Activating the Hospital Incident Command System Response in a Community Specialty Practice: The Mayo Clinic Experience

INTRODUCTION

The COVID-19 pandemic presented health care organizations with a unique challenge in determining effective management of a large-scale incident across an extended time period.

CASE PRESENTATION

This report describes the response of a multisite integrated system to the COVID-19 pandemic through activation of the Hospital Incident Command System.

DISCUSSION

A robust emergency response plan with multidisciplinary involvement can help to ensure clear lines of accountability and expedite decision-making. Consistent physician input across affected specialties allows for a robust understanding of impacted areas, peer-to-peer communication, and a sense of ownership across the medical staff. The necessity of effective communication with staff and patients during times of crisis cannot be understated. The potential for information overload in a pandemic is significant but can be overcome through consistent and transparent communication from leadership.

CONCLUSION

Health systems should have a well-organized emergency response system prepared to launch in small-scale or large-scale situations. The threshold to implement the response system and accountability to make that decision must be a clearly defined organizational policy.

Artificial Intelligence Decision Support for Medical Triage

Applying state-of-the-art machine learning and natural language processing on approximately one million of teleconsultation records, we developed a triage system, now certified and in use at the largest European telemedicine provider. The system evaluates care alternatives through interactions with patients via a mobile application. Reasoning on an initial set of provided symptoms, the triage application generates AI-powered, personalized questions to better characterize the problem and recommends the most appropriate point of care and time frame for a consultation. The underlying technology was developed to meet the needs for performance, transparency, user acceptance and ease of use, central aspects to the adoption of AI-based decision support systems. Providing such remote guidance at the beginning of the chain of care has significant potential for improving cost efficiency, patient experience and outcomes. Being remote, always available and highly scalable, this service is fundamental in high demand situations, such as the current COVID-19 outbreak.

Knowledge Extraction of Cohort Characteristics in Research Publications

When healthcare providers review the results of a clinical trial study to understand its applicability to their practice, they typically analyze how well the characteristics of the study cohort correspond to those of the patients they see. We have previously created a study cohort ontology to standardize this information and make it accessible for knowledge-based decision support. The extraction of this information from research publications is challenging, however, given the wide variance in reporting cohort characteristics in a tabular representation. To address this issue, we have developed an ontology-enabled knowledge extraction pipeline for automatically constructing knowledge graphs from the cohort characteristics found in PDF-formatted research papers. We evaluated our approach using a training and test set of 41 research publications and found an overall accuracy of 83.3% in correctly assembling the knowledge graphs. Our research provides a promising approach for extracting knowledge more broadly from tabular information in research publications.

A decision support framework for prediction of avian influenza

For years, avian influenza has influenced economies and human health around the world. The emergence and spread of avian influenza virus have been uncertain and sudden. The virus is likely to spread through several pathways such as poultry transportation and wild bird migration. The complicated and global spread of avian influenza calls for surveillance tools for timely and reliable prediction of disease events. These tools can increase situational awareness and lead to faster reaction to events. Here, we aimed to design and evaluate a decision support framework that aids decision makers by answering their questions regarding the future risk of events at various geographical scales. Risk patterns were driven from pre-built components and combined in a knowledge base. Subsequently, questions were answered by direct queries on the knowledge base or through a built-in algorithm. The evaluation of the system in detecting events resulted in average sensitivity and specificity of 69.70% and 85.50%, respectively. The presented framework here can support health care authorities by providing them with an opportunity for early control of emergency situations.

