Cystic fibrosis learning network telehealth innovation lab during the COVID-19 pandemic: a success QI story for interdisciplinary care and agenda setting.

INTRODUCTION: The Cystic Fibrosis Foundation chronic care guidelines recommend monitoring clinical status of a patient with cystic fibrosis (CF) through quarterly interdisciplinary visits. At the beginning of the COVID-19 pandemic, the Cystic Fibrosis Learning Network (CFLN) designed and initiated a telehealth (TH) innovation lab (TH ILab) to support transition from the classic CF care model of quarterly in-person office visits to a care model that included TH. AIM: The specific aims of the TH ILab were to increase the percentage of virtual visits with interdisciplinary care (IDC) from 60% to 85% and increase the percentage of virtual visits in which patients and families participated in shared agenda setting (AS) from 52% to 85% by 31 December 2020. METHODS: The model for improvement methodology was used to determine the ILab aims, theory, interventions and measures. In the testing phase of the ILab, data related to process and outcome measures as well as learnings from plan-do-study-act cycles were collected, analysed and shared weekly with the TH ILab teams. Participating centres created processes for IDC and AS for TH visits and developed and shared quality improvement tools specific to their local context with other centres during the ILab weekly meetings and via a secure CFLN-maintained platform. RESULTS: Both specific aims were achieved ahead of the expected target date. By August 2020, 85% of the TH ILab visits provided IDC and 92% of patients were seen for CF care by teams from the TH ILab that participated in AS. CONCLUSION: Shared learning through a collaborative, data-driven process in the CFLN TH ILab rapidly led to standardised TH IDC and AS, which achieved reliable and sustainable processes which could be reproduced by other networks.

Holistic risk assessment of container shipping service based on Bayesian Network Modelling

Container shipping makes significant contribution to the global economy and is confronted with various hazards and risks especially during the COVID-19 pandemic. These risks can disrupt resilient container shipping service, leading to further deterioration of the global economy. Hence, it is vital to develop resilient container shipping service, which is associated with being on-time, safe, and hassle-free. Theoretically, this research identifies 28 root risks using the PESTLE framework, conducts risk assessment using a hybrid method comprising failure modes and effects analysis, evidential reasoning, and rule-based Bayesian network. A three-hierarchy Bayesian network model is established. The results reveal that economic, political, and technical risks are the most threatening risks affecting resilient container shipping service. Moreover, the holistic container shipping risk is most sensitive to environmental risks. Managerially, this research provides container shipping companies with guidance of drafting risk mitigation plans with economic risks and political risks as priorities.

Systems engineering analysis of diagnostic referral closed-loop processes.

BACKGROUND: Closing loops to complete diagnostic referrals remains a significant patient safety problem in most health systems, with 65%-73% failure rates and significant delays common despite years of improvement efforts, suggesting new approaches may be useful. Systems engineering (SE) methods increasingly are advocated in healthcare for their value in studying and redesigning complex processes. OBJECTIVE: Conduct a formative SE analysis of process logic, variation, reliability and failures for completing diagnostic referrals originating in two primary care practices serving different demographics, using dermatology as an illustrating use case. METHODS: An interdisciplinary team of clinicians, systems engineers, quality improvement specialists, and patient representatives collaborated to understand processes of initiating and completing diagnostic referrals. Cross-functional process maps were developed through iterative group interviews with an urban community-based health centre and a teaching practice within a large academic medical centre. Results were used to conduct an engineering process analysis, assess variation within and between practices, and identify common failure modes and potential solutions. RESULTS: Processes to complete diagnostic referrals involve many sub-standard design constructs, with significant workflow variation between and within practices, statistical instability and special cause variation in completion rates and timeliness, and only 21% of all process activities estimated as value-add. Failure modes were similar between the two practices, with most process activities relying on low-reliability concepts (eg, reminders, workarounds, education and verification/inspection). Several opportunities were identified to incorporate higher reliability process constructs (eg, simplification, consolidation, standardisation, forcing functions, automation and opt-outs). CONCLUSION: From a systems science perspective, diagnostic referral processes perform poorly in part because their fundamental designs are fraught with low-reliability characteristics and mental models, including formalised workaround and rework activities, suggesting a need for different approaches versus incremental improvement of existing processes. SE perspectives and methods offer new ways of thinking about patient safety problems, failures and potential solutions.

Home spirometry utilisation in telemedicine clinic for cystic fibrosis care during COVID-19 pandemic: a quality improvement process.

IntroductionThe Cystic Fibrosis (CF) Foundation chronic care guidelines recommend monitoring spirometry during quarterly multidisciplinary visits to identify early lung function decline. During the COVID-19 pandemic, the CF adult clinic at University of Virginia (UVA) transitioned from the classic CF care model to a model that included quarterly multidisciplinary telemedicine visits. While using telemedicine, CF care needed to include spirometry monitoring. Only a fraction of adult CF patients at UVA owned and used home spirometers (HS) in March 2020. AIM: The specific aims of this quality improvement (QI) project were to increase the percentage of eligible adult CF patients who owned an HSs from 37% to 85% and to increase the percentage of adult CF patients seen at UVA with available spirometry in telemedicine from 50% to 95% by 31 December 2020. METHODS: Following the Model for Improvement QI methodology, a standardised process was developed for monitoring forced expiratory volume in 1 s with HS during multidisciplinary telemedicine visits during the COVID-19 pandemic. INTERVENTION: (1) HSs were distributed to eligible patients and (2) Home spirometry was monitored in eligible patients with each telemedicine visit and results were used for clinical care decisions. RESULTS: Both specific aims were achieved ahead of expected date. In March 2020, the beginning of the pandemic, 37% (49/131) of patients owned an HS and 50% (9/18) of patients seen via telemedicine performed spirometry at home. By September 2020, 97% (127/131) of adult patients at UVA owned an HS and by October 2020, 96% (24/25) of patients provided spirometry results during their telemedicine encounters. CONCLUSION: Employing QI tools to standardise the process of monitoring spirometry data with home devices via telemedicine is reliable and sustainable and can be replicated across centres that provide care for patients with CF.

Assisting beginners in root cause analysis operations: analysis and recommendations regarding the spread of COVID-19 in nursing facilities for the elderly.

BACKGROUND: To analyse a medical accident, much time and experience are needed. However, people without experience in analysis have difficulty understanding its conditions and methods, and as a result it takes longer to establish countermeasures. It must be noted that understanding conditions by simply aligning occurrences in the accident in a chronological order is difficult. PURPOSE: A workflow chart that considers time was proposed so that individuals without adequate experience in analysis could easily carry out root cause analysis. METHODS: In the 'workflow chart (WFC)', the time sequence was described horizontally. On the vertical axis, the business manual, the occurrence of the accident, and the time of the occurrence are displayed. In the bottom column of patient event, information regarding damage to patients was written in accordance with time axis. Regarding the degree of damage, the time of error until the accident was identified was connected using a straight line (when the patient was not affected, a dotted line was used) in order to show the overall picture of the accident. RESULTS: According to the time flow chart, hints to identify potential risks were proposed. Focus was placed not only on the error event, but also on keywords such as manual inadequacy, time gap, degree of error and so on to easily lead to the question 'why?' To visualise this, I proposed an operation flow chart. By using time-WFC, even beginners can easily develop accident countermeasure strategies. CONCLUSION: Using a WFC that considers time, time of error and the occurrence of accident could be visualised. As a result, even individuals without experience in analysis could easily perform an analysis.