Category Archives: Policy and Legal aspects

Internet users and mHealth in Europe

Following Social determinants of Health and ICT for Health (eHealth) conceptual framework and the results from Citizens and ICT for Health in 14 EU countries: results from an online panel survey I have been exploring the difussion of mHealth in Europe.  Internet users were asked about the use of health/wellness application on their mobile phone:

  • 77% stated that they never use it;
  • 7% stated that they were not aware of it;
  • 6% stated that they use it less than once a month
  • 5% stated that they use it at least once a month (but not every week)
  • 4% stated that they use it at least once a week (but not every day)
  • 1% stated that they use it every day or almost every day

Socio-demographics’ characterisation revealed that internet users who at least once have used mHealth are more likely to be male; 16-24; students; living in a densely-populated area; reported good health status and not suffering a chronic condition. Therefore, it looks like we are talking mainly about health prevention and promotion opportunities; wellness and healthy life styles. I’m now analysing the data following the conceptual framework to better understand mHealth users and empowerment; trigger; barriers; impact… Comments are always welcome!

Meaningful use of eHealth in Acute Hospital in Europe – Benchmarking eHealth deployment

A few months ago I posted about a report titled A Composite Index for the Benchmarking of eHealth Deployment in European Acute Hospitals Distilling reality into a manageable form for evidence-based policy co-author with Cristiano Codagnone. On 23th March I was invited by the Catalan Agency for Health Information, Assessment and Quality to present the benchmarking exercise, including in the analysis data about Acute hospital in Catalonia gathered by TicSalut.

I wonder if this benchmarking exercise could be understood as a meaningful use of eHealth in Acute Hospital in Europe. The composite indicator is presented in a transparent manner so any practitioner or policy-maker can utilise the weights to benchmark its acute hospital within its country and with other European countries. This can naturally lead to the definition of a different approach to the construction of eHealth deployment and usage composite indicators and may at any rate produce standardised and comparable longitudinal and cross-sectional data.

Enhanced data gathering through active collaboration with Healthcare Actors

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

Social determinants of Health and ICT for Health (eHealth) conceptual framework

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:

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

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.

a-conceptual-framework-for-action-on-the-social-determinants-of-health-discussion-paper-for-the-commission-on-social-determinants-of-health

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).

deeping-digital-divide

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

social-determinants-of-health-and-ict-for-health-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

Health-related Information as Personal Data in Europe: Results from a Representative Survey in Eu27

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).

A Composite Index for the Benchmarking of eHealth Deployment in European Acute Hospitals Distilling reality into a manageable form for evidence-based policy

A Composite Index for the Benchmarking of eHealth Deployment in European Acure HospitalsIn 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:

Composite index Figure

ehealth_figure7

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.

figure_12

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.

Evaluation of Integrated Care: From methods to governance and applications – Economics of eHealth

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.

eHealth Literacy as a catalyst to overall digital literacy among the elderly

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.

van_dijk_framework

“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

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

spain_non_access

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

The Economics of eHealth (I)

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).

Health Economics Scheme

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:

Summary of the key advantages and challenges associated with each  analytical approach

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