Category Archives: Information Policies

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!

Enhanced data gathering through active collaboration with Healthcare Actors

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).

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

Inverse Care Law 2.0

I have posted several times about the “inverse care law” and eHealth. Following some conversations with @drbonis and @rcofinof I have decided to entitle this post “Inverse Care Law 2.0″ to embed my presentation (Spanish) at “V Jornada de debate sobre eficacia y seguridad en la utilización de medicamentos”.

Digital Health Care Demand or eHealth Care Demand in Europe – Eurostat

Lately, I have been working with aggregate data from Eurostat ICT usage household survey focused on the usage of the Internet and Health by European citizens. It is worth mentioning that this is a working in progress. Below you can find all variables available per year.

Table 1. Variables available per year at Eurostat ICT usage household survey

Caption Years
The type of goods and services I ordered over the Internet in the last 12 months for on-work use are: Medicine 2009
The type of goods and services I ordered over the Internet in the last 12 months for non-work use are: Non-prescribed medicine 2009
The type of goods and services I ordered over the Internet in the last 12 months for non-work use are: Prescribed medicine 2009
I would like to do on-line: health-related services (eg interactive advice on availability of services in different hospitals, appointments for hospitals) I_GOVHLP *** 2006
I’ve already done on-line: health-related services (eg interactive advice on availability of services in different hospitals, appointments for hospitals) I_GOVHLY *** 2006
I have used Internet, in the last 3 months, for seeking medical advice online with a practitioner I_IHAD 2003 2004 2005
I used Internet, daily, for seeking medical advice online with a practitioner 2003 2004
I used Internet, monthly, for seeking medical advice online with a practitioner 2003 2004
I rarely used Internet for seeking medical advice online with a practitioner 2003 2004
I used Internet, weekly, for seeking medical advice online with a practitioner 2003 2004
I have used Internet, in the last 3 months, for making an appointment online with a practitioner I_IHAP 2003 2004 2005
I used Internet, daily, for making an appointment online with a practitioner 2003 2004
I used Internet, monthly, for making an appointment online with a practitioner 2003 2004
I rarely used Internet for making an appointment online with a practitioner 2003 2004
I used Internet, weekly, for making an appointment online with a practitioner 2003 2004
I have used Internet, in the last 3 months, for seeking health information on injury, disease, nutrition, improving health, etc.) I_IHIF 2003 2004 2005 2006 2007 2008 2009
I used Internet, daily, for seeking health information on injury, disease or nutrition 2003 2004
I used Internet, monthly, for seeking health information on injury, disease or nutrition 2003 2004
I rarely used Internet for seeking health information on injury, disease or nutrition 2003 2004
I used Internet, weekly, for seeking health information on injury, disease or nutrition 2003 2004
I have used Internet, in the last 3 months, for requesting a prescription online from a practitioner I_IHPR
2003 2004 2005
I used Internet, daily, for requesting a prescription online from a practitioner 2003 2004
I used Internet, monthly, for requesting a prescription online from a practitioner 2003 2004
I rarely used Internet for requesting a prescription online from a practitioner 2003 2004
I used Internet, weekly, for requesting a prescription online from a practitioner 2003 2004

Due to the data available, I have chosen 2005 to carry out a cluster analysis to develop a typology of Digital Health Care Demand or eHealth Care Demand in Europe. This is just a first step, the aim is to analyse the drivers and barriers of eHealth in Europe from the demand side. The next table shows the percentage of total individuals by country, (I_GOVHLP and I_GOVHLY  2006)

