Organizational culture, internal marketing, and perceived organizational support in Portuguese higher education institutions / Cultura organizacional, marketing interno y apoyo organizacional percibido en instituciones de educación superior portuguesas

Changes imposed on public higher education institutions try to adopt some management practices in public organizations. In this study, we intend to understand how organizational culture (support, innovation, goals, rules) and internal marketing can contribute to the organizational support of employees of higher education institutions. The study was developed with a sample of 635 employees. The results show that organizational culture and internal marketing contribute to the explanation of perceived organizational support (POS). Then, through a structural equation model, it was possible to confirm the contribution of support culture and internal marketing to the explanation of POS. More studies are necessary taking students’ point of view into account. These results reveal the importance of the fact that organizations need to implement a culture of support and appropriate internal communication networks that allow employees to perceive social support

Los cambios impuestos por las instituciones de educación superior públicas tratan de encajar algunas prácticas de gestión en las organizaciones públicas. En este estudio pretendemos entender cómo la cultura organizacional (apoyo, innovación, objetivos, reglas) y el marketing interno pueden contribuir al apoyo de la organización a los empleados de las instituciones de educación superior. El estudio fue desarrollado con una muestra de 635 empleados. Los resultados muestran que la cultura organizacional y el marketing interno contribuyen a la explicación de la percepción de apoyo organizacional (PAO). Se pudo confirmar la contribución de la cultura de apoyo y marketing interno a la explicación de la PAO. Se necesitan más estudios que tengan en cuenta el punto de vista de los estudiantes. Estos resultados muestran la importancia de la necesidad que tienen las organizaciones de implementar una cultura de apoyo y redes de comunicación

U.S. Department of Defense Multiple-Parameter Biodosimetry Network.

The U.S. Department of Defense (USDOD) service members are at risk of exposure to ionizing radiation due to radiation accidents, terrorist attacks and national defense activities. The use of biodosimetry is a standard of care for the triage and treatment of radiation injuries. Resources and procedures need to be established to implement a multiple-parameter biodosimetry system coupled with expert medial guidance to provide an integrated radiation diagnostic system to meet USDOD requirements. Current USDOD biodosimetry capabilities were identified and recommendations to fill the identified gaps are provided. A USDOD Multi-parametric Biodosimetry Network, based on the expertise that resides at the Armed Forces Radiobiology Research Institute and the Naval Dosimetry Center, was designed. This network based on the use of multiple biodosimetry modalities would provide diagnostic and triage capabilities needed to meet USDOD requirements. These are not available with sufficient capacity elsewhere but could be needed urgently after a major radiological/nuclear event.

Biodosimetry: Medicine, Science, and Systems to Support the Medical Decision-Maker Following a Large Scale Nuclear or Radiation Incident.

The public health and medical response to a radiological or nuclear incident requires the capability to sort, assess, treat, triage and to ultimately discharge, refer or transport people to their next step in medical care. The size of the incident and scarcity of resources at the location of each medical decision point will determine how patients are triaged and treated. This will be a rapidly evolving situation impacting medical responders at regional, national and international levels. As capabilities, diagnostics and medical countermeasures improve, a dynamic system-based approach is needed to plan for and manage the incident, and to adapt effectively in real time. In that the concepts and terms can be unfamiliar and possibly confusing, resources and a concept of operations must be considered well in advance. An essential underlying tenet is that medical evaluation and care will be managed by healthcare professionals with biodosimetry assays providing critical supporting data.

Decision Support System of Nursing Human Resources Allocation in General Wards Based on Hospital Information System.

AIM: To construct a Decision support system of nursing human resources allocation in general wards based on Hospital information system (HIS). METHOD: Time series prediction model and Information technical method were used based on data of HIS in West China Hospital, Sichuan University (Chengdu, P.R. China). RESULTS: This study completed the function design and system implementation of the nursing human resources allocation decision support system. DISCUSSION: The system would help nursing managers choose the optimal scheme and make scientific decisions in combination with "the actual" situation but more empirical studies are needed.

Decision-Making to Support Smooth Daily Unit Operation in Perioperative Settings.

Decision-making in daily unit operation in perioperative settings needs to be smooth. Decision support systems are mainly used as help in this situation. These systems reduce the possibility of risks caused by poor communication. But the decisions and dimensions of the decisions made by nurse manager are still unsolved. The aim of our study was to describe the timeframe of the decisions made by nurse managers in the daily unit operation in perioperative settings. The results indicated that nurse managers made operational and tactical decisions. These operational and tactical decisions happened coincide during the nurse managers shift. The nurse managers were repeatly interrupted in decision-making.

