Does integration with national registers improve the data completeness of local COVID-19 contact tracing tools? A register-based study in Norway, May 2020 - September 2021.

BACKGROUND: During the COVID-19 response in Norway, many municipalities used the Fiks contact tracing tool (FiksCT) to register positive individuals and follow-up contacts. This tool is based on DHIS2, an open source, web-based platform. In this study we examined if data completeness in FiksCT improved after integration with national registers between May 2020 and September 2021. METHODS: Data from municipalities using FiksCT was extracted from the Norwegian Emergency Preparedness Register for COVID-19 (Beredt C19). We linked FiksCT data to the Norwegian Surveillance System for Communicable Diseases (MSIS), the National Population Register (FREG), and the Norwegian Vaccine Registry (SYSVAK) using unique identification numbers (ID). Completeness for each variable linked with a national register was calculated before and after integration with these registers. RESULTS: Of the 125 municipalities using FiksCT, 87 (69.6%) agreed to share and upload their data to Beredt C19. Data completeness for positive individuals improved after integration with national registers. After integration with FREG, the proportion of missing values decreased from 12.5 to 1.6% for ID, from 4.5 to 0.9% for sex, and from 1.2 to 0.4% for date of birth. Missing values for vaccine type decreased from 63.0 to 15.2% and 39.3-36.7% for first and second dose, respectively. In addition, direct reporting from FiksCT to MSIS increased the proportion of complete records in MSIS (on the selected variables) from 68.6% before to 77.0% after integration. CONCLUSION: The completeness of local contact tracing data can be improved by enabling integration with established national registers. In addition, providing the option to submit local data to the national registers could ease workload and reduce the need to collect duplicate data.

Effectiveness of integrated care models for stroke patients: A systematic review and meta-analysis.

INTRODUCTION: Given that stroke is a leading cause of disability and mortality worldwide, there is an urgent need for a coordinated healthcare approach to mitigate its effects. The objectives of this study were to perform a systematic review and meta-analysis of stroke integrated care models and develop recommendations for a representative model. DESIGN: A systematic review and meta-analysis. METHODS: The literature search identified randomized controlled trials comparing integrated care models with standard care for stroke patients. The included studies followed PICOs inclusion criteria. The qualitative analysis included creating a flowchart for the literature screening process, and tables detailing the basic characteristics of the included studies, the adherence to the ten principles and the results of the quality assessments. Subsequently, quantitative meta-analytical procedures were conducted to statistically pool the data and quantify the effects of the integrated care models on stroke patients' health-related quality of life, activities of daily living, and depression. The China National Knowledge Infrastructure (CNKI), Wanfang Data, Chongqing VIP Chinese Science and Technology Periodical Database (VIP), China Biology Medicine Disc (CBMDISC), Cochrane Library, Cumulated Index to Nursing and Allied Health Literature (CINAHL), PubMed, Web of Science, Embase, Google Scholar, and Clinical Trials were searched from inception to March 13, 2024. RESULTS: Of the 2547 obtained articles, 19 were systematically reviewed and 15 were included in the meta-analysis. The integrated care models enhanced stroke patients' health-related quality of life, ability to perform activities of daily living, and reduced depression. Adherence to the 10 principles varied: comprehensive services, patient focus, and standardized care delivery had strong implementation, while gaps were noted in geographic coverage, information systems, governance structures, and financial management. CONCLUSION: Integrated care models improve outcomes for stroke patients and adherence to the 10 principles is vital for their implementation success. This study's findings call for a more standardized approach to implementing integrated care models, emphasizing the need for integrated services, patient-centred care, and interdisciplinary collaboration, while also addressing the identified gaps in terms of integration efforts. CLINICAL RELEVANCE: This study provides evidence-based recommendations on the most effective integrated care approaches for stroke patients, potentially leading to better patient outcomes, reduced healthcare costs, and improved quality of life.

Leveraging In Situ Simulation for Implementation of Teleobstetric Consultation Services in Rural and Community Hospitals.

