Personalization efforts and the relationship to school climate in select Michigan high schools

The American high school is on the verge of a reform movement like that seen in American middle schools throughout the early and mid-1990s. In 1996 the National Association of Secondary School Principals (NASSP) released its recommendations for reform in the study Breaking Ranks: Changing an American Institution. Among these are recommendations that call for high schools to become smaller, less bureaucratic, and more responsive to student needs, where students feel a sense of belonging. Hoy and Miskel (2001) defined school climate as a “relatively enduring quality of the school’s environment that is experienced by participants, affects their behavior, is based on their collective perceptions of behavior in schools” (p. 190). The purpose of this study was to determine what relationship existed between the implementation of the Breaking Ranks recommendations and school climate. Principals of Michigan high schools of similar size and geography were asked to respond to a survey indicating the level of implementation of the Breaking Ranks recommendations on Personalization and Relationships in their high schools. To assess perceptions of school climate, staff members from these schools were asked to respond to the Organizational Climate Description Questionnaire for Secondary Schools (OCDQ-RS). A Spearman correlation between the level of implementation and the climate of the school was analyzed. The results indicated that while all of the Breaking Ranks recommendations and most of the strategies have been implemented to varying degrees in high schools, there is only a moderately strong relationship between implementation of the recommendations and strategies and school climate items related to principal qualities, teacher/principal relations, and teacher/student relations

Artificial Intelligence in Medicine: A New Way to Diagnose and Treat Disease

Artificial intelligence (AI) has immense potential to transform medicine by improving diagnostic accuracy and enabling personalized treatments. This paper explores how AI systems analyze medical images, lab tests, genetic data, and patient histories to detect disease earlier and guide therapy selection. Though still an emerging field, impressive results demonstrate AI can surpass human clinicians on diagnostic tasks. For example, an AI system detected breast cancer from mammograms more accurately than expert radiologists. In ophthalmology, AI outperformed ophthalmologists in diagnosing diabetic retinopathy. By finding subtle patterns in complex datasets, AI promises to catch diseases like cancer in early, more treatable stages. Beyond diagnosis, AI can identify optimal treatments for individual patients based on their genetic makeup and lifestyle factors. Researchers are also using AI to design new medications. While AI offers many benefits, challenges remain regarding clinician displacement, legal liability, data privacy, and the "black box" nature of AI reasoning. More research is needed, but it is clear that AI will fundamentally alter medical practice. AI empowers clinicians to provide earlier, more precise diagnoses and tailored therapies for patients. Though it will not replace doctors, by automating routine tasks and uncovering hidden insights, AI can free physicians to focus on holistic care. The future of medicine lies in humans and smart machines working together

Data science, analytics and artificial intelligence in e-health : trends, applications and challenges

Acknowledgments. This work has been partially supported by the Divina Pastora Seguros company.More than ever, healthcare systems can use data, predictive models, and intelligent algorithms to optimize their operations and the service they provide. This paper reviews the existing literature regarding the use of data science/analytics methods and artificial intelligence algorithms in healthcare. The paper also discusses how healthcare organizations can benefit from these tools to efficiently deal with a myriad of new possibilities and strategies. Examples of real applications are discussed to illustrate the potential of these methods. Finally, the paper highlights the main challenges regarding the use of these methods in healthcare, as well as some open research lines

Transforming fertility services into remote health care

[EN] With the rising of technology, remote services providing Health Care at home is becoming a must for organizations, as it enables additional patient-centric initiatives. The transition to remote health care has attracted both new competitors and new partners to the health care industry. In the fertility care industry, the entry of new firms indicates there is an opportunity for remote processes also for incumbent firms. This TFM aims to analyze in depth the convenience of transforming on a remote service every medical interaction with patients that are required for fertility care. Previous analyses will include trends in the sector, competitors positioning and the remote services they offer, including technologies and systems required as support for these services. Then, a redefinition of the service design based on the patient journey will be carried out, evaluating how many of the compulsory visits to the clinics can be replaced by a patient-at-home service. This will contain a look at the current or upcoming state of art of technology. The TFM can be useful as a reference for firms in the Health Care market which are considering some transition to remote care services.Almudéver Galán, MÁ. (2022). Transforming fertility services into remote health care. Universitat Politècnica de València. http://hdl.handle.net/10251/187073TFG

