Managing health data Up to 50%of European adults search online for health information. The need for
as well as to personal health data, is essential. The same is true on the research side
where access to wide sets of health data for scientific purposes is vital for making
Access to healthcare data helps researchers to produce more accurate, faster tests on medicines to be launched on the market.
develop new ways of using existing clinical and biomedical data sources to detect EU-ADR
of epilepsy-relevant multi-parametric data. The specificity of each patient and the need for constant adjustment of the treatments will be addressed through a
data capture system to provide the patients with daily valuable Euheart Euheart uses clinical data from various sources,
such as medical imaging, measurements of blood flow, blood pressure and electrocardiography. Computer models integrate heart behaviour and the aorta at molecular, cellular, tissue and organ level.
healthcare professionals with the necessary electronic patient data. The result is a service infrastructure enabling the exchange of patient data †Patient Summaries and eprescriptions
†across borders. 23 different European countries participate in this Large scale Pilot http://www. epsos. eu Funded by the ICT Policy Support Programme (ICT PSP) â€
Concrete goals include the registration of data with governments only once, the EU-wide use of national electronic identities (eid), the
access public egovernment services in other Member States, in full respect of data protection and privacy rules
Connecting existing systems will allow communication and data exchanges based on the development of common technical standards in the field of
•Syndication of data and edirectories •A Secure delivery and data tracking exchanges http://www. eu-spocs. eu
Funded by the ICT Policy Support Programme (ICT PSP -Competitiveness & Innovation Programme (CIP Duration:
Effective transmission of individual data between national authorities must therefore be a priority. The European Civil Registry Network project
more intelligent services by using and combining data integrated seamlessly through the Cloud The Open-DAI project (2012-2014) will test the efficiency and added value of
data collected by public authorities and agencies. It will allow them to model and deploy services,
to a wide range of evolving threats (lack of privacy, loss of data, malfunctioning of the network due to a cyberattack.
Internet of things are bound to bring more pervasive data collection, longer persistence of collected data, higher and more heterogeneous
traffic volume. All these factors make network management an evolving environment that becomes more challenging every day
and exporting data across operator domains and multiple jurisdictions. These issues have prevented previously other security solutions from being deployed widely and
electrical counters that record consumption, generate data, give advice and work bi-directionally), near-zero energy buildings and more energy-efficient transport
The real time data gathered is then centralised and used to generate an action plan for
data they need to optimise their energy-related policy and investment decisions at national, regional and organisational level
In the era of information and data deluge, data centres play an increasingly critical role in every aspect of our socioeconomic activity.
dissemination of data in which the mechanical, lighting, electrical and computer systems are designed for maximum energy efficiency and minimum environmental
unconscious and transmits a set of data, including the exact location of the crash site
technologies (hardware and software) that allow for electronic communication, data collection and processing in distributed networks (e g.
speeds up data retrieval, processing and steering, and reorganizes value chains and their spatial pattern
but these are linked not with data on transport behavior; also, disaggregate data at the level of
regions or cities is often not available. This situation may be explained by a lack of awareness
among statisticians of the urgency to provide such data. Concerning households, the lack of statistics means a need for a smart mix of large-scale surveys,
No available data, but seems effective No available data; seems effective in time but maybe longer journeys
Congestion relief Video Surveillance and Response (fixed)( public private Variable Message Signs (VMS fixed)( public, private
No available data, but seems effective Overall travel time reduction by 1-2%in regular congested areas
No available data Reduces variation in acceleration by 40-50 %EU Reduces fuel use of 8
No available data, but seems effective Fatality reduction Accident Sensors (in-vehicle private Extended Viewing Systems
No data available, but seems effective No data available, but seems effective Substantial decrease of
speed, but compensation US Reduce fatality and heavy injury up to 30-38 %dependent on road type
More recent data are available for the EU 15 where there were 35,905 fatalities in 2003 (ERF, 2005.
as electronic transfer of medical data between professionals, e-prescriptions and lab tests electronically communicated to patients.
