J Med Syst (2011) 35:1455–1464 DOI 10.1007/s10916-009-9422-2
ORIGINAL PAPER
Choosing the Most Efficient Database for a Web-Based System to Store and Exchange Ophthalmologic Health Records Isabel de la Torre & Francisco Javier Díaz & Miriam Antón & Jose Fernando Díez & Beatriz Sainz & Miguel López & Roberto Hornero & María Isabel López
Received: 29 September 2009 / Accepted: 14 December 2009 / Published online: 12 January 2010 # Springer Science+Business Media, LLC 2010
Abstract Response times are a critically important parameter when implementing any telematics application. Hence, it is important to evaluate those times to check the performance of the system. Different database will get different response times. This paper presents a response time comparative analysis of the Web system of Electronic Health Record (EHRs), TeleOftalWeb, with the four databases used: Oracle 10 g, dbXML 2.0, Xindice 1.2, and
I. de la Torre (*) : F. J. Díaz : M. Antón : J. F. Díez : B. Sainz : M. López : R. Hornero Department of Signal Theory and Communications, University of Valladolid, Campus Miguel Delibes, s/n, 47011, Valladolid, Spain e-mail:
[email protected] F. J. Díaz e-mail:
[email protected] M. Antón e-mail:
[email protected] J. F. Díez e-mail:
[email protected] B. Sainz e-mail:
[email protected] M. López e-mail:
[email protected] R. Hornero e-mail:
[email protected] M. I. López University Institute of Applied Ophthalmobiology (IOBA), University of Valladolid, Edificio Ciencias de la Salud—Avda. Ramón y Cajal, 7, 47005 Valladolid, Spain e-mail:
[email protected]
eXist 1.1.1. Final goal of the comparison is choosing the database providing lower response times in TeleOftalWeb. Results obtained using the four databases proposed give the native XML database eXist an edge which, added to other features such as being a free software and easy to set up, makes us opting for it. TeleOftalWeb is being used by 20 specialists from the Institute of Applied Ophthalmobiology (Instituto de Oftalmobiología Aplicada, IOBA) of the University of Valladolid, Spain. At this time, there are more than 1000 EHRs and over 2000 fundus photographs of diabetic patients stored in the system. Keywords Databases . Electronic health record (EHR) . Extensible markup language (XML) . TeleOphthalmology . Web application
Introduction Choosing an Electronic Health Record (EHR) system is a difficult task. On 1990, the Institute of Medicine (IOM) preformed an interesting study identifying the strengths and weaknesses of the traditional paper-based Health Records. The disorganization, the illegibility, and the short availability were some of the weakness detected [1]. These shortcomings are often used to justify the call for widespread use of Electronic Health Record (EHR) systems. An EHR system coordinates the storage and retrieval of individual records with the aid of computers. EHR systems bring great strengths in comparison to paper-based records. Basically, EHRs can reduce errors caused by the incorrect deciphering of poor handwriting [2]. They are also accessible every time and everywhere through an Internet connection, wireless, etc. Most of the EHR systems are structured in
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anamnesis, medical exploration, complementary tests, diagnosis, and treatment. EHRs are searchable for patterns of disease, prescription use, treatment outcomes or even the costs of therapy [3]. Some of the EHRs disadvantages include such items as the startup costs, which can be excessive [4]. Furthermore, there are several barriers to its adoption such as training, costs, complexity, and lack of a national standard for interoperability [5, 6]. Nowadays, many physicians use both EHR systems and traditional paper-based health [7]. The value and importance of EHRs have been repeatedly demonstrated in Europe and United States of America (USA) [8]. Numerous applications related to EHRs systems have been developed in the last years. Some of them use Web technologies, e.g. CareWeb™ [9], PedOne System [10], OphthWeb [11], etc. and others like Julius [12], OpenSDE [13], PHIMS [14], CipherMe [15], etc. are not web-based applications. Excepting CareWeb™ which complies the HL7 standard, PedOne using XML-based OpenEHR, and CipherMe employing XML objects, the remainder applications do not meet any EHR standard. Wen et al. presented a production of EHR research between 1991 and 2005. Most articles were published in English (98%) and were from the region of America (57%). Of all publications, 1455 (80.7%) were articles, followed by meeting abstracts which represented about one-tenth of all types of EHR publications [16]. Analysing scientific papers of the last five years, we found most of them are of American systems and only a small rate, under a 10%, are from European countries. It is required to notice the importance of the databases in EHR systems becoming a force in the estimation of both the response time and the total performance of the system. Nevertheless, few authors focus on the analysis of the EHR system database. The browsing times in the databases decisively affect the total response time of a system [17]. Ophthalmology is a very suitable speciality to implement an EHR system with functional characteristics geared to analyse the patients’ eyes, while an EHR system for primary care needs higher scope (medical tests, diagnosis, etc.). We proposed a Web application, TeleOftalWeb, to storage and exchange EHRs, working cooperatively with specialists from the Institute of Applied Ophthalmobiology (Instituto de Oftalmobiología Aplicada, IOBA) of the University of Valladolid, Spain [18]. The application is focused to store and exchange ophthalmologic EHRs and fundus photographs, in order to provide remote and fast access to specialists. TeleOftalWeb complies with the Health Level 7 / Clinical Document Architecture (HL7/ CDA) standards for EHRs storage, and Digital Imaging and Communications in Medicine (DICOM) for medical images. Important features giving TeleOftalWeb a complete standardization needed for a feasible technologic evolution.
