scholarly journals Abstracting ICU Nursing Care Quality Data From the Electronic Health Record

2016 ◽  
Vol 39 (9) ◽  
pp. 1271-1288 ◽  
Author(s):  
Jennifer B. Seaman ◽  
Anna C. Evans ◽  
Andrea M. Sciulli ◽  
Amber E. Barnato ◽  
Susan M. Sereika ◽  
...  

The electronic health record is a potentially rich source of data for clinical research in the intensive care unit setting. We describe the iterative, multi-step process used to develop and test a data abstraction tool, used for collection of nursing care quality indicators from the electronic health record, for a pragmatic trial. We computed Cohen’s kappa coefficient (κ) to assess interrater agreement or reliability of data abstracted using preliminary and finalized tools. In assessing the reliability of study data ( n = 1,440 cases) using the finalized tool, 108 randomly selected cases (10% of first half sample; 5% of last half sample) were independently abstracted by a second rater. We demonstrated mean κ values ranging from 0.61 to 0.99 for all indicators. Nursing care quality data can be accurately and reliably abstracted from the electronic health records of intensive care unit patients using a well-developed data collection tool and detailed training.

2018 ◽  
Vol 38 (6) ◽  
pp. 23-34 ◽  
Author(s):  
Robert J. Anderson ◽  
Kathleen Sparbel ◽  
Rhonda N. Barr ◽  
Kevin Doerschug ◽  
Susan Corbridge

2018 ◽  
Vol 25 (4) ◽  
pp. 1692-1704 ◽  
Author(s):  
Mark Romig ◽  
Howard Carolan ◽  
Alan Ravitz ◽  
Hildy Schell-Chaple ◽  
Edward Yoon ◽  
...  

Project Emerge took a systems engineering approach to reduce avoidable harm in the intensive care unit. We developed a socio-technology solution to aggregate and display information relevant to preventable patient harm. We compared providers’ efficiency and ability to assess and assimilate data associated with patient-safety practice compliance using the existing electronic health record to Emerge, and evaluated for speed, accuracy, and the number of mouse clicks required. When compared to the standard electronic health record, clinicians were faster (529 ± 210 s vs 1132 ± 344 s), required fewer mouse clicks (42.3 ± 15.3 vs 101.3 ± 33.9), and were more accurate (24.8 ± 2.7 of 28 correct vs 21.2 ± 2.9 of 28 correct) when using Emerge. All results were statistically significant at a p-value < 0.05 using Wilcoxon signed-rank test ( n = 18). Emerge has the potential to make clinicians more productive and patients safer by reducing the time and errors when obtaining information to reduce preventable harm.


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