A comparison of methods to identify antenatal substance use within electronic health records

doi:10.1016/j.ajogmf.2021.100535

. 2022 Mar;4(2):100535.

doi: 10.1016/j.ajogmf.2021.100535. Epub 2021 Nov 19.

A comparison of methods to identify antenatal substance use within electronic health records

Leigh Anne Tang¹, Alvin D Jeffery², Ashley A Leech³, Sarah S Osmundson⁴, Lori Schirle², Julia C Phillippi²

Affiliations

¹ Department of Biomedical Informatics, Vanderbilt University Medical Center, 2525 West End Ave. (Suite 1475), Nashville, TN, 37203. Electronic address: leigh.anne.tang@vumc.org.
² School of Nursing, Vanderbilt University, Nashville, TN.
³ Department of Health Policy, Vanderbilt University School of Medicine, Nashville, TN; Vanderbilt Center for Child Health Policy, Vanderbilt University Medical Center, Nashville, TN.
⁴ Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, TN.

PMID: 34808402
PMCID: PMC8893715
DOI: 10.1016/j.ajogmf.2021.100535

A comparison of methods to identify antenatal substance use within electronic health records

Leigh Anne Tang et al. Am J Obstet Gynecol MFM. 2022 Mar.

. 2022 Mar;4(2):100535.

doi: 10.1016/j.ajogmf.2021.100535. Epub 2021 Nov 19.

Authors

Leigh Anne Tang¹, Alvin D Jeffery², Ashley A Leech³, Sarah S Osmundson⁴, Lori Schirle², Julia C Phillippi²

Affiliations

¹ Department of Biomedical Informatics, Vanderbilt University Medical Center, 2525 West End Ave. (Suite 1475), Nashville, TN, 37203. Electronic address: leigh.anne.tang@vumc.org.
² School of Nursing, Vanderbilt University, Nashville, TN.
³ Department of Health Policy, Vanderbilt University School of Medicine, Nashville, TN; Vanderbilt Center for Child Health Policy, Vanderbilt University Medical Center, Nashville, TN.
⁴ Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, TN.

PMID: 34808402
PMCID: PMC8893715
DOI: 10.1016/j.ajogmf.2021.100535

No abstract available

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Conflict of interest statement

Disclosure:

The authors report no conflicts of interest.

Figures

**Figure 1:**
Charts detected with ICD codes and/or keywords. Solid bars represent the number and positive predictive value of 1, 2, or 3 ICD codes and/or keywords detected by natural language processing as verified by chart review (N = 120). Hashed bars represent the number and percentage of confirmed positive cases detected by each ICD code and/or keyword criteria (N = 102).

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References

1. Haight SC. Opioid Use Disorder Documented at Delivery Hospitalization — United States, 1999–2014. MMWR Morb Mortal Wkly Rep 2018;67. doi:10.15585/mmwr.mm6731a1 - DOI - PMC - PubMed
1. Ghitza UE, Gore-Langton RE, Lindblad R, Shide D, Subramaniam G, Tai B. Common data elements for substance use disorders in electronic health records: the NIDA Clinical Trials Network experience. Addiction 2013;108(1):3–8. doi:10.1111/j.1360-0443.2012.03876.x - DOI - PubMed
1. Ridgway JP, Uvin A, Schmitt J, et al. Natural Language Processing of Clinical Notes to Identify Mental Illness and Substance Use Among People Living with HIV: Retrospective Cohort Study. JMIR Medical Informatics 2021;9(3):e23456. doi:10.2196/23456 - DOI - PMC - PubMed
1. Chapman BE, Lee S, Kang HP, Chapman WW. Document-level classification of CT pulmonary angiography reports based on an extension of the ConText algorithm. J Biomed Inform 2011;44(5):728–737. doi:10.1016/j.jbi.2011.03.011 - DOI - PMC - PubMed
1. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 2009;42(2):377–381. doi:10.1016/j.jbi.2008.08.010 - DOI - PMC - PubMed

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[1] Haight SC. Opioid Use Disorder Documented at Delivery Hospitalization — United States, 1999–2014. MMWR Morb Mortal Wkly Rep 2018;67. doi:10.15585/mmwr.mm6731a1 - DOI - PMC - PubMed

[2] Haight SC. Opioid Use Disorder Documented at Delivery Hospitalization — United States, 1999–2014. MMWR Morb Mortal Wkly Rep 2018;67. doi:10.15585/mmwr.mm6731a1 - DOI - PMC - PubMed

[3] Ghitza UE, Gore-Langton RE, Lindblad R, Shide D, Subramaniam G, Tai B. Common data elements for substance use disorders in electronic health records: the NIDA Clinical Trials Network experience. Addiction 2013;108(1):3–8. doi:10.1111/j.1360-0443.2012.03876.x - DOI - PubMed

[4] Ghitza UE, Gore-Langton RE, Lindblad R, Shide D, Subramaniam G, Tai B. Common data elements for substance use disorders in electronic health records: the NIDA Clinical Trials Network experience. Addiction 2013;108(1):3–8. doi:10.1111/j.1360-0443.2012.03876.x - DOI - PubMed

[5] Ridgway JP, Uvin A, Schmitt J, et al. Natural Language Processing of Clinical Notes to Identify Mental Illness and Substance Use Among People Living with HIV: Retrospective Cohort Study. JMIR Medical Informatics 2021;9(3):e23456. doi:10.2196/23456 - DOI - PMC - PubMed

[6] Ridgway JP, Uvin A, Schmitt J, et al. Natural Language Processing of Clinical Notes to Identify Mental Illness and Substance Use Among People Living with HIV: Retrospective Cohort Study. JMIR Medical Informatics 2021;9(3):e23456. doi:10.2196/23456 - DOI - PMC - PubMed

[7] Chapman BE, Lee S, Kang HP, Chapman WW. Document-level classification of CT pulmonary angiography reports based on an extension of the ConText algorithm. J Biomed Inform 2011;44(5):728–737. doi:10.1016/j.jbi.2011.03.011 - DOI - PMC - PubMed

[8] Chapman BE, Lee S, Kang HP, Chapman WW. Document-level classification of CT pulmonary angiography reports based on an extension of the ConText algorithm. J Biomed Inform 2011;44(5):728–737. doi:10.1016/j.jbi.2011.03.011 - DOI - PMC - PubMed

[9] Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 2009;42(2):377–381. doi:10.1016/j.jbi.2008.08.010 - DOI - PMC - PubMed

[10] Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 2009;42(2):377–381. doi:10.1016/j.jbi.2008.08.010 - DOI - PMC - PubMed

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A comparison of methods to identify antenatal substance use within electronic health records

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A comparison of methods to identify antenatal substance use within electronic health records

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