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Building longitudinal population cohorts in Africa for coordinated research and surveillance can influence the setting of national health priorities, lead to the introduction of appropriate interventions, and provide evidence for targeted treatment, leading to better health across the continent. However, compared to cohorts from the global north, longitudinal continental African population cohorts remain scarce, are relatively small in size, and lack data complexity. As infections and noncommunicable diseases disproportionately affect Africa's approximately 1.4 billion inhabitants, African cohorts present a unique opportunity for research and surveillance. High genetic diversity in African populations and multiomic research studies, together with detailed phenotyping and clinical profiling, will be a treasure trove for discovery. The outcomes, including novel drug targets, biological pathways for disease, and gene-environment interactions, will boost precision medicine approaches, not only in Africa but across the globe.

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Introduction: Implementation of research findings in clinical practice often is not realized or only partially achieved, and if so, with a significant delay. Learning health systems (LHSs) hold promise to overcome this problem by embedding clinical research and evidence-based best practices into care delivery, enabling innovation and continuous improvement. Implementing an LHS is a complex process that requires participation and resources of a wide range of stakeholders, including healthcare leaders, clinical providers, patients and families, payers, and researchers. Engaging these stakeholders requires communicating clear, tangible value propositions. Existing models identify broad categories of benefits but do not explicate the full range of benefits or ways they can manifest in different organizations. Methods: To develop such a framework, a working group with representatives from six Clinical and Translational Science Award (CTSA) hubs reviewed existing literature on LHS characteristics, models, and goals; solicited expert input; and applied the framework to their local LHS experiences. Results: The Framework of LHS Benefits includes six categories of benefits (quality, safety, equity, patient satisfaction, reputation, and value) relevant for a range of stakeholders and defines key concepts within each benefit. Applying the framework to five LHS case examples indicated preliminary face validity across varied LHS approaches and revealed three dimensions in which the framework is relevant: defining goals of individual LHS projects, facilitating collaboration based on shared values, and establishing guiding tenets of an LHS program or mission. Conclusion: The framework can be used to communicate the value of an LHS to different stakeholders across varied contexts and purposes, and to identify future organizational priorities. Further validation will contribute to the framework's evolution and support its potential to inform the development of tools to evaluate LHS impact.

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BACKGROUND: A significant health challenge is evident in the United States, with 6 in 10 adults having a chronic disease and 4 in 10 adults having 2 or more. Chronic disease self-management aims to prevent or delay disease progression and disability and reduce mortality risk. The evidence to support the use of information technology tools, including mobile apps, web-based portals, and web-based educational interventions, that support disease self-management and improve clinical outcomes is growing. Customer discovery and value proposition design methodology is a form of stakeholder engagement and is based on marketing and lean start-up business methods. As applied in health care, customer discovery and value proposition methodology can be used to understand the clinical problem and articulate the product's hypothesized unique value proposition relative to alternative options that are available to end users. OBJECTIVE: This study aims to describe the experience and findings of academic researchers applying the customer discovery and value proposition methodology to identify stakeholders, needs, adaptability, and sustainability of a chronic disease self-management mobile app (CDapp). The motivation of the work is to make mobile health app interventions accessible and acceptable for all segments of patients' chronic diseases. METHODS: Data were obtained through key informant interviews and analyzed using rapid qualitative analysis techniques. The value proposition framework was used to build the interview guide. The aim was to identify the needs, challenges (pains), and potential benefits (gains) of the CDapp for our stakeholders. RESULTS: Our results showed that the primary consumers (end users) of a CDapp were the patients. The app adopters (decision makers) can be medical center leaders including population health department managers or insurance providers, while the consumer adoption influencers (influencers or saboteurs) are clinicians and patient caregivers. We developed an ecosystem map to visualize the clinical practice workflow and how an app for chronic disease management might integrate within an academic health care center or system. A value proposition for the identified customer segments was generated. Each stakeholder segment was working within a different framework to improve patient self-management. Patients needed help to adhere to self-care activities and they needed tailored health education. Health care leaders aim to improve the quality of care while reducing costs and workload. Clinicians wanted to improve patient education and care while reducing the time burden. Our results also showed that within academic medical centers, there were variations regarding patients' self-reported abilities to manage their diseases. CONCLUSIONS: Customer discovery is a useful form of stakeholder engagement when designing studies that seek to implement, adapt, and sustain an intervention. The customer discovery and value proposition methodology can be used as an alternative or complementary approach to formative research to generate valuable information in a brief period.