Background: Our institution implemented acute-care obstetric (OB) telemedicine (TeleOB) to address rural disparities across our health system. We sought to determine whether in situ simulations with embedded TeleOB consultation increase participants' comfort managing OB emergencies and comfort with and likelihood of using TeleOB. Methods: Rural site care teams participated in multidisciplinary in situ OB emergency simulations. Physicians in OB and neonatology at the referral center assisted via telemedicine consultation. Participants were surveyed before and after the simulations and six months later regarding their experience during the simulations. Results: Participants reported increased comfort with TeleOB activation, indications, and workflow processes, as well as increased comfort managing OB emergencies. Participants also reported significantly increased likelihood of using TeleOB in the future. Conclusions: Consistent with previous work, in situ simulation with embedded telemedicine consultations is an effective approach to facilitate telemedicine implementation and promote use by rural clinicians.

The Subjective Habitability & Acceptability Questionnaire (SHAQ): Development and Validation.

OBJECTIVE: Describe the development and validation of the Subjective Habitability & Acceptability Questionnaire (SHAQ). BACKGROUND: Habitat area size, layout, and design may impact individual and team behavioral health and performance (BHP) outcomes in operational environments. However, there are no standardized measures of these relationships. METHOD: SHAQ is a modular survey consisting of two 6-item scales: BHP Outcomes (Performance of Individual Activities, Performance of Group Activities, Mood, Psychological Stress, Sleep, and Social Interactions) and Habitability Moderators (Privacy, Social Density, Efficiency, Control, Comfort, and Convenience). We collected SHAQ data from NASA's Human Exploration Research Analog (HERA) crews (n = 19) in reference to multiple habitat areas (Sleep/Bedroom, Hygiene/Bathroom, Work/Office/Workshop, and Food Preparation/Kitchen/Galley) in the HERA operational environment, private hotel rooms, and individual home habitats. RESULTS: SHAQ has high construct validity (single factor solutions, mean item factor loading = 0.760, mean % variance = 60.37), internal consistency and reliability (item mean α = 0.880, mean ω=0.894, mean ICC = 0.430), concurrent validity (mean item r with System Usability Scale = 0.42), and discriminant validity (e.g., significantly higher facilitation of group activities in HERA Work/Office/Workshop and Food Preparation/Kitchen/Galley areas vs. Hygiene/Bathroom and Sleep/Bedroom areas; significantly higher ratings of privacy, comfort, and convenience in hotel vs. HERA). CONCLUSION: SHAQ is a reliable, valid, and sensitive measure of BHP impacts of habitat size and layout. APPLICATION: SHAQ can be used to inform evidence-based recommendations and thresholds for habitat area size, layout, and design options to support individual and team BHP in operational environments.

Effect of Automating Procedural Work on Situation Awareness and Workload.

OBJECTIVE: In future deep space exploration missions, crew will have to work more autonomously from Earth. Greater crew autonomy will increase dependence on automated systems. This study investigates the performance effects of different strategies to automate procedural work for space exploration operations. BACKGROUND: The following strategies are investigated for performing procedural work:• Manual Work uses no procedure automation and crew performs all actions.• Shared Work uses procedure automation to perform some actions within a procedure while crew performs other actions.• Supervised Work uses procedure automation to perform procedure actions while crew supervises the automation. METHOD: Twenty-seven participants participated in a planetary habitat scenario-based simulation using electronic procedures with automatable actions to investigate the effect of these strategies on situation awareness (SA) and workload. This study used a modification of the Situation Presence Assessment Method to measure SA and the Bedford Workload Scale to measure subjective workload. RESULTS: Mean response times and accuracy for SA queries show no significant difference among the three strategies. Bedford Workload ratings compared across the three strategies indicate that participants rated their workload as highest in the Manual Work condition, followed by the Shared Work condition, and lowest in the Supervised Work condition. CONCLUSION: The study hypothesized that increased levels of automation would lead to lower subjective workload and decreased SA. Although no significant difference in SA was observed, subjective workload was lower in automation strategies. Based on subjective ratings, 93% of participants preferred some form of automation, with 56% preferring the Shared Work automation condition.

