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V. Pannunzio
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13 records found
1
Review
(2025)
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F.K. Bodell, Valeria Pannunzio, Julian Houwen, Guillaume Lame, Dirk Snelders, Maaike Kleinsmann
Implementing changes to digital health systems in real-life contexts poses many challenges. Design as a field has the potential to tackle some of these. This article illustrates how design knowledge, through published literature, is currently referenced in relation to the implementation of digital health. To map design literature’s contribution to this field, we conducted a scoping review on digital health implementation publications and their use of references from nine prominent design journals. The search in Scopus and Web of Science yielded 382 digital health implementation publications, of which 70 were included for analysis. From those, we extracted data on publication characteristics and how they cited the design literature. The 70 publications cited 58 design articles, whose characteristics were also extracted. The results show that design is mainly cited to provide information about specific design methods and approaches, guidelines for using them and evidence of their benefits. Examples of referenced methods and approaches were co-design, prototyping, human-centered design, service design, understanding user needs and design thinking. The results thus show that design knowledge primarily contributed to digital health implementation with insights into methods and approaches. In addition, our method showcases a new way for understanding how design literature influences other fields.
...
Implementing changes to digital health systems in real-life contexts poses many challenges. Design as a field has the potential to tackle some of these. This article illustrates how design knowledge, through published literature, is currently referenced in relation to the implementation of digital health. To map design literature’s contribution to this field, we conducted a scoping review on digital health implementation publications and their use of references from nine prominent design journals. The search in Scopus and Web of Science yielded 382 digital health implementation publications, of which 70 were included for analysis. From those, we extracted data on publication characteristics and how they cited the design literature. The 70 publications cited 58 design articles, whose characteristics were also extracted. The results show that design is mainly cited to provide information about specific design methods and approaches, guidelines for using them and evidence of their benefits. Examples of referenced methods and approaches were co-design, prototyping, human-centered design, service design, understanding user needs and design thinking. The results thus show that design knowledge primarily contributed to digital health implementation with insights into methods and approaches. In addition, our method showcases a new way for understanding how design literature influences other fields.
Journal article
(2024)
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Valeria Pannunzio, Alexander Komashie, Richard Milne, Sebastian Walsh, Timoleon Kipouros, Guillaume Lame, Anja Maier, Carol Brayne, P.J. Clarkson
This contribution departs from an existing model, the Design Framework for Systems-of-Systems Resilience, to explore systems resilience issues across the health, environmental, and economic domains. The reported research activities include 1) a rapid review to collect a set of systems indicators and 2) a design workshop employing causal loop diagramming to map expected causal influences between indicators. Through this exercise, we examine key themes in this research domain and outline directions for further enquiry, while involving members of the design research community in an open dialogue.
...
This contribution departs from an existing model, the Design Framework for Systems-of-Systems Resilience, to explore systems resilience issues across the health, environmental, and economic domains. The reported research activities include 1) a rapid review to collect a set of systems indicators and 2) a design workshop employing causal loop diagramming to map expected causal influences between indicators. Through this exercise, we examine key themes in this research domain and outline directions for further enquiry, while involving members of the design research community in an open dialogue.
Designing remote patient and family centred interventions
an exploratory approach
Journal article
(2024)
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Julian Houwen, Ragini S. Karki, Veronica R. Janssen, Valeria Pannunzio, Douwe E. Atsma, Maaike S. Kleinsmann
This research explores the dynamic nature of family involvement in remote patient management for cardiovascular disease and its impact on lifestyle behaviour changes. Through an interview study with patients and family members, we categorise family involvement into three types: Inform, Integrate, and Influence, highlighting the dynamic and heterogeneous nature of family involvement across different phases and activities. Overall, we emphasise the need for personalised and adaptable interventions to cater to the diversity of families and propose a modular approach to remote monitoring design.
...
This research explores the dynamic nature of family involvement in remote patient management for cardiovascular disease and its impact on lifestyle behaviour changes. Through an interview study with patients and family members, we categorise family involvement into three types: Inform, Integrate, and Influence, highlighting the dynamic and heterogeneous nature of family involvement across different phases and activities. Overall, we emphasise the need for personalised and adaptable interventions to cater to the diversity of families and propose a modular approach to remote monitoring design.