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A low-cost quantitative structured office measurement of movements in the extremities of people with Parkinson's disease [1,2] was performed on participants with Parkinson's disease and multiple system atrophy as well as age- and sex-matched healthy participants with typical development. Participants underwent twelve videotaped procedures rated by a trained examiner while connected to four accelerometers [1,2] generating a trace of the three location dimensions expressed as spreadsheets [3,4]. The signals of the five repetitive motion items (3.4 Finger tapping, 3.5 Hand movements, 3.6 Pronation-supination movements of hands, 3.7 Toe tapping, and 3.8 Leg agility) [1] underwent processing to fast Fourier [5] and amor and bump continuous wavelet transforms [6], [7], [8], [9], [10], [11], [12], [13]. Images of the signals and their transforms [4], [5], [6] of the five repetitive tasks of each participant were randomly expressed as panels on an electronic framework for rating by 35 trained examiners who did not know the source of the original output [14]. The team of international raters completed ratings of the signals and their transforms independently using criteria like the scoring systems for live assessments of movements in human participants [1,2]. The raters scored signals and transforms for deficits in the sustained performance of rhythmic movements (interruptions, slowing, and amplitude decrements) often observed in people with Parkinson's disease [15], [16], [17], [18], [19], [20]. Raters were first presented the images of the signals and transforms of a man with multiple system atrophy as a test and a retest in a different random order. After the raters completed the assessments of the man with multiple system atrophy, they were presented random test and retest panels of the images of signals and transforms of ten participants with Parkinson's disease who completed a single rating session. After the raters completed the assessments of the participants with Parkinson's disease who completed one set of ratings, they were presented random test and retest panels of the images of signals and transforms of (A) ten participants with Parkinson's disease and (B) eight age- and sex-match healthy participants with typical development who completed two rating session separated by a month or more [15], [16], [17], [18], [19], [20]. The data provide a framework for further analysis of the acquired information. Additionally, the data provide a template for the construction of electronic frameworks for the remote analysis by trained raters of signals and transforms of rhythmic processes to verify that the systems are operating smoothly without interruptions or changes in frequency and amplitude. Thus, the data provide the foundations to construct electronic frameworks for the virtual quality assurance of a vast spectrum of rhythmic processes. The dataset is a suitable template for solving unsupervised and supervised machine learning algorithms. Readers may utilize this procedure to assure the quality of rhythmic processes by confirming the absence of deviations in rate and rhythm. Thus, this procedure provides the means to confirm the quality of the vast spectrum of rhythmic processes.

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PURPOSE: The number of FDA-cleared artificial intelligence (AI) algorithms for neuroimaging has grown in the past decade. The adoption of these algorithms into clinical practice depends largely on whether this technology provides value in the clinical setting. The objective of this study was to analyze trends in FDA-cleared AI algorithms for neuroimaging and understand their value proposition as advertised by the AI developers and vendors. METHODS: A list of AI algorithms cleared by the FDA for neuroimaging between May 2008 and August 2022 was extracted from the ACR Data Science Institute AI Central database. Product information for each device was collected from the database. For each device, information on the advertised value as presented on the developer's website was collected. RESULTS: A total of 59 AI neuroimaging algorithms were cleared by the FDA between May 2008 and August 2022. Most of these algorithms (24 of 59) were compatible with noncontrast CT, 21 with MRI, 9 with CT perfusion, 8 with CT angiography, 3 with MR perfusion, and 2 with PET. Six algorithms were compatible with multiple imaging techniques. Of the 59 algorithms, websites were located that discussed the product value for 55 algorithms. The most widely advertised value proposition was improved quality of care (38 of 55 [69.1%]). A total of 24 algorithms (43.6%) proposed saving user time, 9 (15.7%) advertised decreased costs, and 6 (10.9%) described increased revenue. Product websites for 26 algorithms (43.6%) showed user testimonials advertising the value of the technology. CONCLUSIONS: The results of this study indicate a wide range of value propositions advertised by developers and vendors of AI algorithms for neuroimaging. Most vendors advertised that their products would improve patient care. Further research is necessary to determine whether the value claimed by developers is actually demonstrated in clinical practice.