Estimation of Subjectively Reported Trust, Mental Workload, and Situation Awareness Using Unobtrusive Measures.

OBJECTIVE: We use a set of unobtrusive measures to estimate subjectively reported trust, mental workload, and situation awareness (henceforth "TWSA"). BACKGROUND: Subjective questionnaires are commonly used to assess human cognitive states. However, they are obtrusive and usually impractical to administer during operations. Measures derived from actions operators take while working (which we call "embedded measures") have been proposed as an unobtrusive way to obtain TWSA estimates. Embedded measures have not been systematically investigated for each of TWSA, which prevents their operational utility. METHODS: Fifteen participants completed twelve trials of spaceflight-relevant tasks while using a simulated autonomous system. Embedded measures of TWSA were obtained during each trial and participants completed TWSA questionnaires after each trial. Statistical models incorporating our embedded measures were fit with various formulations, interaction effects, and levels of personalization to understand their benefits and improve model accuracy. RESULTS: The stepwise algorithm for building statistical models usually included embedded measures, which frequently corresponded to an intuitive increase or decrease in reported TWSA. Embedded measures alone could not accurately capture an operator's cognitive state, but combining the measures with readily observable task information or information about participants' backgrounds enabled the models to achieve good descriptive fit and accurate prediction of TWSA. CONCLUSION: Statistical models leveraging embedded measures of TWSA can be used to accurately estimate responses on subjective questionnaires that measure TWSA. APPLICATION: Our systematic approach to investigating embedded measures and fitting models allows for cognitive state estimation without disrupting tasks when administering questionnaires would be impractical.

Health Impact Assessment: A Missed Opportunity for MCH Professionals in Their Quest to Address the Social Determinants of Health.

INTRODUCTION: Public health professionals, especially ones concerned with maternal and child health (MCH), need to engage in cross-sector collaborations to address social determinants of health. Health Impact Assessment (HIA) systematically brings public health perspectives into non-health decision-making contexts that influence social determinants. Alignment of MCH and HIA practice has not previously been documented. METHODS: An exploratory review of HIAs conducted in the United States considered several dimensions of MCH-HIA alignment and produced data to test the hypothesis that HIAs involving MCH stakeholders are more likely to address MCH populations and relevant measures. The review examined three key variables for each HIA: inclusion of MCH-focused stakeholders, level of focus on MCH populations, and presence of MCH-relevant content. RESULTS: Of the 424 HIAs included in the database of US HIAs, 350 were included in this review. Twenty-four percent (84) included MCH-focused stakeholders, and 42% (148) focused on MCH populations. Ninety percent (317) included metrics or content relevant to at least one Title V National Performance Measure (NPM). HIAs that clearly included MCH stakeholders had seven times the odds of including both a focus on MCH populations and at least one NPM-relevant topic compared to HIAs that did not clearly include MCH stakeholders (OR 6.98; 95% CI 3.99, 12.20). DISCUSSION: Despite low engagement of MCH stakeholders in HIAs, many still consider MCH populations and measures. Intentional engagement of MCH workforce in HIAs could ensure greater alignment with existing MCH priorities (such as addressing the social determinants of health and equity) in a given jurisdiction.

Integrated approach for noncommunicable disease management in the Americas.

An overview of an integrated approach to improve noncommunicable disease (NCD) management is presented, along with tools on integrating NCD management as part of health system strengthening in the Americas. The study is based on an analysis of Pan American Health Organization/World Health Organization (PAHO/WHO) data and publicly available information on NCD care and capacity, disruptions in NCD services, and guidance on NCD management. Gaps in NCD care are highlighted, in which an estimated 43.0% of men and 28.0% of women with hypertension in Latin America remain undiagnosed; and for those with diabetes, 32.8% in Central and South America are undiagnosed. Yet, only 17/35 countries (49%) in the Americas report having evidence-based national guidelines for NCD management through a primary care approach and only 7/35 countries (20%) report provision of drug therapy, including glycaemic control for eligible persons. To improve NCD management, an integrated approach is needed to coordinate and deliver care across the levels of the health system. This includes increasing primary care capacity and competencies to address multiple chronic conditions, and integration with other complementary programs to avoid missing opportunities for NCD diagnosis and management. An integrated approach to NCD management, and implementation of available tools, should be part of rebuilding health systems after the COVID-19 pandemic.