Table 2. eHealth variables available 2005 at Eurostat ICT usage household survey

COUNTRY I_IHIF I_GOVHLP I_GOVHLY I_IHAD I_IHAP I_IHPR
AT 0,160251 0,227954 0,029526 0,004705 0,007748 0,002626
BE 0,1914 0,183276 0,017496
BG 0,122097 0,009661
CA 0,58
CY 0,080042 0,195897 0,00136 0,002788 0,000551 0,001706
CZ 0,034713 0,096489 0 0,003308 0,003896
DE 0,325024 0,021079
DK 0,238382 0,41458 0,030644 0,02493 0,016902 0,007123
EA 0,162218 0,251884 0,017979 0,005567 0,003255
EA16
EE 0,163774 0,19904 0,030725 0,108567 0,083567 0,049192
EL 0,021608 0,131537 0,001472 0,003506 0,001282 0,000433
ES 0,12751 0,035553 0,024121 0,004409 0,000907
EU15 0,181379 0,245943 0,021312 0,019812 0,005783 0,004567
EU25 0,160867 0,227894 0,019862 0,017239 0,005385 0,004105
EU27 0,160867 0,216619 0,018973 0,017239 0,005385 0,004105
FI 0,38971 0,273988 0,012912 0,027487 0,033743
FR
HR
HU 0,096088 0,119384 0,053411 0,007618 0,004358 0,001954
IE 0,104775 0,043551 0,008591 0,006391 0,001092 0,000679
IS 0,394597 0,388167 0,119582 0,027373 0,013017 0,007694
IT 0,087271 0,17439 0,008182 0,015709 0,003513 0,001996
LT 0,085267 0,179464 0,020233 0,012467 0,002665 0
LU 0,410491 0,367017 0,015976 0,016174 0,006943 0,007728
LV 0,073536 0,156269 0,009821 0,004649 0,001445 0,00052
MK
MT 0,161734 0,122316 0,010373 0,004483 0,003271 0,001495
NL 0,407242 0,387001 0,008289 0,017196 0,007235 0,014481
NO 0,257325 0,36145 0,021409 0,0113 0,008636 0,002586
PL 0,071422 0,174514 0,00652 0,004253 0,001301 0,000916
PT 0,100267 0,174263 0,003997
RO 0,062036
RS
SE 0,232107 0,295204 0,061132 0,042376 0 0,009893
SI 0,153678 0,268123 0,011941 0
SK 0,091329 0,214051 0,013288 0,000493 0,001545 0,000192
TR 0,031177 0,002588 0,000698 0,000024
UK 0,254573 0,200448 0,02922 0,044428

With these values I have constructed new categorical variables considering  descriptive statistics (percentiles per each variable) as follow: less than 25% is LOW, between 25% and 75% is MEDIUM and more than 75% is HIGH.

In order to develop a typology of countries’ utilization of the Internet related with Health, a Non-Hierarchical Cluster Analysis of K-means was undertaken, to five of the five variables identified above I_IHIF, I_GOVHLP, I_GOVHLY, I_IHAD, I_IHAP (Table 2). These factors were selected due to their significance within the cluster analysis.

Table 3. Results of K-means—quick cluster analysis. Method of analysis: non-hierarchical cluster, final cluster centroids.

Clusters

1. Digital Health Care Demand Leaders (n=8)

2. Digital Health Care Demand Primary Strivers (n=3)

3. Digital Health Care Demand Secondary Strivers (n=12)

ANOVA

Sig.

I_IHIF

2,5

3

1,67

12,733

0

I_GOVHLY

3

1,67

1,58

18,345

0

I_GOVHLP

2,5

3

1,58

14,053

0

I_IHAD

2,5

2,33

1,67

6,793

0,006

I_IHAP

2,5

2,67

1,92

4,173

0,031

Cluster one consists of countries where citizens place a greater emphasis on the Internet for health purposes, specially those variables related with health care services. This group is thus referred to as representing ‘Digital Health Care Demand Leaders’. Cluster two is characterised by a minimum difference, with less emphasis on variables related with health care services (transactions) and more emphasis on information, so are consequently labelled ‘Digital Health Care Demand Primary Strivers. Finally, Cluster 3 is labelled ‘Digital Health Care Demand Secondary Strivers

And now… the floor is yours…. pick up a country a put it on a cluster… soon I will post the characterization of the cluster analysis, including traditional, non-digital, variables from the health systems. Furthermore… what about 2010?

Austria AT
Belgium BE
Bulgaria BG
Cyprus CY
Czech Republic CZ
Germany DE
Denmark DK
Estonia EE
Greece EL
Spain ES
Finland FI
France FR
Croatia HR
Hungary HU
Ireland IE
Iceland IS
Italy IT
Lithuania LT
Luxembourg LU
Latvia LV
Macedonia MK
Malta MT
Netherlands NL
Norway NO
Poland PL
Portugal PT
Romania RO
Sweden SE
Slovenia SI
Slovakia SK
Turkey TR
United Kingdom UK
EU (15 countries) EU15
EU (25 countries) EU25
EU (27 countries) EU27

THANKS indeed Ismael Peña for his inspiring work

The inverse care law and the use of e-consultation

I have read Nijland, N., van Gemert-Pijnen, J. E. W. C., Boer, H., Steehouder, M. F., & Seydel, E. R. (2009). Increasing the use of e-consultation in primary care: Results of an online survey among non-users of e-consultation. International Journal of Medical Informatics, In Press, Corrected Proof.

