SUMMARY
Full draft report
Ppt presentation

I.    Background
The Citizen Panel Survey carried out in SIMPHS2 to better assess users and patients’ needs and expectations with regard to ICT for health, directly supports the objectives of the Digital Agenda in the area of eHealth which are to both cope with societal challenges and create opportunities for innovation and economic growth by reducing health inequalities, promoting active and healthy ageing and increasing empowerment. It also contributes to the goals of the European Innovation Partnership on Active and Healthy Aging which addresses the societal challenge of an ageing population focusing on the main areas of life events (Prevention, Care and cure and Independent living) with the following expected results:

• An improvement of the health status and quality of life of Europeans, especially older people;
• An improvement of the sustainability and efficiency of health and social care systems;
• Boosted EU competitiveness through an improved business environment for innovation

In this policy context the analysis of users’ demand undertaken through the SIMPHS2 Citizen panel survey aims to:

• develop typologies of digital healthcare users and measure the impact of ICT and the Internet on health status, health care demand and health management.
• identify factors that can enhance or inhibit the role and use of Personal Health Systems from a citizen’ s perspective with special emphasis on mHealth, RMT, disease management, Telecare, Telemedicine and Wellness.

To reach these objectives, we started by defining a theoretical framework for policy-making, which was used to design and gather relevant information. A multivariate statistical analysis was subsequently carried out to identify the underlying conceptual dimensions emerging from the data collected. Key relationships between concepts (underlying dimensions) were identified to understand ICT for Health as a complex ecosystem. We concluded with some lessons learned.

II.    Conceptual framework: Towards social determinants of ICT for Health

Two frameworks are at the root of our own conceptual framework “Towards social determinants of ICT for Health”. One is the WHO Commission on Social Determinants of Health Framework which summarises how “social, economic and political mechanisms give rise to a set of socioeconomic positions, whereby populations are stratified according to income, education, occupation, gender, race/ethnicity and other factors; these socioeconomic positions in turn shape specific determinants of health status (intermediary determinants) reflective of people’s place within social hierarchies; based on their respective social status, individuals experience differences in exposure and vulnerability to health-compromising conditions”. While this framework does not relate directly to ICT for Health, the structural determinants perfectly overlap the core argument of personal and positional categories of and distribution of resources in van Dijk’s “Causal and Sequential Model of Digital Technology Access by individuals in Contemporary Societies” which is the second framework in which our approach is rooted.

As a result  and as illustrated in the next we defined “Towards social determinants of ICT for Health” as follows:

• Social determinants of health and health inequalities, therefore structural and intermediary determinants produce different levels of ICT access (motivation, material, skills and usage).
• Unequal access to ICT will generate different levels of ICT for Health access as well as different levels of willingness to use ICT for Health.
• ICT for Health access depends on the properties of ICT and the relationship among Motivation; ICT for Health readiness and Internet Health information.
• Motivation includes Triggers, Empowerment and Barriers
• ICT for Health readiness includes Awareness, Material access; Skills and Usage
• ICT for Health Assessment includes how individuals use and evaluate this type of technologies for themselves or for others (social life of information) as well as their perception about usefulness and learning.
• ICT for Health Access gives rise to different level of Participatory Health through the utilisation (individually and socially) of ICT for Health in daily life and behavioural changes due to the ICT for Health impact on: Health management; Health care demand and Health care quality
• These impacts could modify both structural and intermediary determinants and distribution of health and well-being.

III.    Online panel survey technical information

Based on the above framework, we gathered data through a questionnaire which we designed and structured around five main blocks :

• Block A: Health status and health care and social care services use
• Block B: ICT for Health Motivation and Health Information sources
• Block C: ICT Access
• Block D: ICT for Health Readiness and Evaluation
• Block E: Socio demographic profile of participants

To reach our target population, we have used the Internet as a methodological tool. Survey research is becoming a frequently used methodology due to the advancement of computer hardware, software and increasing access to the Internet. Furthermore, online surveys offer a valid alternative to the postal, telephone or face-to-face surveys as long as technical, methodological, ethical and legal considerations are taken into account. Table 1 resumes the technical characteristics of the study.

Technical information

Population: Citizens aged from 16 to 74 years old who have used the Internet in the last three months.
Scope of countries: Austria, Belgium, Germany, Denmark, Estonia, Finland, France, Italy,    Netherlands,  Sweden, Slovenia, Slovakia, Spain, United Kingdom
Type of survey: Online
Sample size:    1,000 interviews per country - 14,000 interviews in total.
Quotas: Country - Gender (Female/Male) - Age Group (16-24/ 25-54/ 55-74)
Sampling error +0.85% for overall data and +3.16% for country-specific data. In all cases, a maximum indeterminate probability (p=q=50), for a confidence level of 95.5% is applicable for each one of the reference populations
Weighting: Proportional allocation for each country. Weighting by country to be able to interpret the overall data.
Sampling: Individuals have been sampled in a completely random manner.
Fieldwork period:  20 July 2011 to 20 August 2011

It should be noted that the data analysed in this report relates to an Internet user population which also forms part of online panels. Accordingly, it can be deduced that the respondents’ profile in terms ICT uses is slightly more advanced than that of the general population of the surveyed countries. However the underlying dimensions identified and their relationship remain valid.

