Docstoc

Measuring the Impact of ICT on Health Care

Document Sample
Measuring the Impact of ICT on Health Care Powered By Docstoc
					         Chapter   6



      Measuring
the Impact of ICT
  on Health Care
                                                                        Chapter                             6
Measuring the Impact of ICT on Health Care
Robbin te Velde (Dialogic), Jesse Bos (Dialogic), Reg Brennenraedts (Dialogic)



6.1 Introduction
This chapter addresses the impact of information and communication technologies (ICT) on the health care in-
dustry in advanced economies. We focus on the direct effect of the availability of e-health infrastructure on the
use of e-health and on the direct effects of its use on the effectiveness and efficiency of health systems. We con-
clude that the use of ICT in health care has had mixed results and has so far fallen far short of its potential.

Our objective is to detect and analyze systematic relationships among aspects of availability, use, and effects
that can be measured and for which broad-based data exist. Thus, we seek to go beyond isolated case studies
and anecdotal reports, which may be important for illuminating the potential for ICT’s impact, to see what im-
pact actually has occurred.

This objective has significant requirements and limitations. The requirements are for access to up-to-date,
broad-based data on important items that may be very hard to measure, such as quality of care, patient satis-
faction, and ease of obtaining care. Ideally, to measure efficiency, for example, we would have to be able to
distinguish prices and the quantity of specific medical services. If our only available measure is total spending
on health care (price multiplied by quantity), we cannot distinguish between favorable outcomes when pre-
sented with two alternatives, one in which ICT allows prices to go down and quantity to go up even more and
the other in which prices go up and quantity stays the same. An important limitation is that, unless we have
data for and engage in a very complicated analysis with both time series and cross-section dimensions, it is
possible that the systematic relationships we seek may be obscured by temporary inconveniences and transi-
tion costs that always arise when new technologies are adopted. Although these requirements and limitations
are important and may affect our findings, we believe that the relationships that we do establish will stand on
solid ground.

Compared to the government and especially the education sectors, there is a long tradition of ICT use in health
care. The first IT systems were used in the United States in the 1950s, primarily for managing medical records
and supporting diagnoses. Today, ICT is being used in nearly every stage of the health care process, from remote
monitoring of patients and distance collaboration between specialists to the use of medical imaging systems
and electronic invoices for medical care. Likewise, health care informatics encompasses a broad set of services,
which include health care information systems, services like telemedicine (including virtual health care teams),
electronic health records (EHR), and consumer health informatics.

Two of the most important societal trends driving developments in health care in general are ageing popula-
tions around the world and the continuous increase of chronic diseases (such as cardiovascular diseases and
diabetes). And the two trends are clearly related: old age has its infirmities. Ageing is directly related to increas-
ing expenditure on health care (Figure 6.1).

As a result, health care expenditures are rising faster than the GDP in many countries, touching off efforts to
control those costs through various means. Many developed countries are attempting to shift from expensive
inpatient care to outpatient care, a move that could take great advantage of telemedicine. At the same time,
countries are becoming more focused on preventive care, an area that could benefit from the use of data mining
of EHR and statistics to target preventive care toward specific population groups.
                                                                                          6. Measuring the Impact of ICT on Health Care
                                                                                                                                     91


      Figure 6.1. PER CAPITA TOTAL EXPENDITURE ON HEALTH (PPP, US$, 2007) X PERCENTAGE OF POPULATION OVER 60 YEARS
                  OLD (2008)

                                   30
                                                                                                                     R2 = 0,52
                                   25
% population over 60 years, 2008




                                   20

                                   15

                                   10

                                    5

                                   0
                                        0   1.000             2.000         3.000           4.000            5.000        6.000
                                   –5
                                                    Per capita total expenditure on health (PPP,US$, 2007)
      Source: WHO (2010). World Health Statistics 2010, Geneva: WHO.




      The most important technological trend for e-health has been the widespread use of the Internet. Its effect has
      even been so great that the term e-health (Internet-based health care practices) has become more or less inter-
      changeable with health care informatics.

      It is useful to distinguish between two realms of e-health–those information flows that occur solely among health
      care providers and payers and those that also involve patients. In traditional health care information systems, we
      have seen a rapid increase in the use of networked systems–that is, the inter-organizational exchange of medical
      data–although many are standalone systems that have yet to be tied into a national health records system. Con-
      sumer health informatics hardly existed before the rise of the Internet. Today, patients can find abundant amounts
      of information–some reliable, some not so much–about their conditions, link up with fellow patients around the
      world, and make judgments (for better or worse) about the efficacy of their physicians and treatment plans.

      One Dutch study found that two-thirds of all people looked for medical information on the Internet prior to a
      visit to their physician, and one-third decided to visit their physician (or at least visit the physician sooner) as a
      result of information found on the Internet.1 At their appointments, one-third of the patients surveyed perceived
      a change in treatment due to the information they discussed with their doctors. The changing relationship bet-
      ween doctor and patient, a relationship that was traditionally very hierarchical, is one reason that ICT’s use is
      greeted with mixed feelings by medical professionals.

      The information and communication possibilities of the Internet apply not only to patients, but also to doctors.
      These could directly and indirectly (via improved communications between medical professionals) lead to an im-
      provement in the quality of health care and, thus, an improvement of the health situation in a country, since better-
      informed medical professionals presumably make better diagnoses. Whether the application of ICT leads to any
      improvement in quality is, however, largely dependent on the quality of the implementation–that is, how ICT is
      actually being deployed in practice. This is true in any domain, but it seems to be even more so in health care due



      1 Ongena, 2008.
The Impact of ICT on the Production of Goods and Services
92


            to the greater socio-technical complexity. Studies indicate that ill-conceived applications may provide a mission-
            hostile experience for busy clinicians, distracting them and actually increasing the chances for medical error.2

            The improvement of efficiency is the second and most often mentioned advantage of the use of ICT in health care
            after the improvement of health care quality. The automation of patient administration, for instance, leads to a re-
            duction in costs and would be expected to indirectly improve the quality of health care since it frees time for pri-
            mary clinical processes (e.g., interaction with patients) and other secondary processes (e.g., self-study by medical
            professionals, which is greatly facilitated by the Internet). But while an extensive meta-literature review by research-
            ers3 led them to conclude that some processes, such as research, audit, and billing, may be more efficient due to the
            use of EHR, some primary clinical processes may be made less efficient. They also found that smaller systems (e.g.,
            EHR on a local or regional scale) may sometimes be more efficient than larger ones (e.g., EHR on a national scale).

            Whether the presumed efficiency gains also lead to quality improvements remains to be seen. The results of a
            pan-European survey among general practitioners (GPs) seem to suggest that the use of ICT does give rise to
            gains in efficiency, but these gains lead to perverse effects in terms of quality. (See Section 3.) For example, as the
            use of ICT leads to more efficient scheduling in doctors’ offices, and as more patients decide to visit their phy-
            sicians because of information found on the Internet, doctors see more patients in a given day. But some
            physicians feel that the increased demand for their services and the efficiency with which patients are moved
            through their offices leaves them with less time to treat each patient, causes a reduction in the range of ser-
            vices they offer, and makes their relationships with patients more impersonal.

            There are also mixed results on the benefits of Internet information for patients. Researchers have found that the
            more serious an illness is, the more likely that people perceive the quality of information on the Internet as higher
            and the quality of the information given by their physician as lower.4 This stands in sharp contrast to the perspec-
            tive of the physicians, who think that Internet information is quite beneficial to standard patients (although few
            physicians refer their patients to Internet sites), but rarely or never helps the chronically ill in self-management.

            In summary, the use of ICT in health care may increase the efficiency of secondary processes, but the impact on
            primary processes is less clear. At the same time, the privileged position of medical professionals is under pres-
            sure from the increased empowerment of patients.


            6.2 The model for measuring impact
            In studying the impact of ICT on health care, we use the same general model that we use in studying ICT’s im-
            pact on government (see Chapter 5, Section 3). The model distinguishes three stages of ICT deployment:

            1. Readiness (mostly referring to the supply side)
            2. Use (mostly referring to the demand side)
            3. Impact

            Indicators for readiness are readily available, albeit with a bias toward hard ICT infrastructure. Only recently has
            more attention (rightly) been paid to soft infrastructure, such as ICT policy and skills. Use is the link between
            readiness and impact. In this study, particular attention is being paid to the use of e-health.



