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”
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 101–200 of 892
Communication breakdowns and diagnostic errors: a radiology perspective
Murphy, D. R., Singh, H., & Berlin, L. (2014) · Diagnosis · doi:10.1515/dx-2014-0035 · Cited by 52
Self-citationZhang, Y., Leuk, J. S.-P., & Teo, W. (2023) · JMIR Aging · doi:10.2196/40460 · Cited by 61
The quantified patient of the future: Opportunities and challenges
Majmudar, M. D., Colucci, L. A., & Landman, A. (2015) · Healthcare · doi:10.1016/j.hjdsi.2015.02.001 · Cited by 50
Ebola US Patient Zero: lessons on misdiagnosis and effective use of electronic health records
Upadhyay, D. K., Sittig, D. F., & Singh, H. (2014) · Diagnosis · doi:10.1515/dx-2014-0064 · Cited by 50
Self-citationKrasuska, M., Williams, R., Sheikh, A., Franklin, B. D., Heeney, C., Lane, W., Mozaffar, H., Mason, K., Eason, S., Hinder, S., et al. (2020) · Journal of Medical Internet Research · doi:10.2196/17022 · Cited by 54
Hagström, J., Blease, C., Haage, B., Scandurra, I., Hansson, S., & Hägglund, M. (2022) · Journal of Medical Internet Research · doi:10.2196/40328 · Cited by 49
Sittig, D. F., Wright, A. T., Meltzer, S. N., Simonaitis, L., Evans, R. S., Nichol, W. P., Ash, J. S., & Middleton, B. (2011) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-11-13 · Cited by 48
Self-citationEthnographic process evaluation in primary care: explaining the complexity of implementation
Bunce, A., Gold, R. B., Davis, J. V., McMullen, C. K., Jaworski, V., Mercer, M., & Nelson, C. A. (2014) · BMC Health Services Research · doi:10.1186/s12913-014-0607-0 · Cited by 50
Martin, G., Ghafur, S., Cingolani, I., Symons, J., King, D., Arora, S., & Darzi, A. W. (2019) · The Lancet Digital Health · doi:10.1016/s2589-7500(19)30057-3 · Cited by 51
Operational measurement of diagnostic safety: state of the science
Singh, H., Bradford, A. M., & Goeschel, C. A. (2020) · Diagnosis · doi:10.1515/dx-2020-0045 · Cited by 51
Self-citationSafety Assurance Factors for Electronic Health Record Resilience (SAFER): study protocol
Singh, H., Ash, J. S., & Sittig, D. F. (2013) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-13-46 · Cited by 53
Self-citationSafety huddles to proactively identify and address electronic health record safety
Menon, S., Singh, H., Giardina, T. D., Rayburn, W. L., Davis, B. P., Russo, E. M., & Sittig, D. F. (2016) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocw153 · Cited by 48
Self-citationElectronic Health Records and Patient Safety
Gans, D. W., White, J., Nath, R., Pohl, J. M., & Tanner, C. L. (2015) · Applied Clinical Informatics · doi:10.4338/aci-2014-11-ra-0099 · Cited by 52
Or, C. K., Holden, R. J., & Valdez, R. S. (2022) · Automation, collaboration, and e-services · doi:10.1007/978-3-031-10788-7_6 · Cited by 50
Use of patient-generated health data across healthcare settings: implications for health systems
Austin, E. J., Lee, J. R., Amtmann, D., Bloch, R., Lawrence, S. O., McCall, D., Munson, S. A., & Lavallee, D. C. (2019) · JAMIA Open · doi:10.1093/jamiaopen/ooz065 · Cited by 46
Barbaria, S., Jemai, A., Ceylan, H. İ., Muntean, R. I., Dergaa, I., & Boussi Rahmouni, H. (2025) · Healthcare · doi:10.3390/healthcare13202594 · Cited by 53
Sittig, D. F., Hazlehurst, B. L., Brown, J. S., Murphy, S. N., Rosenman, M. B., Tarczy-Hornoch, P. Z., & Wilcox, A. B. (2012) · Medical Care · doi:10.1097/mlr.0b013e318259c02b · Cited by 46