IV.    ICT access

With respect to Internet based activities, the sampled population mainly uses it to search for information (68% every day), sending e-mails with attachments (41%), online banking (20%), social networks (39%) and instant messaging (23%). Internet activities are linked with the male gender, the youngest age groups, a university education, self-employment and entrepreneurs, students, population density and a good state of health.

The factor analysis helped identify the main underlying dimensions of Internet activities. Four factors have emerged:

• Basic uses
• Individual uses
• Social - Web 2.0 uses
• Tech uses

These factors represent a social gradient of Internet activities from the easiest use of the Internet (basic uses) to the most sophisticates activities (tech uses).

V.    ICT for Health Motivation

Individuals were asked about the triggers to utilise ICT for Health. More than a third of the sampled European population indicates a significant use of ICTs in health to better understand a health problem or disease (39%), to find additional sources of information (36%) and to develop knowledge and personal satisfaction (35%). A little further behind, but still with a relevant frequency, there is the perception that ICTs in health are very useful to help a family member or a friend who is ill (31%), to prevent illnesses or to adopt a more healthy lifestyle (28%), to find a solution to or a treatment for a health problem (28%), to obtain different points of view about an issue (22%), and to access an online health service (21%). Finally, and as a counterpoint, only 11% of European citizens give much importance to the use of ICTs in health for participating in online discussions.

With respect to the socio-demographic characteristics of the population, the perception of the importance of ICT in health as triggers is much more positive for women, young people, the middle aged, those with a tertiary education, the employed, students, and people in a bad state of health or with long standing illnesses.

From these items two factors have emerged:

• social and services oriented and
• individual oriented uses.

Empowerment, broadly understood as the development of personal involvement and responsibility is one of the goals of prevention, promotion and protection in health. This definition assumes that responsibility is a more active form of control while competence refers to aptitudes or qualities that make it possible to be more autonomous and take a role in decision-making. Factor analysis identified these two dimensions of empowerment Moreover, three different perspectives of personal empowerment seem to coexist with respect to Health:

• ability to comply with expert advice (professional perspective)
• Self-reliance through individual choice (consumer perspective)
• Social inclusion through the development of collective support (community perspective)

Overall, this greater digital empowerment for the European citizens when it comes to their health and the healthcare professionals is linked with higher education levels, the worst states of health and the existence of long-standing illnesses

Finally, individuals were asked about the barriers to utilise ICT for Health. Lack of privacy (52%), security (51%), reliability (47%) and trust (46%) were the four main barriers for ICT uses for health indicated by the sampled European population to be very important. Other justifications were the lack of liability (38%), health literacy (36%), knowledge (33%), access to ICTs for health (29%), motivation and interest (28%), and the lack of digital skills (24 %).

Firstly, women are much more sensitive to barriers to the ICT use for health than men, particularly in terms of a lack of confidence. Similarly, the perception of barriers to ICT use for health is also much more evident in older people, those with lower levels of education and the inactive. Lastly, it is also worth highlighting that the presence of long standing illnesses is also very sensitive to lack of confidence.

The underlying dimensions of these items are:

• Lack of confidence and
• Lack of readiness.

VI.    ICT for Health usage

When it comes to specifically using the Internet for health and wellness, the research has provided interesting information, with notable relative differences. The main use of the Internet for health is for individual information searches, rather than sharing information, communicating or interacting about health and more particularly information searches about physical illnesses or conditions.

Over half of the sampled European citizens have never used the Internet to buy medicine or vitamins online (56% of the total); participated in online support groups for people with the same health issue (60%), used social networking sites for health and wellness issues (58%); used e-mail or websites to communicate with a doctor or their office (58%); analysed the privacy policy for personal information in medical websites (52%); explained a medical issue online in order to make contact with an e-health medical service (61%) or with other users (58%); disclosed medical information on social networking sites (67%); or disclosed medical information on websites to share pictures, videos, or movies (67%).

The specific use of ICTs in the health sector is still quite limited among the sampled European citizens. Around three-quarters of the sampled population have never experienced any of the specified ICTs for health uses: 79% of individuals have never made an online consultation through videoconference with healthcare professionals. 75% have not received medical or clinical tests online either. 77% have not accessed or uploaded medical results via a specialist provider, such as Google Health or Microsoft Vault. 76% have not accessed or uploaded medical results via an Internet application provided by a health organisation. 76.6% have not used health or wellness applications on mobile telephones either. And 73.6% of the sampled population has not used ICT applications to transmit vital signs and other clinical information anytime or anywhere.
With respect to the remaining socio-demographic factors, the analysis shows homogeneity in terms of the overall use of ICT for health, which is more frequent in the young population, those with a tertiary education, students and the employed, those in densely populated urban areas, people in a bad state of health and those with long standing illnesses.

The factor analysis of ICT for health activities reveals two underlying dimensions:

• ICT for Health oriented towards Information and Communication and
• ICT for Health oriented towards services and devices.

Finally, these items allow us to analyse individuals’ level of awareness, skills and willingness. First of all, individuals were directly asked about their level of awareness. Second, the number of activities carried out by individuals was considered as a proxy for skilled individuals. Third,
individuals who stated they never carry out these activities or were not aware of them were asked about their willingness to carry out these activities. The factor analysis of willingness reveals three underlying dimensions

• Willingness to use Internet Health information
• Willingness to use Web 2.0
• Willingness to use services and devices

These factors are consistent with the underlying dimensions of ICT readiness mentioned before.

