The DOI matches its Crossref record; 64 of the 64 references it cites were found in a registry or an index.
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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]
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
“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]
Experimental — accuracy not yet measured
The 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 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]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“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]
The cited source says what the claim attributes to it.
In the citing paper
“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]
The cited source says what the claim attributes to it.
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]
The cited source says what the claim attributes to it.
In the citing paper
“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]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
User Acceptance of Information Technology: Toward A Unified View1
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035
Rogers, E. M., Singhal, A., & Quinlan, M. M. (2019) · Routledge eBooks · doi:10.4324/9780203710753-35 · Cited by 37,670
Hutchins, E. (1995) · doi:10.7551/mitpress/1881.001.0001 · Cited by 10,801
Human error: models and management
Reason, J. (2000) · BMJ · doi:10.1136/bmj.320.7237.768 · Cited by 5,665
Designing the user interface: Strategies for effective human-computer interaction
(1993) · Applied Ergonomics · doi:10.1016/0003-6870(93)90471-k · Cited by 5,592
The Psychology of Everyday Things
Massaro, D. W., & Norman, D. A. (1990) · The American Journal of Psychology · doi:10.2307/1423268 · Cited by 3,484
Risk management in a dynamic society: a modelling problem
Rasmussen, J. (1997) · Safety Science · doi:10.1016/s0925-7535(97)00052-0 · Cited by 2,994
The Technology Acceptance Model: Its past and its future in health care
Holden, R. J., & Karsh, B.-T. (2010) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2009.07.002 · Cited by 2,669
Diffusion of Innovations, 5th Edition
Rogers, E. M., Simon, 。., & Schuster (2003) · Cited by 2,049
Work system design for patient safety: the SEIPS model
Carayon, P., Schoofs Hundt, A., Karsh, B.-T., Gurses, A. P., Alvarado, C. J., Smith, M., & Flatley Brennan, P. (2006) · Quality in Health Care · doi:10.1136/qshc.2005.015842 · Cited by 1,795 · cited 1×
“Third, Carayon's Systems Engineering Initiative for Patient Safety model”
Flagged first, then by citations
Research works printed but not linked: 1
- [36]Sittig DF Wright A Simonaitis L Carpenter JD Allen GO Doebbeling BN Sirajuddin AM Ash JS Middleton B The state of the art in clinical knowledge management: an inventory of tools and techniques Int J Med Inform 2010 Jan 79 1 44 57 19828364 PMC2895508
Cited by
Sorted by citations
Items 201–300 of 892
Barrett, A. K., Ford, J. L., & Zhu, Y. (2020) · Health Communication · doi:10.1080/10410236.2020.1788498 · Cited by 25
Physician activity during outpatient visits and subjective workload
Calvitti, A., Hochheiser, H., Ashfaq, S., Bell, K., Chen, Y., El-Kareh, R. E., Gabuzda, M. T., Liu, L., Mortensen, S., Pandey, B. B., et al. (2017) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2017.03.011 · Cited by 26
