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A new sociotechnical model for studying health information technology in complex adaptive healthcare systems
Open accessAbstract
BACKGROUND: Conceptual models have been developed to address challenges inherent in studying health information technology (HIT). METHOD: 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. DISCUSSION: 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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“Digitisation redistributes responsibility across human and technical actors.”
From Why digital health fails silently: a sociotechnical theory of health information technology–related risk (2026) · cites this paper as [13]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Digital systems frequently mediate clinical work in ways that reduce direct visibility of system state and process integrity.”
From Why digital health fails silently: a sociotechnical theory of health information technology–related risk (2026) · cites this paper as [13]
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“This diffusion complicates accountability and can create gaps in oversight, particularly when responsibilities for monitoring, escalation, and remediation are not clearly defined (13).”
From Why digital health fails silently: a sociotechnical theory of health information technology–related risk (2026) · cites this paper as [13]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Decisions about information accuracy, timing, and relevance are increasingly mediated by algorithms, system configurations, and interoperability rules that are often opaque to end users (1, 13).”
From Why digital health fails silently: a sociotechnical theory of health information technology–related risk (2026) · cites this paper as [13]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The interest in trialing ambient AI scribes in the ICU was tempered by concerns about the sociotechnical implications of voice-based AI in team-based, high-risk environments, highlighting the need for careful, context-sensitive implementation [27].”
From Clinician Perspectives on Ambient AI Scribes in the Intensive Care Unit: Qualitative Interview Study (2026) · cites this paper as [27]
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“The interview guide was previously developed based on sociotechnical theory and will explore the following key constructs (Table 3): perceptions of usefulness, resource needs and constraints, barriers and facilitators to implementation, culture of safety, and adaptations [13,23].”
From Improving Communication in Intensive Care Unit to Ward Transitions: Protocol for Multisite National Implementation of the ICU-PAUSE Handoff Tool (2023) · cites this paper as [13]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“A coding framework rooted in the 8 dimensions of sociotechnical theory has been developed along the following codes: hardware and software, clinical content, human-computer interface, people, workflow and communication, internal organizational features, and external rules and regulations [13].”
From Improving Communication in Intensive Care Unit to Ward Transitions: Protocol for Multisite National Implementation of the ICU-PAUSE Handoff Tool (2023) · cites this paper as [13]
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“Existing approaches, including sociotechnical models and safety frameworks, have provided important insights into the role of system interactions and organisational context (13, 16, 17, 28, 48).”
From Why digital health fails silently: a sociotechnical theory of health information technology–related risk (2026) · cites this paper as [13]
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“This study is informed by sociotechnical theory, which offers a paradigm for studying health information technology innovations [13].”
From Improving Communication in Intensive Care Unit to Ward Transitions: Protocol for Multisite National Implementation of the ICU-PAUSE Handoff Tool (2023) · cites this paper as [13]
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In the citing paper
“This convergent mixed method approach will allow us to quantify the feasibility and acceptability of the ICU-PAUSE tool while also qualitatively assessing user experiences with the tool using the established implementation frameworks of CFIR and sociotechnical theory [13,14,17].”
From Improving Communication in Intensive Care Unit to Ward Transitions: Protocol for Multisite National Implementation of the ICU-PAUSE Handoff Tool (2023) · cites this paper as [13]
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“We recognize that user interaction, the EHR interface, institutional workflows, and regulatory policies are all dynamic and interdependent.”
From Improving Communication in Intensive Care Unit to Ward Transitions: Protocol for Multisite National Implementation of the ICU-PAUSE Handoff Tool (2023) · cites this paper as [13]
In the citing paper
“Detecting and preventing EHR-related safety concerns is challenging because concerns are often multifaceted, involving not only potentially unsafe technological features of the EHR but also EHR user behaviors, organizational characteristics, and rules and regulations that guide EHR-related activities.”
From An analysis of electronic health record-related patient safety concerns (2014) · cites this paper as [24]
In the citing paper
“For instance, we previously developed a sociotechnical model that proposes eight interdependent dimensions that are essential to understand EHR-related safety (table 1; Sittig and Singh model).24 34”
From An analysis of electronic health record-related patient safety concerns (2014) · cites this paper as [24]
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(2013) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2013.11249
USER CONTEXT OF SAFE AND EFFECTIVE EHR USE
Sittig, D. F., Singh, H., & Longhurst, C. (2015) · Apple Academic Press eBooks · doi:10.1201/b18371-4
Self-citationYusof, M. M., Olakotan, O. O., & Puteh, S. E. W. (2019) · doi:10.2196/preprints.16809
Metadata
- Authors
- Sittig, D. F., & Singh, H.
- Affiliations
- Memorial Hermann (US)
- Michael E. DeBakey VA Medical Center (US)
- Corresponding author
- Sittig, D. F.
- Venue
- Quality and Safety in Health Care
- Publisher
- BMJ
- Published
- 2010-10-01
- Volume
- 19
- Issue
- Suppl 3
- Pages
- i68-i74
- ISSN
- 1475-3898 (ISSN-L)
- 1475-3901
- PMC
- PMC3120130
- OpenAlex
- W2110034024
- Cited by
- 897
- References
- 64
- Citations by year
- 2026: 179 · 2025: 91 · 2024: 43 · 2023: 75 · 2022: 58 · 2021: 66 · 2020: 52 · 2019: 70 · 2018: 40 · 2017: 48 · 2016: 41 · 2015: 36 · 2014: 36 · 2013: 34 · 2012: 15
- FWCI
- 36.37
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- BMJ Quality & Safety (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- HighWire Press Open Archive (submittedVersion)
- Funders
- Health Services Research and Development
- National Institutes of Health
- Agency for Healthcare Research and Quality (R18HS017820)
- VA National Center for Patient Safety
- National Cancer Institute (K23CA125585)
- U.S. National Library of Medicine (R01LM006942, R56LM006942)
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Social Sciences › Business, Management and Accounting › Management Information Systems › Information Systems Theories and Implementation
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Technology and Human Factors in Education and Health
- Keywords
- health information technology, socio-technical model, complex adaptive systems, health care system, clinical workflow, human-machine interaction, organizational culture, health policy and regulation, monitoring and measurement, unintended consequences
- MeSH terms
- Diffusion of Innovation, Health Services Research, Humans, Ergonomics, Medical Informatics, Models, Theoretical, Planning Techniques, Programming Languages, Software Design, User-Computer Interface, Organizational Culture, Organizational Policy, Workflow
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