Technique for improving care integration models

Recent developments in technologies and improved life style have had a positive impact on prolonging human life contributing to the increasing elderly population. As a consequence, many countries (particularly developed ones) started to experience higher proportions of elderly people (over 65). This has consequently generated the need for care for the elderly that is necessitating the integration of health and social care to accommodate their complex needs. A number of modelling methods have been employed to assist those concerned to cope with health and social care but albeit separately. The literatures so far, identified several techniques that have been employed mostly to model the care integration. However, literatures also suggest that there are some challenges still persist when modelling integrated care. It can be argued that these techniques are not capable of handling the complexities associated with the requirements of integrated systems. This paper attempts to prove the reason why despite the fact that many models of integrated care have been developed, problems are still exist. Based on the literatures, the problems exist due to the unsuitable techniques used to model the IC systems as most of the developed models are using single technique. Therefore, new technique to improve the care integration model is suggested

Simulation-Based Inference for Global Health Decisions

The COVID-19 pandemic has highlighted the importance of in-silico epidemiological modelling in predicting the dynamics of infectious diseases to inform health policy and decision makers about suitable prevention and containment strategies. Work in this setting involves solving challenging inference and control problems in individual-based models of ever increasing complexity. Here we discuss recent breakthroughs in machine learning, specifically in simulation-based inference, and explore its potential as a novel venue for model calibration to support the design and evaluation of public health interventions. To further stimulate research, we are developing software interfaces that turn two cornerstone COVID-19 and malaria epidemiology models COVID-sim, (https://github.com/mrc-ide/covid-sim/) and OpenMalaria (https://github.com/SwissTPH/openmalaria) into probabilistic programs, enabling efficient interpretable Bayesian inference within those simulators

A STRATEGIC VIEW ON INTERTWINING DIGITAL AND PHYSICAL MATERIALITIES ACROSS LIFECYCLES OF PRODUCTS AND SERVICES

Opportunities to use virtual, augmented, and mixed reality (VAM-R) are emerging in various sectors of the economy. To seize them, managers need to develop comprehensive strategies that intertwine digital and physical forms of materiality. This paper proposes a way to assess and steer the transformations of the reality-virtuality continuum across lifecycles of products and services. Our approach identifies use cases for VAM-R according to the (1) strategic imperative, (2) physical materiality, (3) reality-virtuality assessment, (4) digital materiality, (5) information value, and (6) project portfolio. The findings result from three action research cycles in manufacturing and healthcare. For theory, we propose a framework to evaluate the reality-virtuality continuum and guide VAM-R transformations. For practice, we propose and test an artefact accessible to domain experts with different backgrounds, and a sequence of steps to assist managers in their digitalization strategies with VAM-R. Lifecycle approaches offer an alternative perspective to situational transformation, potentially improving the pervasiveness of organizational changes using information technologies

Principles of Enterprise Systems

The Massachusetts Institute of Technology (MIT) through its Lean Advancement Initiative (LAI) research team has been conducting research and facilitating enterprise-level transformations in large complex sociotechnical enterprises for over fifteen years. These enterprises have spanned a broad base of industries and governmental organizations including aerospace, automotive, electronics, health care, transportation, construction, defense acquisition and logistics, research labs and many others. What has emerged from both the action research in the field and its application in case studies in graduate courses is the concept of “overarching” enterprise principles and transformation methodologies that are independent of the industry or organization. A framework for transformation that consists of a set of interdependent methodologies, tools and enterprise principles that support holistic enterprise transformation is described and includes the following five elements: 1) Key Principles of Enterprise Thinking, 2) Enterprise Transformation Roadmap, 3) Lean Enterprise Self Assessment Tool (LESAT), 4) Enterprise Strategic Analysis for Transformation (ESAT) and 5) Enterprise Architecting Framework. The application of this framework to the enterprise systems analysis and design of various industry and governmental organizations is discussed