            2 Koppel et al., 2005; Silverstein, 2009.


            3 Greenhalgh et al., 2009.


            4 Meyer et al., 2009.
                                                                        6. Measuring the Impact of ICT on Health Care
                                                                                                                   93


Starting from the centerpiece of the general conceptual model, use, we discussed in the introduction that the
developments for patients and doctors are markedly different. This means that we should distinguish between
use by citizens (patients) and use by professionals (doctors). In a similar vein, when considering ICT’s impact on
health care, we should distinguish between effectiveness (changes in the quality of the health care and the
health conditions of citizens) and efficiency (changes in the costs of providing health care). Furthermore, we
should also include the perception of citizens, both on the performance of the health care system (macro level)
and on their own health situation (micro level).

There are at least two relevant building blocks that apply to readiness: the general situation of the health care
system (without the e-component) and a country’s general ICT situation. In turn, both blocks can be divided into
infrastructure, expenditure, and policy. The expenditure on health and ICT, and thus the development of the two
blocks, are finally driven by a country’s general economic situation.

We then arrive at Figure 6.2:


Figure 6.2. GENERAL CONCEPTUAL MODEL APPLIED TO E-HEALTH


                     Readiness                                    Use                          Impact

                                Health care system
                                      Health
                                 ICT infrastructure

                                     Health
                                   expenditure                eHealth use                Health care system

                                                            Use by citizens                 Performance
  General conditions                  Health
                                                              (patients)                   (effectiveness)
                                    care policy
      Economic
                                                                Use by                          Costs
     performance
                                                             professionals                   (efficiency)
                                National ICT policy
                                                               (doctors)
                                                                                             Perception
                                       ICT
                                   expenditure

                                    ICT policy


                                ICT infrastructure
                                        ICT
                                  infrastructure




There is ample international comparative quantitative data for both the readiness and impact indicators (at
least regarding indicators for the health condition of a population). Use is much less well covered in interna-
tional sources (that is, WHO, OECD, UN, etc.) In 2002 and 2007, the European Commission commissioned two
broad studies on the use and the economic impact of e-health. These studies cover all 27 member states plus
The Impact of ICT on the Production of Goods and Services
94


            Norway and Iceland (EU27+2). Though this is not worldwide coverage, it does cover a sizeable set of quite differ-
            ent countries, ranging from small and large to developing and advanced economies.



            6.3 Survey of Physicians
            The European Commission studies surveyed 6,800 GPs. The studies mapped the way physicians used ICT and
            the Internet to communicate with their patients and with primary and secondary care and other health actors,
            such as insurance companies and health authorities. The studies’ results give detailed insight into the current
            situation and recent developments with respect to readiness and use of e-health.

            6.3.1 Readiness

            The presence of computers and Internet connections in GPs’ offices has grown rapidly over the last five years,
            from 81% to 90% (computers) and 63% to 73% (Internet). In a number of countries, complete saturation has been
            reached. Broadband access, which is considered essential for transmitting visual data or the streaming associ-
            ated with monitoring, is highly correlated with the pattern of Internet connection.

            6.3.2 Use

            In line with the trend in readiness, the use of e-health applications has also grown rapidly across the board. In
            Denmark, which leads the pack in Europe, almost all types of data exchange are in the 60% to 70% saturation



            Figure 6.3. DIFFUSION PATTERN FOR VARIOUS TYPES OF E-HEALTH USE, DENMARK, 2007

                                                                                          Hospitals &
                                                                                          specialists

                        Denmark               Transfer medical data (73%)
                         (2007)                                                                         Pharmacies

                                                                              Prescriptions via Internet (77%)


                                   Exchange emails (59%)                                                    Laboratories

                                                                                    Receive test results (83%)

                               Telemedicine (0,4%)                    (62%)
                 Patient                                   GP                             Other GP


               Practice website (70%)                                         Submit reimbursement claims (6%)

                                                                                                          Insurance
                                                  Own
                                                                                                         companies
                                               continuing
                                             education (n/a)
                                                                  Search prescribing information (71%)

                               Internet
                                                                      6. Measuring the Impact of ICT on Health Care
                                                                                                                 95


Figure 6.4. DIFFUSION PATTERN FOR VARIOUS TYPES OF E-HEALTH USE, EU15, 2002-2007

                                                                             Hospitals &
                                                                             Hospitals &
                                                                             specialists
                                                                             specialists

                EU 15
                EU 15             Transfer medical data (8%)
                                  Transfer medical data (8%)
               (2002)
               (2002)                                                                      Pharmacies
                                                                                           Pharmacies

                                                                   Prescriptions via Internet (3%)
                                                                   Prescriptions via Internet (3%)


                        Exchange emails (6%)
                        Exchange emails (6%)                                                    Laboratories
                                                                                                Laboratories
                                                                       Receive test results (11%)
                                                                       Receive test results (11%)

                    Telemedicine (2%)
                    Telemedicine (2%)                     (8%)
                                                          (8%)
     Patient
     Patient                                    GP
                                                GP                           Other GP
                                                                             Other GP

   Practice website (25%)
   Practice website (25%)                                         Submit reimbursement claims (6%)
                                                                  Submit reimbursement claims (6%)
                                                                                             Insurance
                                                                                             Insurance
                                     Own
                                     Own                                                    companies
                                                                                            companies
                                  continuing
                                  continuing
                                education (45%)
                                education (45%)      Search prescribing information (35%)
                                                     Search prescribing information (35%)
                   Internet
                   Internet

                                                                             Hospitals &
                                                                             Hospitals &
                                                                             specialists
                                                                             specialists

                EU 15
                EU 15             Transfer medical data (22%)
                                  Transfer medical data (22%)
               (2007)
               (2007)                                                                      Pharmacies
                                                                                           Pharmacies

                                                                    Prescriptions via Internet (11%)
                                                                    Prescriptions via Internet (11%)


                        Exchange emails (27%)
                        Exchange emails (27%)                                                   Laboratories
                                                                                                Laboratories
                                                                       Receive test results (54%)
                                                                       Receive test results (54%)

                    Telemedicine (4%)
                    Telemedicine (4%)                    (28%)
                                                         (28%)
     Patient
     Patient                                    GP
                                                GP                           Other GP
                                                                             Other GP

   Practice website (29%)
   Practice website (29%)                                         Submit reimbursement claims (22%)
                                                                  Submit reimbursement claims (22%)
                                                                                             Insurance
                                                                                             Insurance
                                      Own
                                      Own                                                   companies
                                                                                            companies
                                   continuing
                                   continuing
                                 education (82%)
                                 education (82%)     Search prescribing information (62%)
                                                     Search prescribing information (62%)
                   Internet
                   Internet
The Impact of ICT on the Production of Goods and Services
96


            range. An exception is the use of telemedicine, probably because Denmark is very small and the density of physi-
            cians and hospitals is very high.

            Across the continent, however, there are some marked differences among the various types of use (Figure 6.4).
            Telemedicine has hardly grown at all in Europe, despite efforts to contain costs. The percentage of practices in
            the EU155 with a website was relatively high in 2002 but has hardly grown since. In contrast, Internet use by
            physicians for their own purposes (searches for medical information and self-education) was already relatively
            high in 2002 and has continued to grow at a quick pace.

            The averages in Figure 6.4 mask the fact that there are still large differences among countries–much larger than
            in readiness. There is a clear leading group consisting of all of Scandinavian countries (including Iceland), the
            Netherlands, and the United Kingdom.

            6.3.3 Impact

            One of the most striking results of the 2007 survey is that there is no relation between doctors’ intensity of
            use and the perception of the impact of e-health (Figure 6.5). Although doctors in all countries tend to think
            that ICT improves the quality of health care services, there are no correlations with the e-health maturity in-
            dex (Figure 6.11). If we zoom in on the underlying motivations, it becomes clear that the perception of the
            physicians is much less positive, actually quite negative, about the impact on quality. Overall, physicians think
            that ICT’s direct impact on quality in terms of diagnosis is neutral. ICT has a positive influence on efficiency,
            but this causes an increase in the workload and the number of patients treated per day. This leads to deterio-




            Figure 6.5. GENERAL PRACTITIONER PERCEPTION OF E-HEALTH IMPACTS, EU27+2, 2007

                                                                                                          Impact on personal working processes

                                                                                                          Impact on working processes of practice staff
                                                                                                          Impact on quality of diagnosis
                                                                                                          and treatment decisions

                                                                                                          Impact on doctor-patient relationship

                                                                                                          Impact on scope of services offered

                                                                                                          Impact on workload of support staff
                                                                                                        Impact on average numbers of patients
                                                                                                        treated per day
                                                                                                        Impact of number of patients
                                                                                                        coming to practice
            –200          –150           –100            –50              0             50            100
                                                                                                              Positive     None       Negative
                             No or negative impact                            Positive impact



            5 EU15 refers to the 15 countries that were members of the European Union before its enlargement in 2004: Belgium, France, Germany, Italy, Luxemburg, the Nether-
            lands, Denmark, Ireland, the United Kingdom, Greece, Portugal, Spain, Austria, Finland and Sweden.
                                                                                                            6. Measuring the Impact of ICT on Health Care
                                                                                                                                                       97


ration in the scope of services offered and in the doctor-patient relationship. In other words, the indirect ef-
fects of efficiency improvements on quality are negative and exceed the neutral direct effects on the improve-
ment of quality.

