scholarly journals Closing the Virtual Gap in Health Care: A Series of Case Studies Illustrating the Impact of Embedding Evaluation Alongside System Initiatives

10.2196/25797 ◽  
2021 ◽  
Vol 23 (9) ◽  
pp. e25797
Author(s):  
Laura Desveaux ◽  
Suman Budhwani ◽  
Vess Stamenova ◽  
Onil Bhattacharyya ◽  
James Shaw ◽  
...  
Keyword(s):  
Case Studies ◽  
Scale Up ◽  
Decision Makers ◽  
Collaborative Problem Solving ◽  
Knowledge Mobilization ◽  
Science And Policy ◽  
Shared Purpose ◽  
Virtual Care ◽  
The Impact ◽  
Structured Communication

Early decisions relating to the implementation of virtual care relied on necessity and clinical judgement, but there is a growing need for the generation of evidence to inform policy and practice designs. The need for stronger partnerships between researchers and decision-makers is well recognized, but how these partnerships can be structured and how research can be embedded alongside existing virtual care initiatives remain unclear. We present a series of case studies that illustrate how embedded research can inform policy decisions related to the implementation of virtual care, where decisions are either to (1) discontinue (red light), (2) redesign (yellow light), or (3) scale up existing initiatives (green light). Data were collected through document review and informal interviews with key study personnel. Case 1 involved an evaluation of a mobile diabetes platform that demonstrated a mismatch between the setting and the technology (decision outcome: discontinue). Case 2 involved an evaluation of a mental health support platform that suggested evidence-based modifications to the delivery model (decision outcome: redesign). Case 3 involved an evaluation of video visits that generated evidence to inform the ideal model of implementation at scale (decision outcome: scale up). In this paper, we highlight the characteristics of the partnership and the process that enabled success and use the cases to illustrate how these characteristics were operationalized. Structured communication included monthly check-ins and iterative report development. We also outline key characteristics of the partnership (ie, trust and shared purpose) and the process (ie, timeliness, tailored reporting, and adaptability) that drove the uptake of evidence in decision-making. Across each case, the evaluation was designed to address policy questions articulated by our partners. Furthermore, structured communication provided opportunities for knowledge mobilization. Structured communication was operationalized through monthly meetings as well as the delivery of interim and final reports. These case studies demonstrate the importance of partnering with health system decision-makers to generate and mobilize scientific evidence. Embedded research partnerships founded on a shared purpose of system service provided an effective strategy to bridge the oft-cited gap between science and policy. Structured communication provided a mechanism for collaborative problem-solving and real-time feedback, and it helped contextualize emerging insights.

scholarly journals Closing the Virtual Gap in Health Care: A Series of Case Studies Illustrating the Impact of Embedding Evaluation Alongside System Initiatives (Preprint)

2020 ◽  
Author(s):  
Laura Desveaux ◽  
Suman Budhwani ◽  
Vess Stamenova ◽  
Onil Bhattacharyya ◽  
James Shaw ◽  
...  
Keyword(s):  
Case Studies ◽  
Scale Up ◽  
Decision Makers ◽  
Collaborative Problem Solving ◽  
Knowledge Mobilization ◽  
Science And Policy ◽  
Shared Purpose ◽  
Virtual Care ◽  
The Impact ◽  
Structured Communication

UNSTRUCTURED Early decisions relating to the implementation of virtual care relied on necessity and clinical judgement, but there is a growing need for the generation of evidence to inform policy and practice designs. The need for stronger partnerships between researchers and decision-makers is well recognized, but how these partnerships can be structured and how research can be embedded alongside existing virtual care initiatives remain unclear. We present a series of case studies that illustrate how embedded research can inform policy decisions related to the implementation of virtual care, where decisions are either to (1) discontinue (red light), (2) redesign (yellow light), or (3) scale up existing initiatives (green light). Data were collected through document review and informal interviews with key study personnel. Case 1 involved an evaluation of a mobile diabetes platform that demonstrated a mismatch between the setting and the technology (decision outcome: discontinue). Case 2 involved an evaluation of a mental health support platform that suggested evidence-based modifications to the delivery model (decision outcome: redesign). Case 3 involved an evaluation of video visits that generated evidence to inform the ideal model of implementation at scale (decision outcome: scale up). In this paper, we highlight the characteristics of the partnership and the process that enabled success and use the cases to illustrate how these characteristics were operationalized. Structured communication included monthly check-ins and iterative report development. We also outline key characteristics of the partnership (ie, trust and shared purpose) and the process (ie, timeliness, tailored reporting, and adaptability) that drove the uptake of evidence in decision-making. Across each case, the evaluation was designed to address policy questions articulated by our partners. Furthermore, structured communication provided opportunities for knowledge mobilization. Structured communication was operationalized through monthly meetings as well as the delivery of interim and final reports. These case studies demonstrate the importance of partnering with health system decision-makers to generate and mobilize scientific evidence. Embedded research partnerships founded on a shared purpose of system service provided an effective strategy to bridge the oft-cited gap between science and policy. Structured communication provided a mechanism for collaborative problem-solving and real-time feedback, and it helped contextualize emerging insights.

