An analysis of electronic health record-related patient safety concerns

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Abstract

Objective

A recent Institute of Medicine report called for attention to safety issues related to electronic health records (EHRs). We analyzed EHR-related safety concerns reported within a large, integrated healthcare system.

Methods

The Informatics Patient Safety Office of the Veterans Health Administration (VA) maintains a non-punitive, voluntary reporting system to collect and investigate EHR-related safety concerns (ie, adverse events, potential events, and near misses). We analyzed completed investigations using an eight-dimension sociotechnical conceptual model that accounted for both technical and non-technical dimensions of safety. Using the framework analysis approach to qualitative data, we identified emergent and recurring safety concerns common to multiple reports.

Results

We extracted 100 consecutive, unique, closed investigations between August 2009 and May 2013 from 344 reported incidents. Seventy-four involved unsafe technology and 25 involved unsafe use of technology. A majority (70%) involved two or more model dimensions. Most often, non-technical dimensions such as workflow, policies, and personnel interacted in a complex fashion with technical dimensions such as software/hardware, content, and user interface to produce safety concerns. Most (94%) safety concerns related to either unmet data-display needs in the EHR (ie, displayed information available to the end user failed to reduce uncertainty or led to increased potential for patient harm), software upgrades or modifications, data transmission between components of the EHR, or ‘hidden dependencies’ within the EHR.

Discussion

EHR-related safety concerns involving both unsafe technology and unsafe use of technology persist long after ‘go-live’ and despite the sophisticated EHR infrastructure represented in our data source. Currently, few healthcare institutions have reporting and analysis capabilities similar to the VA.

Conclusions

Because EHR-related safety concerns have complex sociotechnical origins, institutions with long-standing as well as recent EHR implementations should build a robust infrastructure to monitor and learn from them.

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Most cited references 37

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Role of computerized physician order entry systems in facilitating medication errors.

Ross Koppel, Joshua Metlay, Abigail Cohen … (2005)

Hospital computerized physician order entry (CPOE) systems are widely regarded as the technical solution to medication ordering errors, the largest identified source of preventable hospital medical error. Published studies report that CPOE reduces medication errors up to 81%. Few researchers, however, have focused on the existence or types of medication errors facilitated by CPOE. To identify and quantify the role of CPOE in facilitating prescription error risks. We performed a qualitative and quantitative study of house staff interaction with a CPOE system at a tertiary-care teaching hospital (2002-2004). We surveyed house staff (N = 261; 88% of CPOE users); conducted 5 focus groups and 32 intensive one-on-one interviews with house staff, information technology leaders, pharmacy leaders, attending physicians, and nurses; shadowed house staff and nurses; and observed them using CPOE. Participants included house staff, nurses, and hospital leaders. Examples of medication errors caused or exacerbated by the CPOE system. We found that a widely used CPOE system facilitated 22 types of medication error risks. Examples include fragmented CPOE displays that prevent a coherent view of patients' medications, pharmacy inventory displays mistaken for dosage guidelines, ignored antibiotic renewal notices placed on paper charts rather than in the CPOE system, separation of functions that facilitate double dosing and incompatible orders, and inflexible ordering formats generating wrong orders. Three quarters of the house staff reported observing each of these error risks, indicating that they occur weekly or more often. Use of multiple qualitative and survey methods identified and quantified error risks not previously considered, offering many opportunities for error reduction. In this study, we found that a leading CPOE system often facilitated medication error risks, with many reported to occur frequently. As CPOE systems are implemented, clinicians and hospitals must attend to errors that these systems cause in addition to errors that they prevent.

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A new sociotechnical model for studying health information technology in complex adaptive healthcare systems.

