Reusability of EMR data for applying cubbin and Jackson pressure ulcer risk assessment scale in critical care patients

Eunkyung Kim, Mona Choi, Ju Hee Lee, Young Ah Kim

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Objectives: The purposes of this study were to examine the predictive validity of the Cubbin and Jackson pressure ulcer risk assessment scale for the development of pressure ulcers in intensive care unit (ICU) patients retrospectively and to evaluate the reusability of Electronic Medical Records (EMR) data. Methods: A retrospective design was used to examine 829 cases admitted to four ICUs in a tertiary care hospital from May 2010 to April 2011. Patients who were without pressure ulcers at admission to ICU, 18 years or older, and had stayed in ICU for 24 hours or longer were included. Sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve (AUC) were calculated. Results: The reported incidence rate of pressure ulcers among the study subjects was 14.2%. At the cut-off score of 24 of the Cubbin and Jackson scale, the sensitivity, specificity, positive predictive value, negative predictive value, and AUC were 72.0%, 68.8%, 27.7%, 93.7%, and 0.76, respectively. Eight items out 10 of the Cubbin and Jackson scale were readily available in the EMR data. Conclusions: The Cubbin and Jackson scale performed slightly better than the Braden scale to predict pressure ulcer development. Eight items of the Cubbin and Jackson scale except mobility and hygiene can be extracted from the EMR, which initially demonstrated the reusability of EMR data for pressure ulcer risk assessment. If the Cubbin and Jackson scale is a part of the EMR assessment form, it would help nurses perform tasks to effectively prevent pressure ulcers with an EMR alert for high-risk patients.

Original languageEnglish
Pages (from-to)261-270
Number of pages10
JournalHealthcare Informatics Research
Volume19
Issue number4
DOIs
Publication statusPublished - 2013 Dec 1

    Fingerprint

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

Cite this