Journal article
(2024)
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Frederik K. Karlsson, Valeria Pannunzio, Dirk Snelders, Maaike S. Kleinsmann
Challenges in implementing digital health in clinical practice hinder its potential. The complexities posed by implementation could benefit from using design practices. To explore the current role of design practices in digital health implementation, designers in the Netherlands were interviewed. The preliminary results indicate that designers contribute to digital health implementation processes, especially in the early stages. Design practices are mainly used for engaging the users, testing concepts, aligning the ideas of stakeholders, and adapting interventions to fit within the contexts.
...
Challenges in implementing digital health in clinical practice hinder its potential. The complexities posed by implementation could benefit from using design practices. To explore the current role of design practices in digital health implementation, designers in the Netherlands were interviewed. The preliminary results indicate that designers contribute to digital health implementation processes, especially in the early stages. Design practices are mainly used for engaging the users, testing concepts, aligning the ideas of stakeholders, and adapting interventions to fit within the contexts.
Journal article
(2024)
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Valeria Pannunzio, Hosana Morales Ornelas, Pema Gurung, Robert van Kooten, Dirk Snelders, Hendrikus van Os, Michel Wouters, Rob Tollenaar, Douwe Atsma, Maaike Kleinsmann
Background:
Patient and staff experience is a vital factor to consider in the evaluation of remote patient monitoring (RPM) interventions. However, no comprehensive overview of available RPM patient and staff experience–measuring methods and tools exists.
Objective:
This review aimed at obtaining a comprehensive set of experience constructs and corresponding measuring instruments used in contemporary RPM research and at proposing an initial set of guidelines for improving methodological standardization in this domain.
Methods:
Full-text papers reporting on instances of patient or staff experience measuring in RPM interventions, written in English, and published after January 1, 2011, were considered for eligibility. By “RPM interventions,” we referred to interventions including sensor-based patient monitoring used for clinical decision-making; papers reporting on other kinds of interventions were therefore excluded. Papers describing primary care interventions, involving participants under 18 years of age, or focusing on attitudes or technologies rather than specific interventions were also excluded. We searched 2 electronic databases, Medline (PubMed) and EMBASE, on February 12, 2021.We explored and structured the obtained corpus of data through correspondence analysis, a multivariate statistical technique.
Results:
In total, 158 papers were included, covering RPM interventions in a variety of domains. From these studies, we reported 546 experience-measuring instances in RPM, covering the use of 160 unique experience-measuring instruments to measure 120 unique experience constructs. We found that the research landscape has seen a sizeable growth in the past decade, that it is affected by a relative lack of focus on the experience of staff, and that the overall corpus of collected experience measures can be organized in 4 main categories (service system related, care related, usage and adherence related, and health outcome related). In the light of the collected findings, we provided a set of 6 actionable recommendations to RPM patient and staff experience evaluators, in terms of both what to measure and how to measure it. Overall, we suggested that RPM researchers and practitioners include experience measuring as part of integrated, interdisciplinary data strategies for continuous RPM evaluation.
Conclusions:
At present, there is a lack of consensus and standardization in the methods used to measure patient and staff experience in RPM, leading to a critical knowledge gap in our understanding of the impact of RPM interventions. This review offers targeted support for RPM experience evaluators by providing a structured, comprehensive overview of contemporary patient and staff experience measures and a set of practical guidelines for improving research quality and standardization in this domain. ...
Patient and staff experience is a vital factor to consider in the evaluation of remote patient monitoring (RPM) interventions. However, no comprehensive overview of available RPM patient and staff experience–measuring methods and tools exists.
Objective:
This review aimed at obtaining a comprehensive set of experience constructs and corresponding measuring instruments used in contemporary RPM research and at proposing an initial set of guidelines for improving methodological standardization in this domain.
Methods:
Full-text papers reporting on instances of patient or staff experience measuring in RPM interventions, written in English, and published after January 1, 2011, were considered for eligibility. By “RPM interventions,” we referred to interventions including sensor-based patient monitoring used for clinical decision-making; papers reporting on other kinds of interventions were therefore excluded. Papers describing primary care interventions, involving participants under 18 years of age, or focusing on attitudes or technologies rather than specific interventions were also excluded. We searched 2 electronic databases, Medline (PubMed) and EMBASE, on February 12, 2021.We explored and structured the obtained corpus of data through correspondence analysis, a multivariate statistical technique.