Self-citationPalojoki, S., Pajunen, T., Saranto, K., & Lehtonen, L. (2016) · JMIR Medical Informatics · doi:10.2196/medinform.5238 · Cited by 57
Opportunities to improve clinical summaries for patients at hospital discharge
Sarzynski, E. M., Hashmi, H., Subramanian, J., Fitzpatrick, L., Polverento, M. E., Simmons, M. R., Brooks, K., & Given, C. W. (2016) · BMJ Quality & Safety · doi:10.1136/bmjqs-2015-005201 · Cited by 46
Murphy, D. R., Giardina, T. D., Satterly, T., Sittig, D. F., & Singh, H. (2019) · JAMA Network Open · doi:10.1001/jamanetworkopen.2019.12638 · Cited by 47
Self-citationClinical use of artificial intelligence requires AI-capable organizations
Novak, L. L., Russell, R. G., Garvey, K., Patel, M., Thomas Craig, K. J., Snowdon, J., & Miller, B. (2023) · JAMIA Open · doi:10.1093/jamiaopen/ooad028 · Cited by 43
Autonomy and machine intelligence in complex systems: A tutorial
Vamvoudakis, K. G., Antsaklis, P. J., Dixon, W. E., Hespanha, J. P., Lewis, F. L., Modares, H., & Kiumarsi, B. (2015) · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference · doi:10.1109/acc.2015.7172127 · Cited by 45
Vamvoudakis, K. G., & Hespanha, J. P. (2017) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2017.2734840 · Cited by 45
Benda, N. C., Das, L. T., Abramson, E. L., Blackburn, K., Thoman, A., Kaushal, R., Zhang, Y., & Ancker, J. S. (2020) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocaa021 · Cited by 49
How context affects electronic health record-based test result follow-up: a mixed-methods evaluation
Menon, S., Smith, M. W., Sittig, D. F., Petersen, N. J., Hysong, S. J., Espadas, D., Modi, V., & Singh, H. (2014) · BMJ Open · doi:10.1136/bmjopen-2014-005985 · Cited by 45
Self-citationA distributed approach to the regulation of clinical AI
Panch, T., Duralde, E. R., Mattie, H., Kotecha, G. K., Celi, L. A., Wright, M. C., & Greaves, F. (2022) · PLOS Digital Health · doi:10.1371/journal.pdig.0000040 · Cited by 43
Do safety briefings improve patient safety in the acute hospital setting? A systematic review
Ryan, S., Ward, M. E., Vaughan, D., Murray, B., Moore, Z. E. H., O’Connor, T., Nugent, L., & Patton, D. (2019) · Journal of Advanced Nursing · doi:10.1111/jan.13984 · Cited by 43
Martin, G., Clarke, J., Liew, F., Arora, S., King, D., Aylin, P. P., & Darzi, A. W. (2019) · npj Digital Medicine · doi:10.1038/s41746-019-0118-9 · Cited by 46
Persisting workarounds in Electronic Health Record System use: types, risks and benefits
Boonstra, A., Jonker, T. L., Offenbeek, V. M., & Vos, J. F. J. (2021) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-021-01548-0 · Cited by 39
Wright, A. T., Ash, J. S., Erickson, J. L., Wasserman, J. A., Bunce, A., Stanescu, A., Hilaire, D. S., Panzenhagen, M., Gebhardt, E., McMullen, C. K., et al. (2013) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2013-001771 · Cited by 40
Self-citationBooth, R. G., Andrusyszyn, M., Iwasiw, C., Donelle, L., & Compeau, D. (2015) · Nursing Inquiry · doi:10.1111/nin.12118 · Cited by 39
Public Health and Epidemiology Informatics: Recent Research and Trends in the United States
Dixon, B. E., Kharrazi, H. H. K., & Lehmann, H. P. (2015) · Yearbook of Medical Informatics · doi:10.15265/iy-2015-012 · Cited by 38
Ray, J. M., Ratwani, R. M., Sinsky, C. A., Frankel, R. M., Friedberg, M. W., Powsner, S. M., Rosenthal, D. I., Wachter, R. M., & Melnick, E. R. (2019) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocz098 · Cited by 34
