AdherenceFromOMOP: A Software Package for Secondary Adherence Measurement on OMOP Standardized Health Data
Name
Johannes Holm
Abstract
Medication adherence is a concept that measures how well a person follows their prescribed medication regimen. It is particularly important for chronic diseases, where the effectiveness of treatment largely depends on the consistency and persistence of the medication use. Low medication adherence in the general population is a multidimensional problem that greatly affects both public health and the global economy. To solve this problem, it is necessary to establish a standard for measuring both the current situation and proposed solutions' effects. There are various methods for measuring medication adherence, but given the current trend of digitizing health data over the last decade, secondary database analysis using standardized electronic health data could be applied to measure adherence in large samplesets/population. One observational health data standard is the OMOP common data model, which makes it possible for various institutions to conduct cooperative research. The main objective of the thesis was to create a software package that measures medication adherence in a sample using OMOP standardized health data. The secondary objective was to utilize said package to find the current situation of medication adherence in Estonia, using 10% of the Estonian population's outpatient records from 2016-2019 obtained through random sampling. Based on the secondary objective, adherence was compared by gender, age groups, and the used medication groups. All the observed characteristics played a statistically significant role in determining medication adherence. The adherence rate of female medication users was statistically higher, and age also had a positive effect on adherence until a very old age. To demonstrate the possibilities of the package the change in medication adherence over a short observation period was also examined as well as adherence rates for people with depression diagnosis. The created package is functional and creates prerequisites for further research. Continued development of the package is carried out by the University of Tartu's health informatics research group, and it is hoped that in the future, it will also be applied to OMOP data by other institutions.
Graduation Thesis language
Estonian
Graduation Thesis type
Master - Conversion Master in IT
Supervisor(s)
Raivo Kolde, Marek Oja
Defence year
2023