ORGANIZATION OF INFORMATION FOR REVERSIBLE CAUSES OF PULSELESS IN-HOSPITAL CARDIAC ARREST: A RANDOMIZED CONTROL TRIAL USING A COGNITIVE AID

More than 200,000 in-hospital cardiac arrests are treated each year in the US with 21% survival rate. According to American Heart Association (AHA) guidelines, many causes for these arrests could be successfully treated if identified early. Such causes can be generalized as \u27reversible causes\u27. Medical doctors identify the reversible causes associated with an arrest by recalling them from memory, using a mnemonic. In this study, using a cognitive aid such as an iPad application, the mnemonic was modified and causes were displayed alphabetically, and tested along with a new method that rank-ordered the reversible causes based on the patient context, known as the context-sensitive scheme. Both methods were implemented electronically in an iPad application and presented in a counterbalanced order to 11 anesthesia medical residents using simulated scenarios. Performance and usability measures were recorded and analyzed. It took significantly longer for the participants to identify the reversible causes using the context-sensitive scheme. However, the scheme resulted in significantly lesser number of unnecessary keystrokes when compared to the alphabetical scheme. Some of these unnecessary keystrokes could affect the patient\u27s outcome. Both the schemes agreed in terms of usability. The above results indicate the potential of the context-sensitive scheme of the reversible causes to be useful when applied during an emergency scenario when refined further. A combination of both methods is suggested

Lean Management Principles to the Creation of Postpartum Hemorrhage Care Bundles

Postpartum hemorrhage (PPH) is the number one cause of pregnancy-related death in the US. The Maternity local improvement team (LIT), co-led by an Obstetrician and Board Certified Clinical Nurse Specialist found that each month the maternity unit averages 40 PPHs with 1-2 resulting in an emergency. Over a 6-month period, the LIT decreased response time for emergencies significantly. Supply retrieval time decreased by 99.9%, MD response time decreased by 81%, and Family Centered Care increased by 100%. They recently turned their attention to prevention. Given the lack of literature on preventing PPH in postpartum units, the team developed a PPH prevention bundle-a small set of evidence-based interventions enhancing teamwork and communication to improve patient outcomes. Dr. Crowe as the national lead for benchmarking obstetrical adverse events in the Solutions for Patient Safety collaborative will track the success of the PPH bundle, which could become the first national standard in prevention of PPH requiring a blood transfusion. The team targeted 100% compliance to bundle elements, with an ultimate goal of decreasing need for transfusion. Many problems have been encountered along the way, such as RN handoffs from Labor and Delivery as well as having appropriate staff to help new mothers to the bathroom for the first time, but the team has worked through them one-by-one. Through simulation training over a 6-month period, 100 RNs, MDs, and family representatives simulated the bundle approach. The PPH Prevention Bundle could become the first national standard in prevention of PPHs on a postpartum unit

ERP implementation methodologies and frameworks: a literature review

Enterprise Resource Planning (ERP) implementation is a complex and vibrant process, one that involves a combination of technological and organizational interactions. Often an ERP implementation project is the single largest IT project that an organization has ever launched and requires a mutual fit of system and organization. Also the concept of an ERP implementation supporting business processes across many different departments is not a generic, rigid and uniform concept and depends on variety of factors. As a result, the issues addressing the ERP implementation process have been one of the major concerns in industry. Therefore ERP implementation receives attention from practitioners and scholars and both, business as well as academic literature is abundant and not always very conclusive or coherent. However, research on ERP systems so far has been mainly focused on diffusion, use and impact issues. Less attention has been given to the methods used during the configuration and the implementation of ERP systems, even though they are commonly used in practice, they still remain largely unexplored and undocumented in Information Systems research. So, the academic relevance of this research is the contribution to the existing body of scientific knowledge. An annotated brief literature review is done in order to evaluate the current state of the existing academic literature. The purpose is to present a systematic overview of relevant ERP implementation methodologies and frameworks as a desire for achieving a better taxonomy of ERP implementation methodologies. This paper is useful to researchers who are interested in ERP implementation methodologies and frameworks. Results will serve as an input for a classification of the existing ERP implementation methodologies and frameworks. Also, this paper aims also at the professional ERP community involved in the process of ERP implementation by promoting a better understanding of ERP implementation methodologies and frameworks, its variety and history

