title: Testing of Triggers by Data Mining of Epilepsy Patients' Structured Nursing Records.
abstract: Epilepsies are neurological disorders with many different etiologies, symptoms and prognoses. Care for epilepsy patients should be uniform, homogeneous and optimized to avoid unnecessary hospitalizations or even worse outcomes. FinCC-based structured nursing documentation facilitates analyzing patient profiles and populations, developing care processes, nursing documentation, decision-making, and data reuse. This research aimed to determine the potential for finding possible risks for epilepsy patients' health and well-being from the structured nursing data with defined triggers for epilepsy patients. The research data included structured documentation of nursing diagnoses of and interventions for adult epilepsy patients (n = 100) at one neurological ward in a university hospital in 2009-2013. The results showed that nurses documented abundantly, and all triggers were mostly found. The study results will be reviewed by the neurological ward nurses to assess the FinCC and highlight the importance of documentation.
authors.affiliation: University of Eastern Finland, Department of Health and Social Management, Kuopio, Finland.
authors.forename: Ulla-Mari
authors.initials: UM
authors.lastname: Kinnunen
authors.affiliation: University of Eastern Finland, Department of Health and Social Management, Kuopio, Finland.
authors.forename: Eija
authors.initials: E
authors.lastname: Kivekäs
authors.affiliation: University of Eastern Finland, Department of Health and Social Management, Kuopio, Finland.
authors.forename: Pekka
authors.initials: P
authors.lastname: Paananen
authors.affiliation: Department of Neurology, University of Eastern Finland, Kuopio, Finland.
authors.forename: Reetta
authors.initials: R
authors.lastname: Kälviäinen
authors.affiliation: University of Eastern Finland, Department of Health and Social Management, Kuopio, Finland.
authors.forename: Kaija
authors.initials: K
authors.lastname: Saranto
mesh_terms: D000328:Adult; D015984:Causality; D057225:Data Mining / Q000379:methods*; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D004827:Epilepsy / Q000175:diagnosis* / Q000453:epidemiology*; D005260:Female; D005387:Finland / Q000453:epidemiology; D006801:Humans; D015994:Incidence; D008297:Male; D008875:Middle Aged; D009733:Nursing Diagnosis / Q000706:statistics & numerical data*; D009737:Nursing Records / Q000706:statistics & numerical data*; D011379:Prognosis; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000379:methods; D012307:Risk Factors; D012680:Sensitivity and Specificity