En este artículo se presenta una visión general de un enfoque integrado para mejorar el manejo de las enfermedades no transmisibles (ENT), así como herramientas para integrar el manejo de las ENT como parte del fortalecimiento de los sistemas de salud en la Región de las Américas. El estudio se basa en un análisis de datos de la Organización Panamericana de la Salud/Organización Mundial de la Salud (OPS/OMS) y en información disponible para el público sobre la atención de las ENT y la capacidad, las interrupciones en los servicios y la orientación sobre el manejo de las ENT. Se destacan las brechas en la atención de estas enfermedades; se estima que 43,0% de los hombres y 28,0% de las mujeres con hipertensión en América Latina siguen sin recibir un diagnóstico, mientras que entre las personas con diabetes, 32,8% en América Central y del Sur no están diagnosticadas. Sin embargo, únicamente 17 de 35 países de la Región (49%) afirman disponer de pautas nacionales basadas en la evidencia para el manejo de las ENT mediante un enfoque de atención primaria, y solo 7 de 35 países (20%) refieren la provisión de farmacoterapia ­por ejemplo, para el control glucémico­ para las personas que reúnen los requisitos. Para mejorar el manejo de las ENT, es necesario un enfoque integrado para coordinar y brindar atención en todos los niveles del sistema de salud. Esto supone el aumento de la capacidad y las competencias de la atención primaria para abordar diversas enfermedades crónicas y su integración con otros programas complementarios y así no perder oportunidades de diagnosticar y gestionar las ENT. Un enfoque integrado para el manejo de las ENT y la aplicación de las herramientas disponibles deben formar parte de la reconstrucción de los sistemas de salud después de la pandemia de COVID-19.

O documento apresenta uma visão geral de uma abordagem integrada para melhorar o manejo de doenças não transmissíveis (DNT), bem com ferramentas para posicionar o manejo das DNT como parte integrante do fortalecimento dos sistemas de saúde nas Américas. O estudo tem como base uma análise dos dados da Organização Pan-Americana da Saúde/Organização Mundial da Saúde (OPAS/OMS) e informações disponíveis publicamente sobre cuidados e capacidade de atendimento a DNT, interrupções nos serviços de DNT e orientações sobre o manejo de DNT. São destacadas as lacunas na atenção às DNT. Estima-se que 43,0% dos homens e 28,0% das mulheres com hipertensão na América Latina permanecem sem diagnóstico, e entre aqueles com diabetes, 32,8% na América Central e do Sul permanecem sem diagnóstico. Apenas 17 de 35 países (49%) nas Américas relatam ter diretrizes nacionais baseadas em evidências para o manejo de DNT na atenção primária e apenas 7 de 35 países (20%) relatam o fornecimento de terapia medicamentosa, incluindo medicamentos para o controle glicêmico para pessoas elegíveis. Para melhorar o manejo das DNT, é necessária uma abordagem integrada para coordenar e prestar cuidados em todos os níveis do sistema de saúde. Isso inclui o aumento da capacidade e da competência da atenção primária para atender pessoas com múltiplas doenças crônicas e a integração com outros programas complementares para evitar a perda de oportunidades para o diagnóstico e o manejo das DNT. Uma abordagem integrada ao manejo das DNT e a implementação das ferramentas disponíveis devem fazer parte da reconstrução dos sistemas de saúde após a pandemia de COVID-19.

Mobile Health Application for Seizure Management: A Human-Systems Integration Approach.

