Abstract
The advent of big data promises to revolutionize healthcare and lead to improved and streamlined healthcare processes and improved outcomes. Driving the move to big data in healthcare is the concomitant deployment of health information technologies worldwide. These systems have been shown to improve safety of healthcare by providing automated advice and alerts and by allowing for integration of a wide array of patient and health data held in databases (Shortliffe and Cimino in Biomedical informatics. Springer, New York, 2006 [1]). However, as in other domains where technology has advanced, the potential for inadvertent error to arise as a result of technology use has also increased (Kushniruk et al. in International journal of medical informatics 74(7–8):519–526, 2005 [5]). In order to ensure the quality and safety of healthcare, databases are being developed globally to allow for reporting of a new type of error, known as technology-induced error (Palojoki et al. in Health informatics journal 23(2): 134–145, 2017 [3]; Kushniruk et al. in International journal of medical informatics 74(7–8):519–526, 2005 [5]). Current approaches to collecting and analyzing this type of error are discussed, including the development of national databases of usability and safety information. In addition to this, the potential for automated analysis and detection of error contained in big data are also explored in the context of patient safety and quality of healthcare data.
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References
Shortliffe EH, Cimino JJ (2006) Biomedical informatics. Springer, New York
Sittig DF, Singh H (2012) Electronic health records and national patient-safety goals. N Engl J Med 367:1854–1860
Palojoki S, Mäkelä M, Lehtonen L, Saranto K (2017) An analysis of electronic health record–related patient safety incidents. Health Inform J 23(2):134–145
Alyass A, Turcotte M, Meyre D (2015) From big data analysis to personalized medicine for all: challenges and opportunities. BMC Med Genomics 8(1):33
Kushniruk AW, Triola MM, Borycki EM, Stein B, Kannry JL (2005) Technology induced error and usability: the relationship between usability problems and prescription errors when using a handheld application. Int J Med Inform 74(7–8):519–526
Kushniruk A, Surich J, Borycki E (2012) Detecting and classifying technology-induced error in the transmission of healthcare data. In: 24th international conference of the European federation for medical informatics quality of life quality of information, vol 26
Borycki EM, Keay E (2010) Methods to assess the safety of health information systems. Healthc Q 13:47–52
Borycki E, Dexheimer JW, Cossio CHL, Gong Y, Jensen S, Kaipio J, … Marcilly R (2016) Methods for addressing technology-induced errors: the current state. Yearb Med Inf (1):30
Magrabi F, Ong MS, Runciman W, Coiera E (2010) An analysis of computer-related patient safety incidents to inform the development of a classification. J Am Med Inform Assoc 17(6):663–670
Samaranayake NR, Cheung STD, Chui WCM, Cheung BMY (2012) Technology-related medication errors in a tertiary hospital: a 5-year analysis of reported medication incidents. Int J Med Inform 81(12):828–833
Magrabi F, Ong MS, Runciman W, Coiera E (2011) Using FDA reports to inform a classification for health information technology safety problems. J Am Med Inform Assoc 19(1):45–53
Horsky J, Zhang J, Patel VL (2005) To err is not entirely human: complex technology and user cognition. J Biomed Inform 38(4):264–266
Palojoki S, Tuuli P, Saranto K, Lehtonen L (2016) Electronic health record-related safety soncerns: a cross-sectional survey of electronic health record users. JMIR Med Inform 4(2) Apr–Jun:e13
Kaipio J, Lääveri T, Hyppönen H, Vainiomäki S, Reponen J, Kushniruk A, … Vänskä J (2017) Usability problems do not heal by themselves: national survey on physicians’ experiences with EHRs in Finland. Int J Med Inform 97:266–281
Kushniruk A, Kaipio J, Nieminen M, Hyppönen H, Lääveri T, Nohr C, Kanstrup AM, Christiansen MB, Kuo MH, Borycki E (2014) Human factors in the large: experiences from Denmark, Finland and Canada in moving towards regional and national evaluations of health information system usability: contribution of the IMIA Human Factors Working Group. Yearb Med Inform 9(1):67
Kushniruk A, Nohr C, Jensen S, Borycki EM (2013) From usability testing to clinical simulations: bringing context into the design and evaluation of usable and safe health information technologies. Yearb Med Inform 22(01):78–85
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Borycki, E.M., Kushniruk, A.W. (2019). Big Data and Patient Safety. In: Househ, M., Kushniruk, A., Borycki, E. (eds) Big Data, Big Challenges: A Healthcare Perspective. Lecture Notes in Bioengineering. Springer, Cham. https://doi.org/10.1007/978-3-030-06109-8_7
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DOI: https://doi.org/10.1007/978-3-030-06109-8_7
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