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In the current volatile business environment, companies are obliged to search for new ways of doing business to remain competitive. Accordingly, firms innovate their business model as it became a promising strategy to achieve sustainable outcomes. However, there is still a need for empirical studies that examine the relationship between business model innovation (BMI) and the performance of small and medium-sized enterprises (SMEs). In this study, we aimed to investigate this relationship by collecting data from 264 manufacturing SMEs through structured questionnaires. We employed partial least square structural equation modeling (PLS-SEM) to analyze the collected data and test the hypotheses. The results indicated that changes in any component of the business model, namely value creation, value proposition, or value capture, had a positive and significant relationship with the performance of manufacturing SMEs. Therefore, by innovating their business models, firms can create more value for their customers while capturing value for themselves. In conclusion, increasing use value or decreasing exchange value with customers will help firms create more value and surpass competitors in the marketplace, while also allowing them to capture more value for themselves.

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This Review initiates a wide-ranging discussion over 2023 by selecting and exploring core themes to be investigated more deeply in papers submitted to the Vaccines Special Issue on the "Future of Epidemic and Pandemic Vaccines to Serve Global Public Health Needs". To tackle the SARS-CoV-2 pandemic, an acceleration of vaccine development across different technology platforms resulted in the emergency use authorization of multiple vaccines in less than a year. Despite this record speed, many limitations surfaced including unequal access to products and technologies, regulatory hurdles, restrictions on the flow of intellectual property needed to develop and manufacture vaccines, clinical trials challenges, development of vaccines that did not curtail or prevent transmission, unsustainable strategies for dealing with variants, and the distorted allocation of funding to favour dominant companies in affluent countries. Key to future epidemic and pandemic responses will be sustainable, global-public-health-driven vaccine development and manufacturing based on equitable access to platform technologies, decentralised and localised innovation, and multiple developers and manufacturers, especially in low- and middle-income countries (LMICs). There is talk of flexible, modular pandemic preparedness, of technology access pools based on non-exclusive global licensing agreements in exchange for fair compensation, of WHO-supported vaccine technology transfer hubs and spokes, and of the creation of vaccine prototypes ready for phase I/II trials, etc. However, all these concepts face extraordinary challenges shaped by current commercial incentives, the unwillingness of pharmaceutical companies and governments to share intellectual property and know-how, the precariousness of building capacity based solely on COVID-19 vaccines, the focus on large-scale manufacturing capacity rather than small-scale rapid-response innovation to stop outbreaks when and where they occur, and the inability of many resource-limited countries to afford next-generation vaccines for their national vaccine programmes. Once the current high subsidies are gone and interest has waned, sustaining vaccine innovation and manufacturing capability in interpandemic periods will require equitable access to vaccine innovation and manufacturing capabilities in all regions of the world based on many vaccines, not just "pandemic vaccines". Public and philanthropic investments will need to leverage enforceable commitments to share vaccines and critical technology so that countries everywhere can establish and scale up vaccine development and manufacturing capability. This will only happen if we question all prior assumptions and learn the lessons offered by the current pandemic. We invite submissions to the special issue, which we hope will help guide the world towards a global vaccine research, development, and manufacturing ecosystem that better balances and integrates scientific, clinical trial, regulatory, and commercial interests and puts global public health needs first.

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The primary purpose of companies is to create value. Companies use competitive analysis to develop their value proposition. Performing this analysis manually is a time-consuming task. Automating the process of identifying and expanding value proposition, as well as categorizing it, would bring benefits for industries. This paper aims to summarize and systematize the results of previous research on a mechanism for automatically identifying companies' value proposition. This is a novel task and with this work the author hopes to show feasibility and set a baseline. To narrow down the task, air transportation domain was selected. The goal of the research was to obtain insights and systemize values; to achieve it, the author utilized a bottom-up data-driven approach. The first step was to create a corpus of values. 96 respondents conducted a survey with open-end questions; 796 start-ups were identified and 96 annotators labelled start-ups' landing pages by annotating values. The next step was structuring data for a deeper understanding of values by examining annotations and organizing values into taxonomies. The practical use of the results includes machine learning training material for automation of value-related tasks.

