SEIPS 101 and seven simple SEIPS tools

Holden, Richard J.; Carayon, Pascale

doi:10.1136/bmjqs-2020-012538

Cited by 98 publications

(86 citation statements)

References 46 publications

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“…As with many clinical informatics interventions, there could be numerous social and/or technical factors that may have influenced the reported outcomes beyond the dashboard. Rigorous informatics and human factors design approaches 44–47 are needed to improve the use and impact of patient safety dashboards. Because intervention development is often time constrained, rapid qualitative assessment approaches or human factors methods involving rapid prototyping, 48 49 for example, can be adapted to meet the shorter timelines needed for rapid cycle quality improvement.…”

Section: Discussionmentioning

confidence: 99%

Dashboards for visual display of patient safety data: a systematic review

Murphy

Savoy

Satterly

et al. 2021

BMJ Health Care Inform

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BackgroundMethods to visualise patient safety data can support effective monitoring of safety events and discovery of trends. While quality dashboards are common, use and impact of dashboards to visualise patient safety event data remains poorly understood.ObjectivesTo understand development, use and direct or indirect impacts of patient safety dashboards.MethodsWe conducted a systematic review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched PubMed, EMBASE and CINAHL for publications between 1 January 1950 and 30 August 2018 involving use of dashboards to display data related to safety targets defined by the Agency for Healthcare Research and Quality’s Patient Safety Net. Two reviewers independently reviewed search results for inclusion in analysis and resolved disagreements by consensus. We collected data on development, use and impact via standardised data collection forms and analysed data using descriptive statistics.ResultsLiterature search identified 4624 results which were narrowed to 33 publications after applying inclusion and exclusion criteria and consensus across reviewers. Publications included only time series and case study designs and were inpatient focused and emergency department focused. Information on direct impact of dashboards was limited, and only four studies included informatics or human factors principles in development or postimplementation evaluation.DiscussionUse of patient-safety dashboards has grown over the past 15 years, but impact remains poorly understood. Dashboard design processes rarely use informatics or human factors principles to ensure that the available content and navigation assists task completion, communication or decision making.ConclusionDesign and usability evaluation of patient safety dashboards should incorporate informatics and human factors principles. Future assessments should also rigorously explore their potential to support patient safety monitoring including direct or indirect impact on patient safety.

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Section: Discussionmentioning

confidence: 99%

Dashboards for visual display of patient safety data: a systematic review

Murphy

Savoy

Satterly

et al. 2021

BMJ Health Care Inform

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“…As GAM is structured according to the widely used SEIPS model30 31 56 and built on methods that are currently applied by hospitals, we believe GAM may be easily adopted. Other promising methods that aim to improve learning from RCA such as the Human Factors Analysis and Classification System,57 AcciMap58 and Functional Resonance Analysis Method59 were not specifically build on the well-known SEIPS model and existing methods.…”

Section: Discussionmentioning

confidence: 99%

Generic analysis method to learn from serious adverse events in Dutch hospitals: a human factors perspective

2022

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BackgroundHospitals in various countries such as the Netherlands investigate and analyse serious adverse events (SAEs) to learn from previous events and attempt to prevent recurrence. However, current methods for SAE analysis do not address the complexity of healthcare and investigations typically focus on single events on the hospital level. This hampers hospitals in their ambition to learn from SAEs. Integrating human factors thinking and using a holistic and more consistent method could improve learning from SAEs.AimThis study aims to develop a novel generic analysis method (GAM) to: (1) facilitate a holistic event analysis using a human factors perspective and (2) ease aggregate analysis of events across hospitals.MethodsMultiple steps of carefully evaluating, testing and continuously refining prototypes of the method were performed. Various Dutch stakeholders in the field of patient safety were involved in each step. Theoretical experts were consulted, and the prototype was pretested using information-rich SAE reports from Dutch hospitals. Expert panels, engaging quality and safety experts and medical specialists from various hospitals were consulted for face and content validity evaluation. User test sessions concluded the development of the method.ResultsThe final version of the GAM consists of a framework and affiliated questionnaire. GAM combines elements of three methods for SAE analysis currently practised by Dutch hospitals. It is structured according to the Systems Engineering Initiative for Patient Safety model, which incorporates a human factors perspective into the analysis. These eases aggregated analysis of SAEs across hospitals and helps to consider the complexity of healthcare work systems.ConclusionThe GAM is a valuable new tool for hospitals to learn from SAEs. The method can facilitate a holistic aggregate analysis of SAEs across hospitals using a human factors perspective, and is now ready for further extensive testing.

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“…A esto hay que sumar el uso de otras alternativas metodológicas como los mapas de trayecto (journey maps) (Gibbons, 2018) o el service design blueprint (Aceves-González, 2015), que pueden brindar una mirada más holística, a partir de una visualización de los elementos presentes en el sistema y su forma de relacionarse. Es importante mencionar que la presencia de la ergonomía en los sistemas de salud no se agota en las herramientas presentes en este texto y que es posible encontrar tanto para la evaluación de las tareas, como para la evaluación de los recursos tecnológicos, otras opciones metodológicas relevantes para ser consideradas (Holden & Carayon, 2021).…”

Section: Discussionunclassified

Herramientas de ergonomía en los sistemas de salud. Alternativas para el mejoramiento de las tareas y la tecnología

Rey-Galindo¹,

Duque-Álvarez²

2021

EIDCC

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desde la ergonomía/factores humanos han contribuido a identificar y comprender los componentes de los sistemas de salud y la manera en cómo están relacionados. No obstante, en la búsqueda por hacer que en Latinoamérica, la presencia de la ergonomía/factores humanos se fortalezca en los sistemas de salud, es necesario, además, evidenciar algunas de las herramientas que pueden constituirse en alternativas muy importantes para encontrar avances en el funcionamiento de estos sistemas y con ello del bienestar de la población. Para ello, en el presente texto se describen seis herramientas que pueden ser usadas para la evaluación de las tareas y de los recursos tecnológicos; dos áreas descritas desde el modelo SEIPS 3.0. Se espera con esto, contribuir a la comprensión metodológica de la ergonomía/factores humanos, para su integración más clara en los procesos de mejora de los sistemas de salud.Palabras clave: Sistemas de salud, ergonomía/factores humanos, evaluación de tareas, evaluación de tecnología.

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SEIPS 101 and seven simple SEIPS tools

Cited by 98 publications

References 46 publications

Dashboards for visual display of patient safety data: a systematic review

Dashboards for visual display of patient safety data: a systematic review

Generic analysis method to learn from serious adverse events in Dutch hospitals: a human factors perspective

Herramientas de ergonomía en los sistemas de salud. Alternativas para el mejoramiento de las tareas y la tecnología

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