Results:
In total, 158 papers were included, covering RPM interventions in a variety of domains. From these studies, we reported 546 experience-measuring instances in RPM, covering the use of 160 unique experience-measuring instruments to measure 120 unique experience constructs. We found that the research landscape has seen a sizeable growth in the past decade, that it is affected by a relative lack of focus on the experience of staff, and that the overall corpus of collected experience measures can be organized in 4 main categories (service system related, care related, usage and adherence related, and health outcome related). In the light of the collected findings, we provided a set of 6 actionable recommendations to RPM patient and staff experience evaluators, in terms of both what to measure and how to measure it. Overall, we suggested that RPM researchers and practitioners include experience measuring as part of integrated, interdisciplinary data strategies for continuous RPM evaluation.
Conclusions:
At present, there is a lack of consensus and standardization in the methods used to measure patient and staff experience in RPM, leading to a critical knowledge gap in our understanding of the impact of RPM interventions. This review offers targeted support for RPM experience evaluators by providing a structured, comprehensive overview of contemporary patient and staff experience measures and a set of practical guidelines for improving research quality and standardization in this domain. ...
Background:
Patient and staff experience is a vital factor to consider in the evaluation of remote patient monitoring (RPM) interventions. However, no comprehensive overview of available RPM patient and staff experience–measuring methods and tools exists.
Objective:
This review aimed at obtaining a comprehensive set of experience constructs and corresponding measuring instruments used in contemporary RPM research and at proposing an initial set of guidelines for improving methodological standardization in this domain.
Methods:
Full-text papers reporting on instances of patient or staff experience measuring in RPM interventions, written in English, and published after January 1, 2011, were considered for eligibility. By “RPM interventions,” we referred to interventions including sensor-based patient monitoring used for clinical decision-making; papers reporting on other kinds of interventions were therefore excluded. Papers describing primary care interventions, involving participants under 18 years of age, or focusing on attitudes or technologies rather than specific interventions were also excluded. We searched 2 electronic databases, Medline (PubMed) and EMBASE, on February 12, 2021.We explored and structured the obtained corpus of data through correspondence analysis, a multivariate statistical technique.
Results:
In total, 158 papers were included, covering RPM interventions in a variety of domains. From these studies, we reported 546 experience-measuring instances in RPM, covering the use of 160 unique experience-measuring instruments to measure 120 unique experience constructs. We found that the research landscape has seen a sizeable growth in the past decade, that it is affected by a relative lack of focus on the experience of staff, and that the overall corpus of collected experience measures can be organized in 4 main categories (service system related, care related, usage and adherence related, and health outcome related). In the light of the collected findings, we provided a set of 6 actionable recommendations to RPM patient and staff experience evaluators, in terms of both what to measure and how to measure it. Overall, we suggested that RPM researchers and practitioners include experience measuring as part of integrated, interdisciplinary data strategies for continuous RPM evaluation.
Conclusions:
At present, there is a lack of consensus and standardization in the methods used to measure patient and staff experience in RPM, leading to a critical knowledge gap in our understanding of the impact of RPM interventions. This review offers targeted support for RPM experience evaluators by providing a structured, comprehensive overview of contemporary patient and staff experience measures and a set of practical guidelines for improving research quality and standardization in this domain.
Patient and staff experience is a vital factor to consider in the evaluation of remote patient monitoring (RPM) interventions. However, no comprehensive overview of available RPM patient and staff experience–measuring methods and tools exists.
Objective:
This review aimed at obtaining a comprehensive set of experience constructs and corresponding measuring instruments used in contemporary RPM research and at proposing an initial set of guidelines for improving methodological standardization in this domain.
Methods:
Full-text papers reporting on instances of patient or staff experience measuring in RPM interventions, written in English, and published after January 1, 2011, were considered for eligibility. By “RPM interventions,” we referred to interventions including sensor-based patient monitoring used for clinical decision-making; papers reporting on other kinds of interventions were therefore excluded. Papers describing primary care interventions, involving participants under 18 years of age, or focusing on attitudes or technologies rather than specific interventions were also excluded. We searched 2 electronic databases, Medline (PubMed) and EMBASE, on February 12, 2021.We explored and structured the obtained corpus of data through correspondence analysis, a multivariate statistical technique.
