This working paper presents original data on innovation strategies for smart specialisation (RIS3) in European union (EU) regions and Member States
obtained from the Eye@RIS3 open data tool for sharing information on the areas identified as priority areas by 198 innovation strategies.
Finally, we compare the main areas of planned investment with sectoral data on firms employment and patents, with the conclusion that the connection between priorities and the economic and innovation structures is weak.
smart specialisation, prioritisation, innovation policy, open data, structural funds Acknowledgements The authors would like to express their gratitude to a number of colleagues for their kind comments, cooperation and contributions.
an open data tool for gathering and diffusing information on the envisaged regional and national areas of smart specialisation (1). RIS3 are central to the European commission's effort to foster smart and sustainable growth (European commission, 2010a).
We use these data to give an overview of the most common priority areas and to explore the extent to which policy makers develop unique niches and combine priorities in their RIS3.
One of the main challenges when collecting data on these domains or prioritised areas is their multidimensional nature.
as of 2012, identifying priorities for their RIS3 investments. 3. Developing an open data tool for mapping innovation priorities Eye@RIS3 is an interactive open data tool that gives an overview
Eye@RIS3 has been developed as an open data tool to help strategy development and to facilitate interregional and trans-national cooperation, rather than as a source of statistical data.
The majority of data have been added by S3 Platform staff and a minority by policy makers themselves.
To have listed priorities in the Eye@RIS3 database does not mean that the particular strategy
Currently, the data consist of 1 307 priorities from 20 EU countries, 174 EU regions, 6 non-EU countries and 18 non-EU regions.
In countries without regional RIS3, national data have been added. In total, the sample covers almost all of the EU-28 territory, with the exception of three Italian regions.
The database contains data at NUTS1, 2 and 3 levels, since there are large variations in our sample in terms of regional powers and administrative responsibilities for innovation and development policies.
5) The data used in this paper were retrieved on 5 december 2014, at which time there was almost full coverage across EU Member States.
Since then, additional data have been added. 6 Regional and national innovation priorities are at the heart of the database.
With regard to data quality, there are a number of caveats. First of all, the data are not yet suitable for econometric analyses
since all entries must be confirmed and double-checked against the final versions of strategies. However, the database is continuously being updated with the aim of having up-to-date information.
the data can be validated fully. It must be kept in mind that, originally, the main rationale for developing the tool was to increase transparency
This figure is based on data from 218 regions and countries from the Eye@RIS3 database.
%0%-33%34%-66%67%-100%Share of regions & countries in sample Degree of correspondence with most common sub-categories 12 data entry among the sub-categories.
This figure is based on data from 218 regions and countries from the Eye@RIS3 database.
Looking at sub-category data, we found that, grosso modo, regions and countries have not chosen the same sets of priorities,
we carried out the same type of analysis for main category data. In total, there were 231 combinations of 1 307 encoded priorities.
This figure is based data from 218 regions and countries from the Eye@RIS3 database. The y-axis is the share of all regions and countries in the database (n=198.
be an outcome of our coding and interpretation of data. However, in general, we do find a correlation between EU objectives and the chosen priorities.
we will now examine data on their actual economic structure. This helps us to better understand the extent to which regional and national priorities focus on areas where strong
we have used Eurostat data on the number of organisations, employment data and patent applications in absolute terms,
We have compared these data with the most common RIS3 priorities to determine how the priorities relate to the economic structure.
It seems as though the choices of RIS3 priorities are reflected not strongly in the data on local units in absolute numbers.
SBS data by NUTS 2 regions and NACE Rev. 2 (from 2008 onwards), number of local units However, the number of local units and their growth can be affected by sectoral structure.
Eurostat employment data for 2010, SBS data by NACE Rev. 2 for the EU-28 (and Norway) with missing data for Croatia, Greece, France, Italy, The netherlands and Slovakia.
No data were available for the wholesale and retail sectors. Finally, we examine Eurostat patent data covering patent applications to the European Patent office (EPO), in terms of both absolute numbers and growth in absolute and relative numbers.
There were relatively few connections between regional priorities and the growth of the number of patent applications.
or due to lacking patent data categories and lack of easily assignable NACE codes for sustainable innovation. 0%2%4%6%8%10%12%14%16
This working paper has presented data from the Eye@RIS3 database, an open data tool which gathers information on the innovation priorities of regions and states in the EU and in neighbouring countries.
we explored combinations of both main category and sub-category priority data. We found that very few regions
Finally, we compared Eye@RIS3 data with Eurostat data on numbers of local units in different sectors, employment and patent applications.
or a lack of relevant data or it might simply indicate that priorities are geared towards future potential rather than existing areas of activity.
and performance indicated by regional data on labour, organisations, publications and patents. 21 References Aho, E.,Cornu, J.,Georghiou, L,
(e g. heritage) Open data and sharing of public sector information KETS Advanced manufacturing systems Advanced materials Industrial biotechnology Micro-/nano-electronics Nanotechnology Photonics 27
This working paper presents original data on innovation strategies for smart specialisation (RIS3) in European union (EU) regions
and Member States, obtained from the Eye@RIS3 open data tool for sharing information on the areas identified as priority areas by 198 innovation strategies.
Finally, we compare the main areas of planned investment with sectoral data on firms employment and patents, with the conclusion that the connection between priorities and the economic and innovation structures is weak
At the same time, the Manual makes note of the frequent non-availability of sufficiently detailed data, and for that very reason it suggests that certain simplifications ought to be made
However, a classification system based on the above unfortunately does not always work as such detailed data are unavailable for most types of statistical data sets.
TEÁOR'08), we categorised available data as follows: ICT Industry: Section C (Manufacturing: C. 26: Manufacture of computer, electronic and optical products C. 26.1:
Occasionally, less data is available on the ICT manufacturing as some statistical databases fail to subdivide this section of the national economy into further sectors and subsectors,
and so our analysis was encumbered by the non-availability of sufficiently detailed data. We nevertheless endeavored to present the fullest possible picture of both the ICT industry and ICT services
and online payment systems, making available more radio spectrums (in particular for the mobile data market), investing into high-speed broadband connections,
Company-level R&d data clearly demonstrate that fewer new and innovative large ICT corporations are created in the EU than in the US.