Furniss, D. J., Masci, P. M., Curzon, P., Mayer, A., & BLANDFORD, A. E. (2014) · Applied Ergonomics · doi:10.1016/j.apergo.2014.05.012 · Cited by 38
Kelley, L., Fujioka, J. K., Liang, K., Cooper, M., Jamieson, T., & Desveaux, L. (2020) · JMIR Public Health and Surveillance · doi:10.2196/20579 · Cited by 42
Kushniruk, A. W., Bellwood, P. S., Brender, J., & Borycki, E. M. (2011) · Methods of Information in Medicine · doi:10.3414/me11-02-0009 · Cited by 38
Challenges in patient safety improvement research in the era of electronic health records
Russo, E. M., Sittig, D. F., Murphy, D. R., & Singh, H. (2016) · Healthcare · doi:10.1016/j.hjdsi.2016.06.005 · Cited by 42
Self-citationImproving Test Result Follow-up through Electronic Health Records Requires More than Just an Alert
Sittig, D. F., & Singh, H. (2012) · Journal of General Internal Medicine · doi:10.1007/s11606-012-2161-y · Cited by 37
Self-citationUnintended Consequences of EHR Systems: A Narrative Review
Vanderhook, S., & Abraham, J. (2017) · Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care · doi:10.1177/2327857917061048 · Cited by 37
Garvin, J. H., Kim, Y.-J., Gobbel, G. T., Matheny, M. E., Redd, A. M., Bray, B. E., Heidenreich, P. A., Bolton, D., Heavirland, J., Kelly, N. F. A., et al. (2018) · JMIR Medical Informatics · doi:10.2196/medinform.9150 · Cited by 37
Byrd, T. F., Kim, J. S., Yeh, C., Lee, J. J., & O’Leary, K. J. (2021) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2021.103749 · Cited by 39
Martinez, R. N., Hogan, T. P., Balbale, S., Lones, K., Goldstein, B., Woo, C., & Smith, B. M. (2017) · Telemedicine and e-Health · doi:10.1089/tmj.2016.0200 · Cited by 35
Furniss, D. J., Masci, P. M., Curzon, P., Mayer, A., & BLANDFORD, A. E. (2014) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2014.12.006 · Cited by 36
Austin, E. J., LeRouge, C., Lee, J. R., Segal, C. D., Sangameswaran, S., Heim, J. A., Lober, W. B., Hartzler, A. L., & Lavallee, D. C. (2021) · Learning Health Systems · doi:10.1002/lrh2.10263 · Cited by 35
Darcel, K., Upshaw, T. L., Craig-Neil, A., Macklin, J. A., Gray, C. S., Chan, T. C. Y., Gibson, J., & Pinto, A. D. (2023) · PLoS ONE · doi:10.1371/journal.pone.0281733 · Cited by 36
Design for mobile mental health: an exploratory review
Aryana, B., Brewster, L., & Abdelnour-Nocera, J. (2018) · Health and Technology · doi:10.1007/s12553-018-0271-1 · Cited by 36
Role of Agile in Digital Public Health Transformation
Kokol, P., Vošner, H. B., Kokol, M., & Završnik, J. (2022) · Frontiers in Public Health · doi:10.3389/fpubh.2022.899874 · Cited by 35
Access to What for Whom? How Care Delivery Innovations Impact Health Equity
Szymczak, J. E., Fiks, A. G., Craig, S., Méndez, D. D., & Ray, K. N. (2023) · Journal of General Internal Medicine · doi:10.1007/s11606-022-07987-3 · Cited by 35
Igene, O. O., & Johnson, C. (2019) · Health Informatics Journal · doi:10.1177/1460458219859992 · Cited by 34
Powell, L., Sittig, D. F., Chrouser, K. L., & Singh, H. (2020) · JAMA Network Open · doi:10.1001/jamanetworkopen.2020.6752 · Cited by 34
Self-citationUser Centered Clinical Decision Support Tools
Sofianou, A., Kannry, J. L., Mann, D. M., McGinn, T. G., & McCullagh, L. (2014) · Applied Clinical Informatics · doi:10.4338/aci-2014-05-ra-0048 · Cited by 33
Chung, P., Scandlyn, J. N., Dayan, P. S., & Mistry, R. D. (2017) · American Journal of Infection Control · doi:10.1016/j.ajic.2017.06.005 · Cited by 33
Diagnostic errors: moving beyond ‘no respect’ and getting ready for prime time