Linking Scientific Research to Development Agenda

2018 ◽  
pp. 374-391
Author(s):  
P. K. Kenabatho ◽  
B. P. Parida ◽  
B. Matlhodi ◽  
D.B. Moalafhi
Keyword(s):  
Case Studies ◽  
Scientific Community ◽  
Scientific Research ◽  
Decision Makers ◽  
Knowledge Generation ◽  
Policy Makers ◽  
Scientific Investigations ◽  
Development Agenda ◽  
The Impact

In recent years, the scientific community has been urged to undertake research that can immediately have impact on development issues, including national policies, strategies, and people's livelihoods, among others. While this is a fair call from decision makers, it should also be realized that science by nature is about innovation, discovery and knowledge generation. In this context, there is need for a balance between long term scientific investigations and short term scientific applications. With regard to the former, researchers spend years investigating (or need data of sufficient record length) to provide sound and reliable solutions to a problem at hand while in the latter, it is possible to reach a solution with few selected analyses. In all cases, it is advisable that researchers, where possible should link their studies to topical development issues in their case studies. In this paper, we use a hydrometeorological project in the Notwane catchment, Botswana, to show the importance of linking research to development agenda for mutual benefit of researchers and policy makers. The results indicate that some key development issues are being addressed by the Project and the scope exists to improve the impact of the project.

scholarly journals Scaling up population health interventions from decision to sustainability – a window of opportunity? A qualitative view from policy-makers

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Karen Lee ◽  
Femke van Nassau ◽  
Anne Grunseit ◽  
Kathleen Conte ◽  
Andrew Milat ◽  
...  
Keyword(s):  
Case Studies ◽  
Good Governance ◽  
Scale Up ◽  
Target Population ◽  
Scaling Up ◽  
Structured Interview ◽  
Health Interventions ◽  
Decision Makers ◽  
Framework Analysis ◽  
Policy Makers

Abstract Background While known efficacious preventive health interventions exist, the current capacity to scale up these interventions is limited. In recent years, much attention has focussed on developing frameworks and methods for scale-up yet, in practice, the pathway for scale-up is seldom linear and may be highly dependent on contextual circumstances. Few studies have examined the process of scaling up from decision to implementation nor examined the sustainability of scaled-up interventions. This study explores decision-makers’ perceptions from real-world scaled-up case studies to examine how scale-up decisions were made and describe enablers of successful scale-up and sustainability. Methods This qualitative study included 29 interviews conducted with purposively sampled key Australian policy-makers, practitioners and researchers experienced in scale-up. Semi-structured interview questions obtained information regarding case studies of scaled-up interventions. The Framework Analysis method was used as the primary method of analysis of the interview data to inductively generate common and divergent themes within qualitative data across cases. Results A total of 31 case studies of public health interventions were described by interview respondents based on their experiences. According to the interviewees’ perceptions, decisions to scale up commonly occurred either opportunistically, when funding became available, or when a deliberate decision was made and funding allocated. The latter scenario was more common when the intervention aligned with specific political or strategic goals. Decisions to scale up were driven by a variety of key actors such as politicians, senior policy-makers and practitioners in the health system. Drivers of a successful scale-up process included good governance, clear leadership, and adequate resourcing and expertise. Establishing accountability structures and appropriate engagement mechanisms to encourage the uptake of interventions were also key enablers. Sustainability was influenced by evidence of impact as well as good acceptability among the general or target population. Conclusions Much like Kingdon’s Multiple Streams Theory of ‘policy windows’, there is a conceptually similar ‘window for scale-up’, driven by a complex interplay of factors such as political need, strategic context, funding and key actors. Researchers and policy-makers need to consider scalability from the outset and prepare for when the window for scale-up opens. Decision-makers need to provide longer term funding for scale-up to facilitate longer term sustainability and build on the resources already invested for the scale-up process.

scholarly journals Modelling Flexibility and Qualification Ability to Assess Electric Propulsion Architectures for Satellite Megaconstellations

