RESEARCH PAPER
Using affinity analysis in diagnosing the needs of patients as regards e-Health
 
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1
Collegium Medicum Institute of Health Sciences, Kochanowski University, Kielce, Poland
2
Department of Economics and Finance, Faculty of Law and Social Sciences, Jan Kochanowski University, Kielce, Poland
3
Department of Public Health, Medical University, Lublin, Poland
4
Institute of Rural Health, Lublin, Poland
CORRESPONDING AUTHOR
Monika Kaczoruk   

Department of Public Health, Medical University, Lublin, ul. Chodźki 1, 20-093, Lublin, Poland
 
KEYWORDS
TOPICS
ABSTRACT
Introduction:
E-Health tools allow a medical facility to set a given patient’s data in order using ICT techniques, and the patient to use those techniques when contacting a given organisation.

Material and methods:
Secondary statistical data was used in the research. The study was carried out among primary health care patients. Mining for affinity rules was done in the R programme. The apriori and inspect functions from the arules package were used. Moreover, any redundant rules were removed from thoseobtained using the afero-mentioned method. Applying the general description of the affinity analysis method onto the survey described herein, it should be stressed that the aim of using affinity analysis was to discover the rules which contain the sub-transaction B={V_6=1} as a consequent. This was determined by the intention to discover associations regarding the knowledge about a uniform information system that the patients under study might have.

Results:
In the discovered rules, the antecedent most often contained an indication of the need for introducing a uniform solution as regards telemedicine. Moreover, according to the opinions of ‚conscious‘patients, a uniform IT system should improve the work at primary health care institutions, introducing an on-line booking system for visits should improve the productivity and comfort of doctors, and an IT system should provide unambiguous identification of a patient.

Conclusions:
There is potential in using affinity analysis within e-Health. The example of affinity analysis described in his study led to the discovery of interesting and important (from the point of view of a medical facility) regularities regarding the knowledge and expectations of patients as regards e-Health.

 
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