Symbiotic types of systems thinking with systematic management in occupational health & safety
Karanikas, N., Popovich, A., Steele, S. E., Horswill, N., Laddrak, V., & Roberts, T. (2020) · Safety Science · doi:10.1016/j.ssci.2020.104752 · Cited by 24
Craswell, A., Bennett, K., Hanson, J., Dalgliesh, B., & Wallis, M. (2021) · Journal of Clinical Nursing · doi:10.1111/jocn.15793 · Cited by 24
Ozkaynak, M., Dziadkowiec, O., Mistry, R. D., Callahan, T. J., He, Z. G., Deakyne, S., & Tham, E. (2015) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2015.08.018 · Cited by 24
Physician leadership in e-health? A systematic literature review
Keijser, W., Smits, J., Penterman, L., & Wilderom, C. P. M. (2016) · Leadership in health services · doi:10.1108/lhs-12-2015-0047 · Cited by 28
A Nordic Perspective on Patient Online Record Access and the European Health Data Space
Hägglund, M., Kharko, A., Bärkås, A., Blease, C., Cajander, Å., DesRoches, C. M., Fagerlund, A. J., Hagström, J., Huvila, I., Hörhammer, I., et al. (2024) · Journal of Medical Internet Research · doi:10.2196/49084 · Cited by 23
Consumer Health Informatics: Engaging and Empowering Patients and Families
Nazi, K. M., Hogan, T. P., Woods, S. S., Simon, S. R., & Ralston, J. D. (2015) · Springer eBooks · doi:10.1007/978-3-319-22753-5_19 · Cited by 23
Krasuska, M., Williams, R., Sheikh, A., Franklin, B. D., Hinder, S., TheNguyen, H., Lane, W., Mozaffar, H., Mason, K., Eason, S., et al. (2021) · BMJ Health & Care Informatics · doi:10.1136/bmjhci-2021-100429 · Cited by 30
Doo, F. X., & McGinty, G. B. (2023) · Journal of the American College of Radiology · doi:10.1016/j.jacr.2023.06.014 · Cited by 23
Cognitive bias and decision aid use under stressful conditions
Phillips-Wren, G., Jefferson, T., & McKniff, S. (2019) · Journal of Decision Systems · doi:10.1080/12460125.2019.1643695 · Cited by 22
Utilizing nursing standards in electronic health records: A descriptive qualitative study
Laukvik, L. B., Lyngstad, M., Rotegård, A. K., & Fossum, M. (2024) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2024.105350 · Cited by 22
Bai, E., Zhang, Z., Xu, Y., Luo, X., & Adelgais, K. (2025) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-024-02844-1 · Cited by 22
Human-Centered Design and Development in Digital Health: Approaches, Challenges, and Emerging Trends
Tzimourta, K. D. (2025) · Cureus · doi:10.7759/cureus.85897 · Cited by 22
Closing the loop with an enhanced referral management system
Ramelson, H. Z., Nederlof, A., Karmiy, S., Neri, P., Kiernan, D., Krishnamurthy, R., Allen, A., & Bates, D. W. (2018) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocy004 · Cited by 22
Multi-View Design Patterns and Responsive Visualization for Genomics Data
L’Yi, S., & Gehlenborg, N. (2022) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2022.3209398 · Cited by 24
A Review of the State of the Art of Data Quality in Healthcare
Liu, C., Talaei‐Khoei, A., Storey, V. C., & Peng, G. (2023) · Journal of Global Information Management · doi:10.4018/jgim.316236 · Cited by 27
The electronic health record audit file: the patient is waiting
Hirsch, A. G., Jones, J. B., Lerch, V., Tang, X., Berger, A. L., Clark, D. N., & Stewart, W. F. (2016) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocw088 · Cited by 22