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At this time there are more than 1000 EHRs and over 2000 fundus photographs in the system. Records gathered in TeleOftalWeb come from patients which participate in a telemedicine programme for the diabetic retinopathy screening conducted in a Spanish rural area. The fundus photographs were taken by general practitioners of those areas and were sent by e-mail to the IOBA specialists [19]. In this article we intend to evaluate the TeleOftalWeb system, finding out the response times for four databases in order to determine which one provides better performance. TeleOftalWeb is being used by 20 physicians from the IOBA, Spain. Response time of every telematics system mainly depends on variables such as CPU speed, network connection, and database. Therefore, the analysis for choosing the database is essential in the best implementation of every telematics system. After an in-depth analysis of the commercial and the free software databases for their use in TeleOftalWeb, Oracle 10 g, dbXML 2.0, Xindice 1.2, and eXist 1.1.1 were chosen. All of them allow storing the information in an XML format, a requirement to comply with the clinical information standard HL7/CDA, key feature of TeleOftalWeb. Oracle 10 g database includes a data type called XMLType, to simplify the XML information handling [20]. The native XML databases define a logical model for the XML document. dbXML 2.0 is a Java-developed database available under the GNU licence [21]. eXist database supports different query languages like XPath 2.0 and XQuery 1.0 [22, 23]. Finally, Xindice stores and indexes XML documents to provide data to other applications with low processing in the server side [24]. Present paper shows a comparison of the response times of the TeleOftalWeb application using the aforementioned databases. The main goals of this paper are: – – –
–
Firstly, to propose a benchmark setting to compare the performance of a Web application (TeleOftalWeb) with different databases, using new measure methods. Secondly, to analyse different relational and native XML databases to be used in an EHR system, in this case in an Ophthalmology EHR system. The third objective is to choose the database providing lesser response time to TeleOftalWeb, to obtain a more effective system for both the medical specialists and the patients. And the fourth one is to offer a comparative analysis with four databases (three XML native) that helps researchers to design other telematics applications.
The paper structure is as follows: in the “Methods” section, a description of the TeleOftalWeb application is shown; followed by an explanation of the application
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modules, its architecture and the considerations to bear in mind when measuring the response times. In the “Results” section the different response times of TeleOftalWeb with the said databases are presented. In the “Discussion” section, the results are analysed, and finally, the conclusions derived from this work are exposed in the “Conclusions” section.
Materials and methods Description of the application TeleOftalWeb is a Web application aimed at storing and exchanging ophthalmologic EHRs [18]. It complies with HL7/CDA Release 2.0 and DICOM 3.0 standards. Specialists can create new EHRs and medical reviews, delete them, search for EHRs in the system, add fundus of photographs to the records in any digital format (JPEG, DICOM, etc.), update, delete and select images from the EHR, and print the whole record to a Portable Document Format (PDF) document. In our work, the EHRs include graphic information, like the patients’ fundus of the eye. All data transmissions were carried over encrypted Internet connections such as Secure Sockets Layer (SSL) and HyperText Transfer Protocol over SSL (HTTPS). HTTPS protects data in transit from eavesdropping and man-in-the-middle attacks. We applied SSL v3. The client may use the certificate authority's (CA's) public key to validate the CA's digital signature on the server certificate. Moreover, TeleOftalWeb verifies the standards related to data confidentiality. The physicians and patients share common ground over many of the confidentiality issues raised by EHRs. Next, the two modules composing TeleOftalWeb are described.