Design of a Recommendation System for Adding Support in the Treatment of Chronic Patients.

Rapid growth of chronic disease cases around the world is adding pressure on healthcare providers to ensure a structured patent follow-up during chronic disease management process. In response to the increasing demand for better chronic disease management and improved health care efficiency, nursing roles have been specialized or enhanced in the primary health care setting. Nurses become key players in chronic disease management process. Study describes a system to help nurses manage the care process of patient with chronic disease. It supports focusing nurse's attention on those resources/solutions that are likely to be most relevant to their particular situation/problem in nursing domain. System is based on multi-relational property graph representing a flexible modeling construct. Graph allows modeling a nursing ontology and the indices that partition domain into an efficient, searchable space where the solution to a problem is seen as abstractly defined traversals through its vertices and edges.

Impact of an Atrial Fibrillation Decision Support Tool on thromboprophylaxis for atrial fibrillation.

BACKGROUND: Appropriate thromboprophylaxis for patients with atrial fibrillation (AF) remains a national challenge. METHODS: We hypothesized that provision of decision support in the form of an Atrial Fibrillation Decision Support Tool (AFDST) would improve thromboprophylaxis for AF patients. We conducted a cluster randomized trial involving 15 primary care practices and 1,493 adults with nonvalvular AF in an integrated health care system between April 2014 and February 2015. Physicians in the intervention group received patient-level treatment recommendations made by the AFDST. Our primary outcome was the proportion of patients with antithrombotic therapy that was discordant from AFDST recommendation. RESULTS: Treatment was discordant in 42% of 801 patients in the intervention group. Physicians reviewed reports for 240 patients. Among these patients, thromboprophylaxis was discordant in 63%, decreasing to 59% 1 year later (P = .02). In nonstratified analyses, changes in discordant care were not significantly different between the intervention group and control groups. In multivariate regression models, assignment to the intervention group resulted in a nonsignificant trend toward decreased discordance (P = .29), and being a patient of a resident physician (P = .02) and a higher HAS-BLED score predicted decreased discordance (P = .03), whereas female gender (P = .01) and a higher CHADSVASc score (P = .10) predicted increased discordance. CONCLUSIONS: Among patients whose physicians reviewed recommendations of the decision support tool discordant therapy decreased significantly over 1 year. However, in nonstratified analyses, the intervention did not result in significant improvements in discordant antithrombotic therapy.

[Business intelligence in radiology. Challenges and opportunities]. / Business Intelligence in der Radiologie. Herausforderungen und Möglichkeiten.

Due to economic pressures and need for higher transparency, a ubiquitous availability of administrative information is needed. Therefore radiology managers should consider implementing business intelligence (BI) solutions. BI is defined as a systemic approach to support decision-making in business administration. It is an important part of the overall strategy of an organization. Implementation and operation is initially associated with costs and for a successful launch important prerequisites must be fulfilled. First, a suitable product must be selected, followed by the technical and organizational implementation. After consideration of the type of data to be collected and a system of key performance indicators must be established. BI replaces classic retrospective business reporting with multidimensional and multifactorial analyses, real-time monitoring, and predictive analyses. The benefits of BI include the rapid availability of important information and the depth of possible data analysis. The simple and intuitive use of modern BI applications by the users themselves (!) combined with a continuous availability of information is the key to success. Professional BI will be an important part of management in radiology in the future.

[Prioritization and Consentation of Criteria for the Appraisal, Funding and Evaluation of Projects from the German Innovationsfonds: A multi-perspective Delphi study]. / Priorisierung und Konsentierung von Begutachtungs-, Förder- und Evaluationskriterien für Projekte aus dem Innovationsfonds: Eine multiperspektivische Delphi-Studie.