This is, of course, the view from the physicians’ side. Their negative perception of ICT-induced quality improve-
ments might at least partly be due to the fact that they regard ICT as a threat to their own position and/or the
quality of their own work. An increased workload might not necessarily negatively affect the quality perception
of patients.

Ideally, quality of health care would be measured using objective data, such as length of waiting times, or by di-
rect data, such as patients’ satisfaction. Accenture has recently done a survey6 in a number of countries that co-
vers some of these measures, but the overlap with the countries in the EU 2007 survey is very limited: only seven
countries appear in both surveys.7

We looked at four quality items in the Accenture survey: (1) the policy priority attributed by citizens to reduce
waiting times, (2) setting higher quality standards for all health care providers, (3) increasing the number of
medical professionals, and (4) the average rating of a country’s quality of health care. Again, we found no correla-
tion between the e-health maturity index and any of the quality indicators. The same was true for the percep-
tion that ICT improves health care quality, with one notable exception: the importance of reducing waiting
times. This suggests that citizens’ perceptions are contrary to physicians’ perceptions in that they think ICT use
will reduce waiting times and, thus, increase overall health care quality. Hence, from the patient perspective, ef-
ficiency is not diametrically opposed to quality.



6.4 Macro model
Using various databases for a broad set of counting, we calculated the indirect and direct correlations among
various indicators of readiness, use and impact.8 We used a principal components factor analysis to collapse 125
variables into 24 composite variables (components), while keeping gross national income (GNI) per capita apart
as a control variable. The resulting components coincided nearly perfectly with the distinctions that had been
made in the conceptual model (see Figure 6.6). All components consisted of combinations of variables that
logically made sense. The components could thus be given labels that also empirically made sense (e.g., “Use of
e-health by citizens”, “Efficiency of the health care system”, etc.).

For each of the seven impact components, we test both the indirect relationship between readiness and impact
(via use–that is, readiness → use → impact) and the direct relationships between readiness and impact (that is,
readiness → impact). Figures 6.6 and 6.7, respectively, illuminate the indirect and direct results. In the figures,
each connecting line represents a significant relation.9 Where no lines are shown, no significant relationship
was found. The numeric value along the line represents the correlation coefficient r, which is a proxy for the
strength of the relationship. Negative relations are indicated in red.




6 Accenture, 2010.


7 France, Germany, Ireland, Italy, Norway, Spain, and the United Kingdom.


8 OECD, 2009; Eurostat, 2009; ITU, 2009; Meyer et al., 2009; WHO, 2005; Eurobarometer, 2008; Health Consumer Powerhouse, 2009; WHO, 2009.


9 The exact significance level is indicated by an asterisk. A single asterisk means a level of <0.05 (i.e., a 95% chance that the relationship actually occurs), and double
asterisks mean a level of <0.01 (i.e., a 99% chance that the relationship actually occurs).
The Impact of ICT on the Production of Goods and Services
98


            Figure 6.6. SIGNIFICANT INDIRECT RELATIONS BETWEEN READINESS AND IMPACT (READINESS ⇒ USE ⇒ IMPACT)
                        Health care system
                                                                                                                                Health care system
                  Health ICT infrastructure                                                                                        (Perceptions)
                                                                0.39*                                                        Perception of healthcare
                                                                                eHealth citizens
                                                                                                                                     system
                      Health expenditure                                                                           –0.63**                               0.70**
                                                                               Use by citizens
                      Goverment control                                                                                 Perception of bad own health
                       of health sector                                                                  –0.52**
                                                                             eHealth profesionals
                        ICT infraestructure                                                                                     Health care system
                                                                          Using eHealth for B2C                                     (Efficiency)
                      ICT infraestructure
                                                                0.43**                                      0.37*      Growth in private expenditure
                        National ICT policy                                                                                    on healthcare
                                                                      Use of expert (DSS) systems
                              eHealth
                               policy                           0.38*                                                          Low child mortality
                             Freedom                                      Using eHealth for B2B
                         of information                                                                                Growth in per capita expenditure
                                                              0.52**
                                                                                                                                on healthcare
                              Cultural                             Using eHealth to communicate
                              diversity                                   with authorities                           –0.61*     Health care system
                                                                                                                                                        –0.42*
                                                                                                                                  (Effectiveness)
                              General
                                                                   Using eHealth to communicate
                             ICT policy
                                                                        with insurance firms                                   Long, healthy lives
                           National
                      information policy
                                                                                                                               Low child mortality
                              National
                               ePolicy
                                                                                                                                                     0.64**
                                                                                                                                General conditions
                             Public
                         funding policy                                                                                        Economic strength

                         Public-private
                       partnership policy

                         Affordability
                  of infraestructure policy

                    Intersectoral and NGO
                      cooperation policy

                          National open
                          archive policy

                            Training on
                             ICT policy

                      eLearning in health
                        sciences policy
            Note: Boxes shaded light blue represent dichotomous variables; the other boxes represent components.
                                                                                                       6. Measuring the Impact of ICT on Health Care
                                                                                                                                                 99


Figure 6.7. SIGNIFICANT DIRECT RELATIONS BETWEEN READINESS AND IMPACT (READINESS ⇒ IMPACT)
            Health care system
                                                                                                                         Health care system
       Health infraestructure                                                                          –0.53*               (Perceptions)

                                                                      eHealth citizens
                                                                                                                     Perception of healthcare
                                                                                                                             system
          Health expenditure
                                                                     Use by citizens
                                                                                                        –0.73**
          Goverment control                                                                                        Perception of bad own health
           of health sector                                         eHealth profesionals
            ICT infraestructure                                                                                          Health care system
                                                                Using eHealth for B2C                                        (Efficiency)
          ICT infraestructure
                                                                                                                  Growth in private expenditure
            National ICT policy                                                                                           on healthcare
                                                            Use of expert (DSS) systems
                  eHealth
                   policy                                                                                               Low child mortality

                 Freedom                                        Using eHealth for B2B
             of information                                                                                       Growth in per capita expenditure
                                                                                                        0.46**             on healthcare
                  Cultural                                 Using eHealth to communicate
                  diversity                                       with authorities
                                                                                                                         Health care system
                                                                                                                           (Effectiveness)
                  General                                  Using eHealth to communicate 0.56**
                 ICT policy                                     with insurance firms                                    Long, healthy lives
               National                               0.24*                                            0.28**
          information policy
                                                                                                                        Low child mortality
                 National                                                                              –0.45**
                  ePolicy                         –0.51*
                                                                                                                         General conditions
                 Public
             funding policy                                                                                             Economic strength

             Public-private
           partnership policy

             Affordability
      of infraestructure policy

       Intersectoral and NGO                      –0.55*
         cooperation policy

             National open                        –0.53*
             archive policy

                Training on                                                        –0.67**
                 ICT policy

          eLearning in health
            sciences policy                       0.31**
Note: Boxes shaded light blue represent dichotomous variables; the other boxes represent components.
The Impact of ICT on the Production of Goods and Services
100


            6.4.1 Links between readiness and use

            The ICT infrastructure is positively correlated with various use components–for instance, with citizens’ use of
            e-health. This means that in countries with a more developed ICT infrastructure, people are also more avid users
            of ICT, including e-health. The link with use of expert systems and business-to-business (B2B) signifies that
            those two types of e-health uses by professionals are the most advanced, or mature, and require the most ex-
            tensive investments in ICT infrastructure.

            The positive correlation between public health expenditure and using e-health to communicate with authori-
            ties is a logical one: the more money a government puts into the health care system, the more interested it will
            be to follow the money through such methods as auditing. Hence, overhead increases and communication with
            authorities intensifies.

            The negative correlation between health infrastructure and citizens’ use of e-health is an interesting finding. It
            suggests that, at least at this moment, e-health use is partly a substitute for the use of regular health care. Note
            that, although we have drawn the arrow in only one direction, the causal direction is unknown and the relation-
            ship might work both ways. Thus, it could be that the more doctors and specialists that are available, the less
            need there is for a citizen to resort to e-health, or, the other way around, countries with a less developed health
            system have chosen to modernize their infrastructure via e-health.