Continuous Glucose Monitoring Sensors for Diabetes Management: A Review of Technologies and Applications

By providing blood glucose (BG) concentration measurements in an almost continuous-time fashion for several consecutive days, wearable minimally-invasive continuous glucose monitoring (CGM) sensors are revolutionizing diabetes management, and are becoming an increasingly adopted technology especially for diabetic individuals requiring insulin administrations. Indeed, by providing glucose real-time insights of BG dynamics and trend, and being equipped with visual and acoustic alarms for hypo- and hyperglycemia, CGM devices have been proved to improve safety and effectiveness of diabetes therapy, reduce hypoglycemia incidence and duration, and decrease glycemic variability. Furthermore, the real-time availability of BG values has been stimulating the realization of new tools to provide patients with decision support to improve insulin dosage tuning and infusion. The aim of this paper is to offer an overview of current literature and future possible developments regarding CGM technologies and applications. In particular, first, we outline the technological evolution of CGM devices through the last 20 years. Then, we discuss about the current use of CGM sensors from patients affected by diabetes, and, we report some works proving the beneficial impact provided by the adoption of CGM. Finally, we review some recent advanced applications for diabetes treatment based on CGM sensors.

Methodology and model-based DSS to managing the reallocation of inventory to orders in LHP situations. Application to the ceramics sector

Lack of homogeneity in the product (LHP) is a problem when customers require homogeneous units of a single product. In such cases, the optimal allocation of inventory to orders becomes much more complex. Furthermore, in an MTS environment, an optimal initial allocation may become less than ideal over time, due to different circumstances. This problem occurs in the ceramics sector, where the final product varies in tone and calibre. This paper proposes a methodology for the reallocation of inventory to orders in LHP situation (MERIO-LHP) and a model-based decision-support system (DSS) to support the methodology, which enables an optimal reallocation of inventory to order lines to be carried out in real businesses environments in which LHP is inherent. The proposed methodology and model-based DSS were validated by applying it to a real case at a ceramics company. The analysis of the results indicates that considerable improvements can be obtained with regard to the quantity of orders fulfilled and sales turnover.

Ecological Interface Design: Thirty-Plus Years of Refinement, Progress, and Potential

OBJECTIVE

The objective is to provide a review of ecological interface design (EID), to illustrate its value to human factors/ergonomics, and to identify areas for future research and development.

BACKGROUND

EID uses mature interface technologies to provide decision making and problem solving support. A variety of theoretical concepts and analytical tools have been developed to meet the associated challenges. EID provides support that is simultaneously grounded in the practical realities of a work domain and tailored to human capabilities and limitations.

METHOD

EID's theoretical foundation is discussed briefly. Concrete examples of ecological and traditional interfaces are provided. Different categories of work domains are described, as well as the associated implications for interface design. A targeted literature review is conducted and the experimental outcomes are summarized. A representative evaluation is discussed, and interpretations of performance are provided.

RESULTS

The evidence reveals that EID has been remarkably successful in significantly improving performance for work domains with constraints that are law driven (e.g., process control). In contrast, work domains that are intent-driven (e.g., information retrieval) have, by and large, been ignored. Also, few studies have addressed nonvisual displays.

CONCLUSION

EID has not yet realized its potential to improve safety and efficiency across the entire continuum of work domains.

APPLICATION

EID provides a single integrated framework that is (a) sufficiently comprehensive to deal with complicated work domains and (b) capable of producing innovative support that will generalize to actual work settings.

Directed forgetting in organisations: the positive effects of decision support systems on mental resources and well-being

Decision makers in organisations are often overtaxed by huge amounts of information in daily business processes. As a potential support strategy, this study examined 'directed forgetting' (Bjork, 1970) in a simulated sales planning scenario. We assumed that the availability of a computer-based decision support system (DSS) triggers the forgetting of decision-related background information. Such directed forgetting should not only release memory capacities for additional tasks but also enhance decision quality and decrease strain of decision makers. Assumptions were tested in an experimental study with N = 90 participants. Consistent with our assumptions, results revealed a higher recall of decision-unrelated information, higher decision quality and higher well-being when participants could use a DSS as compared to two Control conditions without a DSS. Moreover, directed forgetting effects were qualified by participants' trust in the DSS. This study provides the first evidence for directed forgetting effects cued by information systems in a business context. Practitioner summary: Information overload is an increasing challenge in modern business organisations. Extending findings from basic memory research, this study shows that availability of a computer-based decision support system triggers forgetting of decision-related background information, which in turn increases users' mental resources for additional tasks, decision quality, and well-being.