Based on 2000-2009 data, the OECD also evaluated the contribution of ICT investments to economic growth.
There is no data available for Poland 1995) 1. The ICT sector's stakeholders, inputs and significance for the national economy 0%2%4%6%8%10%12%14%16%Poland Austria Germany Portugal Slovakia France OECD
The ICT service sector's contribution to international trade is represented relatively well by statistical data published by the Hungarian Central Statistical Office on communication services as well as IT and information services4.
Foreign market entry opportunities The bulk of primary data shown in the text boxes of this report were taken from an RDI survey carried out by the National Innovation Office RDI Observatory in the spring of 2012 with the participation of 1
Based on 2010 data and the standard national economic sector classification, the highest number of active businesses are engaged in the wholesale and retail trade, repair of motor vehicles (139,546 out of a total
OECD Key ICT Indicators, 2012 8based on OECD data for 2009.0%2%4%6%8%10%Portugal Greece Spain Switzerland Austria Germany
According to survey data, this conclusion holds also for companies of the ICT sector. 90%of respondents replied that the necessary resources come from their own company group,
and interpreting innovation data, 3rd edition, 2005, pp 146.0%10%20%30%40%50%60%Czech R. Spain Germany Poland Austria Norway
and interpreting innovation data, 3rd edition, 2005, pp 146. World bank Database http://data. worldbank. org/35 National Innovation Office RDI MIRROR-1. Review on the ICT Sector All figures together with underlying tables are accessible
through the National Innovation Office Kaleidoszkóp internet portal www. kaleidoszkop. nih. gov. hu. Figure 1: The EU's ICT sector in international comparison (2007.
There is no data available for Poland 1995)..12 Figure 4: Gross value added of the Hungarian ICT sector as a percentage of value added of the total economy, 1995-2011.
as well as data and analyses supporting RDI policy related decision-making. With the help of this database, RDI stakeholders can be involved in diagnosing problems as may exist within the sector
All Kaleidoszkóp system data and service functionalities are meant to assist public sector institutions and other organisations in their networking, strategy development and market analysis efforts.
u generic and specific sectoral RDI analyses and statistics u quality data sources informing analysis u information on public funded RDI projects u
The report, together with any data and indicators published therein, can be downloaded from the Kaleidoszkóp website:
132.8 billion HUF 0 50 100 150 200 250 billion HUF Business enterprises Government Higher education Data is for 2012.
The National Innovation Oice RDI Observatory's own calculations based on HCSO, 2013 data. 225.4 billion HUF81 12.5 39.2 157.6 40 27.8 6
102.6 Cyprus Data is for 2011. Source: The National Innovation Oice RDI Observatory's own calculations based on Eurostat, 2013 data. €/fo 1000 600 999 100 599 0 99
510.5 European union average €/capita w w w. k a l e i d o s z k o p. n i h. g o v
15.2 18.4 05 10 15 20 25 30 35 40 45 50 billion HUF Data is for 2012.
The National Innovation Oice RDI Observatory's own calculations based on HCSO, 2013 data. Business Government Abroad enterprises 8 w w w. n i h. g o v. h u/e n g l i s h How much is R&d
electronic and optical products Information and communication NATIONAL ECONOMY'S Average Data is for 2012.
The National Innovation Oice RDI Observatory's own calculations based on HCSO, 2013 data. 41.7 25.9 22.2 20.4 18.2 16.2 16.2 16.0 12.0
Data is for 2012. Source: The National Innovation Oice RDI Observatory's own calculations based on HCSO, 2013 data. average Number of researchers capita/research unit 5. 4 Hungarian
owned corporate research units 34.1 foreign owned corporate research units 10 w w w. n i h. g o v. h u/e
Full-time equivalent Data is for 2011. Source: The National Innovation Oice RDI Observatory's own calculations based on HCSO, 2012 data. w w w. k a l e i d o s z k o
p. n i h. g o v. h u/e n 11 Where are the corporate R&d units?
Jász-Nagykun-Szolnok Békés Csongrád Bács-Kiskun Baranya Tolna Fejér Komárom-Esztergom Gyor-Moson-Sopron Veszprém Vas Zala Somogy Data
The National Innovation Oice RDI Observatory's own calculations based on HCSO, 2013 data. Budapest 0 30 31 60 61 90 91 29 685 Numbers of research units (pc) apart from Budapest898 12 w w w. n i h
. €/capita 250 200 150 100 50 0 Data is for 2010. Source: Eurostat, 2012.
enterprises Large enterprises Data is for 2010. Source: Eurostat, CIS, 2012 74%51%35%21%54%26%30%49%65%79%46%70%14 w w w. n i h. g
Estonia Sweden Italy Malta Austria Cyprus Data is for 2010. Source: Eurostat, 2012. Total number of patent applications by billion EUR of total R&d expenditure (GERD) € w w w. k a l e i d o s z k o p
generic and speciic sectorial RDI analyses and statistics information analysis based on qualitative data sources information on public funded RDI projects maintaining register of Hungarian research
as well as data and analyses supporting RDI policy related decision-making. Kaleidoszkóp is operated by the National Innovation Oice RDI Observatory Department.
Per projections based on Cisco VNI data, average global bandwidth demand per household in 2020 (the target data for achieving the DAE's objectives for ultra-fast broadband) is less than 2 Mbps
Cisco VNI 2011 data, 1 WIK calculations. Ultra-fast broadband access is useful, but in light of realistic consumer demand it is not necessary to assume that every broadband user will consume maximum capacity all the time.