Anecdotal and real data demonstrate excessive costs for overtime, medical card payments and drugs compared with European averages.
patient data delivery to the point of care. Collectively, this is often referred to as the 5 Rights of Medication:
by moving patient data instantly to where it is needed, and using electronic systems to order & view lab, radiology and other tests at high speed
not share) medical data, and also by moving the doctor-patient relationship towards a model of †shared care†through the use of disease management systems.
Electronic Health Records aggregate patient-centric health data from the patient record systems of multiple independent healthcare organisations.
Many EHRS include detailed clinical data such as individual lab results and prescription refill information EHRS are used commonly to transfer a patient†s healthcare information between
less time and effort spent capturing patient data when crossing organisational boundaries. Additionally, ensuring the interoperability of these systems,
data to be transmitted electronically between the prescribing health professional and the pharmacy, making prescribing and dispensing safer and more convenient for patients
dependents) through education and monitoring as well as enable the exchange of data with others regarding their health.
Through the collection, storage, analysis and interpretation of data, Business intelligence systems can generate valuable actionable knowledge for tactical and strategic decision
used to analyse vast amount of data in real time and to help distinguish patterns that could indicate abnormal situations that would require further attention or action from
administration, provision of access to evidence-based clinical data for clinicians and identification of opportunities for clinical, operational, financial and regulatory
York Hospitals NHS Foundation Trust have converged a voice and data network with almost 4000 phones and over 2000 PCS.
The public health portal, Sundhed. dk now integrates health-related data from disparate healthcare systems throughout Denmark.
health records, view data from the National Patient Register and communicate with other healthcare providers.
For patients, the portal offers access to health-related data e-consultations and the ability to communicate with healthcare providers
and the utilisation of this real-time electronic data to reduce claims unpaid. A solution was developed which addressed all of the issues detailed above which also seamlessly
Reducing Hospital Acquired Infections (HAI) through Business intelligence and Data -Mining for Real time Detection of Infections
4wto/UNCTAD relative unit-value data is available at: http://www. intracen. org/country/italy
Micro data on Italian firms confirms that this indeed has been a large part of the Italian story†where the manufacturing
analysis (ANOVA) of bilateral export data, disaggregated by product. The methodology is based on Cheptea and others (2005),
each year in the data. Hence, if Î is the intercept, Ï is the regression coefficient for exporter
Data The analysis draws from the BACI product-level database developed from COMTRADE data by Gaulier & Zingano (2010),
which provides reconciled USD flow figures on more than 200 countries over roughly 5000 products of the Harmonized System (HS
the regressions, 6-digit product data are aggregated down to the 2-digit level Caveats Given the structure of the HS classification,
data 21 References Aghion, P, . and P. Howitt, 2009, â€oethe Economics of Growth, †(MIT Press
integrity of the data chain and techniques that help service providers to assess the reliability of information and data contributed by patients.
This paper sketches various lines of research for the development of trusted healthcare ser -vices namely, patient compliance, reliability of information in healthcare, and
reliability, integrity of the data chain, as well as techniques that help physicians to assess the reliability of information
and data contributed by patients. There is a need for an integrated and easy to understand approach to trust in terms of security, priva
service provider in terms of privacy of the data chain and physicians†trust in the reli -ability of information and data contributed by patients.
In particular, a number of questions should be addressed ï How can compliance with a treatment be measured reliably
ï Can a physician trust data measured by a patient at home ï How can patients use home healthcare services
-tient†s physiological and other contextual data can be collected and transmitted to remote care providers for review or intervention.
-cose meter) a medical hub device that collects the data from measurement devices and sends them to a backend service.
also considered as part of this eco system (the measurement data is sent from the med -ical hub to a PHR system,
health data, thereby endangering people's privacy 3 Trusted Healthcare Services Electronic healthcare services offer important economic and social benefits for our
healthcare providers need to trust the patient data they obtain remotely from the measurement devices deployed in patient†s home.