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brightness and contrast. Other editor functions are: Red, Green, Blue (RGB) scale, add, and delete text and arrows. It supports all type of images (DICOM, JPEG, GIF, etc.). Architecture application with different databases TeleOftalWeb has been built on Java Servlet and JSP technologies. The databases to be evaluated are Oracle 10 g and three XML native databases, dbXML 2.0, Xindice 1.2, and eXist 1.1.1. Choosing the commercial relational database, Oracle 10 g, for this analysis was due to it allowing the storage of documents in XML format, something required for TeleOftalWeb to verify the HL7/ CDA standard. Figure 3 shows the application architecture using Oracle 10 g. The client application consists of a web interface based on JSPs running on the web server. Apache Tomcat 5.5 for Windows has been used as web server. In Oracle 10 g database, we stored all the user data and access information to the web application. Oracle 10 g introduces a new datatype, XMLType, to facilitate native handling of XML data in the database. The other three free software databases were selected considering their scalability, usability, and interoperability features [25]. In this case the communication languages used were XML Path Language (XPath) and XUpdate. The first one allows moving through and processing XML documents. An XML document needs a parser to generate a node tree. XUpdate is a language focused on the XML databases, it analyses the XML file and generates the “tables” to handle the document. XPath selects portions of an XML document based on the tree representation of the document. Figure 4 shows the application architecture using the XML native databases. Moreover, Extensible Stylesheet Language Formatting Objects (XSL-FO) was used to format XML data. XSL-FO is a complete XML vocabulary for laying out text on a page. An XSL-FO document is a well-formed XML document that uses this vocabulary.
Application modules Benchmark setting TeleOftalWeb has two modules: manager and user. The manager can create new users (patients or physicians), show user information, erase users, change physician’s information, and show user statistics and patient records. Moreover, searching users by different criteria (surname, identification number, type of user, and member user) can be done. Only registered users can access to the user module. They can create new records, search for or delete them; create reviews in existing records or delete them; add new images to a record, search for them, update or delete them. Figure 1 displays an image searching in an EHR, and Fig. 2 shows the images editor with a DICOM image. It shows images and allows us to change their shape and colour, zoom in or zoom out. It supports image editing of
The system configuration used to calculate the response time is the following: the server runs on a 2.8 GHz Intel Core™ 2 Quad CPU Q6600. It had 4 GB of system memory; the operating system is Windows Server 2003 Enterprise Edition with Service Pack 2. The client runs on a 1.2 GHz Intel Pentium 4 processor with Hyper-Threading technology enabled. It had 1 GB of system memory; the operating system is Windows XP Home Edition. There are many ways to measure the response time of a Web site. First possibility consists in including a timer function within the application code in order to measure the time expended in completing the procedure requested by the user. This approach is not appropriate because entering
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Fig. 1 Searching fundus photographs in an EHR
a new code in the application inserts new operations that may vary the time consumed and it is also necessary modifying all the web pages included in the application. Another possibility is using specific software to measure the time spent in loading each Web page. These applications provide fast measurements without affecting the loading time, but they depend on the browser used. As a comparison between two browsers is performed, two different applications are needed. These are Firebug for Mozilla Firefox and Web Development Helper for Internet Explorer. Both applications give the possibility to measure the database access time. These tools are independent from the database used. Despite the fact that the calls to an Oracle database are different from a native XML database,
Fig. 2 Images editor in an EHR
to measure the response time it was not necessary to specify the calls to the database. There are also other methods to measure the response time independently from the Web browser used, e.g. the queuing theory, but our proposal add to these measures the difference between the two Web browsers more used. Benchmark tests concerning response times in TeleOftalWeb were performed. In these tests the browsers used were Mozilla Firefox version 2.0 and Internet Explorer version 7.0. Firstly, the network average speed was 1 Mbps. Benchmarking used consisted on measuring times of: – –
Home page loading average time. Average time in loading the records search.
