Annex II: Lessons Learned from e-Health Implementation: Knowledge
The following examples of strategies and implementation of e-Health services and devices were cordially provided by members of ITU-D Study Group 2 Question 14-3/2.
2.1 Czech Republic: 1. Interoperability in Integrated Biomedical Systems
0Our work on biomedical research projects has led us to the conclusion that successful integration of partial solutions is strongly dependent on the issue of interoperability of medical devices and information systems. It comprises problems of standardization of data acquisition, communication, processing, and storage; and connected problem: correct data mapping between different ICT applications. The key issue is the ability to understand the semantic content of the exchanged information.
With development of more advanced sensors, body area networks and ICT the focus will be on the integration in larger systems collecting and processing large volumes of data, evaluating more complex situations and scenarios, precise identification of potentially dangerous situations and finding solutions (e.g. alarms in case of health or life threatening events, access blocking in case of security attack). Key issue is in information reporting and visualization (as widely used in Business reporting). Although many issues have been successfully solved and introduced either in applied research or in development of prototypes or final products there are still many problems on the waiting list. There is a possibility to use an integration platform; however the systems should be able to communicate directly using world-wide recognized standards without third party.
2.1.1 Technological Trends
If we want to develop flexible e-Health, assistive technology (AT) or ambient assisted living (AAL) systems we have to define standard interface that allows “plug-and-play” type of connection. Especially AT and AAL systems are composed of different hardware and software modules that must communicate. The basic condition is that the receiver understands correctly the content of the message. Thus it is not sufficient to be able to receive the message, i.e. to understand the syntax of the message, but it is necessary to understand the semantics. This requirement implies development of data model that maps semantic content from the data received from the devices into an information system that is usually used for collecting and evaluating data from monitored persons. Also there must be guaranteed latency of the information transition and a possibility to verify the source of the message (for example by PKI infrastructure) and to clearly determine the time order of messages. We propose a system architecture allowing above mentioned interoperability. Interoperability may significantly influence effectiveness both of design and development of an integrated system and of its routine operation.
Integrating information deriving from different sources and implementing it with knowledge discovery techniques allows medical and social actions to be appropriately performed with reliable information, in order to improve quality of life of patients and care-givers.
Currently the mobile technologies, sensors and other devices enable collecting vast amount of data of individuals. This multi-parametric data may include physiological measurements, genetic data, medical images, laboratory examinations, and other measurements related to a person's activity, lifestyle and surrounding environment. There will be increased demand on processing and interpreting such data for accurate alerting and signalling of risks and for supporting healthcare professionals in their decision making, informing family members, and the person himself/herself.
Recent development in ICT   shows that it is almost impossible to design and implement a complex system as fixed to certain hardware, operating system, and infrastructure. A possible solution is to create a tiered integration platform. However it is usually ineffective and expensive (to create and maintain). Thus it is necessary to develop such architectures that will be easily extensible and modifiable. For easy extensibility the basic requirement is to understand data exchanged between individual parts of the system.
Based on the facts mentioned above we have tried to define requirements and subsequently system architecture that would satisfy these requirements. The proposed architecture  covers the whole chain from data acquisition/measurement over data collection, identification, transformation up to evaluation and storage in an EHR system (see Figure 19). From the description it follows that there must be interfaces between individual modules. To allow the “plug-and-play” approach the interfaces must be.
Figure 19: Proposed architecture of the chain from medical devices to EHR and HIS
Based on well-defined standards, we have in mind especially following categories: ISO units for measurement of physical quantities, ISO IEEE standards in communication, standard file formats in software area, HL7 standards on the side of information systems and guarantee data accessibility even after long time when there would be data for long-term clinical studies. Another inseparable part of the architecture is constituted by data models. The models will ensure correct exchange of data between devices and information systems. This part represents a great challenge and at the same time the greatest space for future solutions because the correct mapping of acquired data onto a data model that describes electronic health/patient record is not satisfactorily solved yet. A crucial part is to select proper backend solution (such as information systems, databases, platform, etc.). The architecture must also keep pace with the versioning of the information models. Each batch of data must reference the version of information model that was active at the moment the data was acquired and the model must be available together with the archived data.
The proposed architecture is not necessarily centralized. It can be composed of highly distributed units utilizing, for example, multi-agent platforms as software infrastructure . For example, it can be used for more efficient data handling. For data storage there can be smaller local storages and a central data storage used for different types of data. Also replicated and/or distributed storage can be used. Since there can be collected health state data and daily activities patterns the large volumes of data can be stored locally and based on the data analysis during system development the professionals (e.g. medical doctors) can define, which type of data should be sent to a central data storage maintaining electronic health care records.
