Monthly Archives: September 2010

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

E-patients, Cyberchondriacs, and Why We Should Stop Calling Names – European Perspective

On August 30, 2010, Susannah Fox posted E-patients, Cyberchondriacs, and Why We Should Stop Calling Names starting a discussion about names. I think the discussion could be summarised in two main trends.

On the one hand, e-patients name is still useful as a brand to spread the message of individuals utilising the Internet for health purposes. Therefore, using the Internet for seeking health information on injury, disease, nutrition, improving health, etc could be consider as a “proxy” to understand the diffusion of e-patients phenomenon or normalization and routinization of technological resourcefulness, mentioned by Carl May. Susannah Fox has been analysing data from USA since 2000. It looks like that the use of the Internet for health in this country has reached a “saturation” point among Internet users, however non-Internet users and minorities, mentioned by Gilles Frydman, are still far away from this saturation point. As a part of this digital divide in Health, it is different to engage young or elderly populations. For the first group, talk about e-patient does not make any sense because, in plain English, they are digital natives while for elderly population is totally different. However, digital natives will be the patients of the near future.

To tackle the situation in Europe I have collected some data from Eurostat checking Information society statistics based on the surveys on ICT usage in enterprises and households. They have gathered the following question “I have used Internet, in the last 3 months, for seeking health information on injury, disease, nutrition, improving health, etc.)”. I have developed charts of European countries and of EU 15, EU 25 and EU 27 for ‘% of individuals’ and ‘% of individuals who used Internet in the last 3 months’. All charts revealed a positive trend but Europe is still behind USA, even the penetration of broadband in Europe is bigger than in USA.

Click on the image below to enlarge the chart to full viewing size

On the other hand, we have to realise that this proxy does not tackle the complexity of this phenomenon and its relationships with other variables, including digital and non-digital aspects of individuals daily live. Therefore, e-patient name could be considered as an inhibitor of this complexity and it does not help us to go deeper in our analysis.  I guess we may have to find a balance between get bored spreading the message and get excited about deeper analysis.

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