VII.    ICT for Health Impact

The study has also provided evidence about the consequences of ICT for Health utilisation. It has to be said that the perceptions are positive overall. 58% of the sampled European population state they agree that ICT use for health allows savings in terms of  cost of travel and time. 56% state that they would be willing to share personal health information with their doctor despite the privacy issue. 55% state that ICTs for health can improve the possibilities for caring for themselves and monitoring their state of health. 55% agree with the fact that ICT use for health leads to greater patient satisfaction. 54% agree that e-health can improve the quality of the medical services received. 50% of the European citizens consider that ICT use for health can change their behaviour towards a healthy lifestyle.

Slightly under half of the sample of European citizens, 43%, agrees that ICT use for health can improve their state of health. 42% consider that they would feel more comfortable and safe if they used a remote monitoring system for their health condition. 42% consider that ICT use for health increases ICT use in other fields of daily life. 32% agree that the use of health services through the Internet substitutes face-to-face consultations with doctors. 32% agree that online health services and face-to-face services are of equal quality. And lastly, 23% of European citizens would be willing to pay for access to Internet health services to improve their state of health or that of their relatives.

Positive attitudes about the impact of ICT for health are more prominent  among the youngest population, those with a tertiary education, and those that live in densely populated areas. The only notable difference between individuals with bad state of health and those with good state of health is the perception by the former that ICT uses for health can improve the quality of health services received (57%). Meanwhile, citizens with long standing illnesses clearly state their favourable perceptions of ICT use for health, as opposed to citizens that do not have long standing illnesses. In particular, they state that ICT use can improve patient satisfaction (56%), improve caring and health condition monitoring skills (57%), save travelling costs and time (60%), and that they are willing to share personal information through the Internet with doctors and health organisations despite privacy issues (60%).

Finally the factor analysis reveals two underlying dimensions:

• Impact on quality of healthcare and healthy behaviours
• Impact on healthcare access.

VIII.    Social determinants of ICT for Health: key dimensions

All items gathered were grouped into underlying dimensions through multivariate statistics following our conceptual framework. This exercise allows us to transform items into concepts and therefore understand the complexity of the ICT for Health ecosystem.

Underlying dimensions of Social determinants of ICT for Health

All above mentioned unveiled the complexity of ICT for Health. To tackle this complexity,   correlation analyses of all dimensions have been performed. The main results of these analyses are summarised in the following figure:

• Social determinants of Health (structural and intermediary), especially education and age, produces different levels of ICT readiness. Advance uses of the Internet such as Tech and Web 2.0 uses are more likely to be carried out by the young, the healthy and the well-educated population while basic uses are mostly performed by the elderly, therefore individuals with worse health status (chronic patients and individuals having reported higher numbers of health problems).
• Unequal ICT readiness generates different levels of motivation. Individuals making more advance uses are triggered by the potential of ICT to facilitate social interaction and services related to health while individuals whose uses are basic or individual are triggered mainly by Internet health information for personal proposes. Furthermore, individuals with the lowest level of readiness (basic uses) and having reported more health problems lack confidence in the use of ICT for Health. Nevertheless, this lack of confidence is counterbalanced by a higher level of empowerment (competence oriented).
• Both ICT for Health usages (Services and Devices and Information and Communication) are specially driven by social and services triggers while individual triggers are only slightly correlated with Information and Communication usages, therefore less advanced uses.
• Both dimensions of Empowerment push ICT for Health usage. Individuals who are more competence-oriented are more inclined to Information and Communication usage while individuals who are more control-oriented are more likely to use Services and Devices. Thus individuals who feel more responsible for their health status are more likely to use Services and Devices while individuals who want to be more autonomous (competence refers to aptitudes or qualities that make it possible to be more autonomous) are more likely to utilise Information and Communication. If we consider individuals’ education, age and health status it looks like Services and Devices are related with well-being and wellness practice, therefore with health prevention and promotion while Information and Communication are more related with illness, therefore with cure and independent living
• All individuals using ICT for Health faced the same barriers; therefore lack of confidence and lack of readiness are not correlated significantly with ICT for Health usages. Nevertheless, lack of confidence is negatively correlated with the ICT for Health impact on the access dimension. Individuals need a certain level of confidence in ICT for Health to go beyond information and communication and engage with services such as RMT, Personal Health Records or videoconference consultation.
• The utilisation of Services and devices is strongly correlated with the perception that ICT would have an impact on both healthcare access and quality and healthy behaviours while the utilisation of Information and Communication is slightly correlated with Quality and healthy behaviours only.
• The number of health problems reported by individuals is only slightly correlated with Information and Communication Usage and it is unrelated to Services and devices utilisation. Therefore, individuals who could take more advantage of Services and devices, due to their health status, are more likely to be oriented towards information and communication usage only.

IX.    Lessons learned

The study reported here reveals the potential of ICT for Health to promote active and healthy individuals and increase empowerment. Even though our findings relate to Internet users, it is worth pointing out that new health inequalities are emerging due to the impact of the “traditional determinants of heath” on ICT readiness.

Therefore, eInclusion policies related to ICT for Health are needed to ensure that individuals with low socio-economic status and more health problems are able to benefit from these types of technologies. These ICT for Health divides specially impact on the elderly. However, there is an opportunity for them to engage with the Information Society through ICT for Health due to the importance of health issues in their daily life.

