Haiguste komorbiidsusanalüüs
Date
2015
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Abstract
Lühikokkuvõte:
Personaalmeditsiin on uus lähenemine tervisekaitsele, milles tuuakse esile patsientide individuaalsus ja asetatakse rõhku haiguste ennetamisele nendest tekkinud tagajärgedele reageerimise asemel. Sealjuures võetakse arvesse võimalikult palju nii patsientide kui haiguste kohta teadaolevast ja ka muust meditsiinilisest teabest ning üritatakse nende vahel seoseid leida. Personaalmeditsiini üldeesmärgid on pakkuda tulevikus kõigile senisest lühema aja jooksul efektiivsemat ravi madalate kuludega.
Käesoleva töö eesmärgiks on uurida haiguste komorbiidsust Eesti populatsioonis. Töös koostatakse Eesti E-tervise Sihtasutuse 2012.-2013. aasta epikriiside andmete põhjal kõigi sama patsiendi puhul koosesinevate RHK-10 registri haiguste paaride kohta 2x2 sõltuvustabelid. Haigustevahelist võimalikku seost hinnatakse Fisheri täpse testiga, filtreeritakse välja tugevamini assotsieeritud paarid ja visualiseeritakse tulemusi nn kuumuskaartide abil. Haiguste koosesinemise uurimine on eelduseks tulevases teadustöös haigusepisoodide kaevandamisele.
Võtmesõnad:
bioinformaatika, personaalmeditsiin, epidemioloogia, haiguste komorbiidsus, RHK 10, 2x2 sõltuvustabelid, Fisheri täpne test
Abstract: Personalised medicine is a new approach to health care, in which the focus is on the individuality of patients, and disease prediction and prevention are emphasised, as opposed to only reacting to the consequences of medical disorders. As much data about the patients and diseases as possible, as well as other medical information, is taken into account while attempting to find if and how they are linked to each other. The main objective of personalised medicine is to offer more effective treatment to every patient in a shorter period of time at a lower cost in the future. The aim of this thesis is to study and analyse disease comorbidity in the Estonian population. 2x2 contingency tables are constructed about every pair of co-occurring ICD-10 diagnose codes in epicrises gathered by the Estonian E-Health Foundation in the years 2012-2013. The potential correlation between diseases is measured with Fisher’s exact test and diagnose pairs with a stronger association are filtered. The results are visualised using heat maps. Disease comorbidity analysis is a prerequisite for future research about disease episode mining. Keywords: bioinformatics, personalised medicine, epidemiology, disease comorbidity, ICD 10, 2x2 contingency tables, Fisher’s exact test
Abstract: Personalised medicine is a new approach to health care, in which the focus is on the individuality of patients, and disease prediction and prevention are emphasised, as opposed to only reacting to the consequences of medical disorders. As much data about the patients and diseases as possible, as well as other medical information, is taken into account while attempting to find if and how they are linked to each other. The main objective of personalised medicine is to offer more effective treatment to every patient in a shorter period of time at a lower cost in the future. The aim of this thesis is to study and analyse disease comorbidity in the Estonian population. 2x2 contingency tables are constructed about every pair of co-occurring ICD-10 diagnose codes in epicrises gathered by the Estonian E-Health Foundation in the years 2012-2013. The potential correlation between diseases is measured with Fisher’s exact test and diagnose pairs with a stronger association are filtered. The results are visualised using heat maps. Disease comorbidity analysis is a prerequisite for future research about disease episode mining. Keywords: bioinformatics, personalised medicine, epidemiology, disease comorbidity, ICD 10, 2x2 contingency tables, Fisher’s exact test