Integrating Global Data into Local Health Data Base Irena Patasiene, Rima Kregzdyte, Martynas Patasius, Juozas Patasius, and Agne Kazakeviciute

Abstract—Data analysis traditionally belong to scientist’s field of interest. Usually scientists gatherer and analyze their own data. Challenges of 21st century require more global point view in decision making process from each worker in local workplace. Local public health sector is strongly related with global world. So, right managerial decision-making in local workplaces depends on changes in global environment. The speed of changes is very high. Therefore, it is necessary to encourage workers of public health sector to make daily managerial decisions evaluating both global and local data. Information technologies (IT) supports decision making process. It is easier to analyze homogeneous data. Analysis of global data has shown that data formats were often incompatible. Limited IT competencies of public health workers make analysis of data from different sources difficult. This article describes a method for integration of global heterogeneous data in local databases.

I. INTRODUCTION ealth Information System (HIS) is important and useful tool of health sector workers. The purpose of HIS [4]

is: • to provide quality, relevant and timely data,

information and knowledge in order to support public health decision making at Global, European, national, sub-national and local level;

• a tool necessary to make decision at strategic, control and operational level, to set directions, to monitor their implementation and evaluate their impact;

• managing Health Information System means designing organizations capable of running the HIS processes in an orderly way;

• choosing the most relevant set of data and indicators, an up-to-date information technology and relevant statistical analysis, represent some of

the essential steps to assure a functional HIS.

Manuscript received April 16, 2007. I. Patasiene is with faculty of Social Sciences, Kaunas University of

Technology, Donelaicio str. 20, Kaunas LT-44239, Lithuania phone +370 69931197, fax: +370 37 300102, e-mail: irena.patasiene@ktu.lt)

R. Kregzdyte is with Institute for Biomedical Research, Kaunas University of Medicine, Eiveniu str. 4, Kaunas LT-50009, Lithuania (e-mail: rima.kregzdyte@kmu.lt).

M. Patasius is with Biomedical engineering institute, Kaunas University of Technology, Studentu str 65, Kaunas LT-51369, Lithuania (phone +370 37 407119, fax: +370 37 407118; e-mail: martynas.patasius@ktu.lt)

J.Patasius is with State Institute Transport and Road, Kanto 25, Kaunas, LT-44239, phone +370 68723184, e-mail: j.patasius@tkti.lt

A. Kazakeviciute is with faculty of Social Sciences, Kaunas University of Technology, Donelaicio str. 20, Kaunas LT-44239, Lithuania (phone +370 6 99 31197, fax: +370 37 300102, e-mail: agne.kazakeviciute@stud.ktu.lt)

HIS as other kinds of information systems is related with data, knowledge, decision, management and dissemination. Public health sector cares about sharing information among professionals and citizens, since information loses value if does not reach potential users. Often efficiency of HIS is poor because there are problems at all levels of users: the organizational level, at the output level and at the policy level. There is big number of organizations gathering the similar data and collecting different databases. European Union HIS includes more than 10 system elements [4]:

• The European Community Health Indicators (ECHHI) system at national level;

• The system of Regional Indicators on Health (ISARE) at sub-national level;

• A system of indicator in urban areas; • A system of sources and inventories an health

information; • A system of information and knowledge an major

and chronic diseases; • A system of networks and databases in the field of

Rare Disease; • The Epidemiological Surveillance and control of

Communicable diseases Network; • The analysis of consequences of events leading to

unforeseen level of mortality; • A system of information on life styles and other

health determinants; • The European Community Environment and HIS

(ECOEHIS); • The DG SANCO injury database (Euro-IDB); • The European Health Survey System (EHSS); • A Hospital Activity and Resources Information

System; • Performance assessment of health care institutions

to asses and compare quality strategies; • The system of Health Accounts (SHA); • A system of information on patients mobility; • A system of information of health professional

mobility. The European Commission recommends that the

information should be collected for these main components: (1) in a routine register or survey basis when possible (with Eurostat as the main EU provider); (2) on the basisof DG SANCO established systems (ECOEHIS, ISS, communicable diseases); (3) from Community Public Health

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projects in a non routine basis; (4) on the basis of future modules from the Eurostat /DG SANCO European Health Survey System (EHSS) for other health status indicators. [4] To chose fields from databases decision maker should know each of them very well. Sometimes he could use statistical data from European statistical data base (EUROSTAT), WHO databases or national statistical databases. Without professional IT knowledge it is practically impossible to integrate different types of fields that are differently structured.

There are a lot of publications in the field of integration [1], [2], [3], but there are very few related with practical use for nonprofessional users. We suggest methods for solving this problem.

II. METHODS The aim of Health system is improving quality of life.

Evaluation and assessment necessitate collection of data and calculation of set of indicators. To get a full view of quality of life we need to involve almost all health sector workers in assessment, evaluating, monitoring. Evaluation of not just health, but also financial, cultural, social and other indicators seems necessary for that. So, it is necessary to use both global and local data.

