Towards understanding the usage pattern of web-based electronic medical record systems

The benefits and importance of electronic medical record (EMR) systems have been well recognized in the health-care industry. Yet, their wide adoption still face significant barriers in providing on-demand secure medical information access while preserving patients' privacy. Understanding the usage pattern of an EMR system is the first essential step towards building such environment. This paper conducts an in-depth trace analysis of a large-scale EMR system that has been in operation for more than a decade at the Vanderbilt Medical Center. Our study demonstrates several important characteris- tics of EMR system usage from the perspective of user-initiated sessions. First, the workload of the EMR system is highly stable and consistent with a weekly pattern. Second, EMR behavior varies between users, but each user's behavior tends to be consistent with a slow rate of migration across sessions. Finally, the degree of access between users and medical records is sparse, echoing the limits of patient-caregiver relationships that manifest in real healthcare operations. We believe these observations can assist in the development of system security measures, such as EMR-specific anomaly detection systems, and facilitate system performance optimization.

[1]  Krishna P. Gummadi,et al.  Measurement, modeling, and analysis of a peer-to-peer file-sharing workload , 2003, SOSP '03.

[2]  Dario A. Giuse,et al.  Supporting Communication in an Integrated Patient Record System , 2003, AMIA.

[3]  D. Garets,et al.  EMRs and EHRs. Concepts as different as apples and oranges at least deserve separate names. , 2005, Healthcare informatics : the business magazine for information and communication systems.

[4]  Era moderna até Health Insurance Portability and Accountability Act , 2011 .

[5]  Ben Y. Zhao,et al.  Understanding user behavior in large-scale video-on-demand systems , 2006, EuroSys.

[6]  Christopher Krügel,et al.  Anomaly detection of web-based attacks , 2003, CCS '03.

[7]  David Carrell,et al.  Use and Satisfaction of a Patient Web Portal with a Shared Medical Record between Patients and Providers , 2006, AMIA.

[8]  Blackford Middleton,et al.  Design and implementation of a web-based patient portal linked to an ambulatory care electronic health record: patient gateway for diabetes collaborative care. , 2006, Diabetes technology & therapeutics.

[9]  James J. Cimino,et al.  Automated Discovery of Patient-Specific Clinician Information Needs Using Clinical Information System Log Files , 2003, AMIA.

[10]  Bradley Malin,et al.  Learning relational policies from electronic health record access logs , 2011, J. Biomed. Informatics.

[11]  Giovanni Vigna,et al.  Swaddler: An Approach for the Anomaly-Based Detection of State Violations in Web Applications , 2007, RAID.

[12]  Kai Zheng,et al.  Research Article: An Interface-driven Analysis of User Interactions with an Electronic Health Records System , 2009, J. Am. Medical Informatics Assoc..

[13]  Xiangji Huang,et al.  Mining and Modeling Database User Access Patterns , 2006, ISMIS.

[14]  Christopher Stewart,et al.  Performance modeling and system management for multi-component online services , 2005, NSDI.