            6.4.2 Links between use and impact

            Economic strength still has the greatest impact on the outcome of health care systems. This simply means
            that ICT’s contribution to the outcome is (still) relatively modest. For instance, life expectancy is directly related
            to a country’s welfare. Similarly, inhabitants from richer countries tend to think that the health care system in
            their country performs relatively well. The negative relation with growth in per capita expenditure is due to the
            fact that it is easier for countries with lower initial expenditure levels to grow those expenditures than for
            countries that already have high expenditure levels.

            The impact component that stands out is the self-perception of bad health. With the exception of a relative
            growth in health care expenditure, this is the only impact component that is directly linked to one or more
            use components. The fact that it is negatively related to ICT use is explained by self-selection: the most avid
            users of medical information on the Internet are also most concerned about their own health. Interestingly,
            this group is also most questioning of the quality of the diagnosis and treatment by physicians. It is not
            surprising, then, that physicians think Internet use rarely or never helps this particular group of chronically
            ill people. We find here the most succinct example of the changing relationship between doctors and pa-
            tients.

            Similarly, the use of e-health for B2B and communication with insurance companies can also be explained by
            self-selection. Data from chronically ill people is more frequently exchanged than data on standard patients.
            The substitution of electronic workflows for traditional paper-based workflows might save both the physician
            and patient a lot of, well, paperwork.

            The last remaining correlation between the use of e-health for business-to-consumer transactions and growth
            in expenditure on health care related to GDP is perhaps the most relevant one. It simply says that the use of
            e-health increases rather than decreases the expenditure on health care. Thus, the presumed efficiency gains
            do not occur–at least not at the macro level and not in the short run.
                                                                         6. Measuring the Impact of ICT on Health Care
                                                                                                                   101


6.4.3 Direct links between readiness and impact
The number of direct links between readiness and impact surpasses the number of indirect links. This down-
plays the presumed pivotal role of use.

Some of these links are rather obvious. Health infrastructure correlates positively with long, healthy lives. Thus,
investments in health infrastructure do pay off, but naturally come at a price: They also increase the per capita
expenditure on health care. The performance of a health care system (in terms of long, healthy lives) is further
improved by the implementation of national information policies and eStrategy policies. Hence, the importance
of having a clear strategic vision seems to apply on a national level.

Similarly, eLearning in health science policies also correlates positively with long, healthy lives. Thus, it pays to
invest in ICT-supported continuous training of doctors. It is not surprising, then, that the use of ICT for self-edu-
cation is one of the fastest-growing uses of e-health among physicians across all European countries. Another
relevant finding is that the existence of an intersectoral, non-governmental policy of cooperation leads to a re-
duction of public expenditure on health care. This is in sharp contrast to the ICT use that we previously found. In
other words, when a government wants to reduce expenditure on health care, it should invest in streamlining
intersectoral processes rather than in ICT.

Much more surprising is the positive (albeit weak) correlation between having a national archive policy and
long, healthy lives. The only (far-fetched) explanation is that citizens in democratic countries feel less suppressed
and this has direct, positive effects on their health. But note that a national archival policy is not correlated to
the perception of one’s own health.

In contrast to the health components, the significant relationships that were found for the ICT components are
much harder to interpret. On the one hand, there is a very strong direct relationship between ICT infrastructure
(and to a lesser extent between training in ICT policy) and the perception of one’s own health–that is, the better a
country’s ICT infrastructure is (and the more training in ICT policy provided), the more positively citizens in that
country tend to think about their own health. On the other hand, ICT infrastructure is negatively related to im-
provements in infant mortality, and training in ICT policy is negatively related to the perception of the health care
system. There is no apparent explanation for the existence of these relationships or for the direction of the rela-
tionships. The relationships are, however, relatively strong and are also supported by certain anecdotal empirical
evidence. For instance, we have seen that Denmark is the undisputed frontrunner in both readiness and use of
e-health (Section 3.b), but we will see that it is also the country with the worst medical performance in Europe dur-
ing the last decade. Again, this obscures the present contribution of the use of ICT to the quality of health care.


6.5 Country studies
To provide a better understanding of the implications of the model, case studies were performed for three coun-
tries: Denmark, Spain, and Canada. These countries are compared with respect to the readiness, use, and impact
of ICT on health care, using the data gathered for the analysis above.

One of the key drivers for both ICT use and impact on health care was the economic strength of a country (mea-
sured in terms of gross domestic product (GDP) per capita). When evaluating each country’s results, this factor
should be kept in mind. GDP per capita for Canada (US$ 38,500) and Denmark (US$ 35,951) are quite similar, but
GDP for Spain (US$ 31,586) is somewhat lower.10 Another factor with a major influence (in terms of life expectancy



10 OECD Factbook 2009. GDP is US$, current prices and PPPs, 2007.
The Impact of ICT on the Production of Goods and Services
102


            Figure 6.8. EXPENDITURE ON HEALTH x LIFE EXPECTANCY AT BIRTH


                                                       84
                                                                                Japan    Canada
                                                                                                       R2 = 0.40
                                                       82
                                                                        Spain
                    Life expectancy at birth (years)




                                                       80


                                                       78
                                                                                             Denmark               United
                                                                                                                   States
                                                       76


                                                       74


                                                       72
                                                            0   2   4      6        8       10       12       14        16   18
                                                                        Total expenditure on health (% GDP)




            at birth) is the expenditure on health (Figure 6.8). Indeed, the two factors are fairly strongly correlated in most
            countries–the notable exceptions being the United States and Japan. With respect to the reference countries, Spain
            is doing well, with a high life expectancy compared to expenditures, Canada is exactly on the regression line, and
            Denmark’s life expectancy is somewhat below what is to be expected from its total expenditures on health.

            The data on infant mortality and life expectancy show that the health care situation in Spain is favorable–life
            expectancy is relatively high and infant mortality low. In addition, infant mortality has decreased even further in
            recent years. The situation is less favorable in Denmark, however. The infant mortality rate is low, but life expec-
            tancy is also low for a Western country, and, in comparison with OECD countries, the increase in life expectancy is
            even lower. The situation in Canada with respect to life expectancy is average for the OECD.

            6.5.1 Canada

            Canada’s population is extremely unevenly distributed and its population density is very low at 119 square miles
            per person, compared to 4.5 square miles per person in Spain and 3 square miles per person in Denmark. Since
            some 80% of the people live in urban areas in the south, the actual population density in the northern provinces
            is much lower than the average. This makes Canada a logical place for the use of telemedicine. Quebec, for ins-
            tance, started implementing tele-health services in 1989 to reach all of its residents.11 This included such isolated
            regions as Nunavik. In Ontario, the Telemedicine Network covers 500 locations across the province. Alberta has
            its Netcare portal, which is somewhat akin to the Danish national system, connecting GP practices, diagnostic
            laboratories, and pharmacies.



            11 ICTC, 2009.
                                                                          6. Measuring the Impact of ICT on Health Care
                                                                                                                    103


These initiatives have developed in an environment where most of the funds are provided by a single payer, the
public insurance company. Public funds account for 70% of Canada’s health care expenses. The other 30% origi-
nates from private funds. Typical uses of public health care funds are for hospital and GP visits.12

For Canadians, basic health care is provided through public funds and is free. Patients are not involved in billing
and reimbursements. As regulated by law, health care providers are not allowed to bill patients; providers are
obliged to arrange payments directly with the insurance company. As a consequence, medical administration is
rather simple. Also easing administrative tasks is the lack of participation on the part of insurance companies in
day-to-day care or gathering information about an individual’s health. These measures yield a relatively cos t-
efficient medical system.

The health care system is guided by a national Health Act, but provinces are the key administrators in the sys-
tem. E-health is also run provincially, which has resulted in the creation of different, incompatible systems. There
is also no national electronic health care system yet. The introduction of a uniform electronic health record (EHR)
has been delayed for years and it still is not implemented in, for instance, Ontario. As in many other countries,
privacy concerns have greatly hampered the swift implementation of a national EHR. The recent hacking into
Alberta’s Netcare system, which compromised the privacy of more than 10,000 patients, shows that these con-
cerns are quite reasonable. In Canada, it was expected that by the end of 2010, five (out of 13) provinces would
have a fully interoperable (i.e. networked) EHR system with patient information about historical drug prescrip-
tions, laboratory tests, diagnostic imaging, certain clinical reports, and immunization data, regardless of where
the data originated.

Readiness In a country that has strong ambitions to benefit from telemedicine, ICT readiness is of utmost
importance. And readiness is very high in Canada, although not as high as in Denmark.