A Socio-Technical Exploration for Reducing & Mitigating the Risk of Retained Foreign Objects
Corrigan, S., Kay, A., O’Byrne, K., Slattery, D. M., Sheehan, S. R., McDonald, N., Smyth, D. R., Mealy, K., & Cromie, S. (2018) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph15040714 · Cited by 22
Clinical considerations when applying machine learning to decision-support tasks versus automation
Jamieson, T., & Avi Goldfarb, B. (2019) · BMJ Quality & Safety · doi:10.1136/bmjqs-2019-009514 · Cited by 24
Beyond the threshold: real-time use of evidence in practice
Jones, J. B., Stewart, W. F., Darer, J. D., & Sittig, D. F. (2013) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-13-47 · Cited by 22
Self-citationThe Future of Nursing Informatics in a Digitally-Enabled World
Booth, R. G., Strudwick, G., McMurray, J., Chan, R., Cotton, K., & Cooke, S. (2021) · Health informatics · doi:10.1007/978-3-030-58740-6_16 · Cited by 23
Usability of the Swedish Accessible Electronic Health Record: Qualitative Survey Study
Hägglund, M., & Scandurra, I. (2022) · JMIR Human Factors · doi:10.2196/37192 · Cited by 21
McCormack, J. L., & Ash, J. S. (2012) · PubMed Central · Cited by 21
Clinical decision support in small community practice settings: a case study
Ash, J. S., Sittig, D. F., Wright, A. T., McMullen, C. K., Shapiro, M. D., Bunce, A., & Blackford Middleton, A. (2011) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2010-000013 · Cited by 21
Self-citationWaterson, P. E., Hoonakker, P., & Carayon, P. (2013) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2013.01.001 · Cited by 23
State of Science in Alarm System Safety: Implications for Researchers, Vendors, and Clinical Leaders
Sowan, A. K., Staggers, N., Reed, C. C., Austin, T., Chen, Q., Xu, S., & Lopez, E. (2022) · Biomedical Instrumentation & Technology · doi:10.2345/0899-8205-56.1.19 · Cited by 20
Health Care Actions for Reducing Plastic Use and Pollution
Ong, H., Thiel, C. L., & Singh, H. (2024) · JAMA · doi:10.1001/jama.2024.17961 · Cited by 20
Self-citationThe Future Hospital in Global Health Systems: The Future Hospital as an Entity
Sebire, N. J., Adams, A. M., Arpiainen, L., Celi, L. A., Charlesworth, A., Görgens, M., Gorsky, M., Magrabi, F., Nagasawa, Y., Onoka, C. A., et al. (2025) · The International Journal of Health Planning and Management · doi:10.1002/hpm.3893 · Cited by 25
Electronic Health System: Sensors Emerging and Intelligent Technology Approach
Susanto, H. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-809859-2.00012-7 · Cited by 20
Jabin, M. S. R., Magrabi, F., Hibbert, P., Schultz, T., & Runciman, W. (2019) · 2019 IEEE International Conference on Imaging Systems and Techniques (IST) · doi:10.1109/ist48021.2019.9010280 · Cited by 20
Braun, E. J., Singh, S., Penlesky, A. C., Strong, E. A., Holt, J. M., Fletcher, K. E., Stadler, M., Nattinger, A. B., & Crotty, B. H. (2022) · BMJ Quality & Safety · doi:10.1136/bmjqs-2021-014498 · Cited by 23
Kim, K. K., & Backonja, U. (2024) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocae020 · Cited by 19
Threats to safety during sedation outside of the operating room and the death of Michael Jackson
Webster, C. S., Mason, K. P., & Shafer, S. L. (2016) · Current Opinion in Anaesthesiology · doi:10.1097/aco.0000000000000318 · Cited by 20