An ecological framework for informing permitting decisions on scientific activities in protected areas

There are numerous reasons to conduct scientific research within protected areas, but research activities may also negatively impact organisms and habitats, and thus conflict with a protected area’s conservation goals. We developed a quantitative ecological decision-support framework that estimates these potential impacts so managers can weigh costs and benefits of proposed research projects and make informed permitting decisions. The framework generates quantitative estimates of the ecological impacts of the project and the cumulative impacts of the proposed project and all other projects in the protected area, and then compares the estimated cumulative impacts of all projects with policy-based acceptable impact thresholds. We use a series of simplified equations (models) to assess the impacts of proposed research to: a) the population of any targeted species, b) the major ecological assemblages that make up the community, and c) the physical habitat that supports protected area biota. These models consider both targeted and incidental impacts to the ecosystem and include consideration of the vulnerability of targeted species, assemblages, and habitats, based on their recovery time and ecological role. We parameterized the models for a wide variety of potential research activities that regularly occur in the study area using a combination of literature review and expert judgment with a precautionary approach to uncertainty. We also conducted sensitivity analyses to examine the relationships between model input parameters and estimated impacts to understand the dominant drivers of the ecological impact estimates. Although the decision-support framework was designed for and adopted by the California Department of Fish and Wildlife for permitting scientific studies in the state-wide network of marine protected areas (MPAs), the framework can readily be adapted for terrestrial and freshwater protected areas.

Decision support system for management of reactive nitrogen flows in wastewater system

The change in nitrogen balance causes many environmental and socioeconomic impacts. In relation to food production and nitrogen release in wastewater systems, wastewater and sludge discharge and mineral fertilizer use intensify nitrogen imbalance of a region. The replacement of mineral fertilizer by nitrogen from treated wastewater, biosolids, and treated urine is a promising alternative. This work presents a model to support decision taking for the management of reactive nitrogen flows in wastewater systems based on system dynamics. Six scenarios were simulated for nitrogen flows in wastewater systems and related components.

Water leakage management by district metered areas at water distribution networks

The aim of this study is to design a district metered area (DMA) at water distribution network (WDN) for determination and reduction of water losses in the city of Malatya, Turkey. In the application area, a pilot DMA zone was built by analyzing the existing WDN, topographic map, length of pipes, number of customers, service connections, and valves. In the DMA, International Water Association standard water balance was calculated considering inflow rates and billing records. The ratio of water losses in DMAs was determined as 82%. Moreover, 3124 water meters of 2805 customers were examined while 50% of water meters were detected as faulty. This study revealed that DMA application is useful for the determination of water loss rate in WDNs and identify a cost-effective leakage reduction program.

Management algorithms for cervical cancer screening and precancer treatment for resource-limited settings

Management algorithms for screen-positive women in cervical cancer prevention programs have undergone substantial changes in recent years. The WHO strongly recommends human papillomavirus (HPV) testing for primary screening, if affordable, or if not, then visual inspection with acetic acid (VIA), and promotes treatment directly following screening through the screen-and-treat approach (one or two clinic visits). While VIA-positive women can be offered immediate ablative treatment based on certain eligibility criteria, HPV-positive women need to undergo subsequent VIA to determine their eligibility. Simpler ablative methods of treatment such as cryotherapy and thermal coagulation have been demonstrated to be effective and to have excellent safety profiles, and these have become integral parts of new management algorithms. The challenges faced by low-resource countries are many and include, from the management perspective, identifying an affordable point-of-care HPV detection test, minimizing over-treatment, and installing an effective information system to ensure high compliance to treatment and follow-up.

Application fields for the new Object Management Group (OMG) Standards Case Management Model and Notation (CMMN) and Decision Management Notation (DMN) in the perioperative field

PURPOSE

Medical processes can be modeled using different methods and notations. Currently used modeling systems like Business Process Model and Notation (BPMN) are not capable of describing the highly flexible and variable medical processes in sufficient detail.

METHODS

We combined two modeling systems, Business Process Management (BPM) and Adaptive Case Management (ACM), to be able to model non-deterministic medical processes. We used the new Standards Case Management Model and Notation (CMMN) and Decision Management Notation (DMN).