The other readiness component is the quality of the health care system. Canada scores well across the board, with
the remarkable exception of the low number of physicians. Since the 1990s, Canada’s policy of decreasing medical
school enrolments, coupled with net migration of physicians to the United States and the retirement of others,
has resulted in a lack of physicians. This means that each GP has to cover an enormous area, another strong in-
centive for the deployment of telemedicine. Along with the lack of GPs, there is also a severe shortage of hospital
beds. In the period from 1994 to 2004, hospital capacity fell 40%. The lack of publicly funded physicians and hos-
pital beds becomes all the more painful when contrasted with privately funded dentists. The number of dentists
in Canada is far above the OECD average. The declining quality of public health care has not been accompanied
by cost savings. Public expenditure on health care is still significantly above average for Canada.

In summary, given the low density of physicians, the cost pressure on the health care system, and the high avai-
lability of ICT infrastructure, there seems to be ample incentive for deploying telemedicine in Canada. The ques-
tion now is whether (and to what extent) e-health is already being used in Canada.

Use Little data is available on Internet use by Canadian health professionals. On the citizen side, the potential
for distance health care is certainly realized. Canada has, by far, the greatest percentage of citizens who use the
Internet to seek health information (Figure 6.9).

This result is in line with the finding of the macro model that–at least for now–citizens’ use of e-health is a subs-
titute for, rather than a supplement to, regular face-to-face health care. In the particular case of Canada, the
apparent lack of physicians seems to push citizens toward using the Internet to find medical information.



12 Dentists and ophthalmology visits are funded by private initiatives.
The Impact of ICT on the Production of Goods and Services
104


            Figure 6.9. INDIVIDUALS USING THE INTERNET TO SEEK HEALTH INFORMATION, SELECTED COUNTRIES, 2008 (%)

            70%

            60%                                                                                                                                                               58%

                                                                                                                                                                      50.8%
            50%
                                                                                                                                            43.8% 45.9%
                                                                                                                                 38.8%  40.9%
            40%                                                                              36.3%                           38.6% 40.6%
                                                                                    32.4%32.5%
                                                                                29.2%
            30%                                                              26%
                                                               24.5%24.8%
                                                                        24.8%
                                                          21.6%
                                                     18.8%
            20%                     16.4%
                                                18.6%
                                14.2%
                           10.4%
             10%
                     3.1%
              0%
                            Gr ey
                                       e
                                     ic

                            Po ly
                            Ire d
                          Po nd

                              lg l
                          Sl um

                              Sp a
                            ng n
                          Hu om

                           Sw ary

                            Au en

                             nm a
                            Ice rk

                             Fr d
                             rm e
                    Lu Nor y
                           m ay
                          he urg

                           Fi ds
                           Ca nd
                                    da
                          Be ga




                                 an
                       h eec




                         Ge c
                                     i




                         De stri
                                   n




                                   n
                                   ai
                                  bl
                                Ita




                                en




                                   a


                               an




                                  n
                                rk




                       xe w




                               na
                               ed
                                la
                                la




                                la




                                 a
                                u




                              ng
                                d
                                 i




                     N bo
                             pu




                             rla

                              nl
             Tu




                             ov
                             rt
                          Re




                         Ki




                       et
                       d
                     ec




                   ite
                  Cz




                Un




            Source: Eurostat, 2010.




            Impact With regard to effectiveness–presumed improvements in the health situation–Canada does not
            perform particularly well. It has a relatively favorable starting position, with high (healthy) life expectancy
            and average infant mortality rates, but the growth rates have been average and far below average, respec-
            tively.13

            Relative growth in government expenditure on health care has been less strong in Canada than in other
            countries. At first glance, this might indicate that some efficiency gains have been made. But one of the key
            findings of the macro model is that the use of e-health increases, rather than decreases, expenditure on
            health care. Consequently, this could mean that Canada is not a front-runner in e-health use. It remains to be
            seen whether the presumed efficiency gains have actually taken place. It seems that the increasing costs of
            health care have shifted partly to the private sector (growth of total expenditure on health care has been on
            par with the average) and predominantly to consumers (witnessed by the shortage of doctors and hospital
            beds).

            6.5.2 Denmark

            Denmark is a strong welfare state with universal coverage of health services. All Danish residents have free ac-
            cess to doctors and hospital care. The health system is almost entirely financed by the government. Denmark’s
            situation is somewhat comparable to Canada’s, but with the important difference that all Danish hospitals are
            owned by the government. Up until recently, counties were responsible for funding the system. However, in
            2007, contrary to the global trend of decentralization, financing was centralized at the national level.



            13 For the variables “Life expectancy” and “Infant mortality”, we found is no correlation between high initial scores and growth rates–thus, the favorable starting posi-
            tion does not work against Canada.
                                                                        6. Measuring the Impact of ICT on Health Care
                                                                                                                  105


The Danish health system is built around GPs, who act as gatekeepers to hospitals. Physicians are tightly regu-
lated by the regional governments. The counties decide the number and location of practitioners. Thus, the
counties can and do push the implementation of e-health from the top down.

Despite the free and omnipresent access to health care, Denmark performs poorly on such basic indicators as
life expectancy (Figure 6.8) and infant mortality. Some evidence suggests that the poor health results are not so
much due to the ineffectiveness of the health care system as to the particular unhealthy lifestyle of the Danish,
which is characterized by high consumption of alcohol, fatty foods, and tobacco.

Readiness The Danish Health Data Network (DHDN) is the showpiece of the Danish government and–literal-
ly–the information backbone of the health care system. DHDN is a reference for many countries that implement
e-health systems. DHDN started as a small regional network on the island of Funen in the early 1990s. There are
several other similar (and usually bigger) regional initiatives around the world (e.g., Netcare in Alberta, Canada,
and Diraya in Andalusia, Spain).

What is unique about DHDN is that it was successfully scaled up to the national level–an implementation done
in a relatively short period of just two years (1994-1996). Since then, connections to the network have grown at
a steady pace. In 2000, all pharmacies were connected to the network, and, in 2005, nearly all physician clinics
were connected (Figure 6.10).

The DHDN is built around GPs, who are the point of departure for most patients. From there, services that citi-
zens may need access to include pharmacists, diagnostic services at hospitals, specialist consultations at hospi-
tals, referrals to a hospital, and transfers from hospital to home care. The effective access to these services de-
pends on efficient and effective communication among health care providers.

A direct result of the DHDN implementation is that Denmark scores extremely high in ICT readiness. It is, in fact,
the highest in Europe. Nearly all doctors, pharmacies, hospitals, and labs are connected by broadband networks.



Figure 6.10. DIFFUSION OF THE DANISH HEALTH DATA NETWORK (DHDN), 1994-2008

100%                                                 100% 100% 100%        100% 100% 100% 100% 100% 100%
                                               97%                                             99% 100%
90%
                                        95%                                     95% 97% 98%
                                90%                                        92%
                                                                    88%
80%                                                          85%
                 80%     80%                          78%
 70%                                          70%
           61%                    62%
60%
 50%                            50%
40%
                         38%
 30%             32%
 20%
          18%
 10%
  0%
       1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

                          % of GP clinics using DHDN               % of pharmacies clinics DHDN
The Impact of ICT on the Production of Goods and Services
106


            The successful and fast uptake of DHDN can, to a large extent, be explained by the particular institutional ar-
            rangement in Denmark, in which the regional governments have a strong steering role. This is also reflected in
            the government’s expenditure on health care and the government’s control of the health sector, which is far
            above average for Denmark.

            The relatively low score on health infrastructure is mainly determined by the shortage of hospital beds, not by a
            shortage of medical personnel. On the contrary (and very different from the situation in Canada), the number of
            physicians is well above the OECD average.

            In short, readiness in Denmark is very high, but comes at the cost of high public expenditure on health care.

            Use The national rollout of DHDN is instrumental to the further implementation of e-health in Denmark. The use
            of e-health has even become critical to the functioning of the health care system at large; the use of EHR is man-
            dated for Danish hospitals. Penetration rates for B2B e-health applications connecting GPs with hospitals, specialists,
            and laboratories are very high, with the exception of the average use of electronic appointment systems.

            Uptake of standalone e-health applications, such as Decision Support Systems for diagnosis and prescribing, is
            also very high in Denmark. This is because both networked (B2B and B2C) and standalone use are strongly related
            to a country’s general e-health maturity. Thus, there is no sequential adoption of e-health, with saturation in
            standalone use followed by saturation in networked use. Both types of use are directly related to maturity and
            develop simultaneously and are, at least in Denmark, also intertwined. The extensive use of local EHR systems has
            facilitated the recent establishment of a centralized server to store all medical data.

            Another use of e-health that is unique for Denmark is the electronic connection between physicians and pa-
            tients. Denmark is the only country in the reference group that uses e-health in this way. The extent of the e-
            health network–that is, the scope of the electronic exchange of medical and administrative data–is also already
            much wider than the core group of physicians, labs, and hospitals.