2.1.3 Current State in Czech Republic
The state of interoperability in biomedical systems is strongly influenced by legislation. Currently the law on sensitive information has been introduced with no regard to current e-Health and EHR development in EU and from many aspects it blocks the e-solutions even in government projects. Regarding the Health Records, there is regulation that covers health documentation in paper form only. No legislation exists regarding the EHR. There has been a pilot EHR project (called IZIP), however the funding has been suspended and the project represents only a health-book merely. The IZIP project did not use any interoperable standard and the application data interface is not available, so no third party can take advantage of it. Moreover, no developers of hospital information systems (HIS) are forced to use any interoperable standards.
Although the meetings regarding e-Health are taking place, usually no consensus is reached as there is a lack of communication and the conversation usually gets stuck at unimportant details. The government representatives do not act as active intermediates between IT and medical experts. Also there is not sufficient participation from the standardizing organizations. The e-Health is not presented to the medical experts and public in understandable form. They see more an bureaucratic burden then any advantage. From our experience in working with medical doctors, there is usually no use of explaining highly-sophisticated technical issues. It is better to present a GUI of an application, schematic diagrams and demos.
There exist many opinions against interoperability implementation. At the first place there is usually the financial aspect: IT developers, government, health-insurance companies, medical facilities and even patients are asking the crucial question regarding financing. The need of functional e-Health solution is often overlooked without understanding the negative consequences. As mentioned above, there it lacks a constructive debate and communication in the direction to patients and the society that would unify the heterogeneous groups.
With respect to future development and possibility to sense and store far more larger volumes of heterogeneous physiological parameters the issue of interoperability becomes more and more important. Interoperability may significantly influence effectiveness both of design and development of an integrated system and of its routine operation. It will become more and more important with the development of telemedicine, home care and possibility of remote monitoring of patient state. As the technology is developing very quickly we have to assume that new types of sensors and devices will appear. The newly designed and developed systems must be necessarily created as open modular systems allowing direct connection of the new sensors and devices without any need of modification of the communication and data input. Possibly new data processing module will be added. However if we only replace an old type of sensor by a new one delivering the same data (concerning semantic content) in higher quality there should not be any need for changing the software part.
Presented issues show that successful applications need coherent approach of experts from many different disciplines, i.e. information technology, electronics, communication technology, medicine. Standardization can make the way from an idea to an application much easier and faster. Thus acceleration of standardization process represents a key issue. It is important that involved companies, researchers, and standardization bodies agree and cooperate towards the ultimate goal – defined standards. There has not been space to mention the expressive power of ontologies, their flexibility, extensibility, and their potential in various applications in biomedicine. We should be aware of their potential for future applications. It is expected that new tools will be developed that allow more efficient work with ontologies, including development of virtual ontology libraries, or ontology visualizations. We should also mention the inevitable spread of no SQL databases. These might find their use in the EHR solutions due to their inherent properties.
For the Czech Republic, there is no informative material that would present medical experts the advantage of the electronic solution and persuade them that the change can be carried out with minor invasion. The question is whether the impulse should come from government, medical experts or even patients. There is missing a communication based on the view from the position of the patient that might influence medical doctors, medical doctors would apply to medical insurance companies, medical insurance companies to the government, etc. Currently there is no solution for m-Health, so there is perfect opportunity to start from scratch with correctly defined interoperable structure using widely acknowledged standards.
Electronic signature is widely used and understood. However the medical records should also have a guaranteed timestamp that reflects the order of data-change. The permissions and authorizations for manipulation of medical data together with defined responsibility need to be defined.
This research has been partially financed by the research program "Information Society" under grant No. 1ET201210527 "Knowledge-based support of diagnostics and prediction in cardiology" and by the research program MSM 6840770012 of the CTU in Prague, Czech Republic.
 D. Bernstein, E. Ludvigson, K. Sankar, S. Diamond, and M. Morrow. Blueprint for the Intercloud – Protocols and Formats for Cloud Computing Interoperability. IEEE Computer Society. Pp. 328–336, 2009.
 J. Kaplan, et all. Roadmap for Open ICT Ecosystems. Berkman Center for Internet & Society at Harvard Law School. 2005
 L. Lhotska, O. Stepankova, M. Pechoucek, B. Simak, and J. Chod. ICT and e-Health Projects. In Telecom World (ITU WT), 2011 Technical Symposium at ITU. Piscataway: IEEE, pp. 57-62, 2011
 L. Lhotska, and O. Stepankova. Agent architecture for smart adaptive systems. Transactions of the Institute of Measurement and Control. Vol. 26, pp. 245–260, 2004