The relationship between the different typologies of ICT readiness and ICT for Health Motivation and Impact reveal that:

• Young individuals are already using this type of technologies mostly in relation with wellness and healthy live style. These uses enable an entire world of possibilities related with health promotion and prevention, especially considering that young individuals are heavy Web 2.0 users.
• Middle age individuals are also active users of ICT for Health acting as gatekeepers of this type of technologies within the household. Therefore these individuals could act as enablers for others i.e. both for the elderly and the young within households
• The elderly are basically using ICT for Health for information and communication purposes. There is a gap between this type of use and services and devices uses which could be more effective in relation with cure and chronic conditions.

Individuals between 16-54 with chronic conditions, going under long-term treatment and with more than one health problems are more likely to use ICT for Health than individuals without these type of health problems. Individuals between 55-74 who are healthy are more likely to use ICT for Health, especially for Information and Communication, than individuals with worse health status. Therefore, in the short term, this group of individuals will be pushing for health systems to provide them with new solutions (services and devices) when they need to tackle a health problem. This pressure will increase during the next decade when middle age individuals become elderly. Therefore health systems are facing the challenge of having to promote further ICT innovation to answer these new demands. While this is an opportunity to improve both sustainability and efficiency of healthcare system, it is associated with a number of challenges linked to eHealth deployment.

Further, during this transition, health systems can not leave out the elderly who are not active and healthy: this group of individuals can not be omitted as they are the current intensive users of healthcare systems. There is an opportunity to include them in the Information Society by improving ICT readiness and ICT for Health willingness and awareness.

Lately I have been designing, launching and gathering an online panel survey to a representative sample of Internet users in 14 European countries (approximately 14,000 responses). To ground the questionnaire I have developed a conceptual framework inspired and based on the two main sources. On the one hand, the Marmot Review team:

• Solar O & Irwin A (2007). A conceptual framework for action on the social determinants of health. Discussion paper for the Commission on Social Determinants of Health. Geneva, World Health Organization.
• Commission on Social Determinants of Health. (2008).  Closing the gap in a generation: health equity through action on the social determinants of health. Final report of the Commission on Social Determinants of Health. Geneva, World Health Organization.
• Marmot M et al. (2010). Interim first report on social determinants of health and the health divide in the WHO European Region. Copenhagen, WHO Regional Office for Europe.
• Marmot M et al. (2011). Interim second report on social determinants of health and the health divide in the WHO European Region. Copenhagen, WHO Regional Office for Europe.

On the other hand, a Framework for Digital Divide Research developed by Jan van Dijk in several publications:

• Jan van Dijk and Ken Hacker (2003). The ‘Digital Divide’ as a Complex and Dynamic Phenomenon. The Information Society. Vol. 19, Nr. 4, 315-326.
• Jan van Dijk (2005).The Deepening Divide, Inequality in the Information Society. Thousand Oaks, London, New Delhi: Sage, 240 p.

In a recent presentation about Health and Web 2.0 I tried to match both frameworks and I have posted about Inverse care law 2.0  several times using different scientific and statistical sources.  It is worth pointing out (and obviously reasonable) that I have not found any references or mentions to ICT for Health in the literature about social determinants of Health gathered through Marmot Review team website.

However, both frameworks (see red boxes in both figures) mention individual and social characteristics as social determinants of health and of the Internet usage. Furthermore, van Dijk includes HEALTH and ABILITY as a personal category (and I have added Health as a sphere of participation in Society and emphasis the Divides).

Based on and inspired by this two frameworks I have developed Social determinants of Health and ICT for Health (eHealth) conceptual framework.

All concepts and boxes  of this framework are based on scientific references and the relationships established by arrows have been empirical or theoretical driven. I’m currently working on it, however I have shared this framework to gather inputs to improve it. I would love to know your comments and ideas.

UPDATE: Citizens and ICT for Health in 14 EU countries: results from an online panel survey

On behalf of my co-authors, Wainer Lusoli, Margherita Bacigalupo, Ioannis Maghiros, Norberto Andrade, and Cristiano Codagnone from Information Society Unit - European Commission, DG JRC Institute for Prospective Technological Studies (IPTS), Seville, Spain, I’m presenting “Health-related Information as Personal Data in Europe: Results from a Representative Survey in EU27″ at Medicine 2.0′11 (Stanford University, USA).

Abstract published at Medicine 2.0 website here:

ABSTRACT

Emerging technological and societal developments have brought new challenges for the protection of personal data and individuals’ rights. The widespread adoption of social networking, participation, apomediation, openness and collaboration stretches even further the concepts of confidentiality, privacy, ethics and legality; it also emphasizes the importance of electronic identity and data protection in the health field.

Governments across the Atlantic have adopted legal instruments to defend personal data and individuals’ rights, such as the Health Information Portability and Accountability Act (1996) in USA, the Recommendation No. R(97)5 on the Protection of Medical Data issued by the Council of Europe (1997) in addition to specific legislation adopted by each EU Member State as part of the Data protection Directive 48/95 transposition process. These reflect policy makers’ concerns about the need to safeguard medical and health-related information. On the other hand, bottom up developments such as the widespread usage of “PatientLikeMe” and the availability of industry based platforms for user-owned electronic medical records (i.e. Google Health or Microsoft Health Vault) are often pointed at, arguing that users do not really care about data protection as long as sharing such data produces more value than it destroys. There is, however, a clear evidence gap as to the attitudes of Europeans with respect to this issue.