BACKGROUND: The German Innovationsfonds provides the chance for evidence-based developments of the German healthcare system. OBJECTIVE: Prioritization of recommendations for an effective, efficient, fair, transparent, and sustainable granting of funds through a transparent, evidence-driven consensus-process involving all relevant stakeholder groups. METHODS: Representatives from health and research policy, payers, patient representatives, healthcare providers, and scientists were invited to nominate participants for an electronic 3 round iterative Delphi-study to prioritize the thematic focus, requirements concerning study methods, the team of applicants, evaluation, utilization of study results, and for the selection of reviewers. Criteria considered as relevant by at least 60% of the panel (consensus definition) in the first 2 Delphi rounds were rated as facultative, preferable, or obligatory criteria for project funding. Data were analyzed descriptively. ( REGISTRATION: Datenbank Versorgungsforschung Deutschland VfD_15_003561). RESULTS: All invited stakeholder groups except payers participated. 34 (85%) of 40 nominated representatives participated in the Delphi-study. A total of 64 criteria were consented as relevant for project review and funding concerning the thematic focus (n=28), methodological requirements (n=13), requirements for applicants (n=4), for the evaluation (n=4), utilization (n=6), and selection of peer reviewers (n=9). DISCUSSION: It is the collective responsibility of all stakeholders to spend the designated funds as efficient and sustainable as possible. The consented recommendations shall serve decision makers as a resource for the granting of funds and the evaluation of the Innovationsfonds.

Trialling an electronic decision aid for policy developers to support ageing well.

The complex process of developing policies and planning services requires the compilation and collation of evidence from multiple sources. With the increasing numbers of people living longer there will be a high demand for a wide range of aged care services to support people in ageing well. The premise of ageing well is based on providing an ageing population with quality care and resources that support their ongoing needs. These include affordable healthcare, end of life care improvement, mental health services improvement, care and support improvement for people with dementia, and support for healthy ageing. The National Health and Medical Research Council funded a research project to develop a policy tool to provide a framework to assist policy makers and service planners in the area of ageing well in rural and regional Australia. It was identified that development of an electronic version of the policy tool could be useful resulting in a small pilot development being undertaken and tested with policy makers and service planners. This paper describes the development and trialling of a tablet based application used to assess the acceptability of computerised forms for participants actively involved in policy development. It reports on the policy developer's experience of the electronic tool to support ageing well policy making based on evidence.

A conceptual framework for organizational readiness to implement nutrition and physical activity programs in early childhood education settings.

Across multiple sectors, organizational readiness predicts the success of program implementation. However, the factors influencing readiness of early childhood education (ECE) organizations for implementation of new nutrition and physical activity programs is poorly understood. This study presents a new conceptual framework to measure organizational readiness to implement nutrition and physical activity programs in ECE centers serving children aged 0 to 5 years. The framework was validated for consensus on relevance and generalizability by conducting focus groups; the participants were managers (16 directors and 2 assistant directors) of ECE centers. The framework theorizes that it is necessary to have "collective readiness," which takes into account such factors as resources, organizational operations, work culture, and the collective attitudes, motivation, beliefs, and intentions of ECE staff. Results of the focus groups demonstrated consensus on the relevance of proposed constructs across ECE settings. Including readiness measures during program planning and evaluation could inform implementation of ECE programs targeting nutrition and physical activity behaviors.

Interpretable associations over DataCubes: application to hospital managerial decision making.

The world concern about the costs of the health care systems has raised the importance of counting on precise and interpretable tools, that help the health care institution's managers to make decisions to optimize the use of health resources. In this paper we propose a new Classification based on Association Rules (CAR) algorithm that improves the interpretability of the results, making it specially useful for decision making. Changing the usual way to obtain the rules we follow four goals: first to improve the interpretability of the result by obtaining rules meaningful and interpretable by themselves, secondly to reduce the complexity of the result obtaining a lower number of rules; thirdly, to obtain simpler rules, with less size in number of antecedents; and finally to avoid the usual over-fitting problem of the classification methods by obtaining a generic final result set, where specific rules for specific cases are avoided unless they are necessary. To prove the utility of our proposal we have used it in an example of decision support regarding the planning of the surgery rooms.

The development of an online decision support tool for organizational readiness for change.