For the fixed telecommunications network, there are significant uncertainties as to the quality of currently available data.
because there has been little customer demand for upstream data bandwidth. The biggest single impediment is that such a shift would conflict with analogue FM radio
see Section 5. 1 DAE Digital Agenda for Europe DHCP Dynamic Host Configuration Protocol DOCSIS 2. 0/Eurodocsis 3. 0 Data Over Cable
the newest standards for wireless communication of high-speed data Mbps Mega bit per second (one million bits per second) MDF Main distribution frame MDU Multiple Dwelling Unit
Per projections based on Cisco VNI data, average global bandwidth demand per household in the busy hour in 2020 is less than 2 Mbps. Ultra-fast broadband access is useful,
8 Cisco analysts compile data from multiple sources in order to estimate current and future Internet traffic by region, by application,
2015 2016 Voip Online Gaming File sharing Web/Data Internet Video 29%CAGR 2011-2016 Petabytes per Month 22%23%54%18
Cisco VNI (2011). 11 Translating the above Cisco data into Mbps demand, during the average hour and during the busy hour,
we have depicted the results in Table 2. Data networks are designed generally to carry near-peak traffic;
because there is no upper bound to the offered load in an IP data network. See J. S. Marcus (1999:
Cisco VNI 2011 data, 14 WIK calculations. Estimation of the mean aggregate bandwidth demand during the busy hour from the data is straightforward,
and is shown in Figure 3. The 2010-2015 figures are based directly on Cisco data, while the 2016-2020 figures are an extrapolation reflecting an exponential regression of the 2010-2015 data.
The fit of the regression is very good. 14 Ibid. 20 Rethinking the Digital Agenda for Europe (DAE) Figure 3:
The evolution over time of consumer bandwidth demand during the busy hour Source: Cisco VNI 2011 data, 15 WIK calculations.
What is particularly striking is that the mean global bandwidth demand per household is far less than most have assumed,
In a sophisticated study drawing on data from more than 6, 000 New zealand businesses, Grimes et al.
a crosssectional analysis of U s. data; in: Issues in Economic policy no. 6, The Brookings Institute, July 27 Greenstein, S. and R. Mcdevitt (2012), Measuring the Broadband Bonus in Thirty OECD Countries, OECD Digital economy Papers, No. 197
For the fixed telecommunications network, there are significant uncertainties as to the quality of currently available data.
modern Hybrid Fibre Coaxial (HFC) cable solutions are capable of simultaneously carrying voice, data and video services.
for many years. 46 These data have been reflected in a range of Commission studies, and have been picked up without question in other studies such as those of the EIB.
The Case of Spain, op cit. 46 See IDATE (2011), Broadband Coverage in Europe, Final Report, 2011 Survey Data as of 31 december 2010,2011,
A recent WIK study53 attempted to comprehensively quantify the gap between the deployment of fibre-based ultra-fast broadband to 100%of the population of Germany reflecting detailed geographic data on the locations of streets, buildings,
because there has been little customer demand for upstream data bandwidth. The biggest single impediment is that such a shift would conflict with analogue FM radio
cable represents the current state of the art for Europe as regards delivery of data, voice, and video over a cable television system. 63 It is the cable technology platform that competes most directly with fibre-based NGA,
whatever data capacity is available is shared by all connected customers. With proper management, however, the data capacity can meet realistic customer requirements under quite a wide range of assumptions.
First, one must bear in mind that the capacity required to support linear video is separate from the capacity used to support data (as is also the case with GPON.
Second, the cable network operator can progressively upgrade the network infrastructure, as needed and on an incremental basis,
It is important to bear in mind that all modern data networks are shared in some degree. Networks differ in where the sharing takes place.
It is worth noting once again that Cisco VNI data strongly suggest that average data consumption per household during the busy hour will be less than 2 Mbps, even in 2020.
the Cisco VNI 2011 analysis finds that Internet data traffic is become less symmetric over time, not more,
when the data are plotted together. 16.2 10.3 11.7 10.0 8. 8 6. 9 26.8 20.2 16.2 18.2 18.4 10.6 05 10 15 20
a cross-sectional analysis of U s. data, in: Issues in Economic policy no. 6, The Brookings Institute, July.
http://www. iscr. co. nz/f563, 16240/16240 feeding a need for speed v4. pdf. IDATE, Broadband Coverage in Europe, Final Report, 2011 Survey Data as of 31 december 2010,2011
Data collection and content analysis covered a wide range of materials such as journals and conference papers;
Developing the final set of recommendations Following the aforementioned procedure, a set of qualitative data was developed including case reports, workshop findings and conclusions, interview summaries, open items of online
and analyse the qualitative data to develop a set of policy recommendations for sustaining and scaling up educational innovations at local, regional, national,
and reporting implicit and explicit patterns (themes) within the data (Braun & Clarke, 2006). ) In the present study, thematic analysis was used to transcribe qualitative data;
generate initial codes; search for themes (i e. recommendations; review themes; and refine and merge themes.
Helping teachers to acquire much greater proficiency in data handling and methods such as learning analytics
Supporting policy actions for open research and dissemination of data (e g. open access publications, open data repositories, data protection strategies etc.
Supporting policies and initiatives for open research and free dissemination of data (e g. open data, open access publications etc.
Setting evaluation, communication and feedback mechanisms (e g. platforms for collecting big and/or rich data and learning analytics) right from the start of different pilots or initiatives. 121 57,0 47.
Supporting data portability and interoperability between online professional networks, making it easier for teachers to participate in a number of them (e g. without having to duplicate data.
"Policy/decision-makers give their highest recommendation to developing data portability and interoperability between online professional networks, making it easier for teachers to participate in number of them. 27 3. 7 Area 7:
) Key Data on Learning and Innovation through ICT at School in Europe 2011. Retrieved 15 december 2013, from Education, Audiovisual and Culture Executive agency http://eacea. ec. europa. eu/education/eurydice%20/documents/key data series/129en. pdf Griffin, P.,Mcgaw, B,
and the data you provide will be anonymous and confidential. If you have any questions or concerns, please do not hesitate to contact us.