OBJECTIVE: The study aims to develop a mHealth application for seizure management based on the human system integration (HSI) approach. BACKGROUND: Unmet healthcare needs among people with epilepsy continue to exist despite the advancement in healthcare technology. Current seizure management methods are found to be ineffective. Therefore, a more efficient strategy such as mHealth technology is necessary to aid seizure management. METHOD: The needs identification phase involved identifying the user requirements by interviewing 10 stakeholders and conducting thematic analysis and needs interpretation technique. In the solution identification phase, the system requirements were derived using various human-centered design and systems engineering approaches and were evaluated through quality function deployment to determine design targets. For the design and evaluation phase, the design targets were reflected in the app through the iterative prototyping process, and the interface and functional design were evaluated by seven human factors and ergonomics experts and four stakeholders, respectively. RESULTS: Three primary needs and ten user requirements were derived from the needs identification phase. Ten out of fifteen system requirements were selected as design targets to be included in the final prototype. Results of the evaluation showed that the interface design of the proposed app showed superior usability compared to a competitor app and that the app functions were beneficial for the stakeholders. CONCLUSION: The mHealth app designed through the HSI framework showed good potential in addressing the main issues in seizure management. APPLICATION: The mHealth app design methodology based on the HSI approach can be applied to the design of small-scale systems in various domains.

Exploring Optimal Objective Function Weightings to Predict Lifting Postures Under Unfatigued and Fatigued States.

OBJECTIVE: To explore whether the optimal objective function weightings change when using a digital human model (DHM) to predict origin and destination lifting postures under unfatigued and fatigued states. BACKGROUND: The ability to predict human postures can depend on state-based influences (e.g., fatigue). Altering objective function weightings within a predictive DHM could improve the ability to predict tasks specific lifting postures under unique fatigue states. METHOD: A multi-objective optimization-based DHM was used to predict origin and destination lifting postures for ten anthropometrically scaled avatars by using different objective functions weighting combinations. Predicted and measured postures were compared to determine the root mean squared error. A response surface methodology was used to identify the optimal objective function weightings, which was found by generating the posture that minimized error between measured and predicted lifting postures. The resultant weightings were compared to determine if the optimal objective function weightings changed for different lifting postures or fatigue states. RESULTS: Discomfort and total joint torque weightings were affected by posture (origin/destination) and fatigue state (unfatigued/fatigued); however, post-hoc differences between fatigue states and lifting postures were not sufficiently large to be detected. Weighting the discomfort objective function alone tended to predict postures that generalized well to both postures and fatigue states. CONCLUSION: Lift postures were optimal predicted using the minimization of discomfort objective function regardless of fatigue state. APPLICATION: Weighting the discomfort objective can predict unfatigued postures, but more research is needed to understand the optimal objective function weightings to predict postures during a fatigued state.

Improving Healthcare Practice Through the Implementation of Human Factors and Ergonomics Principles.

OBJECTIVE: Present a collection of papers focusing on improving healthcare practice through the implementation of human factors and ergonomics principles that were presented at the International Ergonomics Association (IEA) 2021 international conference. BACKGROUND: The mission of the IEA is to elaborate and advance ergonomics science and practice and to expand its scope of application. METHOD: We reviewed papers that were submitted for presentation at the IEA 2021 international conference and focused on improving healthcare practice through the implementation of human factors and ergonomics principles. RESULTS: The eight papers that are included in this special issue cover varied aspects of human factors application and implementation. CONCLUSION: This special issue provides clear evidence that the science of human factors is relevant and is continuing to grow and so is its implementation in healthcare. APPLICATION: This special issue offers a selection of applied works, providing a wide scope of human factors guidelines, methods, and theories in healthcare work environments.

Digitization of Measurement-Based Care Pathways in Mental Health Through REDCap and Electronic Health Record Integration: Development and Usability Study.