patients and gather data that is interpreted by medical professionals. Health and well -ness services support people in need in many ways on the basis of personal and health
-viders in terms of privacy, reliability, integrity of the data. Standard Internet security techniques provide authentication and encryption of the communication with a service
ï A technical protocol to reliably assess the quality of medical data (e g.,, blood pres
data to support clinical research and knowledge creation for clinical decision sup -port systems In the remainder of this paper, we will focus on trust management for home
ï Can a physician trust data measured by a patient at home? Home healthcare pa -tients measure physiological parameters at home,
and a physician uses this data to make treatment and diagnosis decisions. It is very important that the measurements
Next to ensuring proper patient/device authentication, data authenticity and integrity, it is important to capture the correctness of the authentication process too
18,22 mainly focus on the reliability of the data maintained in the form of electronic and personal health records
to data coming from the Internet. We believe that a reputation-based solution can ensure the reliability of home healthcare data needed by physicians.
To this end, it is necessary to investigate the issue of data trustworthiness from both healthcare provid
-ers and patients†perspectives and elicit the requirements for reputation systems to be 3 http://www. revolutionhealth. com
on data reliability should be easily accessible and understandable. Therefore, methods for assessing data reliability should be coupled with methods
and tools that visualize indicators for data reliability in a way that is understandable by end-users 4. 3 User friendly advanced access control
Healthcare services deal with very personal and sensitive information. The protection of sensitive information is enforced usually using access control.
Furthermore, medical data can also be formed as arbitrary text such as a patient report made by healthcare practitioners, leading to the need for poli
groups on their data (e g.,, wall posts, photos. Although these proposals provide a simple and straightforward solution, they neither allow users to understand the effect
-posure of user data to the network. Pearson et al. 35 propose a client privacy man
-agement scheme based on data obfuscation (not necessarily using encryption) and user â€oepersonasâ€. Although these proposals increase usability and flexibility, they do
their data but also support them in â€oevisualizing†the effect of the defined access con -trol policy and therefore in ensuring that the created policy reflects user†s intentions
and the data objects in which such infor -mation is stored. The aim of this semantic alignment is to support the automatic gen
-sion therapy using retrospective data. Hypertension 47 (6)( 2006) 1039†1048 6. Leslie, S.,Gwadry-Sridhar, F.,Thiebaud, P.,Patel, B.:
Event-driven data integration for personal health monitoring. Journal of Emerging Technologies in Web Intelligence 1 (2)( 2009) 110â€
did you process the data for the in -tended purpose? In: Proceedings of the 8th VLDB Workshop on Secure Data Management
LNCS 6933, Springer (2011) 145†168 18. van Deursen, T.,Koster, P.,Petkoviä, M.:Hedaquin:
A Reputation-based Health Data Quality Indicator. In: Proceedings of the 3rd International Workshop on Security and Trust Manage
A medical data reliability assessment model. J. Theor Appl. Electron. Commer. Res. 4 (2)( 2009) 64†78
The challenge of assuring data trustworthiness. In Proceedings of the 14th International Conference on Database Systems for Advanced Appli
Moreover, these studies focused on a particular year for data collection and are therefore, cross-sectional in nature.
sales, and data on economic variables such as employment, investment, sales turnover etc. The validity and reliability of the questionnaire was ensured and based on the
approached about 150 to 200 SMES in each of the sectors and gathered primary data from
data were gathered for a period of five years from 2001/2 to 2005/6. Data collection was
done during January†December 2007. While the first objective was analysed descriptively making use of frequency tables for innovative SMES, the second objective
We have gathered data on sales at current prices as well as on employment and the current value of investment (in plant and machinery) from the SMES of auto, electronics
years†data on sales comparable by converting the values of current prices into values at
the latest series of data on SSI production, which are given at current prices as well as at
5. 4. Improving comparability of data on ICT in health: What options?..122 References...124
Box 5. 4. Improving comparability of data on ICT in health: working towards an OECD â€oemodel surveyâ€?..