            The situation in Denmark seems to be somewhat contrary to what is found in Canada. Use of e-health among
            professionals is very high, but use among citizens is just slightly above average. This corroborates the macro
            model finding that the use of e-health by citizens is a substitute for, rather than a complement of, the use of
            regular health care. Given the high degree of accessibility of regular health care–physician density is high and
            use is free–there is simply less need to consult the Internet.

            Impact Denmark is clearly one of the global frontrunners in terms of readiness and use of e-health. If ICT use
            already has a significant impact on health care, it should be visible in Denmark. Yet the Danish health care
            system performs rather poorly, both in terms of effectiveness and efficiency. With regard to effectiveness, one
            could put forward the counterargument that the country’s poor health situation is due to the unhealthy Danish
            lifestyle. However, this probably does not entirely explain away the presumed positive effect of ICT use. Most
            telling is that the growth rates also show a rather grim picture. In the same period that the use of e-health took
            off (since 2000), the life expectancy and infant mortality rates deteriorated.

            Another widely assumed impact of ICT use on e-health is cost reduction. However, despite the pivotal role of
            DHDN, the impact on the efficiency of the system as a whole seems to be rather limited so far. Government ex-
            penditure on health care has actually increased sharply. This is in line with the finding from the macro model
            that the use of B2C e-health applications increases, rather than decreases, expenditure on health care.

            Finally, perceptions on the functioning of the health care system are at least quite favorable for the Danish
            system, with the exception of the quality of medical specialists. The perception of the quality of GPs is well
                                                                                                        6. Measuring the Impact of ICT on Health Care
                                                                                                                                                  107


above average, but this is also the case in Spain, which is at a much lower level of e-health maturity (see below).
Given the central position of GPs in the Danish health care system, one would expect a higher score due to the
widespread use of DHDN. The perception of one’s own health is strongly related to Internet use and is, thus,
rather high in Denmark.

6.5.3 Spain

Average life expectancy in Spain is one of the highest in the world. One of the key drivers behind this is a very
low infant mortality rate. Infant mortality has been improving constantly since the 1970s. During the same pe-
riod, the coverage of the health care system has expanded from lower than 80% to nearly 100% of the inhabit-
ants, including low-income groups and immigrant adults and families.

The Spanish health care system is similar to the Danish system. It is publicly funded (mainly through taxation)
and provides universal coverage with free access to health care. The system is regionally organized, but the na-
tional government is responsible for overall system coordination.

A major difference from what is seen in Denmark is that hospitals are the central element in the Spanish health
care system rather than GPs. National coordination, which was quite weak in the past, has substantially im-
proved due, in large part, to ICT’s impact on national health programs. Nevertheless, due to a decentralized
government system, there are still big differences in e-health advancement among the autonomous regions.
Spanish citizens also feel that the most important government action is to ensure that health services coordi-
nate efforts with the other public services to address wider health needs.

Within the regions, the main problems are the coordination between hospitals and physicians, duplication in
clinical records and diagnoses, and long waiting times and delays in treatment.14 One of the consequences of
the long waiting times in Spain is the relative importance of private health care services. Approximately 15%
of the population has taken out a form of private medical insurance to complement, or as an alternative to, the
public health service. Private medical companies have their own clinics, operating rooms, and laboratories. In
the urban regions (especially Madrid and Barcelona), private funding of health care plays a much more impor-
tant role than it does in rural areas, where its share is negligible.

Readiness The differences among the regions also apply very much to readiness. Whereas the overall e-health
readiness in Spain is below the OECD average, some regions are frontrunners in Europe. In Andalusia, the region
with the largest population, the Diraya (EHR) and Receta XXI (e-prescribing) systems are on par with the Danish
DHDN. Spain’s overall low score on readiness is due to low scores on both ICT infrastructure and health infras-
tructure.

The low score on ICT infrastructure–particularly, the low Internet penetration in GP practices–can be explained
by the relatively low Internet penetration in Spain. Although impressive strides have been made under Plan
Avanza over the last several years,15 Spain still lags behind the European average.16 Other factors mentioned as
having a negative impact on e-health readiness are the lack of training in new technologies for professionals,



14 Duran et al., op. cit.


15 Lanvin et al., 2010.


16 Percentages for household Internet access, household broadband access, and regular Internet use by citizens in 2009 are, respectively, 54%, 51%, and 54% for Spain
and 65%, 56%, and 60% for the EU average (EU27). With regard to access, the gap with the EU average has slightly increased (+1/+2%) during the period 2008-2009. In
regular use, the gap has slightly decreased (-1%). See Eurostat, 2010. Note that the figures in this chapter are generally based on 2008 data.
The Impact of ICT on the Production of Goods and Services
108


            the rather conservative culture of health care providers, and the fear that the doctor-patient relationship will
            change. The latter is not specific to Spain, but rather occurs across all countries.

            Given the excellent health situation in Spain, one might expect a very high health care readiness. After all, our
            macro model showed that the quality of the health infrastructure and life expectancy are positively related.
            However, health care readiness in Spain is relatively low, specifically because of a relatively low number of hospi-
            tal beds and non-physician health providers. A positive aspect is the number of physicians (especially compared
            to Canada). This means that the Spanish health care system functions very efficiently or, more likely, that the
            Spanish lifestyle is rather healthy.

            Use. ICT use in health care is very similar to readiness in that large differences exist among the various regions.
            Some regions are frontrunners in the use of e-health, but the overall situation is well below the OECD average.
            For example, in Andalusia, more than 80% of all GPs are connected to the Diraya/Receta XXI systems.

            As of 2007, e-health use in Spain was just below the EU average. Nevertheless, there has been a significant in-
            crease of use during the last few years in particular types of standalone, B2B, and B2C use. 17 The establishment
            of a central node of the National Health Service for interconnection and data exchange among autonomous
            regions has been a major driver. In 2009, all public health care centers were interconnected through a common




            Figure 6.11. LEVEL OF E-HEALTH MATURITY IN ALL EUROPEAN MEMBER STATES, 2007

                      4.9
              5.0

              4.5

              4.0
                            3.6
               3.5                3.4
                                        3.2 3.1 3.1
              3.0
                                                      2.7
               2.5                                          2.4
                                                                  2.3 2.3
                                                                            2.2
                                                                                  2   2   2 1.9 1.9 1.8 1.8                               Average EU 27 + 2
              2.0
                                                                                                              1.7 1.7
                                                                                                                        1.6
               1.5
                                                                                                                              1.2
                                                                                                                                    1.1 1.1 1   1
               1.0
                                                                                                                                                    0.8
                                                                                                                                                          0.6 0.5
              0.5

                 0
                      er rk
                     Fi nds
                 d o nd




                       Gr alta
                          d y

                      Ice en

                        lg d
                      Es um
                       rm ia
                        ng y
                       Fr ry
                      Au ce
                    Bu tria

                           Ita a
                        Sp ly
                      Ire ain

            Cz P va d
                ec or kia

                  xe pu l
                        b c
                       ov g
                       Cy ia
                        M us



                       m d
                      Po ece


                      hu ia
                        La ia
                                ia
                     Sw om




                Lu Re uga
                     m bli
                     ng a




                    Hu an




                                i




                    Sl our
                    Be lan




                    Sl lan




                    Ro lan
                   Ge n




                           en
                            ar




                   Lit an
                           an
                            tv
                              a
                   th ma




                          an




                           pr
                   Ki rw

                          ed
              ite N a




                         to




                          e
                            i




                          s
                         la
                        nl




                        lg




                  h t
                Ne en




                       o
                   D


           Un




            Source: Meyer, et al., 2009.




            17 Lanvin et al., 2010.
                                                                           6. Measuring the Impact of ICT on Health Care
                                                                                                                     109


network and EHRs, e-prescriptions, and e-appointments have become fully available.18 The domestic market for
specific e-health networking applications is also developing. As early as 2000, some Internet service providers
were already providing tailored products for the B2B and B2C health care market.19

In standalone use, the fastest growth has occurred in the basic use of computers during consultations. As has
been argued before, standalone use does not precede, but co-evolves, with networked use.

Most striking in the pattern of B2B use is that electronic communication with other physicians has grown beyond the
EU average. Communication with specialists is now on the EU average, but, given the central role of specialized care
in Spain, there is probably still a significant gap to close. Making appointments over the Internet is also used rela-
tively often in Spain. This contrasts with frontrunner Denmark, where this particular type of use scores relatively low.