Feblowitz, J. C., Takhar, S. S., Ward, M. J., Ribeira, R., & Landman, A. (2017) · Annals of Emergency Medicine · doi:10.1016/j.annemergmed.2017.05.032 · Cited by 20
NHS Scotland’s Decision Support Platform: a formative qualitative evaluation
Cresswell, K. M., Callaghan, M., Mozaffar, H., & Sheikh, A. (2019) · BMJ Health & Care Informatics · doi:10.1136/bmjhci-2019-100022 · Cited by 21
A Review of the Applications of Affordance Theory in mHealth App Research
Alshawmar, M. (2021) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2021.437 · Cited by 22
Towards an inclusive digital health ecosystem
Xie, Y. J., Fadahunsi, K. P., Kelleher, C., Tarn, D. M., Grace, A., & O’Donoghue, J. (2025) · Bulletin of the World Health Organization · doi:10.2471/blt.24.292020 · Cited by 19
Barbieri, A. L., Fadare, O., Fan, L. L., Singh, H., & Parkash, V. (2018) · Journal of Pathology Informatics · doi:10.4103/jpi.jpi_70_17 · Cited by 19
Self-citationNdabu, T., Mulgund, P., Sharman, R., & Singh, R. K. P. G. (2021) · JMIR Human Factors · doi:10.2196/21884 · Cited by 18
Rojas, A. N., de Torres, L. Á. P., Mosquera, F. E. C., & Molina‐Recio, G. (2023) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2023.105089 · Cited by 17
5G and IoT for Intelligent Healthcare: AI and Machine Learning Approaches—A Review
Butt, H. A., Ahad, A., Wasim, M., Madeira, F., & Chamran, M. K. (2024) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-031-52524-7_8 · Cited by 19
A Nursing Focus on EMR Usability Enhancing Documentation of Patient Outcomes
Page, C. A. K., & Schadler, A. D. (2014) · Nursing Clinics of North America · doi:10.1016/j.cnur.2013.11.010 · Cited by 20
Safe Use of Health Information Technology
Ethawi, Y., AlZubaidi, A. K., & Maheshwari, A. (2024) · Elsevier eBooks · doi:10.1016/b978-0-323-69415-5.00003-5 · Cited by 20
Application of Electronic Algorithms to Improve Diagnostic Evaluation for Bladder Cancer
Murphy, D. R., Meyer, A. N. D., Vaghani, V., Russo, E. M., Sittig, D. F., Richards, K. A., Wei, L., Wu, L., & Singh, H. (2017) · Applied Clinical Informatics · doi:10.4338/aci-2016-10-ra-0176 · Cited by 19
Self-citationLanham, H. J., Leykum, L. K., & Pugh, J. A. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.9269 · Cited by 18
Shields, C., Cunningham, S. G., Wake, D. J., Fioratou, E., Brodie, D., Philip, S., & Conway, N. (2021) · JMIR Human Factors · doi:10.2196/29973 · Cited by 18
Using organizational and clinical performance data to increase the value of mental health care.
Schmidt, E. M., Krahn, D. D., McGuire, M. H., Tavakoli, S., Wright, D. M., Solares, H. E., Lemke, S., & Trafton, J. A. (2017) · Psychological Services · doi:10.1037/ser0000098 · Cited by 18
A Sociotechnical Approach to Successful Electronic Health Record Implementation
Irizarry, T., & Barton, A. J. (2013) · Clinical Nurse Specialist · doi:10.1097/nur.0b013e3182a872e3 · Cited by 18
Leveraging Cloud Computing to Address Public Health Disparities: An Analysis of the SPHPS
Jalali, A., Olabode, O. A., & Bell, C. M. (2012) · Online Journal of Public Health Informatics · doi:10.5210/ojphi.v4i3.4325 · Cited by 18
Zhu, X., Tu, S.-P., Sewell, D., Yao, N. (., Mishra, V., Dow, A., & Banas, C. (2019) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2019.05.012 · Cited by 18