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Fig. 3 Application architecture with Oracle 10 g
– – – – – –
Average time in inserting a record with scanned images. Average time in adding a DICOM image. Average time in adding a JPEG image. Average time in loading the images search. Average time in creating a PDF document. Average time in deleting a record.
Each of the eight times was calculated as the average of 200 measures. Each test was performed over the four databases using both browsers and varying both the number of records stored and exchanged in the database from 25 to 5000. Fig. 4 Application architecture with XML native databases
The response time comparison has been performed with four different databases within the same system (TeleOftalWeb). The three-tier system architecture used is the same for every database used, as it is explained in “Architecture application with different databases.” So, this paper is focused to the benchmark of databases for an specific application.
Results In this section, it is shown the results of the response times for the four settings using the different databases previously
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Table 1 Averages of the 200 measures of the response times of the proposed benchmark with 1000 EHRs for a 1 Mbps, in ms Web browser: Internet Explorer
Web browser: Mozilla Firefox
dbXML 2.0 eXist 1.1.1 Xindice 1.2 Oracle 10g dbXML 2.0 eXist 1.1.1 Xindice 1.2 Oracle 10g Home page loading time. Time in loading the records search. Time in inserting a record with scanned images. Time in adding a DICOM image. Time in adding a JPEG image. Time in loading the images search. Time in creating a PDF document. Time in deleting a record.
2189 2218 2130
2010 2034 2087
3300 3342 3289
2065 2129 2266
2119 2100 2130
2005 2046 2099
3200 3210 3215
2105 2119 2144
2200 2430 2220 2233 2228
2209 2099 2009 2185 2175
3408 3356 3280 3245 3300
2238 2244 2240 2250 2200
2401 2256 2200 2398 2316
2237 2198 2098 2100 2009
3350 3200 3119 3209 3209
2398 2301 2200 2132 2233
commented in the “Methods” section. The estimating number of concurrent connections is 20. In the tests performed, server was located in the Telecommunications Engineering School, University of Valladolid, Valladolid, Spain, and clients accessed from the Institute of Applied Ophthalmobiology (IOBA) of the University of Valladolid, Spain. The four system configurations compared have been under the same conditions, so comparatively there are no other hardware configurations for TeleOftalWeb where results can change. Fluctuations affect similarly the four settings compared. Table 1 shows the averages of the 200 measures of each of the eight times for 1000 EHRs and an Internet connection of 1 Mbps. Table 2 displays the same average times for an Internet connection of 6 Mbps. In both tables it can be observed measure times are similar for each Internet connection. Furthermore, all times for the eXist database are slightly lower than those for Oracle and highly lower than those for dbXML. Xindice shows a highly negative behaviour. These observations allow us predicting the behaviour of the eight times throughout the benchmark,
and so comparing the global averages. From now on, we will show the global mean times, to ease the understanding of the paper with too many tables. Table 3 shows the average of the overall mean loading times for the 200 measures, using both browsers and with more than 100 users simultaneously in the system. Two images of the fundus of the eye in a DICOM format are associated to each EHR stored in TeleOftalWeb. The size of the transferred file is 1 MB including two fundi of eye in DICOM format. In Table 3, it can be observed the evolution of the global mean response times for an Internet connection of 1 Mbps, time rises while increasing the number of EHRs. Similar tests were also performed varying the Internet connection rate. Thus, for example, for a 6Mbps Internet connection rate, eXist closely followed by Oracle 10 g obtain better response times (see Table 4). With the other XML native databases, response times exponentially grow from 1000 EHRs stored. Table 5 and 6 show the standard deviations for the 1 Mbps and 6 Mbps Internet connections respectively. As the number of EHRs increases, the standard
Table 2 Averages of the 200 measures of the response times of the proposed benchmark with 1000 EHRs for a 6 Mbps, in ms Web browser: Internet Explorer
Web browser: Mozilla Firefox
dbXML 2.0 eXist 1.1.1 Xindice 1.2 Oracle 10g dbXML 2.0 eXist 1.1.1 Xindice 1.2 Oracle 10g Home page loading time. Time in loading the records search. Time in inserting a record with scanned images. Time in adding a DICOM image. Time in adding a JPEG image. Time in loading the images search.