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OBJECTIVES: How do providers of artificial intelligence (AI) solutions propose and legitimize the values of their solutions for supporting diagnostic radiology workflow? METHODS: We systematically analyze 393 AI applications developed for supporting diagnostic radiology workflow. We collected qualitative and quantitative data by analyzing around 1250 pages of documents retrieved from companies' websites and legal documents. Five investigators read and interpreted collected data, extracted the features and functionalities of the AI applications, and finally entered them into an excel file for identifying the patterns. RESULTS: Over the last 2 years, we see an increase in the number of AI applications (43%) and number of companies offering them (34%), as well as their average age (45%). Companies claim various value propositions related to increasing the "efficiency" of radiology work (18%)-e.g., via reducing the time and cost of performing tasks and reducing the work pressure-and "quality" of offering medical services (31%)-e.g., via enhancing the quality of clinical decisions and enhancing the quality of patient care, or both of them (28%). To legitimize and support their value propositions, the companies use multiple strategies simultaneously, particularly by seeking legal approvals (72%), promoting their partnership with medical and academic institutions (75%), highlighting the expertise of their teams (56%), and showcasing examples of implementing their solutions in practice (53%). CONCLUSIONS: Although providers of AI applications claim a wide range of value propositions, they often provide limited evidence to show how their solutions deliver such systematic values in clinical practice. KEY POINTS: • AI applications in radiology continue to grow in number and diversity. • Companies offering AI applications claim various value propositions and use multiple ways to legitimize these propositions. • Systematic scientific evidence showing the actual effectiveness of AI applications in clinical context is limited.

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BACKGROUND: There is a growing interest to support extended independent living of people with dementia (PwD) via unobtrusive monitoring (UM) technologies which allow caregivers to remotely monitor lifestyle, health, and safety of PwD. However, these solutions will only be viable if developers obtain a clear picture of how to create value for all relevant stakeholders involved and achieve successful implementation. The aim of this study was therefore to explore the value proposition of UM technology in home-based dementia care and preconditions for successful implementation from a multi-stakeholder perspective. METHODS: We conducted an expert-informed survey among potential stakeholders (n = 25) to identify key stakeholders for UM technology in home-based dementia care. Subsequently, focus groups and semi-structured interviews were conducted among 5 key stakeholder groups (n = 24) including informal caregivers (n = 5), home care professionals (n = 5), PwD (n = 4), directors and managers within home care (n = 4), and policy advisors within the aged care and health insurance sector (n = 6). The sessions addressed the value proposition- and business model canvas and were analyzed using thematic analysis. RESULTS: Stakeholders agreed that UM technology should provide gains such as objective surveillance, timely interventions, and prevention of unnecessary control visits, whereas pains mainly included information overload, unplannable care due to real-time monitoring, and less human interaction. The overall design-oriented need referred to clear situation classifications including urgent care (fall- and wandering detection), non-urgent care (deviations in eating, drinking, sleeping), and future care (risk predictions). Most important preconditions for successful implementation of UM technology included inter-organizational collaboration, a shared vision on re-shaping existing care processes, integrated care ICT infrastructures, clear eligibility criteria for end-users, and flexible care reimbursement systems. CONCLUSIONS: Our findings can guide the value-driven development and implementation of UM technology for home-based dementia care. Stakeholder values were mostly aligned, although stakeholders all had their own perspective on what UM technology should accomplish. Besides, our study highlights the complexity of implementing novel UM technology in home-based dementia care. To achieve successful implementation, organizational and financial preconditions, as well as digital data exchange between home care organizations, will be important.

