IncidencePrevalence : An R package to calculate population-level incidence rates and prevalence using the OMOP common data model
© 2023 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons Ltd..
PURPOSE: Real-world data (RWD) offers a valuable resource for generating population-level disease epidemiology metrics. We aimed to develop a well-tested and user-friendly R package to compute incidence rates and prevalence in data mapped to the observational medical outcomes partnership (OMOP) common data model (CDM).
MATERIALS AND METHODS: We created IncidencePrevalence, an R package to support the analysis of population-level incidence rates and point- and period-prevalence in OMOP-formatted data. On top of unit testing, we assessed the face validity of the package. To do so, we calculated incidence rates of COVID-19 using RWD from Spain (SIDIAP) and the United Kingdom (CPRD Aurum), and replicated two previously published studies using data from the Netherlands (IPCI) and the United Kingdom (CPRD Gold). We compared the obtained results to those previously published, and measured execution times by running a benchmark analysis across databases.
RESULTS: IncidencePrevalence achieved high agreement to previously published data in CPRD Gold and IPCI, and showed good performance across databases. For COVID-19, incidence calculated by the package was similar to public data after the first-wave of the pandemic.
CONCLUSION: For data mapped to the OMOP CDM, the IncidencePrevalence R package can support descriptive epidemiological research. It enables reliable estimation of incidence and prevalence from large real-world data sets. It represents a simple, but extendable, analytical framework to generate estimates in a reproducible and timely manner.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2024 |
|---|---|
| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:33 |
|---|---|
| Enthalten in: |
Pharmacoepidemiology and drug safety - 33(2024), 1 vom: 24. Jan., Seite e5717 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Raventós, Berta [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
Common data model |
|---|
| Anmerkungen: |
Date Completed 22.01.2024 Date Revised 22.01.2024 published: Print-Electronic Citation Status MEDLINE |
|---|
| doi: |
10.1002/pds.5717 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM363686053 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM363686053 | ||
| 003 | DE-627 | ||
| 005 | 20240122231917.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231226s2024 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1002/pds.5717 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1267.xml |
| 035 | |a (DE-627)NLM363686053 | ||
| 035 | |a (NLM)37876360 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Raventós, Berta |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a IncidencePrevalence |b An R package to calculate population-level incidence rates and prevalence using the OMOP common data model |
| 264 | 1 | |c 2024 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Completed 22.01.2024 | ||
| 500 | |a Date Revised 22.01.2024 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © 2023 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons Ltd. | ||
| 520 | |a PURPOSE: Real-world data (RWD) offers a valuable resource for generating population-level disease epidemiology metrics. We aimed to develop a well-tested and user-friendly R package to compute incidence rates and prevalence in data mapped to the observational medical outcomes partnership (OMOP) common data model (CDM) | ||
| 520 | |a MATERIALS AND METHODS: We created IncidencePrevalence, an R package to support the analysis of population-level incidence rates and point- and period-prevalence in OMOP-formatted data. On top of unit testing, we assessed the face validity of the package. To do so, we calculated incidence rates of COVID-19 using RWD from Spain (SIDIAP) and the United Kingdom (CPRD Aurum), and replicated two previously published studies using data from the Netherlands (IPCI) and the United Kingdom (CPRD Gold). We compared the obtained results to those previously published, and measured execution times by running a benchmark analysis across databases | ||
| 520 | |a RESULTS: IncidencePrevalence achieved high agreement to previously published data in CPRD Gold and IPCI, and showed good performance across databases. For COVID-19, incidence calculated by the package was similar to public data after the first-wave of the pandemic | ||
| 520 | |a CONCLUSION: For data mapped to the OMOP CDM, the IncidencePrevalence R package can support descriptive epidemiological research. It enables reliable estimation of incidence and prevalence from large real-world data sets. It represents a simple, but extendable, analytical framework to generate estimates in a reproducible and timely manner | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a OMOP | |
| 650 | 4 | |a R package | |
| 650 | 4 | |a common data model | |
| 650 | 4 | |a incidence | |
| 650 | 4 | |a prevalence | |
| 700 | 1 | |a Català, Martí |e verfasserin |4 aut | |
| 700 | 1 | |a Du, Mike |e verfasserin |4 aut | |
| 700 | 1 | |a Guo, Yuchen |e verfasserin |4 aut | |
| 700 | 1 | |a Black, Adam |e verfasserin |4 aut | |
| 700 | 1 | |a Inberg, Ger |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Xintong |e verfasserin |4 aut | |
| 700 | 1 | |a López-Güell, Kim |e verfasserin |4 aut | |
| 700 | 1 | |a Newby, Danielle |e verfasserin |4 aut | |
| 700 | 1 | |a de Ridder, Maria |e verfasserin |4 aut | |
| 700 | 1 | |a Barboza, Cesar |e verfasserin |4 aut | |
| 700 | 1 | |a Duarte-Salles, Talita |e verfasserin |4 aut | |
| 700 | 1 | |a Verhamme, Katia |e verfasserin |4 aut | |
| 700 | 1 | |a Rijnbeek, Peter |e verfasserin |4 aut | |
| 700 | 1 | |a Prieto Alhambra, Daniel |e verfasserin |4 aut | |
| 700 | 1 | |a Burn, Edward |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Pharmacoepidemiology and drug safety |d 1996 |g 33(2024), 1 vom: 24. Jan., Seite e5717 |w (DE-627)NLM091631106 |x 1099-1557 |7 nnns |
| 773 | 1 | 8 | |g volume:33 |g year:2024 |g number:1 |g day:24 |g month:01 |g pages:e5717 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1002/pds.5717 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 33 |j 2024 |e 1 |b 24 |c 01 |h e5717 | ||