RESULTS

First, we explain how CMMN, DMN and BPMN could be used to model non-deterministic medical processes. We applied this methodology to model 79 cataract operations provided by University Hospital Leipzig, Germany, and four cataract operations provided by University Eye Hospital Tuebingen, Germany. Our model consists of 85 tasks and about 20 decisions in BPMN. We were able to expand the system with more complex situations that might appear during an intervention.

CONCLUSION

An effective modeling of the cataract intervention is possible using the combination of BPM and ACM. The combination gives the possibility to depict complex processes with complex decisions. This combination allows a significant advantage for modeling perioperative processes.

Inclusion of social indicators in decision support tools for the selection of sustainable site remediation options

Sustainable remediation requires a balanced decision-making process in which environmental, economic and social aspects of different remediation options are all considered together and the optimum remediation solution is selected. More attention has been paid to the evaluation of environmental and economic aspects, in particular to reduce the human and environmental risks and the remediation costs, to the exclusion of social aspects of remediation. This paper investigates how social aspects are currently considered in sustainability assessments of remediation projects. A selection of decision support tools (DSTs), used for the sustainability assessment of a remediation project, is analyzed to define how social aspects are considered in those tools. The social indicator categories of the Sustainable Remediation Forum - United Kingdom (SuRF-UK), are used as a basis for this evaluation. The consideration of social aspects in the investigated decision support tools is limited, but a clear increase is noticed in more recently developed tools. Among the five social indicator categories defined by SuRF-UK to facilitate a holistic consideration of social aspects of a remediation project only "Human health and safety" is systematically taken into account. "Neighbourhood and locality" is also often addressed, mostly emphasizing the potential disturbance caused by the remediation activities. However, the evaluation of 'Ethics and Equality', Communities and community involvement', and 'Uncertainty and evidence' is often neglected. Nevertheless, concrete examples can be found in some of the investigated tools. Specific legislation, standard procedures, and guidelines that have to be followed in a region or country are mainly been set up in the context of protecting human and ecosystem health, safety and prevention of nuisance. However, they sometimes already include some of the aspects addressed by the social indicators. In this perspective the use of DST to evaluate the sustainability of a site remediation project, should be tuned to the legislation, guidelines and procedures that are in force in a specific country or region.

Setting Objectives for Community and Systems Change: An Application of Concept Mapping for Planning a Statewide Health Improvement Initiative

The Hawaii Department of Health (HDOH) used concept mapping techniques to engage local stakeholders and national subject area experts in defining the community and system factors that affect individuals’ behaviors related to tobacco, nutrition, and physical activity. Over eight working days, project participants brainstormed 496 statements (edited to a final set of 90), which were then sorted and rated for their importance and feasibility. A sequence of multivariate statistical analyses, including multidimensional scaling and hierarchical cluster analysis, generated maps and figures that were then interpreted by project stakeholders. The results were immediately incorporated into an official plan, approved by the governor and state legislature, recommending how Hawaii’s tobacco settlement resources could be used to create sustainable changes in population health. The results also provide empirical support for the premise that both community and systems factors ought to be considered when planning comprehensive health improvement initiatives.

A randomised controlled trial of cognitive aids for emergency airway equipment preparation in a Paediatric Emergency Department

BACKGROUND

Safety of emergency intubation may be improved by standardising equipment preparation; the efficacy of cognitive aids is unknown.

METHODS

This randomised controlled trial compared no cognitive aid (control) with the use of a checklist or picture template for emergency airway equipment preparation in the Emergency Department of The Royal Children's Hospital, Melbourne.