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The purpose of this paper is to create and test an idea management sequence framework to reinvent or redefine the value proposition. Idea management with sequencing activities must be considered as a systematic managerial process and should not be confused with the occasional result of an individual with a design thinking mindset. This paper suggests a new approach-a systematic, 4-step idea management sequence to redefine or reinvent value proposition in a business model, which was validated through an action-based research method involving 20 managers from practice by applying the proposed framework. Based on the idea management approach, authors describe the idea generation and evaluation processes and their possible moderation elements. This research contributes to previous studies of the design thinking and innovation by substantiating a concept of the idea management sequencing and proposing a new 4-step approach that can be applied by organisations to redefine or reinvent value proposition in their business models. Being influenced by pandemic restrictions and the full or partial remote workforce, the 4-step idea management approach is beneficial for virtual group sessions as it increases the quality of outcomes, engagement of individuals, collaborative openness, and confidence.

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Background: The target product profile (TPP) outlines the desired profile of a target product aimed at a particular disease and is used by companies to plan clinical development. Considering the increasing importance of health technology assessment (HTA) in informing reimbursement decisions, a robust TPP needs to be built to address HTA needs, to guide an integrated evidence generation plan that will support HTA submissions. This study assessed current practices and experiences of companies in building HTA considerations into TPP development. Methods: An opinion survey was designed and conducted in 2019, as a cross-sectional questionnaire consisting of multiple-choice questions. The questionnaire provided a qualitative assessment of companies' strategies and experiences in building HTA considerations into the TPP. Eligible survey participants were the senior management of Global HTA/Market Access Departments at 18 top international pharmaceutical companies. Results: 11 companies responded to the survey. All companies included HTA requirements in TPP development, but the timing and process varied. The key focus of HTA input related to health problems and treatment pathways, clinical efficacy/effectiveness, and safety. Variance of HTA methods and different value frameworks were identified as a challenge for development plans. Stakeholder engagement, such as HTA scientific advice, was used to pressure test the TPP. Conclusion: This research provides insight into current practice and potential opportunities for value-based drug development. It demonstrates the evolution of the TPP to encompass HTA requirements and suggests that the TPP could have a role as an iterative communication tool for use with HTA agencies to enhance an integrated evidence generation plan.

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Routine infant immunization with live, oral rotavirus vaccines (LORVs) has had a major impact on severe gastroenteritis disease. Nevertheless, in high morbidity and mortality settings rotavirus remains an important cause of disease, partly attributable to the sub-optimal clinical efficacy of LORVs in those settings. Regardless of the precise immunological mechanism(s) underlying the diminished efficacy, the introduction of injectable next-generation rotavirus vaccines (iNGRV), currently in clinical development, could offer a potent remedy. In addition to the potential for greater clinical efficacy, precisely how iNGRVs are delivered (multiple doses to young infants; alongside LORVs or as a booster; co-formulated with Diphtheria-Tetanus-Pertussis (DTP)-containing vaccines), their pricing, and their storage and cold chain characteristics could each have major implications on the resultant health outcomes, on cost-effectiveness as well as on product preferences by national stakeholders and healthcare providers. To better understand these implications, we critically assessed whether there is a compelling public health value proposition for iNGRVs based on potential (but still hypothetical) vaccine profiles. Our results suggest that the answer is highly dependent on the specific use cases and potential attributes of such novel vaccines. Notably, co-formulation of iNGRVs with similar or greater efficacy than LORVs with a DTP-containing vaccine, such as DTP-Hib-HepB, scored especially high on potential impact, cost-effectiveness, and strength of preference by national stakeholders and health care providers in lower and middle income countries.

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The development and licensure of a safe and highly efficacious Shigella vaccine has been a priority in international public health circles for decades and would represent a great scientific achievement. Nonetheless, in the context of increasingly crowded and costly childhood immunization programs, and with a myriad of other new and improved vaccines currently or soon on the market, there is no guarantee that even a highly effective Shigella vaccine would become a priority for adoption and introduction by the low- and middle-income countries that could benefit from it the most. We discuss here some of the major determinants and questions regarding the introduction of Shigella vaccines and the importance of developing a succinct, compelling public health value proposition.

