Influenza Vaccination Among Pregnant Women : Self-report Compared With Vaccination Data From Electronic Health Records, 2018-2020 Influenza Seasons
OBJECTIVES: Having accurate influenza vaccination coverage estimates can guide public health activities. The objectives of this study were to (1) validate the accuracy of electronic health record (EHR)-based influenza vaccination data among pregnant women compared with survey self-report and (2) assess whether survey respondents differed from survey nonrespondents by demographic characteristics and EHR-based vaccination status.
METHODS: This study was conducted in the Vaccine Safety Datalink, a network of 8 large medical care organizations in the United States. Using EHR data, we identified all women pregnant during the 2018-2019 or 2019-2020 influenza seasons. Surveys were conducted among samples of women who did and did not appear vaccinated for influenza according to EHR data. Separate surveys were conducted after each influenza season, and respondents reported their influenza vaccination status. Analyses accounted for the stratified design, sampling probability, and response probability.
RESULTS: The survey response rate was 50.5% (630 of 1247) for 2018-2019 and 41.2% (721 of 1748) for 2019-2020. In multivariable analyses combining both survey years, non-Hispanic Black pregnant women had 3.80 (95% CI, 2.13-6.74) times the adjusted odds of survey nonresponse; odds of nonresponse were also higher for Hispanic pregnant women and women who had not received (per EHR data) influenza vaccine during current or prior influenza seasons. The sensitivity, specificity, and positive predictive value of EHR documentation of influenza vaccination compared with self-report were ≥92% for both survey years combined. The negative predictive value of EHR-based influenza vaccine status was 80.5% (95% CI, 76.7%-84.0%).
CONCLUSIONS: EHR-based influenza vaccination data among pregnant women were generally concordant with self-report. New data sources and novel approaches to mitigating nonresponse bias may be needed to enhance influenza vaccination surveillance efforts.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:138 |
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| Enthalten in: |
Public health reports (Washington, D.C. : 1974) - 138(2023), 3 vom: 21. Mai, Seite 456-466 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Daley, Matthew F [VerfasserIn] |
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| Links: |
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| Themen: |
Electronic health records |
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| Anmerkungen: |
Date Completed 05.06.2023 Date Revised 12.06.2023 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1177/00333549221099932 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM34196039X |
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| 100 | 1 | |a Daley, Matthew F |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Influenza Vaccination Among Pregnant Women |b Self-report Compared With Vaccination Data From Electronic Health Records, 2018-2020 Influenza Seasons |
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| 500 | |a Date Completed 05.06.2023 | ||
| 500 | |a Date Revised 12.06.2023 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a OBJECTIVES: Having accurate influenza vaccination coverage estimates can guide public health activities. The objectives of this study were to (1) validate the accuracy of electronic health record (EHR)-based influenza vaccination data among pregnant women compared with survey self-report and (2) assess whether survey respondents differed from survey nonrespondents by demographic characteristics and EHR-based vaccination status | ||
| 520 | |a METHODS: This study was conducted in the Vaccine Safety Datalink, a network of 8 large medical care organizations in the United States. Using EHR data, we identified all women pregnant during the 2018-2019 or 2019-2020 influenza seasons. Surveys were conducted among samples of women who did and did not appear vaccinated for influenza according to EHR data. Separate surveys were conducted after each influenza season, and respondents reported their influenza vaccination status. Analyses accounted for the stratified design, sampling probability, and response probability | ||
| 520 | |a RESULTS: The survey response rate was 50.5% (630 of 1247) for 2018-2019 and 41.2% (721 of 1748) for 2019-2020. In multivariable analyses combining both survey years, non-Hispanic Black pregnant women had 3.80 (95% CI, 2.13-6.74) times the adjusted odds of survey nonresponse; odds of nonresponse were also higher for Hispanic pregnant women and women who had not received (per EHR data) influenza vaccine during current or prior influenza seasons. The sensitivity, specificity, and positive predictive value of EHR documentation of influenza vaccination compared with self-report were ≥92% for both survey years combined. The negative predictive value of EHR-based influenza vaccine status was 80.5% (95% CI, 76.7%-84.0%) | ||
| 520 | |a CONCLUSIONS: EHR-based influenza vaccination data among pregnant women were generally concordant with self-report. New data sources and novel approaches to mitigating nonresponse bias may be needed to enhance influenza vaccination surveillance efforts | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, U.S. Gov't, P.H.S. | |
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| 650 | 4 | |a misclassification | |
| 650 | 4 | |a nonresponse bias | |
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| 700 | 1 | |a Naleway, Allison L |e verfasserin |4 aut | |
| 700 | 1 | |a Jackson, Michael L |e verfasserin |4 aut | |
| 700 | 1 | |a Hambidge, Simon J |e verfasserin |4 aut | |
| 700 | 1 | |a McLean, Huong |e verfasserin |4 aut | |
| 700 | 1 | |a Kharbanda, Elyse O |e verfasserin |4 aut | |
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| 700 | 1 | |a Weintraub, Eric S |e verfasserin |4 aut | |
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| 700 | 1 | |a Razzaghi, Hilda |e verfasserin |4 aut | |
| 700 | 1 | |a Singleton, James A |e verfasserin |4 aut | |
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