Singh, H. (2013) · BMJ Quality & Safety · doi:10.1136/bmjqs-2013-002387 · Cited by 32
Self-citationEncouraging Patient Portal Use in the Patient-Centered Medical Home: Three Stakeholder Perspectives
Fix, G. M., Hogan, T. P., Amante, D. J., McInnes, D. K., Nazi, K. M., & Simon, S. R. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.6488 · Cited by 33
What is the safety case for health IT? A study of assurance practices in England
Habli, I., White, S., Sujan, M. A., Harrison, S., & Ugarte, M. (2018) · Safety Science · doi:10.1016/j.ssci.2018.09.001 · Cited by 31
Safe use of the EHR by medical scribes: a qualitative study
Ash, J. S., Corby, S., Mohan, V., Solberg, N., Becton, J., Bergstrom, R., Orwoll, B., Hoekstra, C., & Gold, J. A. (2020) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocaa199 · Cited by 32
Smith, M., Murphy, D., Laxmisan, A., Sittig, D., Reis, B., Esquivel, A., & Singh, H. (2013) · Applied Clinical Informatics · doi:10.4338/aci-2013-04-ra-0019 · Cited by 31
Self-citationGeorgiou, A., Lymer, S. J., Forster, M., Strachan, M., Graham, S. M., HIRST, G. H. L., Callen, J. L., & Westbrook, J. I. (2014) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2013-002466 · Cited by 31
Murphy, D. R., Meyer, A. N. D., Vaghani, V., Russo, E. M., Sittig, D. F., Wei, L., Wu, L., & Singh, H. (2017) · Clinical Gastroenterology and Hepatology · doi:10.1016/j.cgh.2017.08.007 · Cited by 31
Self-citationWang, J., Liang, H., Kang, H., & Gong, Y. (2019) · Applied Clinical Informatics · doi:10.1055/s-0039-1678693 · Cited by 35
Gui, X., Chen, Y., Zhou, X., Reynolds, T. L., Zheng, K., & Hanauer, D. A. (2020) · JAMIA Open · doi:10.1093/jamiaopen/ooz051 · Cited by 31
Elshayib, M., & Pawola, L. M. (2020) · Health Informatics Journal · doi:10.1177/1460458220941750 · Cited by 33
Advancing Diagnostic Safety Research: Results of a Systematic Research Priority Setting Exercise
Zwaan, L., El-Kareh, R. E., Meyer, A. N. D., Hooftman, J., & Singh, H. (2021) · Journal of General Internal Medicine · doi:10.1007/s11606-020-06428-3 · Cited by 31
Self-citationCifra, C. L., Sittig, D. F., & Singh, H. (2021) · BMJ Quality & Safety · doi:10.1136/bmjqs-2020-012464 · Cited by 31
Self-citationCarayon, P., Wetterneck, T. B., Cartmill, R. S., Blosky, M. A., Brown, R., Hoonakker, P., Kim, R., Kukreja, S., Johnson, M., Paris, B. L., et al. (2017) · Journal of Patient Safety · doi:10.1097/pts.0000000000000358 · Cited by 31
Gillner, S. (2024) · Social Science & Medicine · doi:10.1016/j.socscimed.2023.116442 · Cited by 30
McCullough, J. M., Zimmerman, F. J., Bell, D. S., & Rodríguez, H. P. (2014) · BMC Health Services Research · doi:10.1186/1472-6963-14-415 · Cited by 34
Review of Social and Organizational Issues in Health Information Technology
Kuziemsky, C. E. (2015) · Healthcare Informatics Research · doi:10.4258/hir.2015.21.3.152 · Cited by 33
Clinical reasoning in the context of active decision support during medication prescribing
Horsky, J., Aarts, J., Leonie, V., Seger, D. L., van der Sijs, H., & Bates, D. W. (2016) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2016.09.004 · Cited by 33
Dullabh, P., Hovey, L. S., Heaney-Huls, K., Rajendran, N., Wright, A. T., & Sittig, D. F. (2020) · Applied Clinical Informatics · doi:10.1055/s-0039-1701001 · Cited by 32
Self-citationElectronic Health Records as Biased Tools or Tools Against Bias: A Conceptual Model
Rozier, M. D., Patel, K., & Cross, D. A. (2021) · Milbank Quarterly · doi:10.1111/1468-0009.12545 · Cited by 32