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It is widely accepted that somewhere in the region of 90-95% of startups fail. It is often suggested that the majority of unsuccessful startups either failed to identify a viable idea, or they failed to execute the idea effectively enough to get to market before running out of cash. Two approaches stand out as being particularly well-suited to addressing these problems: Design Thinking and Lean Startup, respectively. This paper presents the Concepturealize™ methodology that cross-applies Design Thinking and Lean Startup as a single iterative process and that enables the entrepreneur to generate real-needs-focussed, user-centred, lean business models. Existing literature reveals a need for further exploration of cross-application of Design Thinking and Lean Startup (and other related methodologies) in the areas of business model development and innovation. This work answers the research question by review of prior attempts to combine Design Thinking and Lean Startup and presenting the Concepturealize™ model that cross-applies Design Thinking and Lean Startup in a single iterative methodology and that enables the practitioner to generate real-needs-focussed, user-centred, lean business models. By following this new process model correctly, a practitioner will be guided to uncover a viable way to create value, develop a deep understanding of the value proposition, the target customers and how to reach and serve them, together with the expected revenue and costs, all needed to properly formulate the business model. Finally, the practitioner may use the Concepturealize™ model to retest the problem-solution fit and understand how the customers perception of value has altered, each time a new product or new features are launched, looking to continually add value at each cycle. Whilst prior research has explored how organisations may make use of both DT and LS, it has failed to demonstrate how they may be used in parallel, throughout the entire business model development process, instead it demonstrates examples of insight into where to transition from one model to the other. This work progresses the state of the art by following Design Science guidelines to present how the true, in-parallel, cross-application of DT and LS, in the context of business model development, is possible.

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Companies need reliable employees to support their business. As e-grocery businesses in Indonesia continue to grow during the pandemic, various strategies are required to attract millennials. This study aims to prove the influence of employer branding, e-recruitment, and post-pandemic employee value proposition (radical flexibility, deeper connection, personal growth, and holistic well-being) in encouraging millennials to apply for jobs at e-grocery companies after the pandemic. Few e-grocery companies in Indonesia use employer branding and e-recruitment; this study attempts to combine these two variables to see the effect of their interaction on influencing greater millennial intentions. Using the latest experimental method, which is the experimental vignette method, we conducted three studies with a total of 619 millennial participants, who were recruited using the convenience sampling technique. All participants received a set of job advertisements as a stimulus. The results showed that e-recruitment could not significantly predict the millennials' intentions when applying for jobs in e-grocery companies. Companies in Indonesia may need to analyze millennials' familiarity with e-recruitment platforms, especially on company websites. However, employer branding successfully predicted millennials' intention to apply for a job in e-grocery companies, which was not affected by the length of their work experience. Employer branding serves as a means of building job seekers' trust through personal promotions. With this trust, job seekers are more motivated to apply to the company. When e-recruitment and employer branding were analyzed simultaneously, there were significant interactive effects on millennials' intentions. Employer branding acted as a socialization medium to introduce e-recruitment and vice versa. E-recruitment served as a form of branding that could shape the perceptions and experiences of millennial job seekers. Lastly, the employee value proposition significantly predicted millennials' intentions, where holistic well-being was the most sought-after value. It can support employees' well-being and encourage them to make valuable propositions that will make e-grocery companies excel in Indonesian labor market.

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BACKGROUND: Currently available live, oral rotavirus vaccines (LORVs) have significantly reduced severe rotavirus hospitalizations and deaths worldwide. However, LORVs are not as effective in low- and middle-income countries (LMIC) where rotavirus disease burden is highest. Next-generation rotavirus vaccine (NGRV) candidates in development may have a greater public health impact where they are needed most. The feasibility and acceptability of possible new rotavirus vaccines were explored as part of a larger public health value proposition for injectable NGRVs in LMICs. OBJECTIVE: To assess national stakeholder preferences for currently available LORVs and hypothetical NGRVs and understand rationales and drivers for stated preferences. METHODS: Interviews were conducted with 71 national stakeholders who influence vaccine policy and national programming. Stakeholders from Ghana, Kenya, Malawi, Peru, Senegal, and Sri Lanka were interviewed using a mixed-method guide. Vaccine preferences were elicited on seven vaccine comparisons involving LORVs and hypothetical NGRVs based on information presented comparing the vaccines' attributes. Reasons for vaccine preference were elicited in open-ended questions, and the qualitative data were analyzed on key preference drivers. RESULTS: Nearly half of the national stakeholders interviewed preferred a highly effective standalone, injectable NGRV over current LORVs. When presented as having similar efficacy to the LORV, however, very few stakeholders preferred the injectable NGRV, even at substantially lower cost. Similarly, a highly effective standalone injectable NGRV was generally not favored over an equally effective oral NGRV following a neonatal-infant schedule, despite higher cost of the neonatal option. An NGRV-DTP-containing combination vaccine was strongly preferred over all other options, whether delivered alone with efficacy similar to current LORVs or co-administered alongside an LORV (LORV + NGRV-DTP) to increase efficacy. CONCLUSION: Results from these national stakeholder interviews provide valuable insights to inform ongoing and future NGRV research and development.