AN OBSERVATIONAL STUDY OF THE METHODS AND PROGRESS IN ENTERPRISE LEAN TRANSFORMATION AT A LEARNING HEALTH CARE ORGANIZATION

The health care industry in the United States is increasingly pressured to improve safety and quality performance and increase revenue. In response, many health care institutions are moving to redesign their processes and practices in an effort to decrease costs and provide safer, higher quality, and more efficient care. The purpose of this paper is to document the Lean implementation strategy and progress in implementation at a large teaching health care organization undergoing Lean transformation in order to understand enterprise transformation strategies and the impact of leadership involvement on culture development and Lean implementation. Through direct observations and involvement and transformation activities, the methodology for Lean transformation and progress in implementation were documented and analyzed. The organization employed an outside consultant to assist with transformation activities, and underwent a three-pronged approach to implementation, which included model area development, team member problem solving training, and management-led problem solving activities. It was found that leadership involvement was lacking, especially at the highest levels, and the organization struggled to build the culture necessary to support transformation and develop an operational model area, though successes were realized in efforts to train employees in Toyota’s 8-Step Problem Solving method and in management-led problem solving activities

Modeling the workflow of one primary care physician-nurse team.

Primary care has been identified as a vital part of the healthcare system in the U.S., and one that operates in a challenging, unique environment. Primary care sees a wide variety of patients and is undergoing a series of major transformations simultaneously. As a result, primary care would greatly benefit from a systemic approach to the analysis of its workflows. Discrete-event simulation has been identified as a good tool to evaluate complex healthcare systems. The existing primary care DES models focus on the physician. Also, those models are limited in (a) their usefulness to produce generic models that can easily and quickly be customized and (b) the analysis of the specific tasks performed to treat a patient. Hence, a research idea was developed to address these limitations, which led to a progressive multi-part study developing the necessary components to model a primary clinic. The study was constructed to allow each progressive study to build on the previous. The first part of the study developed a new approach to address those limitations: modeling a primary care clinic from the viewpoint that the physician is the entity that moves through the system. This approach was implemented based on observational data and a standardized primary care physician task list using ARENA© simulation software. The completed model is evidence-based, with the simulation producing predictions and analysis associated with a given patient visit that has not happened by mimicking reality. The benefits of this type of flexible model are that it allows for analysis of any type of “cost” that can be quantified, and it can then be utilized for predicting and potentially subsequently reducing procedural errors and variation in order to increase operational efficiency. The second part of the study was to develop a standardized primary care nurse task list, which is needed given the current transformation of primary care from a doctor-based model to a team-based model. A comprehensive, validated list of tasks occurring during clinic visits was complied from a secondary data analysis. For this, primary care clinics in Wisconsin were selected from a pre-existing study based on 100% participation of the physician-nurse teams. The final task list had 18 major tasks and 174 second-level subtasks, with 103 additional third-level tasks. This task list, combined with the primary care physician task list, provides a tool set that facilitates clinics’ analysis of the workflow associated with a complete patient encounter. Finally, the third part of the study used observational data, the standardized primary care nurse task list, and a similar modeling methodology to the first part to develop a simulation model of the primary care nurse. The model was implemented using ARENA© simulation software. This model is flexible, resulting in an easily-customizable model, and robust in that it allows the analysis of any type of “cost” that can be quantified, such as time, physical or mental resources, money, et cetera. This can potentially be used to predict, and reduce, procedural errors and variation in response to changes to the workflows or environment; hence, the operational efficiency and medical accuracy can be more accurately evaluated