Using the Systems Engineering Initiative for Patient Safety (SEIPS) model to describe the planning and management of the COVID-19 pandemic in Hong Kong

Kwan, Wai-Man; Mok, Chun-Keung; Kwok, Yick-Ting; Ling, H. C.; Lam, Hon-Wai; Law, Tat-Hong; Leung, Pik-Man; Mak, Man-Yu; Que, Tak-Lun; Kan, Chun-Hoi; Tang, Yiu-Hang

doi:10.1093/intqhc/mzab042

Cited by 4 publications

(1 citation statement)

References 8 publications

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“…The model can be used to identify organizational factors related to resilience such as coordination and team work as well as flexibility, adaptability and transformational resilience factors such as health infrastructure, technology and tools. Previous researchers have used the framework to evaluate the response to the COVID-19 pandemic [ 21 ], its impact on health service continuity [ 22 ] and the prevention of intra-hospital COVID-19 infections [ 23 ]. The framework has three main components including work systems (health care personnel, roles, tools & technology, internal and external environment), work processes (physical processes, e.g.…”

Section: Data Collectionmentioning

confidence: 99%

How interventions to maintain services during the COVID-19 pandemic strengthened systems for delivery of maternal and child health services: a case-study of Wakiso District, Uganda

Kabwama,

Wanyenze,

Razaz

et al. 2024

Global Health Action

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Background Health systems are resilient if they absorb, adapt, and transform in response to shocks. Although absorptive and adaptive capacities have been demonstrated during the COVID-19 response, little has been documented about their transformability and strengthened service delivery systems. We aimed to describe improvements in maternal and child health service delivery as a result of investments during the COVID-19 response. Methods This was a descriptive case study conducted in Wakiso District in central Uganda. It included 21 nurses and midwives as key informants and 32 mothers in three focus group discussions. Data were collected using an interview guide following the Systems Engineering Initiative for Patient Safety theoretical framework for service delivery. Results Maternal and child health service delivery during the pandemic involved service provision without changes, service delivery with temporary changes and outcomes, and service delivery that resulted into sustained changes and outcomes. Temporary changes included patient schedule adjustments, community service delivery and negative outcomes such as increased workload and stigma against health workers. Sustained changes that strengthened service delivery included new infrastructure and supplies such as ambulances and equipment, new roles involving infection prevention and control, increased role of community health workers and outcomes such as improved workplace safety and teamwork. Conclusions In spite of the negative impact the COVID-19 pandemic had on health systems, it created the impetus to invest in system improvements. Investments such as new facility infrastructure and emergency medical services were leveraged to improve maternal and child health services delivery. The inter-departmental collaboration during the response to the COVID-19 pandemic resulted into an improved intra-hospital environment for other service delivery. However, there is a need to evaluate lessons beyond health facilities and whether these learnings are deliberately integrated into service delivery. Future responses should also address the psychological and physical impacts suffered by health workers to maintain service delivery.

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Section: Data Collectionmentioning

confidence: 99%

How interventions to maintain services during the COVID-19 pandemic strengthened systems for delivery of maternal and child health services: a case-study of Wakiso District, Uganda

Kabwama,

Wanyenze,

Razaz

et al. 2024

Global Health Action

View full text Add to dashboard Cite

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Analysis of Digital Data on Communication Strategies in Companies During COVID-19

Leon-Dextre,

Salazar-Vegas,

Fernandez-Saucedo

et al. 2023

Lecture Notes in Networks and Systems

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Investigating the cognitive capacity constraints of an ICU care team using a systems engineering approach

et al. 2022

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Background ICU operational conditions may contribute to cognitive overload and negatively impact on clinical decision making. We aimed to develop a quantitative model to investigate the association between the operational conditions and the quantity of medication orders as a measurable indicator of the multidisciplinary care team’s cognitive capacity. Methods The temporal data of patients at one medical ICU (MICU) of Mayo Clinic in Rochester, MN between February 2016 to March 2018 was used. This dataset includes a total of 4822 unique patients admitted to the MICU and a total of 6240 MICU admissions. Guided by the Systems Engineering Initiative for Patient Safety model, quantifiable measures attainable from electronic medical records were identified and a conceptual framework of distributed cognition in ICU was developed. Univariate piecewise Poisson regression models were built to investigate the relationship between system-level workload indicators, including patient census and patient characteristics (severity of illness, new admission, and mortality risk) and the quantity of medication orders, as the output of the care team’s decision making. Results Comparing the coefficients of different line segments obtained from the regression models using a generalized F-test, we identified that, when the ICU was more than 50% occupied (patient census > 18), the number of medication orders per patient per hour was significantly reduced (average = 0.74; standard deviation (SD) = 0.56 vs. average = 0.65; SD = 0.48; p < 0.001). The reduction was more pronounced (average = 0.81; SD = 0.59 vs. average = 0.63; SD = 0.47; p < 0.001), and the breakpoint shifted to a lower patient census (16 patients) when at a higher presence of severely-ill patients requiring invasive mechanical ventilation during their stay, which might be encountered in an ICU treating patients with COVID-19. Conclusions Our model suggests that ICU operational factors, such as admission rates and patient severity of illness may impact the critical care team’s cognitive function and result in changes in the production of medication orders. The results of this analysis heighten the importance of increasing situational awareness of the care team to detect and react to changing circumstances in the ICU that may contribute to cognitive overload.

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Using the Systems Engineering Initiative for Patient Safety (SEIPS) model to describe the planning and management of the COVID-19 pandemic in Hong Kong

Cited by 4 publications

References 8 publications

How interventions to maintain services during the COVID-19 pandemic strengthened systems for delivery of maternal and child health services: a case-study of Wakiso District, Uganda

How interventions to maintain services during the COVID-19 pandemic strengthened systems for delivery of maternal and child health services: a case-study of Wakiso District, Uganda

Analysis of Digital Data on Communication Strategies in Companies During COVID-19

Investigating the cognitive capacity constraints of an ICU care team using a systems engineering approach

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