Abstract

Objective
To identify factors that can enhance the use of e-consultation in primary care. We investigated the barriers, demands and motivations regarding e-consultation among patients with no e-consultation experience (non-users).

Methods
We used an online survey to gather data. Via online banners on 26 different websites of patient organizations we recruited primary care patients with chronic complaints, an important target group for e-consultation. A regression analysis was performed to identify the main drivers for e-consultation use among patients with no e-consultation experience.

Results

In total, 1706 patients started to fill out the survey. Of these patients 90% had no prior e-consultation experience. The most prominent reasons for non-use of e-consultation use were: not being aware of the existence of the service, the preference to see a doctor and e-consultation not being provided by a GP. Patients were motivated to use e-consultation, because e-consultation makes it possible to contact a GP at any time and because it enabled patients to ask additional questions after a visit to the doctor. The use of a Web-based triage application for computer-generated advice was popular among patients desiring to determine the need to see a doctor and for purposes of self-care. The patients’ motivations to use e-consultation strongly depended on demands being satisfied such as getting a quick response. When looking at socio-demographic and health-related characteristics it turned out that certain patient groups – the elderly, the less-educated individuals, the chronic medication users and the frequent GP visitors – were more motivated than other patient groups to use e-consultation services, but were also more demanding. The less-educated patients, for example, more strongly demanded instructions regarding e-consultation use than the highly educated patients.

Conclusion
In order to foster the use of e-consultation in primary care both GPs and non-users must be informed about the possibilities and consequences of e-consultation through tailored education and instruction. We must also take into account patient profiles and their specific demands regarding e-consultation. Special attention should be paid to patients who can benefit the most from e-consultation while also facing the greatest chance of being excluded from the service. As health care continues to evolve towards a more patient-centred approach, we expect that patient expectations and demands will be a major force in driving the adoption of e-consultation.

Summary points

What was already known on the topic?

  • The increased public interest in medical information regarding health issues are driving forces for the growth of health services on the Internet. However, the growth of e-consultation in primary care has been minor.
  • Access to healthcare and information technology is often most difficult for those populations who need it most. E-consultation can be beneficial for certain patient groups, such as frequent GP visitors and chronic users of medication. Yet, it is unclear whether access to e-consultation is most difficult for these populations.

What did this study add to our knowledge?

  • Non-use of e-consultation was primarily due to lack of availability among GPs and to information deficits among patients, such as unawareness of the existence of the service and the possibilities of e-consultation. Proper education and instructions are necessary to increase the use of e-consultation.
  • Patient groups who were most motivated to use e-consultation e.g., elderly patients, less-educated patients, chronic medication users and frequent GP-visitors, perceived the greatest barriers towards econsultation.
  • Web-based triage systems may be promising, because this study indicates that patients are motivated to use such systems for primary evaluation of medical complaints and for self-care advice.

Again, the results of the empirical research revealed the gap between the potencial of ICTs uses in healthcare and the facts that shape these uses. The inverse care law is still working in the transition of healthcare systems to Network Society.

The Ranking Web of World Hospitals

Nowadays, there are several directories and rankings almost for everything. Information flows, mashups, user-generated contents and collaboration tools, among others,  have facilitated the development and the dissemination of these kind of information services.

Nevertheless, I would say (it’s just a hypothesis) that most of these rankings or directories do not mention clearly how they have been developed or in some cases they are build on  ‘black box’ criteria. To sum up methodology issues are just missed. Of course,  it doesn’t mean that they are not useful but extra caution should be paid when you checked them.

Anyway, I’m glad to share what looks like as a good example of ranking, even it is in a “beta” phase: The Ranking Web of World Hospitals. This ranking clearly specifies:

  • Background of the project.
  • Purposes and Goals of Rankings.
  • Design and Weighting of Indicators.
  • Collection and Processing of Data
  • Presentation of Ranking Results

The elements above mention should be mandatory in any ranking, shouldn’t it?

Congratulations to Isidro F. Aguillo and his team