Helping teachers to acquire much greater proficiency in data handling and methods such as learning analytics
1 2 3 4 5 6 7 Supporting policies and initiatives for open research and free dissemination of data (e g. open data, open access publications etc.
communication and feedback mechanisms (e g. platforms for collecting big and/or rich data and learning analytics) right from the start of different pilots or initiatives.
Supporting data portability and interoperability between online professional networks making it easier for teachers to participate in a number of them (e g. without having to duplicate data.
Developing long-term sustainability and scalability strategies for cross-border professional networks, such as etwinning, for disseminating pedagogical innovation.
7 2. 2 4. 4 8. 1 14.7 27.2 42.6 69.9 Helping teachers to acquire much greater proficiency in data handling and methods such as learning analytics,
8 3. 9 3. 9 10.1 22.5 34.1 24.8 58.9 Supporting policies and initiatives for open research and free dissemination of data (e g. open data
data and learning analytics) right from the start of different pilots or initiatives..8 1. 7 6. 6 16.5 17.4 26.4 30.6 57.0 Encouraging collaboration and communication channels between supranational agencies (i e.
7. 6 10.1 16.0 26.9 34.5 61.3 Supporting data portability and interoperability between online professional networks
making it easier for teachers to participate in a number of them (e g. without having to duplicate data..
Helping teachers to acquire much greater proficiency in data handling and methods such as learning analytics,
) Helping teachers to acquire much greater proficiency in data handling and methods such as learning analytics,
communication and feedback mechanisms (e g. platforms for collecting big and/or rich data and learning analytics) right from the start of different pilots or initiatives. 5. 55 53 5. 59
. 38) 26 5. 75 (1. 22) 24 5. 18 (1. 59) 17 Supporting data portability and interoperability between online professional networks, making it easier
, without having to duplicate data. 5. 62 (1. 58) 53 5. 35 (1. 35) 26 5. 92 (1. 21) 24 5. 18 (1. 59) 17
WHO Library Cataloguing-in-Publication Data Management of patient information: trends and challenges in Member States:
. Data collection. I. WHO Global Observatory for ehealth. ISBN 978 92 4 150464 5 (NLM classification:
18 2. 5 Interoperability of patient data...18 2. 6 Conclusions drawn from the literature...
24 Individual patient data 24 Aggregate patient data 27 2 3. 4 Regional/District offices...
30 Individual patient data 30 Aggregate patient data 33 3. 5 National level...36 Individual patient information 36 Aggregate patient data 39 3. 6 mhealth and patient information...
42 3. 7 International standards for ehealth...42 International guidelines documents 43 Metadata standards 44 Messaging standards 45 Medical record standards 46 Vocabulary standards 46 3. 8 National
and health systems 49 Standards to identify patients 49 Individual patient data standards 49 Vocabulary standards 49 Messaging standards 50 Survey metadata standards
Data Collector 68 Preparation to launch the survey 69 Survey 70 Limitations 70 Data processing 71 Response rate 72 Response rate by WHO region 73 Response rate by World bank
Analysis of data in patient information systems can lead to new insight and understanding of health and disease
It examines the adoption and use of patient information systems in Member States and reviews data standards and legal protection for patient data.
internationally-harmonized clinical models and concepts are needed for data interoperability and standardized international case-reporting,
many Member States still rely on paper-based systems for health data collection. The survey data analysed by WHO region showed that all regions have a high use of paper-based systems, particularly the African Region and Southeast asia Region.
Countries within the Regions of The americas, Eastern Mediterranean, and the Western Pacific reported a higher use of electronic transmission of health records than computer use to collect health data.
This may be due to the use of fax or scanned image technology where the communication is electronic
The use of electronic systems is aggregated higher for (summary) data than individual patient data. This could be
because there is an institutional need for the aggregate data at management levels which in turn stimulates the creation of an electronic system.
There may be a perception that individual patient data in electronic format may not be of as much value for administration,
However, the value of individual patient data for improved patient care is very much a case of‘connect the dots':
some form of electronic record system could compile these data and make them accessible to other health care professionals,
Executive summary 7 Electronic health systems must be built in a way to facilitate the exchange of data;
Standards must be applied to the data and the systems themselves to allow for and facilitate the exchange of data between various sources.
The adoption of standards is progressing well across most Member States including standards for ehealth architecture, data, interoperability, vocabulary, and messaging.
These are important foundation blocks for the implementation of patient information systems because they facilitate clear communication.
In addition, most countries have taken steps to establish legal frameworks for the protection of patient data.
standards-based software platforms and data exchange standards to make efficient use of existing resources.
While a significant amount of health data comes from the community and environmental observations a great amount of valuable detailed health data originates from patients in their encounters with health professionals.
In addition, surveys and surveillance activities collect more data from and about individuals. The key to effective patient information systems is to retain the link between the individual
and the data collected over time and to make those data available to multiple health care providers when needed.
Following this‘data trail'that charts the health of an individual is both valuable and important:
these data can be aggregated to provide data trails for communities, regions, and countries, upon which public health policy is shaped.
This includes resource management, monitoring and evaluation, disease surveillance, and operational research (as shown in the flow diagram below).
Many health information systems do not in fact retain data in the form of an individual patient record.
Instead the data are aggregated into summary totals which obscure the individual patient link, making it difficult to follow patients over time.
One of the reasons for this is that systems that collect, manage, and display individual patient data can be difficult to implement particularly in low-resource settings,
where health budgets are strained already. 1 Introduction Introduction 10 Most health systems collect at least some individual patient data during clinical face-to-face encounters.
Keeping these data personalized rather than anonymous is facilitated by using electronic systems which can more easily store,
access, analyse, and share data. While the conventional way to collect such data are on paper forms
and register books, increasingly, face-to-face encounters are being captured electronically. This trend will continue as improvements are made in computer hardware, software,
and telecommunication infrastructure and as countries develop the skills necessary to implement electronic data storage and transmission systems.