Beyond Knowledge Management -- Introducing a Framework for Learning Management Systems

In the knowledge economy, a firm’s intellectual capital represents the only sustainable source of competitive advantage. Intellectual capital manifests itself, predominantly, in the individual and collective competencies of employees in organizations. Hence, the ability to learn and to manage learning becomes critical to the success of organizations. Firm’s adopting knowledge management initiatives seek to facilitate the sharing and integration of knowledge. This approach has had limited success, primarily because of its focus on ‘knowledge as a resource’ rather than on ‘learning as a people process’. A strategic ‘people-oriented’ approach to the management of learning is now emerging in many organizations and a new breed of information system (IS), the ‘Learning Management System’ (LMS), is being used to manage organizational learning. As with previous IS innovations, such as Enterprise Resource Planning (ERP) systems, industry practitioners and IT vendors, are addressing the ‘Learning Management’ challenge; consequently, there is a paucity of empirical research on LMS in the IS field. It is well-accepted that with little researched or understood phenomena, a research framework is required to identify fundamental constructs and variables so that such phenomena can be rigorously studied. Based on an exhaustive analysis of previous research and an extensive case study of an LMS implementation, this paper proposes a conceptual model and framework that delineates a role for LMS with respect to theories that deal with knowledge and learning management and IS which are argued to support learning and knowledge management in organizations. In so doing, this study highlights the roles that LMS can play in the support and management of learning within knowledge-intensive business enterprises

Business Plan to reconfigure Mediseen INC early strategy

El modelo comercial actual de MediSeen se centra en tener doctores en su plataforma virtual para que realicen visitas a domicilio. Sin embargo, esta estrategia no tiene una propuesta de valor direccionable para los doctores o para la compa??a que pueda conducir a un ?xito financiero sostenible. Adem?s, existe un grave riesgo de desintermediaci?n, es decir, los clientes recurren directamente a los proveedores de servicios despu?s de la primera transacci?n a trav?s de la plataforma de Mediseen. Para agravar a?n m?s el problema, MediSeen tiene efectivo limitado y solo puede sobrevivir hasta fines de 2019 sin recaudar capital adicional. MediSeen tiene dos posibles alternativas para abordar estos problemas estrat?gicos clave. Primero, MediSeen podr?a desviar su atenci?n de los doctores y limitarla solo al segmento de atenci?n m?dica aliada, que incluye servicios como masajes, fisioterapia, terapia de yoga, nutricionistas y entrenamiento personal. Al hacer este cambio, la estructura de la comisi?n tambi?n necesitar?a ser revisada para reducir el riesgo de desintermediaci?n y mantener a los proveedores de servicios motivados. Al final del a?o 2019, se deber?an lograr un total de 42,000 descargas de aplicaciones, 1,800 consultas y obtener 1,260 usuarios activos, que se traducir?n en $59,400 de ingresos para hacer viable esta alternativa, y lograr un EBITDA rentable en el a?o 2020. En segundo lugar, MediSeen podr?a salir del negocio cerrando sus operaciones. Como la compa??a no tiene acreedores, no es elegible para declararse en bancarrota (de acuerdo a la Ley Canadiense). Seg?n los valores de liquidaci?n t?picos de los activos, estimamos que el valor de liquidaci?n de MediSeen actualmente es de$ 550,000, lo que representa un retorno de 5.5 ? / $ para los inversionistas originales