2231 2233 2216
2100 2105 2009
3320 3323 3324
2207 2206 2220
2140 2238 2210
2001 2003 2100
3200 3201 3220
2201 2205 2210
2330 2210 2221
2248 2105 2009
3555 3315 3327
2298 2222 2102
2345 2204 2218
2199 2133 2101
3345 3199 3202
2341 2209 2117
Time in creating a PDF document. Time in deleting a record.
2246 2210
2140 2134
3212 3303
2217 2210
2302 2306
2118 2192
3202 3213
2204 2169
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Table 3 Overall average of the mean loading times achieved with 1 Mbps in ms Web browser: Internet Explorer Number of EHRs 20 50 100 250 500 1000 5000
dbXML 2.0
eXist 1.1.1
Web browser: Mozilla Firefox Xindice 1.2
Oracle 10g
dbXML 2.0
eXist 1.1.1
Xindice 1.2
Oracle 10g
2046 2162 2234 2292 2234
1611 1789 1988 2011 2098
2507 2876 2866 3099 3303
1710 1893 2045 2094 2193
2193 2148 2151 2182 2240
1302 1700 1865 2001 2034
2560 2571 2960 3099 3203
1423 1823 1945 2053 2142
2231 >30000
2101 10013
3315 >30000
2204 10243
2240 >30000
2099 10001
3214 >30000
2201 10129
Xindice 1.2
Oracle 10g
Table 4 Overall average of the mean loading times achieved with 6 Mbps in ms Web browser: Internet Explorer Number of EHRs 20 50 100 250 500 1000 5000
dbXML 2.0
eXist 1.1.1
Web browser: Mozilla Firefox Xindice 1.2
Oracle 10g
dbXML 2.0
eXist 1.1.1
2052
1618
2514
1715
2199
1309
2567
1427
2168 2240 2298 2240 2237 >30000
1794 1993 2017 2104 2107 10043
2884 2874 3108 3312 3324 >30000
1898 2051 2100 2199 2210 10273,7
2154 2157 2188 2246 2246 >30000
1705 1870 2007 2040 2105 10032
2578 2968 3108 3212 3223 >30000
1828 1950 2059 2148 2207 10159
Table 5 Standard deviations of the overall mean loading times for an Internet connection of 1 Mbps, in ms Web browser: Internet Explorer
Web browser: Mozilla Firefox
Number of EHRs
dbXML 2.0
eXist 1.1.1
Xindice 1.2
Oracle 10g
dbXML 2.0
eXist 1.1.1
Xindice 1.2
Oracle 10g
20 50 100 250 500 1000 5000
105 113,3 124,1 138,7 16027,7 196,31 198,78
306,8 328,4 357,2 398,3 458,2 561,1 569,8
102 109 120 133,7 154 188,6 198,7
312 334,2 363,7 405,2 465,8 570,4 5719
105 113,4 124,2 138,8 160,2 196,2 198,8
310 332,1 355 399 459,5 560,5 578,9
102,3 110,1 120,1 134 154,6 189,3 189,9
311,8 331,7 360,9 401 460,8 562,2 576
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Table 6 Standard deviations of the overall mean loading times for an Internet connection of 6 Mbps, in ms Web browser: Internet Explorer
Web browser: Mozilla Firefox
Number of EHRs
dbXML 2.0
eXist 1.1.1
Xindice 1.2
Oracle 10g
dbXML 2.0
eXist 1.1.1
Xindice 1.2
Oracle 10g
20 50 100 250 500
113,3 112 124,1 138,7 160,3
305,9 327,4 356,1 397,7 456,8
102 109,8 120,1 133,8 154,1
311,1 333,2 362,7 403,9 464,4
105,1 113,5 124,3 138,8 160,2
309,8 329,6 357,9 397,8 458,1
102,3 110 120,2 134,1 154,6
310,2 330,8 359,8 399,8 459,4
1000 5000
196,3 198,7
559,4 561
188,6 189,9
568,4 576,4
196,2 199,2
558,7 598,8
189,4 190,1
560,5 567,8
deviation also raises Tests were also performed using Mozilla Firefox 7.0 and Internet Explorer 8.0 browsers, but results achieved were similar to those obtained with previous versions. Figure 5 shows the mean response or loading times obtained with 1 Mbps and Internet Explorer (a), with 1 Mbps and Mozilla Firefox (b), with 6 Mbps and Internet Explorer (c), and with 6 Mbps and Mozilla Firefox (d). Analysing Fig. 5, it can be observed response times are mostly slightly lower when using Mozilla Firefox, although this difference is not too significant. While growing the number of EHRs stored in the database, time increases for both browsers. As of 1000 EHRs, time raises sharply. This growth is less significant for the Oracle and eXist databases. For Internet Explorer and Mozilla Firefox, best times are achieved using eXist 1.1.1 database followed by Oracle 10 g. All times directly depends on the number of EHRs,
server load, and the static and dynamic objects in the web pages. Using a 1 Mb Internet connection TeleOftalWeb can store and exchange above 5000 EHRs with an Oracle 10 g or eXist 1.1.1 database. The difference in the time consumed with both databases provides a small advantage to eXist. From 5000 EHRs stored in the system, both Oracle and eXist provide high response times. Using the Xindice and dbXML 2.0 native XML databases, results are quite poor from 1000 EHRs.