Results:
In total, 158 papers were included, covering RPM interventions in a variety of domains. From these studies, we reported 546 experience-measuring instances in RPM, covering the use of 160 unique experience-measuring instruments to measure 120 unique experience constructs. We found that the research landscape has seen a sizeable growth in the past decade, that it is affected by a relative lack of focus on the experience of staff, and that the overall corpus of collected experience measures can be organized in 4 main categories (service system related, care related, usage and adherence related, and health outcome related). In the light of the collected findings, we provided a set of 6 actionable recommendations to RPM patient and staff experience evaluators, in terms of both what to measure and how to measure it. Overall, we suggested that RPM researchers and practitioners include experience measuring as part of integrated, interdisciplinary data strategies for continuous RPM evaluation.
Conclusions:
At present, there is a lack of consensus and standardization in the methods used to measure patient and staff experience in RPM, leading to a critical knowledge gap in our understanding of the impact of RPM interventions. This review offers targeted support for RPM experience evaluators by providing a structured, comprehensive overview of contemporary patient and staff experience measures and a set of practical guidelines for improving research quality and standardization in this domain.
From digital health to learning health systems
Four approaches to using data for digital health design
Digital health technologies, powered by digital data, provide an opportunity to improve the efficacy and efficiency of health systems at large. However, little is known about different approaches to the use of data for digital health design, or about their possible relations to system-level dynamics. In this contribution, we identify four existing approaches to the use of data for digital health design, namely the silent, the overt, the data-enabled, and the convergent. After characterising the approaches, we provide real-life examples of each. Furthermore, we compare the approaches in terms of selected desirable characteristics of the design process, highlighting relative advantages and disadvantages. Finally, we reflect on the system-level relevance of the differentiation between the approaches and point towards future research directions. Overall, the contribution provides researchers and practitioners with a broad conceptual framework to examine data-related challenges and opportunities in digital health design.
...
Digital health technologies, powered by digital data, provide an opportunity to improve the efficacy and efficiency of health systems at large. However, little is known about different approaches to the use of data for digital health design, or about their possible relations to system-level dynamics. In this contribution, we identify four existing approaches to the use of data for digital health design, namely the silent, the overt, the data-enabled, and the convergent. After characterising the approaches, we provide real-life examples of each. Furthermore, we compare the approaches in terms of selected desirable characteristics of the design process, highlighting relative advantages and disadvantages. Finally, we reflect on the system-level relevance of the differentiation between the approaches and point towards future research directions. Overall, the contribution provides researchers and practitioners with a broad conceptual framework to examine data-related challenges and opportunities in digital health design.
Digital health is a vibrant and dynamic field, encompassing subsets such as mobile health, health information technology, wearable devices, telehealth and telemedicine, and personalised medicine. While digital health adoption has been markedly accelerated by the covid-19 pandemic (Inkster et al., 2020), an evolving body of research has focused on describing and addressing specific challenges related to the design and evaluation of digital health technologies (Pagliari, 2007; Murray et al., 2016; Blandford et al., 2018; Marvel et al., 2018). This research articulates a need for novel, interdisciplinary design approaches to digital health innovation, integrating disparate sets of requirements such as clinical soundness, user-centeredness, technical interoperability, and cost-effectiveness (Cornet et al., 2019). In this complex domain, design and health disciplines are called not only to collaborate with each other, but also to learn to work with digital data as the raw material fueling digital technologies. This dissertation explores such challenges through a series of exploratory research efforts at the intersection of design, healthcare and digital data. These explorations are conducted within the context of the Cardiolab, a Delft Design Lab born out of a partnership between Philips Experience Design and Delft University of Technology. Throughout the dissertation, knowledge in this domain is gained through a mix of literature reviews and project-based action research (Somekh, 2005). In this way, the relevant scientific literature is connected and put in dialogue with real-life digital health design practice.
...