Data from patients Data linked to individual patients EMR/EHR/PHR Hospital IS (For use by
or for an individual and also research) Aggregated data (For use in planning, management and research) Part of the ehealth series based on the second global ehealth survey, this report is aimed at professionals in health care policy, planning,
The EMR can also support the collection of data for uses other than clinical care such as billing, quality management, outcome reporting,
Furthermore, an EMR may contain clinical applications that can act on the data contained within its repository, for example, a clinical decision support system (CDSS), a computerized provider order entry system (CPOE), a controlled medical vocabulary,
if they are able to exchange data using standardized data transmission formats (1). The electronic health record (EHR) is a longitudinal electronic record of patient health information generated by one or more encounters in any care delivery setting.
Included in this information are patient demographics progress notes, problems, medications, vital signs, past medical history, immunizations, laboratory data,
and assisting with chronic disease management via an interactive, common data set of electronic health information and ehealth tools.
data collection and analysis. Level 5. Optimized process management includes deliberate process optimization/improvement. Enterprise Architecture An alternative method is the Enterprise Architecture (EA) approach. 1 An early description of this methodology was described by Spewak
This requires data interoperability which is the key to effective use of health information. The Australian National ehealth Transition Authority has defined an Interoperability Maturity Model (6) that identifies increasing capability for data interoperability.
Interoperability Maturity Model levels Initial: There is an early awareness of ehealth interoperability requirements and characteristics and perhaps some initial ehealth interoperability solutions adopted,
shared understanding of data services or internal processes as well as initial governance established to ensure repetition of earlier successes. Defined:
An organization has defined a set of guidelines for the adoption of ehealth standards for data, services and processes,
Major ancillary clinical systems feed data to a clinical document repository (CDR) that provides physicians access to results.
ICT in developing countries Developing countries usually collect district level aggregate health data to plan
After they have established district level health data collection, these countries may move to more complex data systems including patient information systems,
automatic data capture and access to information. Their top level is integrated a fully national health information system,
which includes data from all public and private sources. Results showed that most of the 19 countries selected only collected district level information
presence of data standards and regulatory frameworks; mechanisms to develop the capacity of health workers;
Benefits included increase in immunization rates, improved data collection, increased staff productivity, increased visitor satisfaction with services, improved communication, quality of care, access
to data, reduced medical errors, and more efficient use of staff time. Some of the disadvantages noted were:
time-consuming data entry, slow access of data and decreased quality of patient-doctor interaction.
analysed the data and presented information on national protocols. They demonstrated that the system could efficiently
and presented clinical data that supplemented clinical decision-making. In addition, the data were aggregated and used at the national level for policymaking and analysis. In 2010,
a total of 650 000 patients were registered with 50 000 receiving care for human immunodeficiency virus (HIV. The systems were used for patient registration, HIV care, paediatric patient management, radiology, pharmaceutical and laboratory work.
and outcomes and use this to introduce changes. 2. 4 mhealth The use of mobile technologies for data collection about individuals
and interoperability. 2. 5 Interoperability of patient data The purpose of collecting and storing patient information is to make it available for decision-making at a point of care or for analysis and action for management and policy.
there must be standards for representing the data and for communication. Distributed health data networks have been proposed to improve the ability to collect
and analyse data across institutions leading to improved effectiveness, safety, and quality of care (26).
In the health field, there are several common nomenclatures that have been developed and are maintained by various organizations.
and communication technology in health care due to its potential for improving the efficiency of health care delivery and quality of care, particularly through interoperable data standards.
improved access to timely data by care providers and for access by multiple users (not geographically bound)
The first is need the to ensure that data are exchangeable. Interoperable data standards are fundamental requirements that are overlooked frequently,
with the result that many sites are unable to share data thus limiting the flow of information.
Interoperability depends on agreed standards enforced across all applications. Second attention must be paid to data quality
since this will impact the quality of decisions. Finally, health ICT systems require skilled personnel for their development and maintenance.
Most countries have developed fairly well systems for capturing aggregate health data from clinics for use in disease surveillance and health status. However,
a simplified maturity model with three methods of data collection (levels of technological implementation) was used in the survey.
and data are transferred from paper for analysis or use. Computerized data: Data are entered into a computer (often from paper) from where they can be analysed
and retrieved. Computerized data and electronic communication: This most advanced level combines the use of computerized data with the ability to electronically transmit it to multiple users in multiple locations.
Format use Survey respondents were asked to estimate the use of a format on a five point scale starting at none indicating no use to very high meaning over 75%.
%Details of the measurement scale are found below. None no use Low below 25%Medium 25 to 50%High 50 to 75%Very High above 75%These categories are sufficiently broad to offer a measure of accuracy
while providing meaningful quantitative results from which conclusions can be drawn. All countries have a broad range
Tables 1 and 2 provide summary data of the trends identified in the transition from paper to digital records.
Analysis of survey results 23 Table 1. Use of paper and electronic formats for individual patient data, by health system level and income group National Regional
Table 2. Use of paper and electronic formats for aggregate patient data, by health system level and income group National Regional/District 0%20%40
It is not only the source of patient data but also the location where the information can be put to immediate use to guide the diagnosis
Individual patient data Individual patient information is collected and tagged with a patient identifier and can later be retrieved by that identifier.
Figure 1. Individual patient data collected in local health care facilities, globally Figure 1 shows the global responses to the question about individual patient data.
high or medium adoption) with much lower levels of data collected in electronic format (45%reporting very high,
Key findings Most patient data are collected still on paper. Countries in higher income groups have higher adoption of EMR/EHR systems.
Percent of countries Data format Analysis of survey results 25 Figure 2. Individual patient data collected in local health care facilities,
of data. Figure 2 shows that high-income countries report medium to very high use of electronic information systems in over 50%in these categories for electronic communication of health data.