Table 5. 3. Overview of main data collections reported by countries...118 ABBREVIATIONS †9
EDI Electronic data interchange EFT Electronic funds transfer ehi e-Health Initiative EHR Electronic health record
NEHEN New england Healthcare Electronic Data Interchange Network NEHTA National e-Health Transition Authority NGO Non-governmental organisation
and exchange of health data are likely to foster better care co-ordination, and the more efficient use of resources
Data from 22 sites in British columbia show that report 14 †EXECUTIVE SUMMARY IMPROVING HEALTH SECTOR EFFICIENCY:
the New england Healthcare Electronic Data Interchange Network NEHEN), a consortium of providers and payers established in 1997
the two major technologies used in electronic payment, electronic data interchange (EDI) and electronic funds transfer (EFT),
Electronic data collection and processing can provide data in an accessible form that facilitates reporting on different quality metrics, benchmarking and
16 †EXECUTIVE SUMMARY IMPROVING HEALTH SECTOR EFFICIENCY: THE ROLE OF INFORMATION AND COMMUNICATION TECHNOLOGIES  OECD 2010
subset of data necessary for quality reporting and expanded the measurement of outcomes at GP practice level
electronic data collection and reporting on quality improvement activities There is a growing body of practical experience across OECD countries that
consistently if it is to permit effective secondary analysis of health data Electronic capture of data through EHRS can facilitate clinical research, as
well as improve evidence-based care delivery The development of standards to enable interoperability continues to be
patient data among different providers in a network raises the question of who should be allowed access to the file
case study countries require that patients be informed at the time of data collection of all the purposes for which their data may be used.
Others operate on the basis of an implied consent model for disclosure of health information for treatment purposes, coupled with the individual's right to
In Canada, well-intentioned privacy laws have created barriers to data access. In British columbia, an unintended consequence of this commitment
government cannot access critical health data and carry out the necessary associative studies to improve services for citizens
These methodological difficulties are exacerbated further by data limitations, definitional problems and the lack of appropriate sets of indicators
there is little or no available data which would allow measurement. Despite a plethora of anecdotal information
Failure to collect the data necessary to evaluate the impact of ICTS is one of the core challenges to achieving widespread adoption of
data from the patient†s primary care record can facilitate greater efficiency and safety as well as contribute to future research
1. Data refer to 2006 2. Data refer to 2005 Source: OECD Health Data 2009, June 2009
26 †INTRODUCTION IMPROVING HEALTH SECTOR EFFICIENCY: THE ROLE OF INFORMATION AND COMMUNICATION TECHNOLOGIES  OECD 2010
From 1990 through 2009, an increasing share of the gross domestic product (GDP) of OECD countries has been devoted to the provision of
data have remained unacceptably high despite the many calls for reforms. In 2007, an OECD survey reported that medical records of individual patients
exchange of health data are likely to foster better care, and the more efficient use of resources.
OECD (2009), OECD Health Data 2009 †Statistics and Indicators for 30 countries, online and on CD-ROM, OECD Publishing, Paris. See
compared with baseline data, the proportion of people with diabetes who had Hba1c, blood pressure and lipid tests complying with guidelines from
PACS also benefits radiologists who also have improved access to patient data and no longer have to forward information to other health care facilities
system, was conducted on data extracted for 22 sites in British columbia. The analysis showed that report turnaround time decreased following the implementation of PACS by 41%(mean
They related this gain to easier access to patient data, faster communication, and the availability of higher quality and more complete data
Similarly, pharmacists in Sweden reported that processing prescriptions had become quicker and easier through the use of e-prescriptions and that they
return to their practices to consult patient data or clinical notes. These time gains may lead to improved quality of life, decision making, and higher quality
processing through the New england Healthcare Electronic Data Interchange Network (NEHEN), a consortium of providers and payers
the two major technologies used in electronic payment, electronic data interchange (EDI) and electronic funds transfer (EFT),
Although data was limited, in Western australia, physicians reported faster communication, fewer telephone calls, and savings in mail handling, stamps, and paper
records to make critical patient data available not only at the point of care, but to all essential
Case studies show that automated data collection and processing can provide richer data in an accessible form that facilitates benchmarking and
identification of quality improvement opportunities. It can also enhance CHAPTER 1. GENERATING VALUE FROM HEALTH ICTS †45
other data sources necessary to expand measurement of outcomes. The MAEHC€ s effort to extract health care quality data from the community
level database, which is an agreed upon subset of data stored in physicians†EHRS, offers an opportunity to engage providers effectively and increase
alignment between incentives programmes (Box 1. 6 Health authorities and payers can now have a more timely view of how
Only good quality data can enable valid conclusions to be drawn, which in turn enable changes to be made for the better.
and collection and analysis of quality of care data have traditionally followed divergent paths. Although more and more patient data are held on computer
systems, traditionally, quality data is collected and analysed retrospectively on the basis of insurance claims. Structured electronic data sources can,
however, provide useful, and in principle, more accurate and granular complementary information. Improving quality of care
measurement has been a key goal of the Massachusetts e-Health Collaborative (MAEHC since its inception.