An Adaptive, Contextual, Technology‐Aided Support (ACTS) System for Chronic Illness Self‐Management
GLASGOW, R. E., HUEBSCHMANN, A. G., KRIST, A. H., & DEGRUY, F. V. (2019) · The Milbank Quarterly · doi:10.1111/1468-0009.12412 · Cited by 18
Mahajan, P., Mollen, C. J., Alpern, E. R., Baird-Cox, K., Boothman, R. C., Chamberlain, J. M., Cosby, K. S., Epstein, H. M., Gegenheimer-Holmes, J., Gerardi, M. J., et al. (2019) · Journal of Patient Safety · doi:10.1097/pts.0000000000000624 · Cited by 28
Self-citationValue-Based Health Care Supported by Data Science
Leung, T. I., & van Merode, G. G. (2018) · Springer eBooks · doi:10.1007/978-3-319-99713-1_14 · Cited by 18
Seuren, L. M., & Shaw, S. E. (2022) · Qualitative Health Research · doi:10.1177/10497323221077297 · Cited by 20
Vermeulen, L. C., Eddington, N. D., Gourdine, M. A., Jorgenson, J. A., Kvancz, D. A., Nesbit, S. A., Bicket, M. C., Zellmer, W. A., Hine, A., Belford, S. M., et al. (2018) · American Journal of Health-System Pharmacy · doi:10.2146/sp180010 · Cited by 17
Gefen, D., Ben‐Assuli, O., Stehr, M. F., Rosen, B., & Denekamp, Y. (2019) · European Journal of Information Systems · doi:10.1080/0960085x.2019.1666038 · Cited by 17
Optimizing health IT to improve health system performance: A work in progress
Rudin, R. S., Fischer, S. H., Damberg, C. L., Shi, Y., Shekelle, P., Xenakis, L., Khodyakov, D., & Ridgely, M. S. (2020) · Healthcare · doi:10.1016/j.hjdsi.2020.100483 · Cited by 18
Sittig, D. F., & Ash, J. S. (2011) · The Annals of Family Medicine · doi:10.1370/afm.1291 · Cited by 17
Self-citationGlobal Health in the Age of AI: Charting a Course for Ethical Implementation and Societal Benefit
Morley, J., Hine, E., Roberts, H., Sirbu, R. A., Ashrafian, H., Blease, C., Boyd, M., Chen, J. L., Filho, A. D. P. C., Coiera, E. W., et al. (2025) · Minds and Machines · doi:10.1007/s11023-025-09730-3 · Cited by 19
A qualitative study of provider burnout: do medical scribes hinder or help?
Corby, S., Ash, J. S., Mohan, V., Becton, J., Solberg, N., Bergstrom, R., Orwoll, B., Hoekstra, C., & Gold, J. A. (2021) · JAMIA Open · doi:10.1093/jamiaopen/ooab047 · Cited by 16
Teo, S., Chew, E., Ng, D., Tang, W., Koh, G., & Teo, V. (2023) · BMC Primary Care · doi:10.1186/s12875-023-02014-8 · Cited by 15
Fernando, M., Abell, B., Tyack, Z. F., Donovan, T., McPhail, S., & Naicker, S. (2023) · Journal of Medical Internet Research · doi:10.2196/45163 · Cited by 22
Integration of the Enterprise Electronic Health Record and Anesthesia Information Management Systems
Springman, S. R. (2011) · Anesthesiology Clinics · doi:10.1016/j.anclin.2011.05.007 · Cited by 17
Creating a Culture of Safety Around Bar-Code Medication Administration
Kelly, K. M., Harrington, L., Matos, P., Turner, B. S., & Johnson, C. (2015) · JONA The Journal of Nursing Administration · doi:10.1097/nna.0000000000000290 · Cited by 16
Methodological framework for evaluating clinical processes: A cognitive informatics perspective
Kannampallil, T., Abraham, J., & Patel, V. L. (2016) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2016.11.002 · Cited by 16
Kurahashi, A. M., Stinson, J., van Wyk, M., Luca, S., Jamieson, T., Weinstein, P., Cafazzo, J. A., Lokuge, B., Cohen, E., Rapoport, A., et al. (2018) · JMIR Human Factors · doi:10.2196/humanfactors.7882 · Cited by 16