The purpose of this paper is to identify and characterize individuals’ perception, behaviors and attitudes towards health-related information and health institutions regarding electronic identity and data protection. The research is based on Eurobarometer 359 “The State of Electronic Identity and Data Protection in Europe”, a representative sample of people in EU27 conducted in December 2010. The survey was conducted in each 27 EU Member States via a national random-stratified samples of ~ 1,000 interviews; overall, 26,574 Europeans aged 15 and over were interviewed face-to-face in their homes. The questionnaire asked questions about data disclosure in different context, including health. Specifically, it included questions related to health and personal information, disclosure in Social Networking Sites and on eCommerce sites, trust in health institutions, approval required for disclosure and sensitivity of DNA data. Specifically, we will provide an encompassing portrait of people’s perceptions, behaviors and attitudes across EU27, we will examine the influence of socio-demographic traits and Internet use on such attitudes and behaviors. We will explore significant differences across major regional block. Finally, we will present results from factor analysis that aimed to identify commonalities between variables, and from cluster analysis, use to create typologies of individuals concerning health-related behaviors. Empirical analysis allows to broaden and deepen understanding of the consequences of data protection in Medicine 2.0. Our data also call for further, joint research on this issue, which links demand and supply of medical and health-related data. Indeed, not all people need or want the same level of detail: researchers and physicians clearly need to access more while end users or insurance companies can live with less information. This is one of the crucial points regarding the revision of the Data Protection Directive in Europe (Directive 95/46).

In a previous post entitled Benchmarking HIT Adoption in European Healthcare Organisations several challenges, including transparency, were mentioned. To tackle of those challenges, during the past few months I had the pleasure to collaborate with my colleague Cristiano Codagnone in the development of JRC Scientific and Technical Report entitled “A Composite Index for the Benchmarking of eHealth Deployment in European Acute Hospitals Distilling reality into a manageable form for evidence-based policy” published May 2011 .

Compared to other areas of the Information Society, where benchmarking has been conducted more systematically for longer (i.e. eGovernment), it is evident that benchmarking of eHealth deployment is lagging behind.

In this context, the results of the eHealth Benchmarking, Phase III survey, carried out by Deloitte and IPSO on behalf of Unit C4 of DG INFSO, with the rich information provided on about 1,000 European acute hospitals, could be a strategically important tool to close this gap. As we show in more detail later, this survey sheds light on key issues such as hospitals’ deployment of ICT infrastructure, applications, and much more.

The reasons why benchmarking of eHealth deployment is lagging behind are structurally related to the multi-dimensional complexities of this field, to the relatively greater difficulty/costs of getting the data (i.e. data cannot come from web-based measurement, as it can for eGovernment benchmarking), and especially to the challenges of making sense of the data.

This report uses multivariate statistical methods to analyse with a selective but deep vertical focus the results of the above-mentioned survey. The objectives of this exercise are two-fold:

a) to make sense of the results by constructing a composite index;
b) to extract key policy messages and new directions for future research.

The main objective is the elaboration of a composite index of eHealth deployment with a view to proposing a roadmap towards systematised and replicable benchmarking. In addition, we also explore the possible link between benchmarking and eHealth impact.
Therefore, our focus is much more selective but deeper than the broader descriptive analysis produced by Deloitte and Ipsos. In addition, we do not simply conduct multivariate statistical analysis but we put this into a conceptual and theoretical perspective and we follow it with a discussion of the results and with a set of policy and research recommendations.

This first introductory section is followed by four more. Section 2 provides the general conceptual and theoretical framework for benchmarking within an international policy perspective. Section 3 presents the data and the methodology used. In Section 4, we present and comment on the results of our multivariate statistical analysis. Finally, in Section 5 we discuss these results and extract recommendations for future research and policy making.

The Composite Index

The Hospital eHealth Deployment CI has been developed following a totally transparent multistage approach, which is graphically rendered in the figure below:

Countries with more intensive (per capita) healthcare spending in ICT score higher in our hospitals eHealth Deployment CI and it seems now perfectly sound that Italy, France and Germany have lower than expected CI in view of the fact that their ICT expenditure is considerably less intensive than in countries such as for instance Denmark, Sweden, and Norway. The data used are too aggregate and we do not dare going further than simply pointing out a mere statistical association. Yet, at least the direction is comforting: if it was negative (high rank in CI associate with low level of spending intensity) than we might have had a problem.

We replicated the operation done with ICT expenditure in healthcare with the following supply side indicators: “Hospital beds - Per 100,000 of population”; “Practising physicians - Per 100,000 of population”; “Number of Computer tomography scanners per 100,000″.

Again we stress that our aim was explorative and we looked for mere trends and statistical associations, with no claim to demonstrated significant statistical correlations and even less so infer causal relation. Yet, all of the trends illustrated in the following figures are comforting and not counterintuitive with respect to what one would expect as a result of wide introduction of eHealth on the above three supply side indicators: a) it would be counterintuitive and challenging to find the our CI is higher in countries with the highest number of hospital beds; b) it would be counter-intuitive and challenging to find the our CI is higher in countries with the lowest number of practicing physicians; c) it would be counter-intuitive and challenging to find the our CI is higher in countries with the highest number of computer tomography scanners. The trends in the figures do not support such instances. Naturally, we do not claim that having a higher CI enable to use fewer beds, to support more physicians, and to substitute scanners, for a much more in depth and granular analysis would be needed to substantiate this hypothesis. We simply observe that at least the direction of the trend is in line with what one may expect from relatively higher deployment of eHealth in hospitals.

