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.

Innovation, Active patients and Diabetes

Yesterday I participated in a workshop about Innovation, active patients and Diabetes. I would like to share some of the scientific references I used for my presentation

Glasgow, R. E., Kurz, D., King, D., Dickman, J. M., Faber, A. J., Halterman, E., et al. (2011). Twelve-month outcomes of an Internet-based diabetes self-management support program. Patient Educ Couns, .

Osborn, C. Y., Mayberry, L. S., Mulvaney, S. A., & Hess, R. (2010). Patient web portals to improve diabetes outcomes: a systematic review. Curr Diab Rep, 10(6), 422-435.

Greene, J. A., Choudhry, N. K., Kilabuk, E., & Shrank, W. H. (2011). Online social networking by patients with diabetes: a qualitative evaluation of communication with Facebook. J Gen Intern Med, 26(3), 287-292.

Weitzman, E. R., Cole, E., Kaci, L., & Mandl, K. D. (2011). Social but safe? Quality and safety of diabetes-related online social networks. J Am Med Inform Assoc, 18(3), 292-297.

I would like to thank Joan Carles March (@joancmarch) for the invitation.

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

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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.

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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.