Aerospace ◽  
2020 ◽  
Vol 7 (12) ◽  
pp. 176
Author(s):  
Massimo Panarotto ◽  
Olivia Borgue ◽  
Ola Isaksson
Keyword(s):  
Case Studies ◽  
Electric Propulsion ◽  
Decision Makers ◽  
Market Behavior ◽  
Production Rates ◽  
Program Managers ◽  
Engineering Teams ◽  
Trade Offs ◽  
The Impact ◽  
The Way

The higher satellite production rates expected in new megaconstellation scenarios involve radical changes in the way design trade-offs need to be considered by electric propulsion companies. In relative comparison, flexibility and qualification ability will have a higher impact in megaconstellations compared to traditional businesses. For these reasons, this paper proposes a methodology for assessing flexible propulsion architectures by taking into account variations in market behavior and qualification activities. Through the methodology, flexibility and qualification ability can be traded against traditional engineering attributes (such as functional performances) in a quantitative way. The use of the methodology is illustrated through an industrial case related to the study of xenon vs. krypton architectures for megaconstellation businesses. This paper provides insights on how to apply the methodology in other case studies, in order to enable engineering teams to present and communicate the impact of alternative architectural concepts to program managers and decision-makers.

Market-Based Solutions for Poverty Reduction in India

2018 ◽  
Author(s):  
Brian English
Keyword(s):  
Case Studies ◽  
Poverty Reduction ◽  
Scale Up ◽  
International Aid ◽  
Social Enterprises ◽  
Social Benefits ◽  
The Impact

The rapid increase in slum populations in India has far outpaced the impact of interventions to date. Market-based solutions have started gaining the attention of governments, international aid groups, NGOs and entrepreneurs as they look for new ways to scale up their impact and sustain their interventions. Thousands of new social enterprises that seek to provide social benefits, and sustain largely on business revenues, have sprung up in response. Their rapid proliferation has attracted the attention of impact investors looking to create the next microfinance industry. This chapter profiles two case studies of market-based solutions in India that provide some important lessons for others fostering similar initiatives.

scholarly journals Development of a Sustainability Assessment Algorithm and Its Validation Using Case Studies on Cryogenic Machining

2020 ◽  
Vol 4 (2) ◽  
pp. 42 ◽  
Author(s):  
Prathamesh Bhat ◽  
Chetan Agrawal ◽  
Navneet Khanna
Keyword(s):  
Case Studies ◽  
Sustainability Assessment ◽  
Decision Makers ◽  
Machining Processes ◽  
Entropy Weight ◽  
Proposed Model ◽  
Order Preference ◽  
Entropy Weight Method ◽  
Weight Method ◽  
The Impact

This work presents a comprehensive structure for evaluating the sustainability of machining processes. Industries can contribute towards developing a sustainable future by using algorithms that evaluate the sustainability of their processes. Inspired by the literature, the proposed model involves a set of metrics that are critical in evaluating the impact of a process on society, environment, and economy. The flexibility of this model allows decision-makers to use the available responses to identify the most favorable process. The entropy weight method was suggested for objectively calculating the weights of each indicator. A multi-criteria decision-making method i.e., Technique for Order Preference based on Similarity to Ideal Solution (TOPSIS), was used to rank processes in the decreasing order of their sustainability. The proposed algorithm was successfully validated with case studies from the published literature. A MATLAB code was also created so that industries may expeditiously apply this method to evaluate the sustainability of machining processes.

What is the Business with AI? Preparing Future Decision Makers and Leaders

2020 ◽  
Author(s):  
Helena S. Wisniewski
Keyword(s):  
Data Science ◽  
Decision Makers ◽  
Management Skills ◽  
Business Courses ◽  
College Of Business ◽  
College Of Engineering ◽  
Investment Firm ◽  
Business Curricula ◽  
The University ◽  
The Impact

With companies now recognizing how artificial intelligence (AI), digitalization, the internet of things (IoT), and data science affect value creation and the maintenance of a competitive advantage, their demand for talented individuals with both management skills and a strong understanding of technology will grow dramatically. There is a need to prepare and train our current and future decision makers and leaders to have an understanding of AI and data science, the significant impact these technologies are having on business, how to develop AI strategies, and the impact all of this will have on their employees’ roles. This paper discusses how business schools can fulfill this need by incorporating AI into their business curricula, not only as stand-alone courses but also integrated into traditional business sequences, and establishing interdisciplinary efforts and collaborative industry partnerships. This article describes how the College of Business and Public Policy (CBPP) at the University of Alaska Anchorage is implementing multiple approaches to meet these needs and prepare future leaders and decision makers. These approaches include a detailed description of CBPP’s first AI course and related student successes, the integration of AI into additional business courses such as entrepreneurship and GSCM, and the creation of an AI and Data Science Lab in partnership with the College of Engineering and an investment firm.

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