INFORMATIZAÇÃO DA ATENÇÃO BÁSICA A SAÚDE: AVANÇOS E DESAFIOS
Cavalcante, R. B., Vasconcelos, D. D., Gontijo, T. L., Guimarães, E. A. D. A., Machado, R. M., & de Oliveira, V. C. (2018) · Cogitare Enfermagem · doi:10.5380/ce.v23i3.54297 · Cited by 16
Kang, H., Wang, J., Yao, B., Zhou, S., & Gong, Y. (2018) · JAMIA Open · doi:10.1093/jamiaopen/ooy042 · Cited by 17
Wyatt, K. D., Benning, T. J., Morgenthaler, T. I., & Arteaga, G. M. (2020) · Applied Clinical Informatics · doi:10.1055/s-0040-1717084 · Cited by 16
Barriers to Adoption of a Secure Text Messaging System: a Qualitative Study of Practicing Clinicians
Byrd, T. F., Speigel, P., Cameron, K. A., & O’Leary, K. J. (2022) · Journal of General Internal Medicine · doi:10.1007/s11606-022-07912-8 · Cited by 15
Cho, I., Han, H., Phansalkar, S., Bates, D. W., & Lee, J. (2014) · Applied Clinical Informatics · doi:10.4338/aci-2014-01-ra-0005 · Cited by 16
Patel, B. N., Peiris, D., Usherwood, T. P., Li, Q., Harris, M., Panaretto, K. S., Zwar, N. A., & Patel, A. A. (2017) · Journal of the American Heart Association · doi:10.1161/jaha.117.007093 · Cited by 15
Burton, S., Valenta, A. L., Starren, J. B., Abraham, J., Nelson, T. A., Kochendorfer, K. M., Hughes, A. M., Harris, B. A., & Boyd, A. D. (2021) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocab257 · Cited by 15
Applying requisite imagination to safeguard electronic health record transitions
Sittig, D. F., Lakhani, P., & Singh, H. (2021) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocab291 · Cited by 16
Self-citationPhysicians’ Perceptions of Clinical Decision Support to Treat Patients With Heart Failure in the ED
Casey, S. D., Reed, M., LeMaster, C., Mark, D. G., Gaskin, J., Norris, R. P., & Sax, D. R. (2023) · JAMA Network Open · doi:10.1001/jamanetworkopen.2023.44393 · Cited by 15
Sittig, D. F., Kahol, K., & Singh, H. (2013) · Studies in health technology and informatics · doi:10.3233/978-1-61499-289-9-515 · Cited by 15
Self-citationBooth, R. G., Sinclair, B., Brennan, L., & Strudwick, G. (2016) · CIN Computers Informatics Nursing · doi:10.1097/cin.0000000000000309 · Cited by 15
McDonald, K. M., Su, G., Lisker, S., Patterson, E. S., & Sarkar, U. (2017) · Implementation Science · doi:10.1186/s13012-017-0609-5 · Cited by 15
Inpatient Clinical Information Systems
Cresswell, K. M., & Sheikh, A. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-809523-2.00002-9 · Cited by 15
Joint Design with Providers of Clinical Decision Support for Value-Based Advanced Shoulder Imaging
Brunner, M. C., Sheehan, S. E., Yanke, E. M., Sittig, D. F., Safdar, N., Hill, B., Lee, K. S., Orwin, J. F., Vanness, D. J., Hildebrand, C. J., et al. (2020) · Applied Clinical Informatics · doi:10.1055/s-0040-1701256 · Cited by 15
Self-citationCorby, S., Gold, J. A., Mohan, V., Solberg, N., Becton, J., Bergstrom, R., Orwoll, B., Hoekstra, C., & Ash, J. S. (2019) · PubMed Central · Cited by 15
Fisher, A. M., Mtonga, T. M., Espino, J. U., Jonkman, L. J., Connor, S. E., Cappella, N., & Douglas, G. P. (2018) · BMC Health Services Research · doi:10.1186/s12913-018-3517-8 · Cited by 16
Basit, M. A., Baldwin, K. L., Kannan, V., Flahaven, E. L., Parks, C. J., Ott, J. M., & Willett, D. L. (2018) · JMIR Medical Informatics · doi:10.2196/medinform.9679 · Cited by 15