BACKGROUND: Much importance has been placed on assessing readiness for change as one of the earliest steps of implementation, but measuring it can be a complex and daunting task. Organizations and individuals struggle with how to reliably and accurately measure readiness for change. Several measures have been developed to help organizations assess readiness, but these are often underused due to the difficulty of selecting the right measure. In response to this challenge, we will develop and test a prototype of a decision support tool that is designed to guide individuals interested in implementation in the selection of an appropriate readiness assessment measure for their setting. METHODS: A multi-phase approach will be used to develop the decision support tool. First, we will identify key measures for assessing organizational readiness for change from a recently completed systematic review. Included measures will be those developed for healthcare settings (e.g., acute care, public health, mental health) and that have been deemed valid and reliable. Second, study investigators and field experts will engage in a mapping exercise to categorize individual items of included measures according to key readiness constructs from an existing framework. Third, a stakeholder panel will be recruited and consulted to determine the feasibility and relevance of the selected measures using a modified Delphi process. Fourth, findings from the mapping exercise and stakeholder consultation will inform the development of a decision support tool that will guide users in appropriately selecting change readiness measures. Fifth, the tool will undergo usability testing. DISCUSSION: Our proposed decision support tool will address current challenges in the field of organizational change readiness by aiding individuals in selecting a valid and reliable assessment measure that is relevant to user needs and practice settings. We anticipate that implementers and researchers who use our tool will be more likely to conduct readiness for change assessments in their settings when planning for implementation. This, in turn, may contribute to more successful implementation outcomes. We will test this tool in a future study to determine its efficacy and impact on implementation processes.

Improving emergency medical dispatching with emphasis on mass-casualty incidents.

Dispatching ambulances is a demanding and stressful task for dispatchers. This is especially true in case of mass-casualty incidents. Therefore, the aim of this work was to investigate if and to what extent the dispatch operation of the Red Cross Salzburg can be optimized on such occasions with a computerized system. The basic problem of a dynamic multi-vehicle Dial-a-Ride Problem with time windows was enhanced according to the requirements of the Red Cross Salzburg. The general objective was to minimize the total mileage covered by ambulances and the waiting time of patients. Furthermore, in case of emergencies suitable adaptions to a plan should be carried out automatically. Consequently, the problem is solved by using the Adaptive Large Neighborhood Search. Evaluation results indicate that the system outperforms a human dispatcher by between 2.5% and 36% within 1 minute of runtime concerning total costs. Moreover, the system's response time in case that a plan has to be updated is less than 1 minute on average.

Decision-support information system to manage mass casualty incidents at a level 1 trauma center.

Mass casualty incidents are probably the greatest challenge to a hospital. When such an event occurs, hospitals are required to instantly switch from their routine activity to conditions of great uncertainty and confront needs that exceed resources. We describe an information system that was uniquely designed for managing mass casualty events. The web-based system is activated when a mass casualty event is declared; it displays relevant operating procedures, checklists, and a log book. The system automatically or semiautomatically initiates phone calls and public address announcements. It collects real-time data from computerized clinical and administrative systems in the hospital, and presents them to the managing team in a clear graphic display. It also generates periodic reports and summaries of available or scarce resources that are sent to predefined recipients. When the system was tested in a nationwide exercise, it proved to be an invaluable tool for informed decision making in demanding and overwhelming situations such as mass casualty events.

A conceptual framework for automating the operational and strategic decision-making process in the health care delivery system.

Making reliable and justified operational and strategic decisions is a really challenging task in the health care domain. So far, the decisions have been made based on the experience of managers and staff, or they are evaluated with traditional methods, using inadequate data. As a result of this kind of decision-making process, attempts to improve operations usually have failed or led to only local improvements. Health care organizations have a lot of operational data, in addition to clinical data, which is the key element for making reliable and justified decisions. However, it is progressively problematic to access it and make usage of it. In this paper we discuss about the possibilities how to exploit operational data in the most efficient way in the decision-making process. We'll share our future visions and propose a conceptual framework for automating the decision-making process.

Improving decision quality in healthcare with an Error Prevention Model (EPM).

Human factors involved in decision quality are critical issues in healthcare. In this paper, issues related to the impact of human factors on decision quality in healthcare are considered. Specifically, the focus is on the issue of reducing human error as well as improving decision quality. An Error Prevention Model (EPM) is presented for considering tools and techniques that can be used to analyze complex errors that may be considered latent.

Predefined three tier business intelligence architecture in healthcare enterprise.

Business Intelligence (BI) has caused extensive concerns and widespread use in gathering, processing and analyzing data and providing enterprise users the methodology to make decisions. Different from traditional BI architecture, this paper proposes a new BI architecture, Top-Down Scalable BI architecture with defining mechanism for enterprise decision making solutions and aims at establishing a rapid, consistent, and scalable multiple applications on multiple platforms of BI mechanism. The two opposite information flows in our BI architecture offer the merits of having the high level of organizational prospects and making full use of the existing resources. We also introduced the avg-bed-waiting-time factor to evaluate hospital care capacity.