a healthcare environment

The health information system

The individual performance of the different components of the health cluster, as well as their interactions, causes the creation of multiple data flows, which are also greatly varied, since they involve several business processes. This set of data flows creates the health information system as a result.

As mentioned above, just as healthcare is the center of any health system, patient-related healthcare information must be the center of the health information system as well, since it may and will also be used for activities other than healthcare, such as epidemiological surveillance, planning, overseeing of management, clinical research, and education and training, as stated in the introduction. The fact that these data are stored in healthcare information systems is a consequence of them being generated during the patient’s care, but their usefulness goes clearly beyond this limit.

Therefore, the health information system must allow users to register, process, consult and share large amounts of data, ensuring their availability at the appropriate moment and point of the health cluster. On the healthcare side, this cluster reveals itself as a huge generator and at the same time consumer of enormous sets of information, related to personalized healthcare processes that take place on a daily basis and in a massive way. Healthcare is considerably intense regarding data treatment, by constantly creating immense datasets and frequently requiring access to knowledge sources.

For IT to be fully integrated in the health system value chain, it is mandatory to have a health information system which serves as an instrument for knowledge management being useful to all its users. Healthcare professionals cannot perform their duties properly without registering and using patients’ information, or without accessing the knowledge sources that allow them to make decisions on a solid basis. Public health departments need to know the population health status in order to detect or prevent potential collective health issues, as well as defining the necessary corrective and preventive measures. To those ends, these professionals must rely on data generated during every patient’s healthcare encounter, properly aggregated, as well as other data sources.

Managers are not able to plan a strategy, oversee its performance, and assess the achieved outcomes without a tool that allows them to process all the necessary information and provides them with accurate data, timely and in due form. These data are required from the very beginning, since the definition of an appropriate strategy must be based on the knowledge of the population’s health status, complemented with projections of its potential progress.

This complexity has been increased in recent years by a major change in healthcare organizations, which have evolved from a clearly paternalist way of interaction with their patients to a completely different one, focused on seeking their empowerment. In addition, patients are not content anymore with the information provided to them by their doctors, but search the internet for additional data about their diseases, engage on social networks, make their own decisions, and register information on their health records. This new role is indeed required if, for instance, health authorities seek to promote one of the most important lines of action in the field of chronic patient management, self-care encouragement, which has a beneficial impact on both the patient and the health system. However, this requires also a more varied interaction between them, combining traditional simple events, like setting up appointments with a general practitioner, with more complex actions, like monitoring health data analyzed and stored by wearable devices.

Despite this, it is clearly positive that both society and the medical community have evolved from a discussion about giving patients clearance to access their own healthcare information, to a totally different one about seeking the best way for the patients to register data in their health records, either in an active and conscious way or in an passive and automated one via specific devices. In any case, it must be always taken into account that the management of healthcare information is not a process unrelated to healthcare but rather an inseparable component of healthcare itself, hence its management and supervision are the healthcare professionals’ responsibility, even though the patients take a more active role. Furthermore, every professional must accept this new reality and provide the patient with the necessary training so that this initiative ends up being successful.

Apart from this, the temptation of exploiting the information stored on different social networks turns out to be very powerful. It is true that, to the health system, it is a possibility worth exploring, but several conditioning factors must also be considered. The first one is data protection as a consequence of people’s right to privacy, something that, from the beginning, seems to collide clearly with the business model of social networks themselves, designed to share large amounts of information in a quick, heterogeneous, and, up to some point, uncontrolled way.

Precisely these features represent another important conditioning factor, since social networks are nothing but huge repositories that store unstructured, poorly classified, or simply uncategorized data, not to mention the more than likely irrelevance of most of them regarding healthcare and, moreover, their doubtful veracity, a feature essential to this field. Given their market penetration, with millions of users around the world, it seems advisable to assess the possibility of using social networks as an information source for health systems, as long as a model can be defined that solves or at least mitigates all the inconveniences mentioned above.

Potential contributions of big data to health systems

The field of big data analytics is rapidly expanding, up to the point that it has begun to play a main role in the evolution of healthcare practices and research, by providing tools to register, manage, and analyze huge amounts of both structured and unstructured data produced by current healthcare information systems.

Health-related big data streams can be classified into three categories:

• Traditional healthcare data are generated within the health system and stored in datasets such as health records, medical imaging tests, lab reports, or pathology results, among others. Analyzing this information allows to achieve a better understanding of disease outcomes and their risk factors, and also to reduce health system costs, thus making them more efficient.

• “Omics’’ data deal with large-scale datasets in the biological and molecular fields, such as genomics, microbiomics or proteomics, for instance. The study of this information leads to deeper knowledge about how diseases behave, accelerating the individualization of medical treatments.

• Data from social media allow to figure out how individuals or groups use the internet, social media, apps, sensor devices, wearable devices or any other tools to better inform and enhance their health.

Additionally, the inclusion of geographical and environmental information may further increase the ability to interpret gathered data and extract new knowledge.

Notes

This presentation is faithful to the original, with only a few minor changes to grammar, spelling, and presentation, including the addition of PMCID and DOI when they were missing from the original reference. Citation three is listed in the references of the original but inadvertently omitted from the inline citations; it has been placed in the text at what is believed to be the appropriate citation point. Additionally, the original document placed citations 11 and 12 before nine and 10; this version shows citations in order of appearance, by design.