Smart Interventions for Effective Medication Adherence

In this research we present a model for medication adherence from information systems and technologies (IS/IT) perspective. Information technology applications for healthcare have the potential to improve cost-effectiveness, quality and accessibility of healthcare. To date, measurement of patient medication adherence and use of interventions to improve adherence are rare in routine clinical practice. IS/IT perspective helps in leveraging the technology advancements to develop a health IT system for effectively measuring medication adherence and administering interventions. Majority of medication adherence studies have focused on average medication adherence. Average medication adherence is the ratio of the number of doses consumed and the number of doses prescribed. It does not matter in which order or pattern patients consume the dose. Patients with enormously diverse dosing behavior can achieve the same average levels of medication adher­ence. The same outcomes with different levels of ad­herence raise the possibility that patterns of adherence affect the effectiveness of medication adherence. We propose that medication adherence research should utilize effective medication adherence (EMA), derived by including both the pattern and average medication adherence for a patient. Using design science research (DSR) approach we have developed a model as an artifact for smart interventions. We have leveraged behavior change techniques (BCTs) based on the behavior change theories to design smart intervention. Because of the need for real time requirements for the system, we are also focusing on hierarchical control system theory and reference model architecture (RMA). The benefit of using this design is to enable an intervention to be administered dynamically on a need basis. A key distinction from existing systems is that the developed model leverages probabilistic measure instead of static schedule. We have evaluated and validated the model using formal proofs and by domain experts. The research adds to the IS knowledge base by providing the theory based smart interventions leveraging BCTs and RMA for improving the medication adherence. It introduces EMA as a measurement of medication adherence to healthcare systems. Smart interventions based on EMA will further lead to reducing the healthcare cost by improving prescription outcomes

Smart Interventions for Effective Medication Adherence

In this research we present a model for medication adherence from information systems and technologies (IS/IT) perspective. Information technology applications for healthcare have the potential to improve cost-effectiveness, quality and accessibility of healthcare. To date, measurement of patient medication adherence and use of interventions to improve adherence are rare in routine clinical practice. IS/IT perspective helps in leveraging the technology advancements to develop a health IT system for effectively measuring medication adherence and administering interventions. Majority of medication adherence studies have focused on average medication adherence. Average medication adherence is the ratio of the number of doses consumed and the number of doses prescribed. It does not matter in which order or pattern patients consume the dose. Patients with enormously diverse dosing behavior can achieve the same average levels of medication adher­ence. The same outcomes with different levels of ad­herence raise the possibility that patterns of adherence affect the effectiveness of medication adherence. We propose that medication adherence research should utilize effective medication adherence (EMA), derived by including both the pattern and average medication adherence for a patient. Using design science research (DSR) approach we have developed a model as an artifact for smart interventions. We have leveraged behavior change techniques (BCTs) based on the behavior change theories to design smart intervention. Because of the need for real time requirements for the system, we are also focusing on hierarchical control system theory and reference model architecture (RMA). The benefit of using this design is to enable an intervention to be administered dynamically on a need basis. A key distinction from existing systems is that the developed model leverages probabilistic measure instead of static schedule. We have evaluated and validated the model using formal proofs and by domain experts. The research adds to the IS knowledge base by providing the theory based smart interventions leveraging BCTs and RMA for improving the medication adherence. It introduces EMA as a measurement of medication adherence to healthcare systems. Smart interventions based on EMA will further lead to reducing the healthcare cost by improving prescription outcomes

The Interval Kicking Program (IKP) as a Reprogramming Technique for the Soccer Player in an Anterior Cruciate Ligament (ACL) Rehabilitation: A Technical Report

Introduction. We can state as technical-athletic gestural movements that we might call clinical (pivoting, cutting maneuvers, sidestep cuts, changes of direction) associated with ACL injuries. Objective. This technical report was conducted to research methods of reprogramming basic technical skills in the soccer player after anterior cruciate ligament reconstructive surgery. Technical report results. The Interval Kicking Program (IKP) is a model proposed as a neuromotor remodelling of basic gestures and techniques after an ACL injury in soccer player. The teaching progression is ordered regarding the diversified techniques of passing and receiving the ball. The volume, intensity, and progression steps are governed by 1) clinical status (i.e., type of injury, conservative/surgical treatment type, type of sport), 2) performance status, and 3) objective evaluative analysis of periodic follow-ups. The steps provid-ed by the IKP can be 15 and end with the introduction of the player into technical drills with the presence of opponents the first sessions include about 30 minutes of sport-specific, low-intensity exercises, while in the last ones, the volume remains constant, but the intensity and technical complexity of the movements increase. Conclusions. In this technical report, we have highlighted how IKP can be a teaching model for reprogramming basic technical skills in the soccer player after injury. It remains fair to point out how aberrant technical movement partners, side-to-side asymmetries, and postur-al dysfunction are predictive of the risk of compliance and second injury. Further studies and insights are needed to customize the reprogramming of the soccer player’s gestural movements during return to play. © 2023, EDRA S.p.A. All rights reserved