Despite very relevant comparability problems, we can risk concluding that the results of the eHealth Benchmarking Phase III survey show that progress has been made in Europe with respect to the levels of eHealth deployment registered in previous, less systematic and extensive data gathering activities such as Business Watch and Hine. For instance, the penetration of Electronic Patient Records (EPRs) has increased from the 34% reported for 2006 by Business Watch to the current 81%. This 81% penetration of EPRs puts
Europe way ahead of Japan and US, where only between 10% and 15% of hospitals have introduced them. However, there are also several indications of areas in need of policy action, of which we emphasise the following four:

1) The CI shows large scope for improvement. The average EU27 CI stands at 0.347, whereas that of top scoring Sweden is just slightly above 0.5. This means that there is still room for general improvement.

2) Wide variation across countries. In particular, the lowest deployment measured by our CI is concentrated mostly among the new Member States and candidate countries. Of the bottom 13 countries, 12 are from this group – Greece is the exception. The only new Member State that scores above the EU27 average is Estonia, confirming its excellence in the domain of ICT. This calls for awareness raising policies and possibly financial support targeting this group of countries.

3) The summary indexes of the four dimensions identify areas to be prioritised. Whereas infrastructure deployment is quite high in most countries, electronic exchange of information lags behind fairly generally (across countries). It is important to close this gap, since these exchanges constitute one of the pillars of the vision and promises of ICT-supported integrated personal health services. These services are the key to producing better health outcomes while pursuing system sustainability and they must be developed around a seamless view of the user, for which exchange of information and timely clinical decisions are crucial. Yet, our analysis shows that electronic exchanges are still limited among the potential interacting players. Furthermore, cross-border exchanges are extremely limited, a gap that from the perspective of EU policy should be quickly addressed.

4) Predominant intramural orientation. From both simple descriptive statistics and from our multivariate statistical analysis, it emerges clearly that the deployment of eHealth in hospitals has been predominantly focussed on intramural needs and applications. For instance, levels of deployment for Personal Health Records and home-based Telemonitoring are very low. We need to stress that if the objectives and targets of the upcoming European Innovation Partnership on Active and Healthy Ageing are to be realised, much more progress will be needed in terms of both electronic exchange of information and user-oriented applications and services, such
as PHR and Telemonitoring.

Based on The Economics of eHealth (I) and some inputs from my colleague Cristiano Codagnone I have developed my presentation to “Recent Developments and Future Challenges of Integrated Care in Europe and Northern America” - 11th International Conference on Integrated Care organised by The International Network of Integrated Care, The Julius Center of the University Medical Center Utrecht and the University of Southern Denmark (March 30 - April 1, 2011 in Odense, Denmark). I would like to thank Dr. Albert Alonso for his invitation to participate in the conference.

Susannah Fox has invited Jessica Mark to post on www.e-patient.net:

This is a guest post by Jessica Mark, healthfinder.gov and Outreach Program Manager, Health Communication and eHealth Team in the Office of Disease Prevention and Health Promotion at the U.S. Department of Health and Human Services

The result of this invitation is entitled Making Strides Toward Improving Health Literacy Online where Jessica Mark highlighted part of the work done by the Office of Disease Prevention and Health Promotion. I really enjoy her post so I commented this:

Wonderful post! I wonder if eHealth literacy could be also a tool to integrate the elderly into Information Society / Network Society. It could be a tool to engage them within the tremendous potential of the Internet for other aspects of their lives. Health contents could be just an excuse to capture their attention (e-awareness) and help them to be online (e-readiness)

and Jessica Mark replied:

Francisco, thank you! I love the idea of eHealth literacy as a catalyst to overall digital literacy too. I’d love to hear/talk more about how that might work.

First of all, I would like to quote the main message of Prof. Jan van Dijk’s book “The Deepening Divide: Inequality in the Information Society”

“The digital divide is deepening where it has stopped widening. In places where most of peopel are motivated to gain access and physical access is spreading, differences   in skill and usage come forward. The more information and communication technology is immersed in society and pervades everyday life, the more it becomes attached to all exiting social divisions. It tends to strengthen them, as it offers powerful tools for everyone engaged. This occurs in the context of the evolving information society and network society. This type of society makes both digital and social divisions even more critical” (…) The digital divide is conceived of as a social and political problem, not a technological one. Physical access is portrayed as only one kind of (material) access among at least four: motivational, material, skills, and usage” (p.2-3)

As a part of his framework for understanding the digital divide, Prof. van Dijk has developed “A Causal and Sequential model of Digital Technology Access by individuals in Contemporary Societies” (p.24). I have included HEALTH as a field of participation in Society.

“The core argument of the book sets particular relationships between four states of affairs, in a process creating more or less information and communication inequality in using digital technologies (p.14):

1. A number of personal and positional categorical inequalities in society
2. The distribution of resources relevant to this type of inequality
3. A number of kinds of access to ICTs
4. A number of fields of participation in society

1 and 2 held to be the causes, and 3 is the phenomenon to be explained, together with 4, the potential consequences of the whole process (…). The core argument can be summarized in the following statements, which comprise the core of a potential theory of the digital divide (p.15):

1. Categorical inequalities in society produce an unequal distribution of resources.
2. An unequal distribution of resources causes unequal access to digital technologies.
3. Unequal access to digital technologies also depends on the characteristics of these technologies.
4. Unequal access to digital technologies brings about unequal participation in society.
5. Unequal participation in society reinforces categorical inequalities and unequal distribution of resources.

