Repeatable process for extracting health data from HL7 CDA documents.

Objective: This study aims to address the gap in the literature on converting real-world Clinical Document Architecture (CDA) data into the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM), focusing on the initial steps preceding the mapping phase. We highlight the importance of a repeatable Extract-Transform-Load (ETL) pipeline for health data extraction from HL7 CDA documents in Estonia for research purposes.

Methods: We developed a repeatable ETL pipeline to facilitate the extraction, cleaning, and restructuring of health data from CDA documents to OMOP CDM, ensuring a high-quality and structured data format.

Mutant-selective AKT inhibition through lysine targeting and neo-zinc chelation.

Somatic alterations in the oncogenic kinase AKT1 have been identified in a broad spectrum of solid tumours. The most common AKT1 alteration replaces Glu17 with Lys (E17K) in the regulatory pleckstrin homology domain, resulting in constitutive membrane localization and activation of oncogenic signalling. In clinical studies, pan-AKT inhibitors have been found to cause dose-limiting hyperglycaemia, which has motivated the search for mutant-selective inhibitors.

Markov modeling for cost-effectiveness using federated health data network.

Objective: To introduce 2 R-packages that facilitate conducting health economics research on OMOP-based data networks, aiming to standardize and improve the reproducibility, transparency, and transferability of health economic models.

Materials And Methods: We developed the software tools and demonstrated their utility by replicating a UK-based heart failure data analysis across 5 different international databases from Estonia, Spain, Serbia, and the United States.

Results: We examined treatment trajectories of 47 163 patients.

Transforming Estonian health data to the Observational Medical Outcomes Partnership (OMOP) Common Data Model: lessons learned.

Objective: To describe the reusable transformation process of electronic health records (EHR), claims, and prescriptions data into Observational Medical Outcome Partnership (OMOP) Common Data Model (CDM), together with challenges faced and solutions implemented.

Materials And Methods: We used Estonian national health databases that store almost all residents' claims, prescriptions, and EHR records. To develop and demonstrate the transformation process of Estonian health data to OMOP CDM, we used a 10% random sample of the Estonian population ( = 150 824 patients) from 2012 to 2019 (MAITT dataset).

Prevaccination Prevalence of Type-Specific Human Papillomavirus Infection by Grade of Cervical Cytology in Estonia.

Importance: Large-scale data on type-specific human papillomavirus (HPV) prevalence and disease burden worldwide are needed to guide cervical cancer prevention efforts. Promoting the research and application of health care big data has become a key factor in modern medical research.

Objective: To examine the prevaccination prevalence of high-risk HPV (hrHPV) and type distribution by cervical cytology grade in Estonia.