From Individual EHR Maintenance to Generalised Findings: Experiments for Application of NLP to Patient-Related Texts

  • Galia Angelova
  • Dimitar Tcharaktchiev
  • Svetla Boytcheva
  • Ivelina Nikolova
  • Hristo Dimitrov
  • Zhivko Angelov
Part of the Studies in Computational Intelligence book series (SCI, volume 473)


Experiments in automatic analysis of free texts in Bulgarian hospital discharge letters are presented. Natural Language Processing (NLP) has been applied to medical texts since decades but high-quality results have been demonstrated only recently. The progress in automatic text analysis opens new directions for secondary use of Electronic Health Records (EHR). It enables also the design and development of software systems which provide better patient access to his/her health records as well as better maintenance of large EHR archives. We report about successful extraction of important patient-related entities from hospital EHR texts and consider several scenarios for application of NLP modules in healthcare software systems.


Information Extraction AI in Health Informatics 


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  1. 1.
    Meystre, S., Savova, G., Kipper-Schuler, K., Hurdle, J.F.: Extracting Information from Textual Documents in the EHR: A Review of Recent Research. In: Geissbuhler, A., Kulikowski, C. (eds.) IMIA Yearbook of Medical Informatics, pp. 138–154 (2008)Google Scholar
  2. 2.
    Demner-Fushman, D., Chapman, W., McDonald, C.: What can NLP do for Clinical Decision Support? J. of Biomedical Informatics 42(5), 760–772 (2009)CrossRefGoogle Scholar
  3. 3.
    Patrick, J., Li, M.: A Cascade Approach to Extracting Medication Events. In: Proc. Australian Language Technology Workshop (ALTA), pp. 99–103 (2009)Google Scholar
  4. 4.
    Halgrim, S., Xia, F., Solti, I., Cadag, E., Uzuner, Ö.: Extracting Medication Information from Discharge Summaries. In: Louhi 2010, Proc. of the NAACL HLT 2010 Second Louhi Workshop on Text and Data Mining of Health Documents, pp. 61–67 (2010)Google Scholar
  5. 5.
    Xu, H., Stenner, S., Doan, S., Johnson, K., Waitman, L., Denny, J.: MedEx: a Medication Information Extraction System for Clinical Narratives. J. Am. Med. Informatics Assoc. (17), 19–24 (2010)Google Scholar
  6. 6.
    Pestian, J., Brew, C., Matykiewicz, P., Hovermale, D.J., Johnson, N., Cohen, K.B., et al.: A Shared Task Involving Multi-label Classification of Clinical Free Text. In: ACL 2007 Workshop on Biological, Translational, and Clinical Language Processing (BioNLP 2007), Prague, pp. 36–40 (2007)Google Scholar
  7. 7.
    UMLS, the Unified Medical Language System,
  8. 8.
    Savova, G., Ogren, P., Duffy, P., Buntrock, J., Chute, C.: Mayo Clinic NLP System for Patient Smoking Status Identification. J. Am. Med. Inform. Assoc. 15, 25–28 (2008)CrossRefGoogle Scholar
  9. 9.
    Zhou, L., Hripcsak, G.: Temporal Reasoning with Medical Data - a Review with Emphasis on Medical NLP. J. Biom. Informatics 40(2), 183–202 (2007)CrossRefGoogle Scholar
  10. 10.
    Adlassnig, K.-P., Combi, C., Das, A., Keravnou, E., Pozzi, G.: Temporal Representation and Reasoning in Medicine: Research Directions and Challenges. AI in Medicine 38(2), 101–113 (2006)Google Scholar
  11. 11.
    Savova, G., Bethard, S., Styler, W., Martin, J., Palmer, M., Masanz, J., Ward, W.: Towards Temporal Relation Discovery from the Clinical Narrative. In: Proc. AMIA Annual Symposium 2009, pp. 568–572 (2009)Google Scholar
  12. 12.
    Nikolova, I., Dimitrov, H., Tcharaktchiev, D.: Ethics and Security in Text Mining of Patient Records in Bulgarian: the EVTIMA Solution. In: ACM Proceedings of CompSysTech (2010)Google Scholar
  13. 13.
    Tcharaktchiev, D., Angelova, G., Boytcheva, S., Angelov, Z., Zacharieva, S.: Completion of Structured Patient Descriptions by Semantic Mining. In: Koutkias, V., Niès, J., Jensen, S., Maglaveras, N., Beuscart, R. (eds.) Studies in Health Technology and Informatics, vol. 166, pp. 260–269. IOS Press (2011)Google Scholar
  14. 14.
    Boytcheva, S.: Shallow Medication Extraction from Hospital Patient Records. In: Koutkias, V., Nies, J., Jensen, S., Maglaveras, N., Beuscart, R. (eds.) Studies in Health Technology and Informatics, vol. 166, pp. 119–128. IOS Press (2011)Google Scholar
  15. 15.
    Boytcheva, S., Tcharaktchiev, D., Angelova, G.: Contextualization in Automatic Extraction of Drugs from Hospital Patient Records. In: Moen, A., et al. (eds.) Proc. of MIE-2011, the 23rd Int. Conf. of EFMI, Studies in Health Technology and Informatics, Norway, vol. 169, pp. 527–531. IOS Press (August 2011)Google Scholar
  16. 16.
    Boytcheva, S.: Automatic Matching of ICD-10 Codes to Diagnoses in Discharge Letters. In: Proc. of Biomedical NLP Workshop, Satellite Event of Int. Conf. RANLP 2011, pp. 19–26 (2011),
  17. 17.
    Boytcheva, S., Nikolova, I., Paskaleva, E., Angelova, G., Tcharaktchiev, D., Dimitrova, N.: Obtaining Status Descriptions via Automatic Analysis of Hospital Patient Records. Special Issue on Semantic IT of Informatica, Int. J. of Computing and Informatics (Slovenia) 34(4), 269–278 (2010); Fomichov, V. (ed.)Google Scholar
  18. 18.
    Boytcheva, S., Angelova, G., Nikolova, I.: Automatic Analysis of Patient History Episodes in Bulgarian Hospital Discharge Letters. In: Proc. Demonstrations at the EACL 2012, pp. 77–81. ACL, France (2012), Google Scholar
  19. 19.
    Nikolova, I.: Unified Extraction of Health Condition Descriptions. In: Proc. of the NAACL HLT 2012 Student Research Workshop, pp. 23–28. ACL, Montreal (2012), Google Scholar
  20. 20.
    Ivanov, L., Ganova-Yolovska, M., Konstantinov, B.: Quality of Coding and Reliability of Medical Information for Distribution of Financial Resources into Diagnostically-related Groups. Social Medicine 4, 32–34 (1999) (in Bulgarian)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Galia Angelova
    • 1
  • Dimitar Tcharaktchiev
    • 2
  • Svetla Boytcheva
    • 1
    • 3
  • Ivelina Nikolova
    • 1
  • Hristo Dimitrov
    • 2
  • Zhivko Angelov
    • 1
  1. 1.Institute of Information and Communication TechnologiesBulgarian Academy of SciencesSofiaBulgaria
  2. 2.University Specialised Hospital for Active Treatment of Endocrinology ”Acad. I. Penchev” (USHATE)Medical UniversitySofiaBulgaria
  3. 3.American University in BulgariaBlagoevgradBulgaria

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