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Analysis of Smartphone Interruptions on Academic General Internal Medicine Wards

Journal: Applied Clinical Informatics
ISSN: 1869-0327
DOI: https://doi.org/10.4338/ACI-2016-08-RA-0130
Issue: Vol. 8: Issue 1 2017
Pages: 1-11

Analysis of Smartphone Interruptions on Academic General Internal Medicine Wards

Frequent Interruptions may cause a ‘Crisis Mode’ Work Climate

Research Article

A. Vaisman (1), R. C. Wu (1)

(1) Division of General Internal Medicine, Department of Medicine, University Health Network, Toronto, Ontario

Keywords

Communication, Information technology, interruptions, smartphones

Summary

Introduction: Hospital-based medical services are increasingly utilizing team-based pagers and smartphones to streamline communications. However, an unintended consequence may be higher volumes of interruptions potentially leading to medical error. There is likely a level at which interruptions are excessive and cause a ‘crisis mode’ climate.

Methods: We retrospectively collected phone, text messaging, and email interruptions directed to hospital-assigned smartphones on eight General Internal Medicine (GIM) teams at two tertiary care centres in Toronto, Ontario from April 2013 to September 2014. We also calculated the number of times these interruptions exceeded a pre-specified threshold per hour, termed ‘crisis mode’, defined as at least five interruptions in 30 minutes. We analyzed the correlation between interruptions and date, site, and patient volumes.

Results: A total of 187,049 interruptions were collected over an 18-month period. Daily weekday interruptions rose sharply in the morning, peaking between 11 AM to 12 PM and measuring 4.8 and 3.7 mean interruptions/hour at each site, respectively. Mean daily interruptions per team totaled 46.2 ± 3.6 at Site 1 and 39.2 ± 4.2 at Site 2. The ‘crisis mode’ threshold was exceeded, on average, 2.3 times/day per GIM team during weekdays. In a multivariable linear regression analysis, site (β6.43 CI95% 5.44 – 7.42, p<0.001), day of the week (with Friday having the most interruptions) (β0.481 CI95% 0.236 – 0.730, p<0.05) and patient census (β1.55 CI95% 1.42 – 1.67, p<0.05) were all predictive of daily interruption volume although there was a significant interaction effect between site and patient census (β-0.941 CI95% -1.18 – -0.703, p<0.05).

Conclusion: Interruptions were related to site-specific features, including volume, suggesting that future interventions should target the culture of individual hospitals. Excessive interruptions may have implications for patient safety especially when exceeding a maximal threshold over short periods of time.

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