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This chapter addresses the grand challenge of an aging society and the subsequent growing demand for in-home care for the elderly - often referred to as homecare. It examines how emergent homecare models in England differ from the "time and task" model and how they are shaping the care market. These models offer new approaches regarding what, how, and when care is delivered at home. Homecare providers face rising demand driven not only by population aging but also by market demand for personalized care, choice, continuity of care, and real-time availability. The landscape presents an opportunity for innovative models to become established, by offering a more inducing service design and value propositions that respond to customers' needs. Using the "business model canvas" to guide data collection, this study presents an ethnographic case analysis of four homecare organizations with distinct emergent homecare models. The study includes 14 months of field observation and 33 in-depth interviews. It finds that providers are becoming increasingly aware of evolving customer needs, establishing models such as the "uberization," "community-based," "live-in," and "preventative" described in the chapter. These models are becoming more pervasive and are mostly market-driven; however, some of their innovations are market shaping. The major innovations are in their value propositions, partnership arrangements, and customer segments. Their value propositions focus on well-being outcomes, including choice and personalization for care users; their workforces are perceived to be a major stakeholder segment, and their networks of partners offer access to complementary services, investments, and specialist knowledge.

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BACKGROUND: Medicines that are based on known molecules and are further developed to address healthcare needs and deliver relevant improvement for patients, healthcare professionals and/or payers are called value-added medicines (VAMs). The evaluation process of VAMs is heterogeneous across countries, and it has been primarily designed for originator pharmaceuticals with confirmatory evidence collected alongside pivotal clinical trials. There is a mismatch between evidence requirements by public decision-makers and evidence generated by manufacturers of VAMs. Our objective was to develop a core evaluation framework for VAMs. METHODS: Potential benefits offered by VAMs were collected through a systematic literature review and allocated to separate domains in an iterative process. The draft list of domains and their applicability were validated during two consecutive virtual workshops by health policy experts representing countries with different economic statuses, geographical and decision-making contexts. RESULTS: Based on 158 extracted studies, the final consensus on the evaluation framework resulted in 11 value domains in 5 main clusters, including unmet medical needs, health gain (measured by health care professionals), patient-reported outcomes, burden on households, and burden on the health care system. CONCLUSIONS: The proposed framework could reduce the heterogeneity in value assessment processes across countries and create incentives for manufacturers to invest in incremental innovation. However, some domains may not be equally relevant or accepted in all countries, therefore the core framework needs thorough adaptation in specific jurisdictions.

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Across so many industries, non-destructive evaluation has proven its worth time and again through quality and safety assurance of valuable assets. Yet, over time, it became underappreciated in business decisions. In most cases, the data gathered by NDT is used for quality assurance assessments resulting in binary decisions. And we seem to miss out on value of the information content of NDE which goes way deeper and can help other stakeholders: such as engineering, management, inspectors, service providers, and even regulators. Some of those groups might not even be aware of the benefits of NDE data and its digitalization. Unfortunately, the NDE industry typically makes the data access unnecessarily difficult by proprietary interfaces and data formats. Both those challenges need to be addressed now by the NDE industry. The confluence of NDE and Industry 4.0, dubbed as NDE 4.0, provides a unique opportunity for the NDE/NDT Industry to not only readjust the value perception but to gain new customer groups through a broad set of value creation activities across the ecosystem. The integration of NDE into the Cyber-Physical Loop (including IIoT and Digital Twin) is the chance for the NDE industry to now shift the perception from a cost center to a value center. This paper provides an overview of the NDE ecosystem, key value streams, cyber-physical loops that create value, and a number of use cases for various stakeholders in the ecosystem.