Discussion Results obtained in our comparison give a small advantage to the eXist database. This fact together with other features like it is a free software, it is easy to set up, and with an efficient maintenance releases, makes us opting for it.
Fig. 5 Overall mean response times of TeleOftalWeb a with 1 Mbps with Internet Explorer, b with 1 Mbps and Mozilla Firefox, c with 6 Mbps and Internet Explorer, d with 6 Mbps and Mozilla Firefox
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Tools used for measuring the response times (Firebug and Web Developer) are transparent with respect to the database employed. There are also other methods to measure the response time independently from the Web browser used. The speed connections proven were 1 Mbps and 6 Mbps. Results obtained with both speed connections give a small advantage to the eXist database regarding to the Oracle database, and a large advantage concerning the other two databases. From this comparison it can be derived that varying the Internet connection, the response times are modified, but this fact does not affect the results of the global comparison of the four databases. Browsers used are Mozilla Firefox and Internet Explorer, as they are the most used in the day-to-day medical practice. The response times measured are slightly lower using the Mozilla Firefox browser. Other hardware configurations of the TeleOftalWeb system would not vary the comparative results in relation to the response times obtained respecting the configurations studied in this paper. The response time evaluation using the databases proposed can provide a background to other developers aiming to develop a Web system similar to TeleOftalWeb (with a three-tier architecture). When selecting the database to store the XML information of a system and obtain reasonable response times, Oracle or eXist databases have to be chosen. In our application, we opt for eXist 1.1.1 database as it is the winner of the benchmark performed, aside from being a free software and easy to set up and support.
Conclusions In this work, the response times of the TeleOftalWeb application with different database managers (Oracle 10 g, Xindice 1.2, eXist 1.1.1, and dbXML 2.0) have been analysed and calculated. Results obtained show a slight edge to eXist next to Oracle, but a higher advantage next to the other two databases. From the analysis performed, it can be derived that TeleOftalWeb can store and exchange up to 5000 EHRs when concurrently accessing more than 100 users with an Oracle 10 g database with a 1 Mb Internet connection, and up to 5000 EHRs using eXist 1.1.1 database with the same Internet connection. With more than 1000 EHRs stored in dbXML 2.0 or Xindice 1.2 databases, time sharply increases. We have elaborated a new method to measure times which can be useful in the development of other telematics applications. Results show high differences in the behaviour of eXist and Oracle next to dbXML and Xindice. Resulting from this comparison, we can conclude that for an EHR telematics application development, only Oracle and eXist should be consider.
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At present, TeleOftalWeb system with the most efficient database, eXist 1.1.1, which provides the best response times, and its features like cost, availability, and maintenance are favourable, is being used by 20 physicians from the Institute of Applied Ophthalmobiology (Instituto de Oftalmobiología Aplicada, IOBA) of the University of Valladolid, Spain. At this time there are more than 1000 EHRs in the system. Records gathered in TeleOftalWeb come from patients which participate in a telemedicine programme for the diabetic retinopathy screening conducted in a Spanish rural area. The fundus photographs were taken by general practitioners of those areas and were sent by e-mail to the IOBA specialists [19]. A long-term goal is to incorporate mobile services allowing specialists to manipulate the patient EHRs anywhere from their mobile terminal or Terrestrial Digital Television (TDT). Acknowledgements This research has been supported by the Spanish Ministry of Science and Innovation under the project TEC2008-02241.
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