Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Original Article
  • Published:

Evaluation of identifier field agreement in linked neonatal records

Abstract

Objective:

To better address barriers arising from missing and unreliable identifiers in neonatal medical records, we evaluated agreement and discordance among traditional and non-traditional linkage fields within a linked neonatal data set.

Study Design:

The retrospective, descriptive analysis represents infants born from 2013 to 2015. We linked children’s hospital neonatal physician billing records to newborn medical records originating from an academic delivery hospital and evaluated rates of agreement, discordance and missingness for a set of 12 identifier field pairs used in the linkage algorithm.

Results:

We linked 7293 of 7404 physician billing records (98.5%), all of which were deemed valid upon manual review. Linked records contained a mean of 9.1 matching and 1.6 non-matching identifier pairs. Only 4.8% had complete agreement among all 12 identifier pairs.

Conclusion:

Our approach to selection of linkage variables and data formatting preparatory to linkage have generalizability, which may inform future neonatal and perinatal record linkage efforts.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1

Similar content being viewed by others

References

  1. Weber GM, Mandl KD, Kohane IS . Finding the missing link for big biomedical data. JAMA 2014; 311 (24): 2479–2480.

    CAS  PubMed  Google Scholar 

  2. Vatsalan D, Christen P, Verykios VS . A taxonomy of privacy-preserving record linkage techniques. Inf Syst 2013; 38 (6): 946–969.

    Article  Google Scholar 

  3. Li B, Quan HD, Fong A, Lu MS . Assessing record linkage between health care and Vital statistics databases using deterministic methods. BMC Health Serv Res 2006; 6: 48.

    Article  Google Scholar 

  4. Dufendach KR, Lehmann CU . Topics in neonatal informatics: essential functionalities of the neonatal electronic health record. Neoreviews 2015; 16 (12): e668–e673.

    Article  Google Scholar 

  5. Delnord M, Szamotulska K, Hindori-Mohangoo AD, Blondel B, Macfarlane AJ, Dattani N et al. Linking databases on perinatal health: a review of the literature and current practices in Europe. Eur J Public Health 2016; 26 (3): 422–430.

    Article  CAS  Google Scholar 

  6. Herman A, McCarthy B, Bakewell J, Ward R, Mueller B, Maconochie N et al. Data linkage methods used in maternally-linked birth and infant death surveillance data sets from the United States (Georgia, Missouri, Utah and Washington State), Israel, Norway, Scotland and Western Australia. Paediatr Perinat Epidemiol 1997; 11 (S1): 5–22.

    Article  Google Scholar 

  7. Kotelchuck M, Hoang L, Stern JE, Diop H, Belanoff C, Declercq E . The MOSART database: linking the SART CORS clinical database to the population-based Massachusetts PELL reproductive public health data system. Matern Child Health J 2014; 18 (9): 2167–2178.

    Article  Google Scholar 

  8. Baldwin E, Johnson K, Berthoud H, Dublin S . Linking mothers and infants within electronic health records: a comparison of deterministic and probabilistic algorithms. Pharmacoepidemiol Drug Saf 2015; 24 (1): 45–51.

    Article  Google Scholar 

  9. Spooner SA Council on Clinical Information Technology, AAoP. Special requirements of electronic health record systems in pediatrics. Pediatrics 2007; 119 (3):631–637.

    Article  Google Scholar 

  10. Adelman J, Aschner J, Schechter C, Angert R, Weiss J, Rai A et al. Use of temporary names for newborns and associated risks. Pediatrics 2015; 136 (2): 327–333.

    Article  Google Scholar 

  11. Gray JE, Suresh G, Ursprung R, Edwards WH, Nickerson J, Shiono PH et al. Patient misidentification in the neonatal intensive care unit: quantification of risk. Pediatrics 2006; 117 (1): e43–e47.

    Article  Google Scholar 

  12. Hall ES, Goyal NK, Ammerman RT, Miller MM, Jones DE, Short JA et al. Development of a linked perinatal data resource from state administrative and community-based program data. Matern Child Health J 2014; 18 (1): 316–325.

    Article  Google Scholar 

  13. Seske LM, Muglia LJ, Hall ES, Bove KE, Greenberg JM . Infant mortality, cause of death, and vital records reporting in Ohio, United States. Matern Child Health J 2017; 21 (4): 727–733.

    Article  Google Scholar 

  14. Hall ES, Venkatesh M, Greenberg JM . A population study of first and subsequent pregnancy smoking behaviors in Ohio. J Perinatol 2016; 36 (11): 948–953.

    Article  CAS  Google Scholar 

  15. Goyal NK, Folger AT, Hall ES, Ammerman RT, Van Ginkel JB, Pickler RS . Effects of home visiting and maternal mental health on use of the emergency department among late preterm infants. J Obstet Gynecol Neonatal Nurs 2015; 44 (1): 135–144.

    Article  Google Scholar 

  16. Goyal NK, Hall ES, Jones DE, Meinzen-Derr JK, Short JA, Ammerman RT et al. Association of maternal and community factors with enrollment in home visiting among at-risk, first-time mothers. Am J Public Health 2014; 104 (Suppl 1): S144–S151.

    Article  Google Scholar 

  17. Goyal NK, Hall ES, Meinzen-Derr JK, Kahn RS, Short JA, Van Ginkel JB et al. Dosage effect of prenatal home visiting on pregnancy outcomes in at-risk, first-time mothers. Pediatrics 2013; 132 (Suppl 2): S118–S125.

    Article  Google Scholar 

  18. Russell RC . Index. US Patent 1,261,167. 1918.

  19. Cheung VY, Bocking AD, Dasilva OP . Preterm discordant twins: what birth weight difference is significant? Am J Obstet Gynecol 1995; 172 (3): 955–959.

    Article  CAS  Google Scholar 

  20. Philips L . Hanging on the metaphone. Comput Lang 1990; 7 (12): 38–43.

    Google Scholar 

  21. Winkler WE The State of Record Linkage and Current Research Problems. US Census Bureau: Washington DC, 1999..

Download references

Acknowledgements

DISCLAIMER

The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

This work was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health through the Center for Clinical and Translational Science and Training at the University of Cincinnati (5UL1TR001425-02) and the Cincinnati Children’s Research Foundation Academic and Research Committee.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to E S Hall.

Ethics declarations

Competing interests

The authors declare no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hall, E., Marsolo, K. & Greenberg, J. Evaluation of identifier field agreement in linked neonatal records. J Perinatol 37, 969–974 (2017). https://doi.org/10.1038/jp.2017.70

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/jp.2017.70

This article is cited by

Search

Quick links