Wakefield, B. J., Turvey, C., Nazi, K. M., Holman, J. E., Hogan, T. P., Shimada, S. L., & Kennedy, D. R. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.7638 · Cited by 32
Barriers to Implementing an Artificial Intelligence Model for Unplanned Readmissions
Baxter, S. L., Bass, J. S., & Sitapati, A. M. (2020) · ACI Open · doi:10.1055/s-0040-1716748 · Cited by 30
Cheung, J. L. S., Paolucci, N., Price, C. M., Sykes, J. R., & Gupta, S. (2020) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocaa019 · Cited by 30
Definitions, components and processes of data harmonisation in healthcare: a scoping review
Schmidt, B., Colvin, C., Hohlfeld, A., & Leon, N. (2020) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-020-01218-7 · Cited by 24
Enhancing Diagnosis Through Technology
El-Kareh, R. E., & Sittig, D. F. (2021) · Critical Care Clinics · doi:10.1016/j.ccc.2021.08.004 · Cited by 31
Self-citationExploring physicians’ continuous use of clinical decision support systems
Abouzahra, M., Guenter, D., & Tan, J. (2022) · European Journal of Information Systems · doi:10.1080/0960085x.2022.2119172 · Cited by 33
Turner, P. A., Kushniruk, A. W., & Nøhr, C. (2017) · Yearbook of Medical Informatics · doi:10.15265/iy-2017-014 · Cited by 36
Electronic medical record implementation in a large healthcare system from a leadership perspective
Arabi, Y. M., Ghamdi, A. A. A., Al-Moamary, M. S., Mutrafy, A. A., AlHazme, R. H., & Al-Knawy, B. (2022) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-022-01801-0 · Cited by 28
Rights and responsibilities of users of electronic health records
Sittig, D. F., & Singh, H. (2012) · Canadian Medical Association Journal · doi:10.1503/cmaj.111599 · Cited by 30
Self-citationPatient safety goals for the proposed Federal Health Information Technology Safety Center
Sittig, D. F., Classen, D. C., & Singh, H. (2014) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2014-002988 · Cited by 28
Self-citationProgress understanding diagnosis and diagnostic errors: thoughts at year 10
Graber, M. L. (2020) · Diagnosis · doi:10.1515/dx-2020-0055 · Cited by 32
Wesley, D. B., Schubel, L., Hsiao, C., Burn, S., Howe, J. L., Kellogg, K., Lincoln, A. E., Kim, B. I., & Ratwani, R. M. (2019) · Journal of Biomedical Informatics · doi:10.1016/j.yjbinx.2019.100048 · Cited by 27
Human Factors and Ergonomics in Healthcare: Industry Demands and a Path Forward
Keebler, J. R., Rosen, M. A., Sittig, D. F., Thomas, E. J., & Salas, E. (2022) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/00187208211073623 · Cited by 33
Self-citationA Safe Practice Standard for Barcode Technology
Leung, A. A. C., Denham, C. R., Gandhi, T. K., Bane, A., Churchill, W. W., Bates, D. W., & Poon, E. G. (2014) · Journal of Patient Safety · doi:10.1097/pts.0000000000000049 · Cited by 28
Savoy, A., Militello, L. G., Patel, H., Flanagan, M., Russ, A. L., Daggy, J., Weiner, M., & Saleem, J. J. (2018) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2018.07.021 · Cited by 27
Resilient practices in maintaining safety of health information technologies
Smith, M. W., Ash, J. S., Sittig, D. F., & Singh, H. (2014) · Journal of Cognitive Engineering and Decision Making · doi:10.1177/1555343414534242 · Cited by 26
“In view of the dynamic complexity of EHR-enabled health care delivery systems (Carayon et al., 2006; Kannampallil, Schauer, Cohen, & Patel, 2011; Sittig & Singh, 2010), we propose that successful safety management of EHRs entails the use of resilience-related practices.”