The general term access to digital technologies has been divided into four specific, successive kinds of access to digital technology, computes, and the Internet connections (p.21):

1. Motivational access (motivation to use these technologies)
2. Material or physical access (possession of computers and Internet connection or permission to use them and their contents)
3. Skills access (possession of digital skills: operational, informational, and strategic)
4. Usage access (number and diversity of application, usage time)

I have posted before about the importance of eInclusion and eHealth and Inverse Care Law 2.0 talking about the successive kinds of access to digital technology but I have not posted about what are the reasons for not having access to the Internet at home to explain why eHealth literacy could be a catalyst to overall digital literacy among the elderly.

Eurostat’s survey on ICT usage in households and by individuals (2010) stated that the main reasons not to access the Internet at home in almost all countries are related with MOTIVATIONAL ACCESS (does not need to; does not want to) and SKILLS ACCESS

Using Spain as an example I have crossed these reasons by Age:

Individuals between 55-74 emphasised the importance of SKILLS ACCESS and MOTIVATIONAL ACCESS. Following the framework and the figures above mentioned, eHealth literacy could be a catalyst to overall digital literacy among the elderly because:

1. Health could be a motivation for the elderly to use the Internet (e-awareness)
2. This motivation could be used as a trigger to learn how to use this technology (e-readiness)
3. Health professional and/or health care workers as well as relatives and/or friends could facilitate this learning process (ehealth literacy)
4. Use of the Internet for health could open new fields of participation in society for the elderly.
5. These new fields of participation in society could diminish categorical inequalities and unequal distribution of resources.

Thanks Susannah Fox and Jessica Mark for your inspiring post and comments

In my last post about The economics of eHealth (I) I quoted OECD. (2010). Improving Health Sector Efficiency: The Role of Information and Communication Technologies. Health Policy Studies to point out that this study mentioned an absence, in general, of independent, robust monitoring and evaluation of programmes and projects to determine the actual payoff from the adoption and use of ICT. A few days ago, PLoS Medicine has published:

Black AD, Car J, Pagliari C, Anandan C, Cresswell K, et al. (2011) The Impact of eHealth on the Quality and Safety of Health Care: A Systematic Overview. PLoS Med 8(1): e1000387. doi:10.1371/journal.pmed.1000387

I would recommend you to read the whole systematic overview. However, I would like to highlight the conclusions that are align with The Economics of eHealth (I) before mentioned:

There is a large gap between the postulated and empirically demonstrated benefits of eHealth technologies. In addition, there is a lack of robust research on the risks of implementing these technologies and their cost-effectiveness has yet to be demonstrated, despite being frequently promoted by policymakers and “techno-enthusiasts” as if this was a given. In the light of the paucity of evidence in relation to improvements in patient outcomes, as well as the lack of evidence on their cost-effectiveness, it is vital that future eHealth technologies are evaluated against a comprehensive set of measures, ideally throughout all stages of the technology’s life cycle. Such evaluation should be characterised by careful attention to socio-technical factors to maximise the likelihood of successful implementation and adoption.

This conclusion also challenges researchers to apply and develop new methods with “attention to socio-technical factors”, work with other discipline and combine  strong quantitative and/or qualitative approaches.

Lately, I have been reading and checking the research literature  about Health economics and ICT . This is the first post of a collection about this topic. Soon I’ll be sharing with you all my notes.

The Economics of eHealth (I)

Health economics, an applied field of economics, draws its theoretical inspiration principally from four traditional areas of economics: finance and insurance, industrial organisation, labour and public finance (Fuchs, 1997). Culyer and Newhouse, editors of the Handbook of Health Economics (2000), developed a schematic of Health Economics based on a first approach developed by Williams (1987).

Culyer and Newhouse (2000) stated that Box A contains the conceptual foundation; Box B is concerned with the determinants of health; Box C concerns the demand for health care while Box D contains the supply-side economics. These four boxes are the disciplinary “engine room”. On the other hand, the four peripheral boxes E, F, G and H are the main empirical fields of application. Box E deals with the ways markets or quasi-markets operate. Box F is more specifically evaluative and normative. Box G focuses on the great variety of health care delivery institutions, insurance and reimbursement mechanisms and the various roles played by different agencies. Box H is concerned with the highest level of evaluation and appraisal across systems and countries.

Within this broad scheme health economists have started to tackle the landscape of ICT in health systems. Investments in ICT in health care are greater than they have ever been, and in most countries, not less than 2.6%-6% of health budgets are dedicated to ICT. These investments are being presented as a means to improve productivity, quality of health and/or system efficiency (Lapointe, 2010). Case studies reported by OECD (2010) stated that ICT implementation benefits could be grouped according to four inter-related categories of objectives: (1) Increasing quality of care and efficiency; (2) Reducing operating costs of clinical services; (3) Reducing administrative costs and (4) Enabling entirely new modes of care. Therefore, ICT in health systems affects the disciplinary “engine room” of health economics, due to its impact on health care demand and supply, as well as the main empirical fields of application.