Furniss, D. J., Mayer, A., Franklin, B. D., & BLANDFORD, A. E. (2019) · Safety Science · doi:10.1016/j.ssci.2019.06.006 · Cited by 15
Educational Program for Physiologic Monitor Use and Alarm Systems Safety
Phillips, J., Sowan, A. K., Ruppel, H., & Magness, R. (2020) · Clinical Nurse Specialist · doi:10.1097/nur.0000000000000507 · Cited by 15
Kelly, S., Kaye, S.-A., White, K. M., & Oviedo-Trespalacios, O. (2025) · AI & SOCIETY · doi:10.1007/s00146-025-02334-6 · Cited by 17
Leveraging the Electronic Health Record to Implement Emergency Department Delirium Screening
Chary, A. N., Brickhouse, E., Torres, B., Santangelo, I., Carpenter, C. R., Liu, S. W., Godwin, K. M., Naik, A. D., Singh, H., & Kennedy, M. (2023) · Applied Clinical Informatics · doi:10.1055/a-2073-3736 · Cited by 14
Self-citationHogg, H. D. J., Al-Zubaidy, M., Keane, P. A., Hughes, G., Beyer, F. R., & Maniatopoulos, G. (2023) · Frontiers in Health Services · doi:10.3389/frhs.2023.1161822 · Cited by 18
Brunner, J., Cannedy, S., McCoy, M., Hamilton, A. B., & Shelton, J. B. (2023) · Journal of General Internal Medicine · doi:10.1007/s11606-023-08280-7 · Cited by 20
Cavalini, L. T., & Cook, T. W. (2014) · Lecture notes in computer science · doi:10.1007/978-3-642-53956-5_9 · Cited by 14
Patient-Centred Coordinated Care in Times of Emerging Diseases and Epidemics
Cummings, E. A., Dexheimer, J. W., Gong, Y., Kennebeck, S., Kushniruk, A. W., Kuziemsky, C. E., Saranto, K., Weber, J. H., Takeda, H., & Borycki, E. M. (2015) · Yearbook of Medical Informatics · doi:10.15265/iy-2015-019 · Cited by 14
Toouli, G., Georgiou, A., & Westbrook, J. I. (2012) · Journal of Pathology Informatics · doi:10.4103/2153-3539.95128 · Cited by 14
Electronic Detection of Delayed Test Result Follow-Up in Patients with Hypothyroidism
Meyer, A. N. D., Murphy, D. R., Al-Mutairi, A., Sittig, D. F., Wei, L., Russo, E. M., & Singh, H. (2017) · Journal of General Internal Medicine · doi:10.1007/s11606-017-3988-z · Cited by 14
Self-citationWu, M.-W., Lee, T., Lai, S.-M., Huang, C.-Y., & Chang, T. (2019) · CIN Computers Informatics Nursing · doi:10.1097/cin.0000000000000548 · Cited by 14
Toward More Proactive Approaches to Safety in the Electronic Health Record Era
Sittig, D. F., & Singh, H. (2017) · The Joint Commission Journal on Quality and Patient Safety · doi:10.1016/j.jcjq.2017.06.005 · Cited by 14
Self-citationRangachari, P., Arkoubi, K. A., & Shindi, R. S. (2025) · International Journal for Equity in Health · doi:10.1186/s12939-025-02663-4 · Cited by 16
Martin, G., Arora, S., Shah, N., King, D., & Darzi, A. W. (2019) · Health Informatics Journal · doi:10.1177/1460458219854602 · Cited by 15
Jabin, M. S. R., Schultz, T., Mandel, C., Bessen, T., Hibbert, P. D., Wiles, L., & Runciman, W. B. (2020) · Journal of Patient Safety · doi:10.1097/pts.0000000000000709 · Cited by 13
Application of Human Factors Methods to Understand Missed Follow-up of Abnormal Test Results
Rogith, D., Satterly, T., Singh, H., Sittig, D. F., Russo, E. M., Smith, M. W., Roosan, D., Bhise, V., & Murphy, D. R. (2020) · Applied Clinical Informatics · doi:10.1055/s-0040-1716537 · Cited by 13
Self-citation
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