In contrast, only a small percentage (4%)of low-income countries report medium adoption of electronic patient information systems and communication of health data and none report higher levels
of adoption. These patterns of adoption can be explained primarily by the fact that high-income countries have the clear advantage of greater available resources
Analysis of survey results 26 Figure 3. Individual patient data collected in local health care facilities
Lower-middle income Low income None No answer Paper Electronic Electronic transmission Data formats Data format When the same data are analysed by WHO region (Figure 3),
and the Western Pacific Region show a higher adoption rate of electronic transmission of data than actual collection of patient information in electronic format.
It could also be the case that data are transferred offline using compact discs (CDS) or cassette tapes between data centres from the health care centre to the districts or central agency.
Analysis of survey results 27 Aggregate patient data The data collected from individuals can be aggregated to give counts of various diseases
In basic health information systems, data may be aggregated directly at the time and point of care using tally sheets
Figure 4. Aggregate patient data collected in local health care facilities, globally Figure 4 shows there is still a large proportion of countries worldwide using paper to record health data.
Results show that use of electronic formats for aggregate patient data is higher than for individual patient data
except at local levels where it appears many facilities are collecting and using their aggregate data on paper.
While this may be feasible for local use, paper-based reporting at higher levels of the health system is more cumbersome (labour-intensive) and prone to error.
Key findings Use of electronic formats is aggregated higher for data than individual data. There is a relationship between country income and the use of electronic formats.
High Medium Low None No answer Paper Electronic Electronic transmission Percent of countries Data format Analysis of survey results 28 Figure 5. Aggregate patient data collected in local health care facilities,
data collected in local health care facilities by WHO region It is interesting that countries of the Southeast asia
and representative data from local facilities is crucial to this work. Regional or district offices are involved often in immediate short-term operational planning for the facilities
Individual patient data Figure 7. Individual patient data collected in regional offices, globally Figure 7 shows that most responding countries reported that they continue to use paper-based methods of collecting patient information at the regional level with 38%and 26%reporting very high and high use
Percent of countries Data format Analysis of survey results 31 Figure 8. Individual patient data collected in regional offices,
mostly paper-based data recording. Low and lower-middle income countries report both very high
Analysis of survey results 32 Figure 9. Individual patient data collected in regional offices, by WHO region Approximately 70%of responding countries from the African Region reported very high use of paperbased systems followed by the Western Pacific (46%)and Eastern Mediterranean (43%)Regions (Figure 9). The pattern of using paper
%100%Very high High Medium Low None No answer Paper Electronic Electronic transmission Data format Southeast asia Region Western Pacific Region 0%20%40
Electronic transmission Data formats Data format Analysis of survey results 33 Aggregate patient data Aggregate patient data provide the core data on which regions
Aggregate patient data collected in regional offices, globally Globally, there is still a high use of paper-based systems accounting for 31%of responding countries ranking its deployment level as very high.
There is also generally low deployment of electronic patient data and electronic communication systems with these systems showing none or low deployment (approximately 37%and 48%,respectively;
Aggregate patient data collected in regional offices, by World bank income group The deployment trend of paper-based systems compared to electronic formats across all World bank income groups is clear:
which are usually set up to facilitate the collection of aggregate data. High-income countries have a more diverse system for delivering care including an active private sector where it is more difficult to collect data.
High income Upper-middle income Percent of countries 0%20%40%60%80%100%Very high High Medium Low None No answer Paper Electronic
Aggregate patient data collected in regional offices by WHO region Countries of THE WHO African, Eastern Mediterranean,
but overall noting of data is low. Thus, it appears that where data are recorded, they are being transmitted electronically roughly half the time.
Again the data show that the European Region and Region of The americas are advanced more in the transition to digital formats,
and that the African Region is likely to have the most significant challenges digitizing their records in the future.
individual patient data are most useful for operational research, planning, and policy. Longitudinal records of the history of individual patients can be useful in tracking the course of diseases and responses to treatment,
Individual patient data collected at the national level, globally Globally, the use of paper-based systems remains high for the collection of individual patient information with half of the participating countries ranking their use as either high or very high (Figure 13).
Key findings The use of paper-based systems continues to be high for individual patient data at the national level.
Individual patient data collected at the national level, by World bank income group High income Upper-middle income Percent of countries 0%20%40%60%80%100%Very high High Medium
Individual patient data collected at the national level, by WHO region THE WHO regional differences are similar to the trends seen at the health facilities and regional/district levels.
transmission Data formats Data format Analysis of survey results 39 Aggregate patient data Aggregate patient data is useful at the national level for planning, policy formulation, programme
Aggregate patient data collected at the national level, globally Figure 16 shows that one third of countries reported high to very high use of electronic records and electronic transmission of data, respectively, at the global level.
which indicates that use of electronic systems for data collection and dissemination is growing. Key findings Globally
approximately one third of responding countries collect aggregate data in electronic formats and one third transmit it electronically at the national level indicating fairly widespread adoption of electronic systems.
High-income countries have moved clearly to electronic formats with a majority reporting high to very high use of electronic data collection and transmission at the national level.
and Eastern Mediterranean Regions show a higher use of electronic communication modalities than electronic data collection.
Aggregate patient data collected at the national level, by World bank income group The trend of increased deployment of electronic systems seen globally does not appear to apply to low-income countries, however:
Aggregate patient data collected at the national level by WHO region African Region Eastern Mediterranean Region 0%20%40%60%80%100%Very high High Medium Low None No answer Paper Electronic Electronic
and other wireless devices. mhealth applications include the use of mobile devices in collecting community and clinical health data,
in order to share and aggregate data, countries utilizing such systems need to collect data using standard definitions and formats.
Messaging standards describe protocols to communicate data. Medical record standards specify the structure, content, and organization of individual patient medical records.
and environment of data. The purpose of defining metadata is to improve interoperability of data through standardization,
that is, giving the collector and receiver of information as much information as possible on the context of the data so that the receiver will attach the same meaning to the data as the original collector.