To integrate global data the set of indicators, which we need to calculate, has to be defined. The portal of International Compendium of Health Indicators (ICHI) helps to understand them more deeply. The same indicators can be received from different sources: WHO, OECD (Organization for Economic Cooperation and Development), EUROSTAT and ECHI (European Community Health Indicators) etc. Usually they allow downloading the list with selected fields as a MS Excel file or a chart.

Necessity of integrating data could be proven by analysis of the model of Health Planning and Evaluation (Fig. 1).

Fig. 1. Model of Health Planning and Evaluation

Model of possible integration of data from global DB is

shown in Figure 2. Our survey has shown that it is too difficult for public health worker to use lots of different databases in daily work, as public health experts’ competencies in IT field tend to be limited. We suggested designing database of metadata of all known global databases, where data describing output of different data

sources (global databases) would be gathered. Using that data would make it easier to design queries for daa integration.

Fig. 2. Model of possibilities of applying global data

Figure 2 shows two ways for solving this problem:

• a finite set of most popular queries could be defined and subsequently implemented by IT expert;

• a user-friendly tool to facilitate designing different queries could be created.

First option does not require any special IT competencies, but it will be difficult to get quick answer in non-regulated situation. Second option seems more useable in more dynamic case. In this case it is necessary to educate public health experts in some relatively advanced uses of IT. For example, they should understand ODBC, export/import in MS Excel, MS Access and should be able to design queries in MS Access.

Figures 3, 4 show examples of different structures of output data.

Fig. 3. An example of data from EUROSTAT DB

Fig. 4. An example of data from global DB

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It is impossible to integrate them according to the same rules.

The final result (chart) is shown in Figure 5, where data from global DB is adopted for user needs and compared with local data.

Fig. 5 An example of using integrated data

However, forming the chart shown in figure 5 required to design some additional queries. They were needed to transform data to unified structure. An example of such query is shown in figure 6.

Fig. 6. An example of query for updating data for data unification

Public health experts should have abilities to design simple

queries like the one shown in figure 6. It is easy to notice that in global DB field of Time structure consists of 7 characters (full date). Most of local DBs use 4 characters (year only). So, it is necessary to remove excessive characters as shown in figure 6.

We suggest an open tool (interface) for integration of global and local data. The model of tool is shown in figure 7.

Fig. 7. Model of tool of applying global and local data

IT professional should design some macros for converting data to suitable format. If export file from global DB includes many of indicators (figure 4), we suggest to design tool for converting data to format according to DB requirements. This procedure could be written in formalized form:

{ } { },,_,,,,,, 1 iiiinii indindnameTCindindTCM →= … (1) where M is model of table, Ci is name of region, indi is

selected indicator, name_indi is name of selected indicator. The main idea of this model is design of intermediate

database in MS Access. Public health worker should be able to use MS Access and MS Excel, since they are studied in ECDL program. Export file from global databases usually is in MS Excel format, so we suggest that final result would be in MS Excel format too.

Use of described model requires adequate competencies of end user (public health worker). They could be provided both in traditional seminars in education centers and in distance learning courses.

III. RESULTS The tool was shown for students from Kaunas University

of Medicine studying program of public health management. The study program included seminars about MS Access. Both before and after these seminars a survey noting their opinion about possibility of integration of global and local DB was done. It involved 58 respondents – both full-time and part-time students (80% of them working in the public health sector).

It was found that before the course just 2 students considered use of integration of global and local databases (in their Master Thesis) useful. However, after the course 72% of respondents were of this opinion. Also at first 56 students preferred to have pre-made queries, but after the course all of them changed their opinion.

That would indicate a possibility to prepare the users to use the proposed methodic. However, the course would be more effective if the users could have more motivation to use the proposed methodic before it.

IV. DISCUSSION AND CONCLUSIONS It seems rational to check if there is relationship between

inclination to use this methodic and general computer literacy in the society. For this, a similar survey at both national and international level might be used.

REFERENCES [1] A. C. Siepel A. N. Tolopko, A. D. Farmer, P. A. Steadman, F. D.

Schilkey, B. D. Perry, and W. D. Beavis, “An integration platform for heterogeneous bioinformatics software components” Deep computing for the life sciences, Vol. 40, No. 2, 2001, p. 570-591.

[2] T. J. Eggebraaten, J. W. Tenner, and J. C. Dubbels, “A health-care data model based on the HL7 Reference Information Model” Information-Based Medicine, Volume 46, Number 1, 2007, p. .5-18

[3] J. D. Gold and M. J. Ball, “The Health Record Banking imperative: A conceptual model” Information-Based Medicine, Volume 46, Number 1, 2007, p. 43-57.

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[4] Strategy on European Community Health Indicators (ECHI), Network of Competent Authorities on Health Information, Luxembourg, 5-6 July, 2004. Available: http://ec.europa.eu/health/ph_information/documents/ev20040705_rd09_en.pdf

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