BACKGROUND: The delivery of standardized self-report assessments is essential for measurement-based care in mental health. Paper-based methods of measurement-based care data collection may result in transcription errors, missing data, and other data quality issues when entered into patient electronic health records (EHRs). OBJECTIVE: This study aims to help address these issues by using a dedicated instance of REDCap (Research Electronic Data Capture; Vanderbilt University)-a free, widely used electronic data capture platform-that was established to enable the deployment of digitized self-assessments in clinical care pathways to inform clinical decision making. METHODS: REDCap was integrated with the primary clinical information system to facilitate the real-time transfer of discrete data and PDF reports from REDCap into the EHR. Both technical and administrative components were required for complete implementation. A technology acceptance survey was also administered to capture physicians' and clinicians' attitudes toward the new system. RESULTS: The integration of REDCap with the EHR transitioned clinical workflows from paper-based methods of data collection to electronic data collection. This resulted in significant time savings, improved data quality, and valuable real-time information delivery. The digitization of self-report assessments at each appointment contributed to the clinic-wide implementation of the major depressive disorder integrated care pathway. This digital transformation facilitated a 4-fold increase in the physician adoption of this integrated care pathway workflow and a 3-fold increase in patient enrollment, resulting in an overall significant increase in major depressive disorder integrated care pathway capacity. Physicians' and clinicians' attitudes were overall positive, with almost all respondents agreeing that the system was useful to their work. CONCLUSIONS: REDCap provided an intuitive patient interface for collecting self-report measures and accessing results in real time to inform clinical decisions and an extensible backend for system integration. The approach scaled effectively and expanded to high-impact clinics throughout the hospital, allowing for the broad deployment of complex workflows and standardized assessments, which led to the accumulation of harmonized data across clinics and care pathways. REDCap is a flexible tool that can be effectively leveraged to facilitate the automatic transfer of self-report data to the EHR; however, thoughtful governance is required to complement the technical implementation to ensure that data standardization, data quality, patient safety, and privacy are maintained.

Cybersecurity in ICT Supply Chains: Key Challenges and a Relevant Architecture.

The specific demands of supply chains built upon large and complex IoT systems, make it a must to design a coordinated framework for cyber resilience provisioning, intended to guarantee trusted supply chains of ICT systems, built upon distributed, dynamic, potentially insecure, and heterogeneous ICT infrastructures. As such, the solution proposed in this paper is envisioned to deal with the whole supply chain system components, from the IoT ecosystem to the infrastructure connecting them, addressing security and privacy functionalities related to risks and vulnerabilities management, accountability, and mitigation strategies, as well as security metrics and evidence-based security assurance. In this paper, we present FISHY as a preliminary architecture that is designed to orchestrate existing and beyond state-of-the-art security appliances in composed ICT scenarios. To this end, the FISHY architecture leverages the capabilities of programmable networks and IT infrastructure through seamless orchestration and instantiation of novel security services, both in real-time and proactively. The paper also includes a thorough business analysis to go far beyond the technical benefits of a potential FISHY adoption, as well as three real-world use cases highlighting the envisioned benefits of a potential FISHY adoption.

Dancing With Algorithms: Interaction Creates Greater Preference and Trust in Machine-Learned Behavior.

OBJECTIVE: We examined a method of machine learning (ML) to evaluate its potential to develop more trustworthy control of unmanned vehicle area search behaviors. BACKGROUND: ML typically lacks interaction with the user. Novel interactive machine learning (IML) techniques incorporate user feedback, enabling observation of emerging ML behaviors, and human collaboration during ML of a task. This may enable trust and recognition of these algorithms. METHOD: Participants judged and selected behaviors in a low and a high interaction condition (IML) over the course of behavior evolution using ML. User trust in the outputs, as well as preference, and ability to discriminate and recognize the behaviors were measured. RESULTS: Compared to noninteractive techniques, IML behaviors were more trusted and preferred, as well as recognizable, separate from non-IML behaviors, and approached similar performance as pure ML models. CONCLUSION: IML shows promise for creating behaviors by involving the user; this is the first extension of this technique for vehicle behavior model development targeting user satisfaction and is unique in its multifaceted evaluation of how users perceived, trusted, and implemented these learned controllers. APPLICATION: There are many contexts where the brittleness of ML cannot be trusted, but the advantage of ML over traditional programmed behaviors may be large, as in some military operations where they could be scaled. IML in this early form appears to generate satisfactory behaviors without sacrificing performance, use, or trust in the behavior, but more work is necessary.

