The ergonomics of electronic patient records: an interdisciplinary development of methodologies for understanding and exploiting free text to enhance the utility of primary care electronic patient records. (360G-Wellcome-086105_Z_08_Z)

Electronic patient records contain a mixture of coded information and free text. We will develop generalisable methods for the identification and interrogation of potentially important data concealed in free text, use the results to enhance coded data, and evaluate the utility of this approach. Through user centred methods, we will explore what influences clinicians in the balance between recording free text vs using standard codes (e.g. 002.23 Appendicectomy), and how information needs to b e stored for it to be useful to and retrievable by clinicians. Natural Language Processing (NLP) will be used to search the free text of large quantities of anonymised free text patient records, and to enhance coded data with pseudo-codes. Statistical methods will be used to explore the impact of integrating the additional information on (a) prevalence estimates (rheumatoid arthritis), and (b) estimates of dates of first relevant presentation (ovarian cancer). A visualization tool for the int egrated graphical display of coded and NLP generated data will be developed. It will be used to validate the novel data through clinician and researcher review, and thus to explore the value of these techniques in improving the quality and accessibility of information in electronic patient records.