Digital health is a vibrant and dynamic field, encompassing subsets such as mobile health, health information technology, wearable devices, telehealth and telemedicine, and personalised medicine. While digital health adoption has been markedly accelerated by the covid-19 pandemic (Inkster et al., 2020), an evolving body of research has focused on describing and addressing specific challenges related to the design and evaluation of digital health technologies (Pagliari, 2007; Murray et al., 2016; Blandford et al., 2018; Marvel et al., 2018). This research articulates a need for novel, interdisciplinary design approaches to digital health innovation, integrating disparate sets of requirements such as clinical soundness, user-centeredness, technical interoperability, and cost-effectiveness (Cornet et al., 2019). In this complex domain, design and health disciplines are called not only to collaborate with each other, but also to learn to work with digital data as the raw material fueling digital technologies. This dissertation explores such challenges through a series of exploratory research efforts at the intersection of design, healthcare and digital data. These explorations are conducted within the context of the Cardiolab, a Delft Design Lab born out of a partnership between Philips Experience Design and Delft University of Technology. Throughout the dissertation, knowledge in this domain is gained through a mix of literature reviews and project-based action research (Somekh, 2005). In this way, the relevant scientific literature is connected and put in dialogue with real-life digital health design practice.
Background: Remote patient monitoring (RPM) interventions are being increasingly implemented in health care environments, given their benefits for different stakeholders. However, the effects of these interventions on the workflow of clinical staff are not always considered in RPM research and practice. Objective: This review explored how contemporary RPM interventions affect clinical staff and their workflows in perioperative settings. Methods: We conducted a scoping review of recent articles reporting the impact of RPM interventions implemented in perioperative settings on clinical staff and their workflow. The databases accessed were Embase and PubMed. A qualitative analysis was performed to identify the main problems and advantages that RPM brings to staff, in addition to the approaches taken to evaluate the impact of those interventions. Different themes were identified in terms of the challenges of RPM for clinical staff as well as in terms of benefits, risk-reduction strategies, and methods for measuring the impact of these interventions on the workflow of clinical staff. Results: A total of 1063 papers were found during the initial search, of which 21 (1.98%) met the inclusion criteria. Of the 21 included papers, 15 (71%) focused on evaluating new RPM systems, 4 (19%) focused on existing systems, and 2 (10%) were reviews. Conclusions: The reviewed literature shows that the impact on staff work experience is a crucial factor to consider when developing and implementing RPM interventions in perioperative settings. However, we noticed both underdevelopment and lack of standardization in the methods for assessing the impact of these interventions on clinical staff and their workflow. On the basis of the reviewed literature, we recommend the development of more robust methods for evaluating the impact of RPM interventions on staff experience in perioperative care; the adoption of a stronger focus on transition management when introducing these interventions in clinical practice; and the inclusion of longer periods of assessment, including the evaluation of long-term goals.
...
Background: Remote patient monitoring (RPM) interventions are being increasingly implemented in health care environments, given their benefits for different stakeholders. However, the effects of these interventions on the workflow of clinical staff are not always considered in RPM research and practice. Objective: This review explored how contemporary RPM interventions affect clinical staff and their workflows in perioperative settings. Methods: We conducted a scoping review of recent articles reporting the impact of RPM interventions implemented in perioperative settings on clinical staff and their workflow. The databases accessed were Embase and PubMed. A qualitative analysis was performed to identify the main problems and advantages that RPM brings to staff, in addition to the approaches taken to evaluate the impact of those interventions. Different themes were identified in terms of the challenges of RPM for clinical staff as well as in terms of benefits, risk-reduction strategies, and methods for measuring the impact of these interventions on the workflow of clinical staff. Results: A total of 1063 papers were found during the initial search, of which 21 (1.98%) met the inclusion criteria. Of the 21 included papers, 15 (71%) focused on evaluating new RPM systems, 4 (19%) focused on existing systems, and 2 (10%) were reviews. Conclusions: The reviewed literature shows that the impact on staff work experience is a crucial factor to consider when developing and implementing RPM interventions in perioperative settings. However, we noticed both underdevelopment and lack of standardization in the methods for assessing the impact of these interventions on clinical staff and their workflow. On the basis of the reviewed literature, we recommend the development of more robust methods for evaluating the impact of RPM interventions on staff experience in perioperative care; the adoption of a stronger focus on transition management when introducing these interventions in clinical practice; and the inclusion of longer periods of assessment, including the evaluation of long-term goals.