Only 5%of countries responding to the survey use the DCMI model methodology. This low uptake could represent a lack of knowledge of the standard or difficulty in implementation.
The Data Documentation Initiative (DDI) The Data Documentation Initiative8 is a metadata specification for the social sciences to promote data interoperability and integration
using Extensible Markup language (XML) to express the data. It takes a life-cycle approach to data;
from collection, analysis, publication, and management, data can be reprocessed at later stages of their life-cycle.
This creates an iterative, circular process with respect to data usage. Only 5%of responding countries report using this standard for their data.
Its low level of adoption could be that the standard is not well known or is considered not appropriate for use in the health sector.
Statistical Data and Metadata exchange (SDMX) SDMX is an initiative for standards for statistical data and metadata exchange.
The SDMX sponsoring institutions are the Bank for International Settlements, the European central bank Eurostat (the 7 http://www. dublincore. org 8 http://www. ddialliance. org 45 statistical office of the European union), the International monetary fund (IMF), the Organisation for Economic Co
because of their utility and interoperability they have found use for health data with the adoption of the Statistical Data and Metadata Exchange Health Domain9 (SDMX-HD).
These standards are useful for exchanging health data and the metadata describing health data. Nine per cent of responding countries use the SDMX standards.
Metadata standards have a much lower rate of adoption. This could be due to difficulty of implementation or perhaps due to the lack of awareness by,
Messaging standards Overall, messaging standards have been adopted widely because of their clear utility in communicating health data.
XMLBASED data exchange. 9 http://www. sdmx-hd. org 46 Thirty-four countries report using a version of CRIS;
they seek to build synergies, through data exchange, with other data management tools between sectors.
ISO TC 215 and CEN/TC 251 ISO's Technical Committee (TC) 215 on health informatics works on health information and communications technology to facilitate interoperability of health data.
data structure, data interchange, semantic content, security, pharmacy and medicines business, devices, business requirements for electronic health records,
A number of workgroups, each dealing with a specific aspect of the data have been formed under TC 251.
and device communication as well as privacy and security issues related to patient data. Fifteen per cent of the responding countries use this standard.
and retrieve clinical data across care boundaries and sites, and consists of over a million medical concepts.
and a patient care data set. LOINC is preferred the code set for HL7 laboratory test names in transactions.
category of health data for use in-country. National standards are usually based on the international standards discussed in the previous section,
and effort but has the benefits of improved information flow and better use of health data with better health outcomes as a result.
Often the guideline documents will specify the use of national data sets or identifiers in order to improve the compatibility of health data.
Fifty-eight per cent of the responding countries use guidelines documents for national health data standards. 0 10 20 30 40 50 60 Other Survey
metadata Messaging Vocabularies Indiv patient data Patient identiers Indicators Guidelines Percent of countries National standards 49 Standards for indicators used to monitor health
and health systems Most countries will have a national set of indicators which are used to monitor health status and health system performance.
Usually these have a legacy of data and usage that means that they may not fully adhere to international standards.
since there is a risk of losing compatibility with historical data. However, if the definitions in the standards are not clear,
When dealing with individual patient data it is important to identify specific information so that the patient can be referenced uniquely and reliably.
Individual patient data standards Thirty-eight per cent of responding countries have standards for individual patient data.
This can be anything from a small data set of demographic and basic clinical information to a complete longitudinal electronic medical record with full professional, laboratory, radiology and ancillary service input.
Most commonly, countries have defined some set of individual patient data that is useful for continuity of care, monitoring and evaluation,
or aggregate data for planning or research. Examples of international individual patient data standards are the Continuity of Care Record (CCR)( 33) and the Continuity of Care Document (CCD)( 34;
the latter is based on the Clinical Document Architecture (CDA) in use in the USA. The CCR was developed to facilitate transfer of the essential health record of an individual patient from one care provider to another through the use of a standard format and vocabulary.
Countries might find it useful to define their own vocabulary for a data set that is used within the country such as national health indicators, routine facility reporting,
Messages can be used to retrieve historical data as well as current data. A health message includes health data that is expressed in a standard vocabulary.
It may also include metadata about the definitions or environment of the data. The message itself is in a precisely defined format
so that it can be received by a computer program which will understand its meaning. HL7 is the most commonly used health message standard.
Survey metadata standards Surveys are a valuable method of collecting health data. They usually identify a specific topic
or collect data using standards which allows comparison with other surveys. In order to compare survey data,
it is necessary to have a standard set of metadata about the survey so that the complete context of the data,
as well as the health data set definitions, are specified. Only a relatively small percentage (19%)of responding countries have adopted standards for survey metadata.
However, it is anticipated that uptake will increase as more countries realize the value of defining standards for survey metadata (e g. reaping the benefits of having standard reference data about time and location.
3. 9 Legal framework and adoption By its nature health information is sensitive, particularly when it comes to individual health information.
it is assumed that the legal framework governing health information would apply. 3. 10 Summary of key findings Most patient data are still being collected on paper in spite of the high costs, limited usefulness,
Use of electronic formats is aggregated higher for data than individual data. This can be due to the relative difficulty of implementing electronic formats for individual patient data
which require more complex software and training. High-income countries have transitioned to the point where there is today a higher use of electronic formats than paper records for patient data.
Only a limited number of countries report widespread use of electronic formats coupled with electronic communications,
which could be indicative of adoption of interoperable systems to communicate electronic data. The increasingly widespread availability of mobile telephone communications technology is an important asset
many countries collect aggregate health data in electronic formats at the national level indicating fairly widespread adoption of electronic systems for reporting at this level.
Many countries have adopted standards for data interoperability and have national plans for implementation. Often these are based on international standards developed by international organizations such as UNAIDS,
and benchmarking of data. The survey illuminates active exploration and adoption of electronic tools for management of patient information.
The body should include a division responsible for the governance of ehealth data interoperability standards and patient data privacy and security.
It is essential that Member States adopt data interoperability standards for the recording and communication of health information.
and receiver of data have the same definition and understanding of them. Without this understanding, health data communication is not reliable.
