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Observational Study
. 2020 Dec;68(12):2965-2967.
doi: 10.1111/jgs.16831. Epub 2020 Sep 20.

RESEARCHComparing Strategies for Identifying Falls in Older Adult Emergency Department Visits Using EHR Data

Affiliations
Observational Study

RESEARCHComparing Strategies for Identifying Falls in Older Adult Emergency Department Visits Using EHR Data

Brian W Patterson et al. J Am Geriatr Soc. 2020 Dec.
No abstract available

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Conflict of interest statement

STATEMENTS OF CONFLICTS OF INTEREST: No conflicts of interest to declare

References

    1. Patterson BW, Jacobsohn GC, Shah MN, et al. Development and validation of a pragmatic natural language processing approach to identifying falls in older adults in the emergency department. BMC Med Inform Decis Mak. 2019;19(1):138. - PMC - PubMed
    1. Velupillai S, Suominen H, Liakata M, et al. Using clinical Natural Language Processing for health outcomes research: Overview and actionable suggestions for future advances. Journal of biomedical informatics. 2018;88. - PMC - PubMed
    1. Kaggal VC, Elayavilli RK, Mehrabi S, et al. Toward a Learning Health-care System – Knowledge Delivery at the Point of Care Empowered by Big Data and NLP. Biomed Inform Insights. 2016;8(Suppl 1):13–22. - PMC - PubMed
    1. Hoffman GJ, Hays RD, Shapiro M, Wallace SP, Ettner SL. Claims-Based Identification Methods and the Cost of Fall-related Injuries among U.S. Older Adults. Med Care. 2016;54(7):664–671. - PMC - PubMed
    1. Kim SB, Zingmond DS, Keeler EB, et al. Development of an algorithm to identify fall-related injuries and costs in Medicare data. Inj Epidemiol. 2016;3:1. - PMC - PubMed

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