A smart decision: smartphone use for operative data collection in arthroscopic shoulder instability surgery. (12th June 2019)

• Record Type: Journal Article
• Authors: Mohr, Jill; Strnad, Gregory J; Farrow, Lutul; Heinlein, Kate; Hettrich, Carolyn M; Jones, Morgan H; Miniaci, Anthony; Ricchetti, Eric; Rosneck, James; Schickendantz, Mark; Saluan, Paul; Vega, Jose F; Spindler, Kurt P
• Is Part Of: Journal of the American Medical Informatics Association. Volume 26:Number 10(2019)
• Page Start: 1030
• Page End: 1036
• Publication Date: 2019-06-12
• Subjects: smartphone -- electronic medical record -- information standardization -- shoulder instability -- outcomes; Medical informatics -- Periodicals; Information Services -- Periodicals; Medical Informatics -- Periodicals; Médecine -- Informatique -- Périodiques; Informatica; Geneeskunde; Informatique médicale; Computer network resources; Electronic journals; 610.285
• DOI: 10.1093/jamia/ocz074
• Languages: English
• ISSNs: 1067-5027

Abstract

Abstract: Objective: This study tested validity, accuracy, and efficiency of the Orthopaedic Minimal Data Set Episode of Care (OME) compared with traditional operative report in arthroscopic surgery for shoulder instability. As of November 2017, OME had successfully captured baseline data on 97% of 18 700 eligible cases. Materials and Methods: This study analyzes 100 cases entered into OME through smartphones by 12 surgeons at an institution from February to October 2015. A blinded reviewer extracted the same variables from operative report into a separate database. Completion rates and agreement were compared. They were assessed using raw percentages and McNemar's test (with continuity correction). Agreement between nominal variables was assessed by unweighted Cohen's kappa and a concordance correlation coefficient measured agreement between continuous variables. Efficiency was assessed by median time to complete. Results: Of 37 variables, OME demonstrated equal or higher completion rates for all but 1 and had significantly higher capture rates for 49% (n = 18; P < .05). Of 33 nominal variables, raw proportional agreement was ≥0.90 for 76% (n = 25). Raw proportional agreement was perfect for 15% (n = 5); no agreement statistic could be calculated due to a single variable in operative note and OME. Calculated agreement statistic was substantial or better (κ > 0.61) for 51% (n = 17) for the 33 nominal variables. All continuous variables assessed (n = 4) demonstrated poor agreement (concordance correlation coefficient <0.90). Median time for completing OME was 103.5 (interquartile range, 80.5-151) seconds. Conclusions: The OME smartphone data capture system routinely captured more data than operative report and demonstrated acceptable agreement for nearly all nominal variables, yet took <2 minutes to complete on average.