WHO and its partners maintain a repository of indicator metadata to promote harmonization and management of indicators (37) for summary data.
Individual patient clinical data can be standardized using the standards already covered in this publication WHO further recognizes the important need for the development of patient health data privacy and security standards.
Individual patient data must be protected from unauthorized disclosure. This requires the development and adoption of national regulations governing the collection, storage,
and use of patient health data. 11 http://www. who. int/ehealth 55 The collection of individual patient information permits the establishment of a longitudinal medical record which is invaluable for improving care
Enterprise Architecture planning-developing a blueprint for data applications and technology. Hoboken, NJ, John Wiley and Sons, 1993.6.
guiding protocols and managing data in Malawi. Baobab Health unpublished observations, 2008.18. Douglas GP et al.
Distributed health data networks: a practical and preferred approach to multiinstitutional evaluations of comparative effectiveness, safety,
Data exchange with the country response information system and UN AGENCY software. A step by step guide. Geneva, UNAIDS, 2006 (http://data. unaids. org/pub/Basedocument/2007/cris de web final en. pdf, accessed 28 march 2012). 33.
Continuity of care record. Version 2. 1b. American Society for Testing and Materials/Massachusetts Medical Society/Health Information management and Systems Society, 2012.
Geneva, World health organization, 2011 (http://www. who. int/gho/indicator registry/en/,accessed 28 march 2012). 61 Bandwidth A measure of the amount of data that can be transmitted per unit of time.
Data Data refer to raw, unedited observations. Glossary 62 Data dictionary A specialized type of database containing metadata,
which is managed by a data dictionary system. This centralized repository of information describes the characteristics of data used to design, monitor,
document, protect, and control data in information systems and databases; it can also refer to an application of data dictionary systems.
Data management A set of procedures to collect, store, analyse, and distribute data. Once data are collected,
a sound management approach is essential. Firstly, a metadata dictionary is necessary to accurately describe the data elements.
Next, effective data storage procedures require a well-designed logical structure to permit data retrieval and analysis. Data analysis and presentation include calculating indicators
and preparing tables and graphs. Finally, the data should be made available to all those who can use
and act upon them. ehealth ehealth refers to the use of information and communications technology for health.
GNI Gross National income is the total value of all that is produced within a country plus the net income from trade with other countries.
Health information system A health information system includes the people, processes and technology to collect, communicate, manage, analyse,
and present information for decision-making. It represents sources of population based data like census, vital events registration, surveys,
as well as facility based data like individual health records, health service records, and resource management records.
A health information system may be referred to as a health management information system or health management information system and is also likely to comprise any number of subsystems.
Information Information is data which has been processed and organized into a meaningful output which can be used for decision-making or understanding concepts.
software, data-capture devices, wireless communication devices, and local and wide area networks that move information, and the people that are required to design, implement,
and support these systems. 63 Interoperability The ability of health information systems to exchange data in a semantically meaningful way,
which describes data. Metadata is used to describe the definition, structure, and administration of data whereby the communication and use of those data are improved. 65 Purpose The World health organization's ehealth resolution WHA 58.28 was adopted in 2005 and focused on strengthening health systems in countries through the use of ehealth (1);
building public-private partnerships in ICT development and deployment for health; supporting capacity building for the application of ehealth in Member States;
The aim was to provide governments with data that could be used as benchmarks for their own development as well as a way to compare their own progress with that of other Member States.
The thematic design of the survey has provided the GOE with a rich source of data that is being used to create a series of eight publications The Global Observatory for ehealth Series due for publication during 2010 and 2011.
as well as processing the data and analysing the results. Survey instrument The instrument focused on issues relating to processes and outcomes in key ehealth areas.
Legal and ethical frameworks for ehealth Review the trends in the introduction of legislation to protect personally identifiable data
and health-related data in digital format as well as the right to access and control one's own record.
and effectiveness of elearning for the health sciences for students and health professionals. ehealth country profiles Presentation of all participating Member States ehealth data aggregated by country to act as ready reference of the state
One of the constraints identified in the first survey was on the management of data
and its availability for compilation and analysis. In order to facilitate data collection and management, Data Collector (Datacol) 12 was used to make the survey instrument available online
and therefore streamlining the collection and processing of data. A set of questions was developed and circulated in the first quarter of 2009 for comments to selected partners in all regions through virtual teleconferences.
The range of partners included those from government, WHO regional and country offices collaborating centres and professional associations.
instructions and data entry procedures were translated into all WHO official languages plus Portuguese. Data Collector Data Collector, Datacol, is based a web tool that simplifies online form creation for data collection
and management and is designed, developed and supported by WHO. The collected data are stored in a SQL database maintained by WHO database administrators,
and can be exported as a Microsoft excel file for further analysis using other statistical software. This is the first time that Datacol has been used as the primary method of implementing an online survey of over 40 pages of text and questions.
Significant preparation and testing was required to ensure that the system was robust and able to accommodate the data entry process from around the world,
as well as the volume of data entered and stored online. The various language versions of the survey instrument and supporting documentation were entered into Datacol by language.
Data were exported from Datacol in Microsoft excel format and the data analysis was performed using R statistical programming language. 14 Data were analysed by thematic section.
For closed-ended questions percentages were computed for each possible response to obtain the global level results.
In addition, the data were aggregated and analysed by WHO region and World bank income group to see trends by region and by income level.
or act on GOE data. World bank income group Clear economic definition based on GNI per capita. Consistent application of criteria across all countries.
Responding Member States Reponding Member State Data not available Not applicable Responding WHO Member States The boundaries
Data Source: World health organization Map Production: Public health Information and Geographic Information systems (GIS) World health organization 73 Response rate by WHO region Administratively WHO is made up of six geographical regions,
http://data. worldbank. org/about/country-classifications. World bank income group High income Upper-middle income Lower-middle income Low income Total no. countries 49 44 53 43 No. of responding countries
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