Dataset Information

Trajectories: a framework for detecting temporal clinical event sequences from health data standardized to the Observational Medical Outcomes Partnership (OMOP) Common Data Model.

ABSTRACT:

Objective

To develop a framework for identifying temporal clinical event trajectories from Observational Medical Outcomes Partnership-formatted observational healthcare data.

Materials and methods

A 4-step framework based on significant temporal event pair detection is described and implemented as an open-source R package. It is used on a population-based Estonian dataset to first replicate a large Danish population-based study and second, to conduct a disease trajectory detection study for type 2 diabetes patients in the Estonian and Dutch databases as an example.

Results

As a proof of concept, we apply the methods in the Estonian database and provide a detailed breakdown of our findings. All Estonian population-based event pairs are shown. We compare the event pairs identified from Estonia to Danish and Dutch data and discuss the causes of the differences. The overlap in the results was only 2.4%, which highlights the need for running similar studies in different populations.

Conclusions

For the first time, there is a complete software package for detecting disease trajectories in health data.

SUBMITTER: Kunnapuu K

PROVIDER: S-EPMC9097714 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

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Publications

Trajectories: a framework for detecting temporal clinical event sequences from health data standardized to the Observational Medical Outcomes Partnership (OMOP) Common Data Model.

Künnapuu Kadri K Ioannou Solomon S Ligi Kadri K Kolde Raivo R Laur Sven S Vilo Jaak J Rijnbeek Peter R PR Reisberg Sulev S

JAMIA open 20220316 1

<h4>Objective</h4>To develop a framework for identifying temporal clinical event trajectories from Observational Medical Outcomes Partnership-formatted observational healthcare data.<h4>Materials and methods</h4>A 4-step framework based on significant temporal event pair detection is described and implemented as an open-source R package. It is used on a population-based Estonian dataset to first replicate a large Danish population-based study and second, to conduct a disease trajectory detection ...[more]

PMID: 35571357

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Dataset Information

Trajectories: a framework for detecting temporal clinical event sequences from health data standardized to the Observational Medical Outcomes Partnership (OMOP) Common Data Model.

Objective

Materials and methods

Results

Conclusions

Publications

Trajectories: a framework for detecting temporal clinical event sequences from health data standardized to the Observational Medical Outcomes Partnership (OMOP) Common Data Model.

Similar Datasets

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