Most of the data today is sent directly to a central quality data warehouse, from HIES via EHRS deployed in physician†s practices, together with data from their billing system
The shorter-term end product has been the production and distribution of EHR clinical performance feedback reports to participating providers,
health care quality data directly from HIES has opened a live window on the performance of the local health system and provided a shorter feedback loop for clinicians who can adjust
as service delivery data can now be captured in real-time 46 †CHAPTER 1. GENERATING VALUE FROM HEALTH ICTS
clinical and demographic data, viewing and managing results of laboratory tests and imaging managing order entry (including electronic prescriptions),
Health information and data: five functions Basic system Fully functional system Patient demographics x X
e-mail, working with data from new sources, and facilitating 58 †CHAPTER 2. WHAT PREVENTS COUNTRIES FROM IMPROVING EFFICIENCY THROUGH ICTS
Improved efficiency, better access to medical information and faster chronic patient data charting and health trend analysis all act as drivers of physician interest
exchange data with and use data from other systems. Simply converting data from a paper format to a digital format is not enough to ensure
interoperability. Interoperability depends primarily on all the computer systems that need to exchange information being able to communicate.
patient data (Chaudhry, 2005 At present, both health care delivery and the ICT that supports it are fragmented.
and this now makes it difficult to achieve adequate electronic data exchange among different patient management and/or other clinical data systems
and quality of data that can be conveyed. While users have complained long about the situation,
a greater or lesser extent to enable smooth data transfer into the planned national database
) This provides a functional taxonomy based on three factors in data exchange: the amount of human involvement, the sophistication of the ICT, and the adoption
interoperability or below, the data can be used by humans, but for the most part cannot be used by machines to provide automated decision support, active guidance, or pattern
1 Non-electronic data †no use of ICT to share information. The most commonly used manual process for sharing
abstract data from paper sources Examples: postal mail, phone 2 Machine transportable data †transmission of nonstandard information via basic ICT;
information within the document cannot be manipulated electronically. Clinicians can access the information, but no computerised
3 Machine-organisable data †transmission of structured messages containing non-standardised data; requires multiple interfaces that can translate incoming data from the each of the sending organisation†s vocabulary to
the receiving organisation†s vocabulary; usually results in imperfect translations because the vocabularies used have incompatible levels of detail.
Data content is indexed down to single fields, however human translation is required to convert actual data in each field from the vocabulary of the sending organisation to that of the
receiving organisation Examples: secure e-mail of free text, or PC-based exchange of files in incompatible/proprietary file formats
4 Machine-interpretable data †transmission of structured messages containing standardised and coded data; the
ideal situation in which all systems exchange information using the same formats and vocabularies. All systems
exchange data using the same messaging, format, and content standards, removing the need for multiple
Sharing sensitive patient data in a large and heterogeneous environment through the use of web-based
Data used to calculate clinical quality indicators are extracted from the individual GP clinical IT systems
Electronic data availability & exchange Electronic diagnosis & treatment 2003-04 2004-05 2005-06
sessions, training and support (e g. by providing help with data entry. The â€oebasket†of incentives, described below,
and the ability to submit data on 2. These programmes provide health coverage for eligible individuals and families
and robust data have been obtained. This conundrum is addressed later in the report Box 3. 3. Delayed benefit realisation
their data to be shared in ways that clinicians and payers find valuable. The business model also depends on incentives that adequately reward physicians
for their participation in quality improvement activities which require data collection and reporting. Payers and purchasers willingness to differentially
leaders, and 3) participation in other relevant activities, such as clinical data exchange (e g. Medsinfo) or Computerised Physician Order Entry (CPOE â€
Medical data repositories Accurate patient medical data Very favourable Other stakeholder co-operation Source: Adapted from Deloitte Center for Health Solutions (2006
94 †CHAPTER 3. ALIGNING INCENTIVES WITH HEALTH SYSTEM PRIORITIES IMPROVING HEALTH SECTOR EFFICIENCY: THE ROLE OF INFORMATION AND COMMUNICATION TECHNOLOGIES  OECD 2010
simplest clinical data exchange (Box 4. 1)( Goroll et al. 2009 In Canada, the focus has similarly been on developing common
From its inception MAEHC has had in place a Data Exchange Standards Workgroup The goal of the Workgroup was to establish interoperability standards that systems must
meet that will allow for adequate data exchange to achieve the goals of clinical data sharing and access,
EHR product suitability, quality, interoperability, and data portability can often be very difficult to judge,
•Developing solutions to move patient data from one physician office system to another •Reducing the risk of data loss in physician offices caused by human, hardware or
software failure •Working with stakeholders to update the Vendor Conformance and Usability Requirements (VCUR) for physician's offices.