RESULTS

Sixty-three participants were recruited, 21 randomised to each group. Equal numbers of nursing, junior medical, and senior medical staff were included in each group. Compared to controls, the checklist or template group had significantly lower equipment omission rates (median 30% IQR 20-40% control, median 10% IQR 5-10 % checklist, median 10% IQR 5-20% template; p < 0.05). The combined omission rate and sizing error rate was lower using a checklist or template (median 35 % IQR 30-45 % control, median 15% IQR 10-20% checklist, median 15% IQR 10-30% template; p < 0.05). The template group had less variation in equipment location compared to checklist or controls. There was no significant difference in preparation time in controls (mean 3 min 14 s sd 56 s) compared to checklist (mean 3 min 46 s sd 1 min 15 s) or template (mean 3 min 6 s sd 49 s; p = 0.06).

DISCUSSION

Template use reduces variation in airway equipment location during preparation foremergency intubation, with an equivalent reduction in equipment omission rate to the use of a checklist. The use of a template for equipment preparation and a checklist for team, patient, and monitoring preparation may provide the best combination of both cognitive aids.

CONCLUSIONS

The use of a cognitive aid for emergency airway equipment preparation reduces errors of omission. Template utilisation reduces variation in equipment location.

TRIAL REGISTRATION

Australian and New Zealand Trials Registry (ACTRN12615000541505).

A decision support framework for characterizing and managing dermal exposures to chemicals during Emergency Management and Operations

Emergency Management and Operations (EMO) personnel are in need of resources and tools to assist in understanding the health risks associated with dermal exposures during chemical incidents. This article reviews available resources and presents a conceptual framework for a decision support system (DSS) that assists in characterizing and managing risk during chemical emergencies involving dermal exposures. The framework merges principles of three decision-making techniques: 1) scenario planning, 2) risk analysis, and 3) multicriteria decision analysis (MCDA). This DSS facilitates dynamic decision making during each of the distinct life cycle phases of an emergency incident (ie, preparedness, response, or recovery) and identifies EMO needs. A checklist tool provides key questions intended to guide users through the complexities of conducting a dermal risk assessment. The questions define the scope of the framework for resource identification and application to support decision-making needs. The framework consists of three primary modules: 1) resource compilation, 2) prioritization, and 3) decision. The modules systematically identify, organize, and rank relevant information resources relating to the hazards of dermal exposures to chemicals and risk management strategies. Each module is subdivided into critical elements designed to further delineate the resources based on relevant incident phase and type of information. The DSS framework provides a much needed structure based on contemporary decision analysis principles for 1) documenting key questions for EMO problem formulation and 2) a method for systematically organizing, screening, and prioritizing information resources on dermal hazards, exposures, risk characterization, and management.

Cross-sectoral optimization and visualization of transformation processes in urban water infrastructures in rural areas

Predicted demographic, climatic and socio-economic changes will require adaptations of existing water supply and wastewater disposal systems. Especially in rural areas, these new challenges will affect the functionality of the present systems. This paper presents a joint interdisciplinary research project with the objective of developing an innovative software-based optimization and decision support system for the implementation of long-term transformations of existing infrastructures of water supply, wastewater and energy. The concept of the decision support and optimization tool is described and visualization methods for the presentation of results are illustrated. The model is tested in a rural case study region in the Southwest of Germany. A transformation strategy for a decentralized wastewater treatment concept and its visualization are presented for a model village.

Comparing the performance of expert user heuristics and an integer linear program in aircraft carrier deck operations

Planning operations across a number of domains can be considered as resource allocation problems with timing constraints. An unexplored instance of such a problem domain is the aircraft carrier flight deck, where, in current operations, replanning is done without the aid of any computerized decision support. Rather, veteran operators employ a set of experience-based heuristics to quickly generate new operating schedules. These expert user heuristics are neither codified nor evaluated by the United States Navy; they have grown solely from the convergent experiences of supervisory staff. As unmanned aerial vehicles (UAVs) are introduced in the aircraft carrier domain, these heuristics may require alterations due to differing capabilities. The inclusion of UAVs also allows for new opportunities for on-line planning and control, providing an alternative to the current heuristic-based replanning methodology. To investigate these issues formally, we have developed a decision support system for flight deck operations that utilizes a conventional integer linear program-based planning algorithm. In this system, a human operator sets both the goals and constraints for the algorithm, which then returns a proposed schedule for operator approval. As a part of validating this system, the performance of this collaborative human-automation planner was compared with that of the expert user heuristics over a set of test scenarios. The resulting analysis shows that human heuristics often outperform the plans produced by an optimization algorithm, but are also often more conservative.