BackgroundMethodSelf-citationLaxmisan, A., Sittig, D. F., Pietz, K., Espadas, D., Krishnan, B., & Singh, H. (2012) · Medical Care · doi:10.1097/mlr.0b013e31825f6619 · Cited by 26
Self-citationChai, P. R., Zhang, H., Baugh, C. W., Jambaulikar, G. D., McCabe, J., Gorman, J. M., Boyer, E. W., & Landman, A. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.9454 · Cited by 27
Why Test Results Are Still Getting “Lost” to Follow-up: a Qualitative Study of Implementation Gaps
Zimolzak, A. J., Shahid, U., Giardina, T. D., Memon, S. A., Mushtaq, U., Zubkoff, L., Murphy, D. R., Bradford, A. M., & Singh, H. (2021) · Journal of General Internal Medicine · doi:10.1007/s11606-021-06772-y · Cited by 27
Self-citationSittig, D. F., Sherman, J. D., Eckelman, M. J., Draper, A., & Singh, H. (2022) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocac137 · Cited by 29
Self-citationMethods for Addressing Technology-induced Errors: The Current State
Dexheimer, J. W., Cossio, C. H. L., Gong, Y., Jensen, S., Kaipio, J., Kennebeck, S., Kirkendall, E. S., Kushniruk, A. W., Kuziemsky, C. E., Marcilly, R., et al. (2016) · Yearbook of Medical Informatics · doi:10.15265/iy-2016-029 · Cited by 26
Humphrey-Murto, S. M., Makus, D., Moore, S., Duffy, K. W., Maniate, J. M., Scowcroft, K., Buba, M., & Rangel, J. C. (2022) · Medical Education · doi:10.1111/medu.14944 · Cited by 25
Automation in Contemporary Clinical Information Systems: a Survey of AI in Healthcare Settings
Magrabi, F., Lyell, D., & Coiera, E. W. (2023) · Yearbook of Medical Informatics · doi:10.1055/s-0043-1768733 · Cited by 28
Mache, S., Bernburg, M., Würtenberger, A., & Groneberg, D. A. (2025) · Clinics and Practice · doi:10.3390/clinpract15080138 · Cited by 27
Potential Unintended Consequences of Health Information Exchange
Kuperman, G. J., & McGowan, J. J. (2013) · Journal of General Internal Medicine · doi:10.1007/s11606-012-2313-0 · Cited by 25
McDonald, K. M., Rodríguez, H. P., & Shortell, S. M. (2018) · Medical Care · doi:10.1097/mlr.0000000000000974 · Cited by 25
Gaps in standards for integrating artificial intelligence technologies into ophthalmic practice
Baxter, S. L., & Lee, A. (2021) · Current Opinion in Ophthalmology · doi:10.1097/icu.0000000000000781 · Cited by 25
Sistemas de información en salud: integrando datos clínicos en diferentes escenarios y usuarios
Plazzotta, F., Luna, D. R., & de Quirós, F. G. B. (2015) · Revista Peruana de Medicina Experimental y Salud Pública · doi:10.17843/rpmesp.2015.322.1630 · Cited by 25
An Evaluation of Understandability of Patient Journey Models in Mental Health
Percival, J., & McGregor, C. (2016) · JMIR Human Factors · doi:10.2196/humanfactors.5640 · Cited by 26
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