Lessons learned from these case studies pointed out that successful implementation and widespread adoption are linked to the ability to address three main issues: (1) Alignment of incentives and fair allocation of benefits and costs; (2) Lack of commonly defined and consistently implemented standards; and (3) Concerns about privacy and confidentiality.

Within this context OECD (2010) claimed that Governments could provide motivation for high-performing projects through targeted incentives and also occupied a central position as initiator, funding provider, project facilitator, and neutral convener, playing a special role to encourage the utilization of standards to reach a common goal. Furthermore, the main findings of this study could be summarised as follow: (1) Establish robust and coherent privacy protection; (2) Align incentives with health system priorities; (3) Accelerate and steer interoperability efforts; and (4) Strengthen monitoring and evaluation.

However, it is worth pointing out that this study mentioned an absence, in general, of independent, robust monitoring and evaluation of programmes and projects to determine the actual payoff from the adoption and use of ICT. Due to the special characteristics of ICT market, Christensen and Remler (2007) mentioned that the main barriers to ICT adoption in health sector (low product differentiation, high switching costs in replacing technologies, and lack of technical compatibility of all the different components of ICT) explained why it lags behind other sectors in ICT adoption, even though the centrality of information exchange in the care process and its usefulness in management, accountability, research and financial transaction (Street, 2007).

A particular problem in health sector is that there is no measure of performance analogous to profits from private sector firms, and health care organisations tend to pursue multiple objectives. Furthermore, ICT implementation may have effects that are multidimensional and often uncertain in their reach and scope, and difficult to control. In addition, the realisation of benefits from ICT implementation strongly depends on contextual conditions (Street, 2007). On the one hand, these difficulties are further exacerbated by data limitations, definitional problems and lack of appropriate sets of indicators on adoption and use of ICT comparison. On the other hand, dimensions related with measurement errors, time lag, redistribution and mismanagement of ICT are being pointed out within the application of “productivity paradox” (Brynjolfsson, 1993; Brynjolfsson & Hitt, 1998) into health care. These dimensions are essential to understand the competitiveness and profitability of health care organizations investment in ICT (Lapointe et al., 2010).

There has been a significant and growing debate internationally about whether or not these much touted benefits and savings are gained or, indeed, even measured (OECD, 2010). This debate has been supported decision makers to belief that clear profitability has not been demonstrated (Meyer, 2010). The need to accurately quantify the added value of ICT in health care sector has reached a critical requirement level (Meyer, 2008).

To understand the real impact of ICT within health care adopting a single analytical approach is inadvisable and that insight into the overall effects of ICT is best gained from consideration of a mix of study types (Street, 2007). Empirical studies into the impact of ICT could be grouped into four broad categories: (1) Aggregate analyses that take a macro perspective by looking at the economy as a whole; (2) Industry or sectoral level analyses that focus on specific industries or sectors within the economy; (3) Firm or organisational-level analyses and (5) Case studies that focus on specific examples of ICT (Street, 2007).

Due to the characteristics of health sector below mentioned applying an aggregate analysis or a sectoral level analysis remains difficult. Street (2007) has summarised the key advantages and challenges associated with each analytical approach:

All the references cited could be found at my online personal reference manager.

Recently, EUROSTAT has published the results from ICT usage household survey 2010. I have been analysing these data developing a Digital Health Care Demand in Europe and I would like also to share my analysis of  “individuals who  used the Internet for seeking health information on injury, disease or nutrition” (European Union 27 Member States), inspired by The Power of Mobile written by Susannah Fox. In my case, I would like to emphasis the raise of the inverse care law 2.0 to justify that there is no eHealth without eInclusion, in other words quoting Europe’s Digital Competitiveness Report 2010:

“In addition, while health-on-the-web may empower in various ways those who have access to the internet, the flip side of this is that those without internet access may become relatively more disadvantaged in health matters. For them, the experience may be more one of disempowerment through inability to take advantage of new opportunities. Factors linked to existing health divides, including lower health literacy and less proactive health attitudes, continue to contribute significantly to unequal health experiences and outcomes among less advantaged socio-economic groups. There is already some evidence that these groups may be experiencing a ‘double jeopardy’ as a result of an intertwining of these traditional health divides with the new digital divides.”

Firstly, since 2004 the percentage of individuals who used the Internet for seeking health information on injury, disease or nutrition (total individuals and individuals who have used the Internet in the last three months) has increased, even though from 2009 we can see a slower increase, specially in those who used the Internet. These trends facilitate the identification of a first gap between users and non-users.

To better capture this gap, I have divided the analysis in two part. On the one hand, considering the total individuals we can see the differences between groups of age and level of education.

Furthermore, we can also identify this gap if we focus on age and education together:

On the other hand, considering  individuals who have used the Internet in the last three months, you can see that there is still a difference between groups of age, level of education and both together:

It has to be remarked that most of these trends show that the divides are not going to disappear with time, in some cases these divides will get wider.  Therefore some groups may be experiencing a ‘double jeopardy’ as a result of an intertwining of these traditional health divides with the new digital divides. THUS, THERE IS NO eHEALTH WITHOUT eINCLUSION. Social care, Health care, Health Professionals and Social workers may work together and play a role not just in eHealth or on eInclusion but both to avoid ‘double jeopardy’ and  the inverse care law 2.0.

Note: I have developed the same analysis for all Member States and the gaps are even wider in some countries.