Using pooled electronic health records data to conduct pharmacoepidemiology safety studies : Challenges and lessons learned
© 2023 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons Ltd..
PURPOSE: We assessed the suitability of pooled electronic health record (EHR) data from clinical research networks (CRNs) of the patient-centered outcomes research network to conduct studies of the association between tumor necrosis factor inhibitors (TNFi) and infections.
METHODS: EHR data from patients with one of seven autoimmune diseases were obtained from three CRNs and pooled. Person-level linkage of CRN data and Centers for Medicare and Medicaid Services (CMS) fee-for-service claims data was performed where possible. Using filled prescriptions from CMS claims data as the gold standard, we assessed the misclassification of EHR-based new (incident) user definitions. Among new users of TNFi, we assessed subsequent rates of hospitalized infection in EHR and CMS data.
RESULTS: The study included 45 483 new users of TNFi, of whom 1416 were successfully linked to their CMS claims. Overall, 44% of new EHR TNFi prescriptions were not associated with medication claims. Our most specific new user definition had a misclassification rate of 3.5%-16.4% for prevalent use, depending on the medication. Greater than 80% of CRN prescriptions had either zero refills or missing refill data. Compared to using EHR data alone, there was a 2- to 8-fold increase in hospitalized infection rates when CMS claims data were added to the analysis.
CONCLUSIONS: EHR data substantially misclassified TNFi exposure and underestimated the incidence of hospitalized infections compared to claims data. EHR-based new user definitions were reasonably accurate. Overall, using CRN data for pharmacoepidemiology studies is challenging, especially for biologics, and would benefit from supplementation by other sources.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:32 |
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| Enthalten in: |
Pharmacoepidemiology and drug safety - 32(2023), 9 vom: 02. Sept., Seite 969-977 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Beukelman, Timothy [VerfasserIn] |
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| Links: |
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| Themen: |
Biological therapy |
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| Anmerkungen: |
Date Completed 08.08.2023 Date Revised 02.11.2023 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1002/pds.5627 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM355105527 |
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| 100 | 1 | |a Beukelman, Timothy |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Using pooled electronic health records data to conduct pharmacoepidemiology safety studies |b Challenges and lessons learned |
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| 500 | |a Date Revised 02.11.2023 | ||
| 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: We assessed the suitability of pooled electronic health record (EHR) data from clinical research networks (CRNs) of the patient-centered outcomes research network to conduct studies of the association between tumor necrosis factor inhibitors (TNFi) and infections | ||
| 520 | |a METHODS: EHR data from patients with one of seven autoimmune diseases were obtained from three CRNs and pooled. Person-level linkage of CRN data and Centers for Medicare and Medicaid Services (CMS) fee-for-service claims data was performed where possible. Using filled prescriptions from CMS claims data as the gold standard, we assessed the misclassification of EHR-based new (incident) user definitions. Among new users of TNFi, we assessed subsequent rates of hospitalized infection in EHR and CMS data | ||
| 520 | |a RESULTS: The study included 45 483 new users of TNFi, of whom 1416 were successfully linked to their CMS claims. Overall, 44% of new EHR TNFi prescriptions were not associated with medication claims. Our most specific new user definition had a misclassification rate of 3.5%-16.4% for prevalent use, depending on the medication. Greater than 80% of CRN prescriptions had either zero refills or missing refill data. Compared to using EHR data alone, there was a 2- to 8-fold increase in hospitalized infection rates when CMS claims data were added to the analysis | ||
| 520 | |a CONCLUSIONS: EHR data substantially misclassified TNFi exposure and underestimated the incidence of hospitalized infections compared to claims data. EHR-based new user definitions were reasonably accurate. Overall, using CRN data for pharmacoepidemiology studies is challenging, especially for biologics, and would benefit from supplementation by other sources | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a biological therapy | |
| 650 | 4 | |a electronic health records | |
| 650 | 4 | |a infections | |
| 650 | 4 | |a pharmacoepidemiology | |
| 700 | 1 | |a Chen, Lang |e verfasserin |4 aut | |
| 700 | 1 | |a Annapureddy, Narender |e verfasserin |4 aut | |
| 700 | 1 | |a Oates, Jim |e verfasserin |4 aut | |
| 700 | 1 | |a Clowse, Megan E B |e verfasserin |4 aut | |
| 700 | 1 | |a Long, Millie |e verfasserin |4 aut | |
| 700 | 1 | |a Kappelman, Michael D |e verfasserin |4 aut | |
| 700 | 1 | |a Rhee, Rennie L |e verfasserin |4 aut | |
| 700 | 1 | |a Merkel, Peter A |e verfasserin |4 aut | |
| 700 | 1 | |a Nowell, William Benjamin |e verfasserin |4 aut | |
| 700 | 1 | |a Xie, Fenglong |e verfasserin |4 aut | |
| 700 | 1 | |a Clinton, Cassie |e verfasserin |4 aut | |
| 700 | 1 | |a Curtis, Jeffrey R |e verfasserin |4 aut | |
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