Hardeep Singh, Dean Sittig (2010)

Conceptual models have been developed to address challenges inherent in studying health information technology (HIT). This manuscript introduces an eight-dimensional model specifically designed to address the sociotechnical challenges involved in design, development, implementation, use and evaluation of HIT within complex adaptive healthcare systems. The eight dimensions are not independent, sequential or hierarchical, but rather are interdependent and inter-related concepts similar to compositions of other complex adaptive systems. Hardware and software computing infrastructure refers to equipment and software used to power, support and operate clinical applications and devices. Clinical content refers to textual or numeric data and images that constitute the 'language' of clinical applications. The human--computer interface includes all aspects of the computer that users can see, touch or hear as they interact with it. People refers to everyone who interacts in some way with the system, from developer to end user, including potential patient-users. Workflow and communication are the processes or steps involved in ensuring that patient care tasks are carried out effectively. Two additional dimensions of the model are internal organisational features (eg, policies, procedures and culture) and external rules and regulations, both of which may facilitate or constrain many aspects of the preceding dimensions. The final dimension is measurement and monitoring, which refers to the process of measuring and evaluating both intended and unintended consequences of HIT implementation and use. We illustrate how our model has been successfully applied in real-world complex adaptive settings to understand and improve HIT applications at various stages of development and implementation.

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Enhancing patient safety and quality of care by improving the usability of electronic health record systems: recommendations from AMIA.

Blackford Middleton, Meryl Bloomrosen, Mark A Dente … (2013)

In response to mounting evidence that use of electronic medical record systems may cause unintended consequences, and even patient harm, the AMIA Board of Directors convened a Task Force on Usability to examine evidence from the literature and make recommendations. This task force was composed of representatives from both academic settings and vendors of electronic health record (EHR) systems. After a careful review of the literature and of vendor experiences with EHR design and implementation, the task force developed 10 recommendations in four areas: (1) human factors health information technology (IT) research, (2) health IT policy, (3) industry recommendations, and (4) recommendations for the clinician end-user of EHR software. These AMIA recommendations are intended to stimulate informed debate, provide a plan to increase understanding of the impact of usability on the effective use of health IT, and lead to safer and higher quality care with the adoption of useful and usable EHR systems.

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Author and article information

Journal

Journal ID (nlm-ta): J Am Med Inform Assoc

Journal ID (iso-abbrev): J Am Med Inform Assoc

Journal ID (hwp): amiajnl

Journal ID (publisher-id): jamia

Title: Journal of the American Medical Informatics Association : JAMIA

Publisher: BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )

ISSN (Print): 1067-5027

ISSN (Electronic): 1527-974X

Publication date (Print): November 2014

Publication date (Electronic): 20 June 2014

Publication date PMC-release: 20 June 2014

Volume: 21

Issue: 6

Pages: 1053-1059

Affiliations

[1 ]Houston VA Center for Innovations in Quality, Effectiveness and Safety, Michael E DeBakey Veterans Affairs Medical Center, Houston, Texas, USA

[2 ]Department of Family and Community Medicine, Baylor College of Medicine, Houston, Texas, USA

[3 ]Section of Health Services Research, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA

[4 ]Informatics Patient Safety, Office of Informatics and Analytics, Veterans Health Administration, Ann Arbor, MI and Albany, NY, USA

[5 ]University of Texas School of Biomedical Informatics and UT-Memorial Hermann Center for Healthcare Quality and Safety, Houston, Texas, USA

Author notes

[Correspondence to ] Dr Hardeep Singh, Houston VA Center for Innovations in Quality, Effectiveness and Safety (152), 2002 Holcombe Boulevard, Houston, TX 77030, USA; hardeeps@ 123456bcm.edu

Article

Publisher ID: amiajnl-2013-002578

DOI: 10.1136/amiajnl-2013-002578

PMC ID: 4215044

PubMed ID: 24951796

SO-VID: 0f87a3b0-c2b6-4440-8335-b89c68ad997c

License:

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 3.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/3.0/

History

Date received : 12 December 2013

Date revision received : 25 April 2014

Date accepted : 29 April 2014

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ScienceOpen disciplines: Bioinformatics & Computational biology

Keywords: electronic health records,sociotechnical,reporting systems,medical errors,human factors,patients safety

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ScienceOpen disciplines: Bioinformatics & Computational biology

Keywords: electronic health records, sociotechnical, reporting systems, medical errors, human factors, patients safety

An analysis of electronic health record-related patient safety concerns

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Abstract

Objective

Methods

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Discussion

Conclusions

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Most cited references 37

Role of computerized physician order entry systems in facilitating medication errors.

A new sociotechnical model for studying health information technology in complex adaptive healthcare systems.

Enhancing patient safety and quality of care by improving the usability of electronic health record systems: recommendations from AMIA.

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