Impact Spain is not particularly a frontrunner in e-health, but it outperforms Denmark on every single impact
indicator. We have seen that Denmark’s leading position has not particularly translated into significant improve-
ments in the effectiveness and/or efficiency of its health care system as a whole. Thus, the relatively modest use of
e-health does not seem to be a major hindrance to the performance of the health care system as a whole.

If we turn to cost efficiency, Spain again outperforms Denmark on every indicator, with the exception of growth
of private expenditure on health care. This exception however, can be entirely explained by the very low starting
position of private expenditure in Denmark. The relative efficiency of the Spanish health care system is all the
more impressive if we take into account that Spain has one of the oldest populations in the world. As has been
argued, ageing is the key driver for the cost explosions in health care worldwide.

At first glance, when it comes to perceptions of the functioning of health care systems, Denmark scores signifi-
cantly better than Spain across the board. For example, Spain scores relatively low on frequency of “doing a
general checkup” and “being limited due to a limited physical or mental condition”. However, as has been ex-
plained in the Danish case, these indicators are driven by the same underlying condition–namely, a country’s
general health condition. The Spanish lifestyle appears to be much healthier than is the Danish one. Conse-
quently, the Spanish have a relative positive perception of their own health (thus a low score on the “being lim-
ited” variable) and have less need to regularly do general checkups (thus also a low score). If we take these inter-
related phenomena into account, the image changes completely. On the remaining three variables–perceived
quality of hospitals, GPs, and specialists–Spain scores either similar to or better than Denmark. The latter high
score (the perceived quality of medical specialists) is probably partly due to the particular setup of the Spanish
health care system, with a central role for specialized care.

In short, although both in Denmark and Spain bold claims have been made with respect to quality (e.g., error re-
duction, prompt monitoring by pharmacists) and efficiency (e.g., fewer visits to the physician for long-term pa-
tients) improvements, upon examination of the health system at large, we find little evidence to support these
claims. Without doubt, Denmark is far ahead of Spain in terms of readiness and use of e-health. However, it is also
clear that the impact of the Spanish health care system in terms of quality and efficiency is considerably better
than the impact of the Danish system. Widening the scope of the comparison to all EU member states (plus Ice-
land and Norway) we found no correlation whatsoever between the independent variable e-health maturity and
any of the key impact indicators, be it the relative decrease in life expectancy or the relative decline in infant mor-
tality over the past few years, or the diminishing growth of per capita expenditure on health care.



18 Ibid.


19 Carlos III Institute of Health, 2000.
The Impact of ICT on the Production of Goods and Services
110


            6.6 Conclusions
            As a result of this study, we draw the following eight important conclusions:

            1.   The widespread diffusion of the Internet has greatly boosted the use of ICT in health care.
                 Contrary to other social domains, ICT has been used extensively in health care at least since the early 1970s.
                 However, ICT’s early use was limited to standalone applications, such as local storage of patient records. The
                 Internet greatly boosted the use of ICT and networked applications. The presence of computers and Internet
                 connections has grown rapidly over the last several years. This growth, combined with the introduction of an
                 increasing number of ICT applications related to health, has opened new avenues for developing the
                 e-health concept. However, at this stage, we found that for both citizens and professionals, use is strongly
                 correlated with readiness; hence, the rapid growth of ICT infrastructure has translated into the rapid growth
                 of the use of e-health applications, with the exception of some types of use noted below (Conclusion 4).
            2.   Use of networked e-health applications is not sequential to the use of standalone e-health applications.
                 Long-term trends in IT represent paradigm shifts in business processes. Historically, we have seen at least
                 three such 15 to 20 year waves: from centralized mainframes (enterprise view of information) to distributed
                 personal computers (individual view of information) to interconnected computers (shared view of informa-
                 tion). Likewise, we expected to find that the use of standalone applications preceded the use of networked
                 applications. However, we found that both types of use are actually strongly correlated to a country’s overall
                 e-health maturity. The two types of uses develop simultaneously and, in many cases, reinforce each other.
                 Thus, they develop in parallel, rather than serially.
            3.   Standalone and networked e-health applications have different adoption patterns.
                 There is still a marked difference between standalone and networked applications, and the two types should
                 not be confused. For instance, standalone EHRs have been in use at least since the 1970s, and they have ra-
                 pidly been adopted by physicians since the 1980s. The new generation of networked EHRs, especially the
                 uniform national EHRs, are another piece of (bitter) cake. Privacy concerns have delayed national rollouts in
                 many countries. In the absence of a national system and because of the incompatibility of local and regional
                 systems, the electronic exchange of health records and administrative data on a national scale is still fraught
                 with difficulties. Where such national systems have been implemented (as in Denmark), the use of e-health
                 has grown very quickly.
            4.   Telemedicine’s potential as a primary dimension of e-health has not yet been fully realized.
                 Health care systems around the world face increasing pressure due to autonomous yet interrelated trends,
                 such as ageing populations and the increase of chronic diseases. As a consequence, total expenditure on
                 health care is expected to double in the next 20 years. Technology is supposed to be one of the ways to com-
                 bat increases, especially when it is supported by major organizational changes, such as a shift from curative
                 to preventive health care. Telemedicine was regarded as one of the early killer applications for e-health and
                 was intended to play a pivotal role in containing the ever-increasing health care costs and shifting toward
                 preventive health care. However, the use of telemedicine has hardly grown during the last few years, and
                 adoption rates remain very low, whereas other types of use have experienced double-digit growth (Conclu-
                 sion 1). Unlike other ICT uses in the health arena, such as storage of patient records, telemedicine requires
                 complex changes in procedure and it has met with cultural resistance–factors that undoubtedly have slowed
                 its growth.
            5.   Economic strength is the strongest determinant for impact on health care systems.
                 Economic strength (GDP) still has the greatest impact on the outcome of health care systems. Healthy life ex-
                 pectancy is directly related to the welfare of a country. Similarly, inhabitants of richer countries tend to think
                 that the health care system in their country performs relatively well. This simply means that the relative contri-
                 bution of ICT to the outcome is still modest, at least to this point. One of the few direct links that we found
                 between IT-readiness and (health) impact at the macro level is having a clear national information strategy.
            6.   Efficiency gains create differing perceptions of quality change.
                                                                          6. Measuring the Impact of ICT on Health Care
                                                                                                                     111


   In the perception of physicians, there is no direct effect from using ICT on the quality of health care provided.
   One of the reasons for this is how ICT is being used. In other words, implementation quality largely deter-
   mines the eventual impact of ICT use. This applies to ICT use in general but is especially important to the
   critical environment of health care practices. With regard to ICT use, physicians feel that the perceived effi-
   ciency gains lead to increased workloads and an increase in the number of patients treated per day. This
   deteriorates the scope of services offered and the doctor-patient relationship.
   Patients’ perceptions differ from GPs, according to the evidence that we found. Patients value efficiency im-
   provements (in terms of a reduction in waiting times for treatments) more highly than a perceived deterio-
   ration in quality. It may well be that the difference in perceptions between GPs and patients is attributable
   to temporary transition costs that disappear as best practices that incorporate efficiencies and cost savings
   become more firmly established.
7. Widespread Internet use has a profound impact on the doctor-patient relationship.
   The relationship between doctors and patients is affected by the sharp increase in Internet use by patients.
   Citizens have eagerly embraced the Internet as a readily available source of medical information, whereas
   doctors were once the sole source of information in a rather hierarchical relationship. The Internet has great-
   ly empowered and emancipated patients. Over the last couple of years, health care consumers have in-
   creased confidence in the medical information they find online and have lost some confidence in the infor-
   mation they get from their physicians. The most avid users of medical information on the Internet are also
   most concerned about their own health. It is exactly this group that most closely questions the quality of
   their doctor’s diagnosis and the treatment offered.
   It might come as no surprise that in many countries, physicians are wary about patients using the Internet
   to find medical information. At the same time, they turn en masse to the Internet to look for prescribing in-
   formation and to continue their own education, both positive impacts on the health care system.
8. E-health increases the reach of the health care system.
   We observe a negative correlation between the readiness of the health infrastructure and the use of e-health
   by citizens. The more doctors and specialists there are in a country, the less need there is for a citizen to resort
   to e-health (Denmark) and vice versa (Canada). It could also be that countries with less developed conventional
   health systems have the urge to modernize their infrastructure via e-health. Thus, e-health increases the reach
   of health care provision to a country’s population. This means that without e-health, fewer people would re-
   ceive health care, since the available medical personnel would be the only resource to provide this care.