and access to patient health data, and on patient consent. Interpretation of privacy and security requirements are still often
sharing data becomes more difficult because stakeholders may have differing views of what can be shared and with whom.
In Canada, well-intentioned privacy laws have created barriers to data access. In British columbia, an unintended consequence of this commitment
government cannot access critical health data and carry out the necessary associative studies to improve services for citizens
To overcome some of the obstacles to the secondary use of data, in May 2006 the B c. Government passed Bill 29
the opt-in approach to consent, patients declare what data they are willing to share.
option at the point of care to prohibit a clinician from looking up data. Both
that wanted to share patient data, rather than on the patients themselves since no data could be shared without written permission from the patient
From the MAEHC perspective, the consent form would educate individuals about how health information is exchanged,
clinical data to be copied or â€oeuploaded†to the HIE community database. As such, patient recruitment became a preeminent concern for the HIE enterprise,
how to improve the availability and comparability of data on health ICTS at OECD level
the efficiency of health care systems, there is little or no available data that could allow any quantitative estimation.
collected shows that the currently available national and international data on health ICTS is often not comparable for a whole range of statistical
patient data. Consequently, policy makers, developers and managers have thus far been concerned primarily with addressing the many challenges
1. OECD Health Data 2009; 2. 2007; 3. 2008; 4. 2006; 5. Source: HHS, FY 2010
OECD Population Data, 2007; 11. Through March 2010, exchange rate CAD 1. 10; 12. NAO, through December 2015, exchange rate GBP 0. 61
•Secondary use of data for monitoring public health 5. 2. Countries have adopted a range of different approaches to
and at EU level shows that the major types of data collections are •Stand-alone surveys of health care providers (businesses or
•Use of administrative data 7. An example of how this model can be applied to health ICT is Finland, where the
sector, most OECD countries have not yet set out to collect national data on health ICT adoption on any systematic basis. In addition, most surveys are
the OECD study also use routine administrative data to monitor ICT adoption. This approach may represent a low cost alternative way for
The downside is compiled that data from such sources are constrained by the fact that in most cases administrative data collection
has been designed for other purposes than monitoring ICT use and impact Activity by OECD countries national statistics offices to monitor
The main drawback is that the data is generally not comparable with other data sets that might be available for the
same country or across countries for statistical reasons, including the use of different sampling techniques, definitions and the scope of the surveys.