Predicting Design-Induced Error on the Flight Deck : An Aircraft Engine Oil Leak Scenario.

OBJECTIVE: To explore the types of errors that commercial pilots may make when trying to resolve a suspected engine oil leak using the interfaces currently available. BACKGROUND: The decisions that pilots make often have to be made quickly and under time pressure, with the emphasis on avoiding critical situations from arising. To make the correct decisions, it is vital that pilots have accurate and up-to-date information available. However, interaction with flight deck interfaces may lead to error if they are not effectively designed. METHOD: A hierarchical task analysis was conducted using evidence from pilot interview data to understand the pilots' typical response to a suspected engine oil leak scenario. This was used as the primary input into the Systematic Human Error Reduction and Prediction Approach (SHERPA). RESULTS: A total of 108 possible errors were identified. The most common error type was a retrieval error, in which flight crews may retrieve the wrong information about the engine. A number of remedial measures are proposed to try and overcome such issues. CONCLUSION: This analysis provides an initial starting point for identifying potential future design ideas that can assist the pilots in dealing with oil leaks. APPLICATION: This work has identified the value of applying human error identification methodologies to the assessment of current flight deck processes surrounding engine oil leaks. The method presented permits the operational analysis of possible errors on the flight deck and facilitates the proposition of remedial measures to implement technological innovations that can mitigate error.

Communities of practice in Alberta Health Services: advancing a learning organisation.

BACKGROUND: In 2009, Alberta Health Services (AHS) became Canada's first and largest fully integrated healthcare system, involving the amalgamation of nine regional health authorities and three provincial services. Within AHS, communities of practice (CoPs) meet regularly to learn from one another and to find ways to improve service quality. This qualitative study examined CoPs as an applied practice of a learning organisation along with their potential influence in a healthcare system by exploring the perspectives of CoP participants. METHODS: A collective case study method was used to enable the examination of a cross-section of cases in the study organisation. Semi-structured interviews were conducted with 31 participants representing 28 distinct CoPs. Using Senge's framework of a learning organisation, CoP influences associated with team learning and organisational change were explored. RESULTS: CoPs in AHS were described as diverse in practice domains, focus, membership boundaries, attendance and sphere of influence. Using small-scale resource investments, CoPs provided members with opportunities for meaningful interactions, the capacity to build information pathways, and enhanced abilities to address needs at the point of care and service delivery. Overall, CoPs delivered a sophisticated array of engagement and knowledge-sharing activities perceived as supportive of organisational change, systems thinking, and the team learning practice critical to a learning organisation. CONCLUSION: CoPs enable the diverse wealth of knowledge embedded in people, local conditions and special circumstances to flow from practice domain groups to programme and service areas, and into the larger system where it can effect organisational change. This research highlights the potential of CoPs to influence practice and broad-scale change more directly than previously understood or reported in the literature. As such, this study suggests that CoPs have the potential to influence and advance widespread systems change in Canadian healthcare.

Defining and Managing the Preanalytical Phase With FMECA: Automation and/or "Human" Control.

OBJECTIVE: Our scope is to provide methodological elements on how to manage effectively the preanalytical phase in the laboratory testing process, by objectively measuring the risk connected to the phases handled by man with respect to those managed by machines. BACKGROUND: Preanalytical errors account for most of the mistakes related to laboratory testing and can affect patient care. Hence, it is necessary to manage the risk connected to the preanalytical phase, as required by certification and accreditation bodies. The risk assessment discloses the steps at greater risk and gives indications to make decisions. METHOD: We have reviewed the state of art in the automation of the preanalytical phase, addressing needs and problems. We have used the proactive risk assessment methodology FMECA (Failure Mode, Effects, and Criticality Analysis) to identify the most critical phases in our preanalytical process and have calculated the risk associated. RESULTS: The most critical phases were the human controlled ones. In particular, the highest risk indexes were associated to manual acceptance of test orders, identification of the patients, tube labeling, and sample collection. CONCLUSION: Automation in the preanalytical phase is fundamental to replace, support, or extend the human contribution. Nevertheless each organization is different about workloads and competencies, so the most suitable management must be tailor-made in each context. APPLICATION: We present a method by which each organization is able to find its best balance between automation and human contribution in the control of the preanalytical phase.

