Considerations for online deviation detection in medical processes
Pages 50 - 56
Abstract
Medical errors are a major cause of unnecessary suffering and even death. To address this problem, we are investigating an approach for automatically detecting when an executing process deviates from a set of recommended ways to perform that process. Such deviations could represent errors and, thus, detecting and reporting deviations as they occur could help catch errors before something bad happens. This paper presents the proposed deviation detection approach, identifies some of the major research issues that arise, and discusses strategies to address these issues. A preliminary evaluation is performed by applying the approach to a part of a detailed process model. This model has been developed in an in-depth case study on modeling and analyzing a blood transfusion process.
References
[1]
L. T. Kohn, J. M. Corrigan, and M. S. Donaldson, Eds., To Err is Human: Building a Safer Health System. Washington DC: Nat. Acad. Press, 1999.
[2]
W. W. Stead and H. S. Lin, Eds., Computational Technology for Effective Health Care: Immediate Steps and Strategic Directions. Nat. Acad. Press, 2009.
[3]
G. Avrunin, L. Clarke, L. Osterweil, et al., "Smart checklists for human-intensive medical systems," in 42nd Intl. Conf. on Dependable Systems and Networks (DSN-W), Workshop on Open, Resilient, Human-aware, Cyber-physical Systems, IEEE/IFIP, 2012, pp. 1--6.
[4]
N. Leveson, Safeware: System Safety and Computers. Addison-Wesley, 1995.
[5]
A. G. Cass, B. S. Lerner, J. Stanley M. Sutton, et al., "Little-JIL/Juliette: a process definition language and interpreter," in ICSE '00: Proceedings of the 22nd Intl. Conf. on Softw. Eng.. ACM, 2000, pp. 754--757.
[6]
B. Chen, G. S. Avrunin, E. A. Henneman, et al., "Analyzing medical processes," in ICSE '08: Proceedings of the 30th Intl. Conf. on Softw. Eng. ACM, 2008, pp. 623--632.
[7]
E. A. Henneman, G. S. Avrunin, L. A. Clarke, et al., "Increasing patient safety and efficiency in transfusion therapy using formal process definitions," Transfusion Medicine Review, vol. 21, no. 1, pp. 49--57, 2007.
[8]
G. S. Avrunin, L. A. Clarke, L. J. Osterweil, et al., "Experience modeling and analyzing medical processes: Umass/Baystate medical safety project overview," in Proceedings of the 1st ACM Intl. Health Informatics Symposium, ACM, 2010, pp. 316--325.
[9]
B. M. Hales and P. J. Pronovost, "The checklist: a tool for error management and performance improvement," Journal of Critical Care, vol. 21, pp. 231--235, 2006.
[10]
J. M. Wilkinson and K. V. Leuven. Procedure checklist for administering a blood transfusion. {Online}. Available: http://davisplus.fadavis.com/wilkinson/Procedure_Checklists/PC_Ch36-01.doc
[11]
World Health Organization, "Surgical safety checklist," 2008. {Online}. Available: http://www.who.int/patientsafety/safesurgery/tools_resources/SSSL_Checklist_finalJun08.pdf
[12]
W. C. Mertens, D. E. Brown, R. Parisi, et al., "Detection, classification, and correction of defective chemotherapy orders through nursing and pharmacy oversight," Journal of Patient Safety, vol. 4, no. 3, pp. 195--200, 2008.
[13]
M. Fitzgerald, P. Cameron, C. Mackenzie, et al., "Trauma resuscitation errors and computer-assisted decision support," Archives of Surgery, vol. 146, no. 2, pp. 218--225, 2011.
[14]
S. C. Christov, G. S. Avrunin, L. A. Clarke, et al., "A benchmark for evaluating software engineering techniques for improving medical processes," in Proceedings of the 2010 ICSE Workshop on Softw. Eng. in Health Care, ACM, 2010, pp. 50--56.
[15]
D. Sankoff and J. Kruskal, Time warps, string edits, and macromolecules: the theory and practice of sequence comparison. Addison-Wesley Pub. Co., Advanced Book Program, 1983.
[16]
J. E. Cook and A. L. Wolf, "Software process validation: quantitatively measuring the correspondence of a process to a model," ACM Transactions on Softw. Eng. and Methodology, vol. 8, pp. 147--176, 1999.
[17]
V. I. Levenshtein, "Binary codes capable of correcting deletions, insertions, and reversals," Doklady Akademii Nauk SSSR, vol. 163, no. 4, pp. 845--848, 1965.
Recommendations
Early deviation detection in modeling activities of MDE processes
MODELS'10: Proceedings of the 13th international conference on Model driven engineering languages and systems: Part IISoftware Process Models (SPM) are used to communicate around the processes and analyze it. They represent the entry point to PSEEs (Process-centered Software Engineering Environments) which use them to coordinate process agents in their tasks. When the ...
An approach to automatic process deviation detection in a time-critical clinical process
Graphical abstractDisplay Omitted
Highlights- The knowledge-driven workflow model and actual practice significantly differed.
Abstract MotivationPrior research has shown that minor errors and deviations from recommended guidelines in complex medical processes can accumulate to increase the likelihood that a major error will go uncorrected and lead to an ...
Group Deviation Detection Methods: A Survey
Pointwise anomaly detection and change detection focus on the study of individual data instances; however, an emerging area of research involves groups or collections of observations. From applications of high-energy particle physics to health care ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
Sponsors
Publisher
IEEE Press
Publication History
Published: 20 May 2013
Check for updates
Qualifiers
- Research-article
Conference
ICSE '13
Sponsor:
ICSE '13: 35th International Conference on Software Engineering
May 20 - 21, 2013
California, San Francisco
Upcoming Conference
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 31Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 09 Dec 2024
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in