Bibliography
accenTure.inSTiTuTe.For.HealTH.&.PuBlic.Service.value (2010). Accenture Citizen Experience Study: Measuring
   People’s Impressions of Health.
anderSon, G. (2007). Chronic Conditions: Making the Case for Ongoing Care. Baltimore, MD: Johns Hopkins Uni-
   versity.
anGloinFo.(2010). Living in Spain - Health Systems. http://madrid.angloinfo.com/countries/spain/life9.asp Text
   last edited on August 2010.
arMiJo, C.C. (2008). Las Tecnologias de la Informacion y las Comunicaciones (TIC) en los Sistemas de Salud. Tele-
   fonica (mimeo).
Barer, M.L., and W.A. weBBer.(1999). Immigration and Emigration of Physicians to/from Canada. Centre for
   Health services and policy research. http://www.chspr.ubc.ca/files/publications/1999/hhru99-06.pdf
Beal,.a.c.,.doTy,.M.M.,.Hernandez,.S.e.,.SHea, K.K., and K. daviS.(2007). Closing the Divide: How Medical Homes
   Promote Equity in Health Care: Results from the Commonwealth Fund 2006 Health Care Quality Survey.
canadian.Medical.aSSociaTion.(2008). Information Technology and Health Care in Canada: 2008 Status Report.
   http://www.cma.ca/multimedia/CMA/Content_Images/Inside_cma/HIT/2008_status_report/IT_hand-
   book.pdf.
The Impact of ICT on the Production of Goods and Services
112


            canada.HealTH.inFoway.(2008). EHR 2015: Advancing Canada’s next generation of healthcare. http://www2.in-
                foway-inforoute.ca/Documents/Vision_2015_Advancing_Canadas_next_generation_of_healthcare%5B1%
                5D.pdf.
            canweST.MediaworkS.PuBlicaTionS.inc. (2007). Why are doctors leaving Canada? http://www.canada.com/
                nationalpost/news/story.html?id=04c4d089-35f5-4427-b78d-dae67df07bec.
            carloS.iii.inSTiTuTe.oF.HealTH.(2000). The e-health development framework in Spain. http://bvs.isciii.es/mono/
                pdf/UCIS_01l.pdf.
            cikowSki,.z.,.lindSkold,.l.,.MalMqviST,.G.,.BillinG,.H.,.JoHanSSon..L., and T. PaTel.(2006). Sollefteå and Borås hos-
                pitals; Sjunet, Sweden: radiology consultations between Sweden and Spain.
            duran,.a.,.lara, J.L., and M. van.waveren.(2006). Spain: Health system review, Health Systems in Transition,
                8(4):1–208.
            eGGerTSon, L. (2004). ED problems result of bed shortages, doctors contend. Canadian Medical association jour-
                nal. http://www.cmaj.ca/cgi/content/full/170/11/1653.
            eHr.iMPacT.(2009a). Diraya, the regional EHR and ePrescribing system of Andalucia’s public health service.
            eHr.iMPacT.(2009b). Receta XXI, the ePrescribing system of Andalucia’s public health service.
            euroPean.coMMiSSion.(2010). Europe’s Digital Competitiveness Report (Vol. I). Brussels: EC.
            euroPean.coMMiSSion.(2005). “Eurobarometer: Health and Long-Term Care in the European Union.”
            e-uSer.(2005). e-Health. Country Brief: Spain. http://www.euser-eu.org/ShowCase.asp?CaseID=2218&LevelCode
                ID=98&print=YES.
            GreenHalGH,.T.,.PoTTS,.H.w.w.,.wonG,.G.,.Bark, P., and D. SwinGleHurST.(2009). Tensions and paradoxes in elec-
                tronic patient record research: a systematic literature review using the meta-narrative method. Milbank
                Quarterly, 87 (4). pp. 729–788.
            HealTH.conSuMer.PowerHouSe.(2009). “Euro Health Consumer Index 2009”, Patient View Survey.
            Holland,.c.,.BonGerS,.F.,.vandeBerG,.r.,.keller,.W., and R.A. Te.velde.(2004). “Measuring and evaluating e-Govern-
                ment. Building blocks and recommendations for a standardised measuring tool”, in: M. Khosrow-Pour (Ed.),
                Practicing E-Government: A Global Perspective, Idea Group: Hershey, PA.
            ICTC (2009). e-Health in Canada, Current Trends and Future Challenges. http://www.ictcctic.ca/uploadedFiles/
                Labour_Market_Intelligence/ICTC_e-health_e_v2%20(2).pdf.
            iTu.daTaBaSe.(2010). www.itu.int.
            Juel,.k.,.BJerreGaard,.P., and M. MadSen.(2000). Mortality and life expectancy in Denmark and in other European
                countries. What is happening to middle-aged Danes? European Journal of Public Health 10 (2), pp. 93–100.
            kirkMan,.G.S.,.oSorio, C.A., and J.D..SacHS.(2001). The Networked Readiness Index: Measuring the Preparedness
                of Nations for the Networked World, Center for International Development at Harvard University.
            koPPel,.r.,.MeTlay.J.P.,.coHen,.a.,.aBaluck,.B.,.localio,.a.r.,.kiMMel, S.E., and B.L. STroM.(2005). Role of Computer-
                ized Physician Order Entry Systems in Facilitating Medication Errors. Journal of the American Medical Infor-
                matics Association, 293(10), pp. 1197–1203.
            lanvin,.B.,.TorreS.Mancera,.d., and J. BuSqueTS.(2010). Promoting Information Societies in Complex Environ-
                ments: An In-Depth Look at Spain’s Plan Avanza. In: Dutta, S. and I. Mia (eds.) World Economic Forum (2010).
                Global Information Technology Report 2009-2010. Davos: World Economic Forum, pp. 127–139.
            lewin.GrouP.(2003). Trends Affecting Hospitals and Health Systems (TrendwatchChartbook 2003), prepared for
                American Hospital Association.
            linder,.J.a.,.Ma,.J.,.BaTeS,.d.w.,.MiddleTon, B., and R.S. STaFFord.(2007). Electronic Health Record Use and the Qual-
                ity of Ambulatory Care in the United States. Arch Intern Med. 2007;167(13):1400–1405.
            ManHaTTan.reSearcH.(2007) 2007 Annual Cybercitizen® Health Report. www.manhattanresearch.com.
            Meyer,.i.,.doBrev,.a.,.HaeSner,.M.,.HüSinG,.T., and W.B. korTe.(2009). Benchmarking ICT use among General Prac-
                titioners in Europe, Bonn: Empirica.
            OIPC (2009). Commissioner urges vigilance in wake of computer virus outbreak at Alberta Health Services (June
                2009). http://alberta.ca/acn/200907/264315B7CECB4-AB71-A6E4-9F121F400E08D2CD.html.
            onGena, G. (2008). Zorgen over Internet inzicht. Gebruik, ervaringen, determinanten en effecten van online me-
                                                                       6. Measuring the Impact of ICT on Health Care
                                                                                                                 113


    dische informatie [Worries about Internet opinion. Use, experiences, determinants and effect of online me-
    dical information]. Utrecht: University of Utrecht (mimeo).
PaTTon.G.A. and R.M. Gardner.(1999). “Medical informatics education: the University of Utah experience.” Jour-
    nal of the American Medical Informatics Association 6 (6): 457–465.
SilverSTein, S. (2009). Are Health IT Designers, Testers and Purchasers Trying to Harm Patients? (Parts 1 to 8).
    http://hcrenewal.blogspot.com/2009/02/are-health-it-designers-testers-and_26.html (last accessed: 1
    March 2010).
SolSTen.e. and S.W. MediTz.(eds) (1988). Spain: A Country Study. Washington: GPO for the Library of Congress,
    1988.
STrandBerG-larSen,.M.,.nielSen,.M.B.,.vallGårda,.S.,.kraSnik,.a.,.vranGBæk, K., and E. MoSSialoS.(2007). Denmark:
    Health system review. Health Systems in Transition, 9(6): 1–164.
STroeTMann,.k.a.,.JoneS,.T.,.doBrev, A., and V.N. STroeTMann.(2006). e-Health is Worth It. The economic benefits
    of implemented e-health solutions at 10 European sites. Brussels: European Commission.
THe.oecd.HealTH.ProJecT.(2005). Health Technologies and Decision Making. Paris. France.
UNPAD (2005). Global e-Government Readiness Report 2005. From E-Government to E-Inclusion. New York: Uni-
    ted Nations.
wanScHer,.c.e.,.PederSon, C.D., and T. JoneS.(2006). MedCom, Denmark: Danish Health Data Network (DHDN),
    Empirica: Bonn.
world.HealTH.orGanizaTion.(2009). World Health Statistics.
world.HealTH.orGanizaTion.(2005). “Global E-health Survey.”

				
DOCUMENT INFO
Shared By:
Categories:
Tags:
Stats:
views:4
posted:11/11/2011
language:English
pages:25