Simulation and modeling efforts to support decision making in healthcare supply chain management

Recently, most healthcare organizations focus their attention on reducing the cost of their supply chain management (SCM) by improving the decision making pertaining processes' efficiencies. The availability of products through healthcare SCM is often a matter of life or death to the patient; therefore, trial and error approaches are not an option in this environment. Simulation and modeling (SM) has been presented as an alternative approach for supply chain managers in healthcare organizations to test solutions and to support decision making processes associated with various SCM problems. This paper presents and analyzes past SM efforts to support decision making in healthcare SCM and identifies the key challenges associated with healthcare SCM modeling. We also present and discuss emerging technologies to meet these challenges.

A framework to support human factors of automation in railway intelligent infrastructure

Technological and organisational advances have increased the potential for remote access and proactive monitoring of the infrastructure in various domains and sectors - water and sewage, oil and gas and transport. Intelligent Infrastructure (II) is an architecture that potentially enables the generation of timely and relevant information about the state of any type of infrastructure asset, providing a basis for reliable decision-making. This paper reports an exploratory study to understand the concepts and human factors associated with II in the railway, largely drawing from structured interviews with key industry decision-makers and attachment to pilot projects. Outputs from the study include a data-processing framework defining the key human factors at different levels of the data structure within a railway II system and a system-level representation. The framework and other study findings will form a basis for human factors contributions to systems design elements such as information interfaces and role specifications.

Measuring best value from 'refurb' projects

Research at Aberdeen's Robert Gordon University has identified the requirement for the development of a 'Decision Support Model' to 'facilitate and measure the selection of main elements and sub-elements within refurbishment and maintenance projects'. One of the major drivers, explains Grant Wilson, a completing PhD researcher with the University's Institute for Innovation, Design and Sustainability (IDEAS), was to provide a mechanism via which NHS estates managers, design teams, and contractors, could 'evidence and demonstrate' that best value-for-money had been pursued, 'specific to the facility in question, and in the context of its unique business case requirements'.

Healthcare performance turned into decision support

PURPOSE

The purpose of this study is to first create an overview of relevant factors directly influencing employee absence in the healthcare sector. The overview is used to further investigate the factors identified using employee satisfaction survey scores exclusively. The result of the overall objective is a management framework that allows managers to gain insight into the current status of risk factors with high influence on employee absence levels.

DESIGN/METHODOLOGY/APPROACH

The research consists of a quantitative literature study supported by formal and semi-formal interviews conducted at the case organisations. Employee satisfaction surveys were applied to analyse the development over time of selected factors correlated with concurrent employee absence rates. Checking for causal results, comparisons with the included published literature findings were also carried out.

FINDINGS

Four major clustered factors, three of which constitute the term "social capital", showed a high degree of connection with employee absence rates. The factors are general satisfaction, fairness, reliance and co-operation. Integrating the four elements in a management framework will provide valuable and holistic information about the determinants with regard to current levels of employee absence. The framework will be a valuable support for leaders with the authority to alter the determinants of employee absence.

RESEARCH LIMITATIONS/IMPLICATIONS

Since a great part of the empirical material is supplied from the healthcare sector, the results obtained could be restricted to this sector. Inclusion of data from Arbejdsmarkedets Tillaegspension (ATP) showed no deviation from the results in the healthcare sector.

PRACTICAL IMPLICATIONS

The product of the study is a decision support tool for leaders to cope with levels of employee absence. The framework is holistic and can prove to be a valuable tool to take a bearing of where to focus future initiatives.

ORIGINALITY/VALUE

Gathering former observational studies in a complete overview embracing many relevant factors that influence sickness absence has not yet been attempted. Hospital management is provided with valuable information when given insight into the factors that control employee absence behaviour. Having this insight will enable the managers to promote a healthy working environment, thus lowering employee absence rates to a minimum.