different data sources in terms of: a) relevance, i e. how well the data reflects the information priorities of policy makers;
b) feasibility, i e. how easily data can be gathered (cost and time; c) prevalence, i e. whether the
type of data collection is used frequently or not; d) extent of comparability Table 5. 3. Overview of main data collections reported by countries
Data collections Relevance Feasibility Prevalence Comparability National statistics surveys of ICT use Low Low Low High
Use of administrative data Medium High low Low Surveys of the population Medium Low Low Low
Stand-alone surveys of health care providers businesses or personnel High Medium High low Source: OECD The OECD study also reviewed how countries define ICTS in their
surveys. With the exception of the term â€oeelectronic health record†and â€oeelectronic medical recordâ€, there was very little or no overlap in the lists
data, within and across countries, or to link survey data to other data sources Nonetheless, it is possible to identify a core set of indicators widely
used in these surveys. These indicators were assessed against a set of criteria listed in Box 5. 2 and assigned to three broad priority groups of
relevant data to address the adoption and use gap. A number of surveys have adopted a â€oepurpose of use†approach in their questions on the use of EMRS
demographic data, viewing and managing results of laboratory tests and imaging, managing order entry (including electronic prescriptions),
data transfer across settings. The efficient application of e-health solutions is predicated on the seamless sharing of patient information across the health
5. 4. Improving comparability of data on ICT in health: What options Evidence-based policy analysis for health ICTS appears still a distant
ideal, and the necessary data cannot be gathered from existing national statistics or data collections There is clearly much work to be done to gather relevant information for
a) improving the quality of existing data and indicators; b) improving the linkages between policy and indicators;
c) developing indicators for unmet information needs. However, in addition to producing better data, it is important to improve the comparability of data and consequently the
methodologies used to collect and analyse this data. Data should be more easily accessible to the relevant users †not only policy makers, but also health care
providers, and analysts and researchers, who serve as important intermediaries in processing the information for evaluation and policy analysis
The creation, initial testing and subsequent use of an indicator entail high fixed costs (initial tests, survey design and implementation), and these
are hard for a small group of initiators to bear. This means that OECD countries have a lot to gain from pooling their efforts and sharing the
international guidelines to improve the availability and comparability of data on health ICTS. In the model survey approach an agreed set of indicators
Box 5. 4. Improving comparability of data on ICT in health working towards an OECD â€oemodel surveyâ€
way to improve the availability and comparability of data for a core set of indicators on
efforts to improve the comparability of health ICT data internationally. These features are reviewed below
OECD (2009), OECD Health Data 2009 †Statistics and Indicators for 30 countries, online and on CD-ROM, OECD Publishing, Paris. See
•Improved patient data capture •Improved medication reconciliation A wide variety of benefits and impacts of electronic messaging have
professionals, which related this effect to easier access to patient data (they were able to access information about their patients that was previously
unavailable, at least routinely), faster communication, higher quality of data and more complete information. GSMHN allowed health providers to
managed for over three decades population health data in Western australia on behalf of the Department of health. It was acknowledged that the
training and support (e g. by providing help with data entry reimbursement for complex care e-mail/telephone follow-up, direct payments to spur use of the
of data within and across health authorities while maintaining their autonomy is an ongoing concern †along with a need to deal more
physicians was that sharing identifiable patient data among different providers raised the questions of who should be allowed access to the file
implementation of electronic health records (EHRS) and clinical data exchange capabilities in three Massachusetts communities.
as needed electronic exchange of their clinical data between clinical sites (however, no permission is sought to have stored data in the practice's EHR;
and the benefits of HIE participation were touted to encourage patient participation rather than making security
•Built a novel health care quality data infrastructure to collect organise, and analyse, health care system performance
and data for neurologists at Son Dureta to â€oevirtually†examine stroke patients Results on outcomes show that efficacy
patient data, pictures, medical applications and services for which the Internet is not acceptable. Subsequently, in 2001 when the first large scale e-prescription implementation
data items in their medical record by withholding authorisation or by requesting the masking or concealing of specific information at the local level
and, 3) participate in data collection and reporting In addition, until 2008, physicians could also receive an additional 25 cent
Under this system, clinical data will be maintained locally, i e. in the databases of the health care provider or regional databases and will be
data from local databases. The LSP cannot store patient histories, and doctors†systems will not be able to store records retrieved by LSP.
retrieve data, LSP keeps an index of specific patient information kept by each healthcare practitioner.
specifically on surveys or data collections that are considered useful from a policy perspective and the most common indicators used today
Given the dearth of data, the workshop concluded that implementation of case studies would be the most promising approach
Improving comparability of data on ICT in health: What options References Annex A. Country case studies
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