Digital networks for laboratory data: potentials, barriers and current initiatives.

Medical care is increasingly delivered by multiple providers across healthcare sectors and specialties, leading to a fragmentation of the electronic patient record across organizations and vendor IT systems. The rapid uptake of wearables and connected diagnostic devices adds another source of densely collected data by the patients themselves. Integration of these data sources opens up several potentials: a longitudinal view of laboratory findings would close the gaps between individual provider visits and allow to more closely follow disease progression. Adding non-laboratory data (e.g. diagnoses, procedures) would add context and support clinical interpretation of findings. Case-based reasoning and disease-modelling approaches would allow to identify similar patient groups and classify endotypes. Realization of these potentials is, however, subject to several barriers, including legal and ethical prerequisites of data access, syntactic and semantic integration, comparability of items and user-centered presentation. The German Medical Informatics Initiative is presented as a current undertaking that strives to address these issues by establishing a national infrastructure for the secondary use of routine clinical data.

A perspective on Quality-by-Control (QbC) in pharmaceutical continuous manufacturing.

The Quality-by-Design (QbD) guidance issued by the US Food and Drug Administration (FDA) has catalyzed the modernization of pharmaceutical manufacturing practices including the adoption of continuous manufacturing. Active process control was highlighted recently as a means to improve the QbD implementation. This advance has since been evolving into the concept of Quality-by-Control (QbC). In this study, the concept of QbC is discussed, including a definition of QbC, a review of the recent developments towards the QbC, and a perspective on the challenges of QbC implementation in continuous manufacturing. The QbC concept is demonstrated using a rotary tablet press, integrated into a pilot scale continuous direct compaction process. The results conclusively showed that active process control, based on product and process knowledge and advanced model-based techniques, including data reconciliation, model predictive control (MPC), and risk analysis, is indispensable to comprehensive QbC implementation, and ensures robustness and efficiency.

Using Tools to Help Us Think: Actual but Also Believed Reliability Modulates Cognitive Offloading.

OBJECTIVE: A distributed cognitive system is a system in which cognitive processes are distributed between brain-based internal and environment-based external resources. In the current experiment, we examined the influence of metacognitive processes on external resource use (i.e., cognitive offloading) in such systems. BACKGROUND: High-tech working environments oftentimes represent distributed cognitive systems. Because cognitive offloading can both support and harm performance, depending on the specific circumstances, it is essential to understand when and why people offload their cognition. METHOD: We used an extension of the mental rotation paradigm. It allowed participants to rotate stimuli either internally as in the original paradigm or with a rotation knob that afforded rotating stimuli externally on a computer screen. Two parameters were manipulated: the knob's actual reliability (AR) and an instruction altering participants' beliefs about the knob's reliability (believed reliability; BR). We measured cognitive offloading proportion and perceived knob utility. RESULTS: Participants were able to quickly and dynamically adjust their cognitive offloading proportion and subjective utility assessments in response to AR, suggesting a high level of offloading proficiency. However, when BR instructions were presented that falsely described the knob's reliability to be lower than it actually was, participants reduced cognitive offloading substantially. CONCLUSION: The extent to which people offload their cognition is not based solely on utility maximization; it is additionally affected by possibly erroneous preexisting beliefs. APPLICATION: To support users in efficiently operating in a distributed cognitive system, an external resource's utility should be made transparent, and preexisting beliefs should be adjusted prior to interaction.