Finding the land, planting first seeds
Lead user research in early stage design for intelligent ecosystems
This contribution explores the potential of lead user research for early-stage designing for intelligent ecosystems through a literature review and a single case study concerning a lead user research initiative on blood pressure monitoring. The results suggest advantages of executing lead user research in early-stage designing for intelligent ecosystems from the points of view envisioning broad initial ecosystem boundaries, developing first intelligence components, and overcoming research challenges related to technical issues.
...
This contribution explores the potential of lead user research for early-stage designing for intelligent ecosystems through a literature review and a single case study concerning a lead user research initiative on blood pressure monitoring. The results suggest advantages of executing lead user research in early-stage designing for intelligent ecosystems from the points of view envisioning broad initial ecosystem boundaries, developing first intelligence components, and overcoming research challenges related to technical issues.
Conference paper
(2020)
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V. Pannunzio, Peter Lovei, Ineke Neutelings, Eva Deckers, Jos-marien Jansen, Anne Wil Burghoorn
Data-enabled design is an approach used when designing for intelligent ecosystems. It makes use of open-ended design probes situated in participants’ everyday life. These probes are employed both to gain contextual, behavioural and experiential insights and to remotely conceptualize and deploy new design interventions. While the user-experience oriented perspective and the experimental, prototype-centric perspective on designing for intelligent ecosystems through a data-enabled design approach have been extensively described in previous literature, an examination of a service-system perspective is missing to date. In the present contribution, the latter perspective is explored through the lenses of a first-of-a-kind case study. The study was directed towards the development of an intelligent ecosystem for postoperative bariatric care, fuelled by clinical, behavioural, experiential and contextual data, able to provide tailored and personalized care and connecting patients, partners, and health professionals. Practical challenges and opportunities related to the adoption of a service-system perspective within the study were identified and connected to a reflection on the role of service design in contemporary eHealth innovation.
...
Data-enabled design is an approach used when designing for intelligent ecosystems. It makes use of open-ended design probes situated in participants’ everyday life. These probes are employed both to gain contextual, behavioural and experiential insights and to remotely conceptualize and deploy new design interventions. While the user-experience oriented perspective and the experimental, prototype-centric perspective on designing for intelligent ecosystems through a data-enabled design approach have been extensively described in previous literature, an examination of a service-system perspective is missing to date. In the present contribution, the latter perspective is explored through the lenses of a first-of-a-kind case study. The study was directed towards the development of an intelligent ecosystem for postoperative bariatric care, fuelled by clinical, behavioural, experiential and contextual data, able to provide tailored and personalized care and connecting patients, partners, and health professionals. Practical challenges and opportunities related to the adoption of a service-system perspective within the study were identified and connected to a reflection on the role of service design in contemporary eHealth innovation.
Three Approaches to Design Engineering in the Health Domain
A Systemic Perspective
This paper proposes a categorization of existing approaches to healthcare-related engineering design based on systems thinking principles. Three existing approaches to healthcare-related engineering design are isolated which contribute differently to health systems fundamental purposes and interconnections. The three approaches are labeled as 'silent', 'overt', and 'convergent' health design. Each approach is defined and illustrated through an example. Following, practical advantages and disadvantages of each approach are discussed. A reflection is offered on the expected relevance of the convergent health design approach for present and future societal challenges in the health domain, and specifically on the recently growing field of e-health. Finally, open methodological challenges related to convergent health design are outlined and characterized as opportunities for future research.
...
This paper proposes a categorization of existing approaches to healthcare-related engineering design based on systems thinking principles. Three existing approaches to healthcare-related engineering design are isolated which contribute differently to health systems fundamental purposes and interconnections. The three approaches are labeled as 'silent', 'overt', and 'convergent' health design. Each approach is defined and illustrated through an example. Following, practical advantages and disadvantages of each approach are discussed. A reflection is offered on the expected relevance of the convergent health design approach for present and future societal challenges in the health domain, and specifically on the recently growing field of e-health. Finally, open methodological challenges related to convergent health design are outlined and characterized as opportunities for future research.
The Quadruple Aim is a framework which prioritizes four 'aims', or dimensions of performance, for innovating in the healthcare domain, respectively: 1) enhancing the individual experience of care; 2) improving the work life of health care clinicians and staff; 3) improving the health of populations; and 4) reducing the per capita cost of care. In this contribution, recent literature providing examples of design research in the eHealth domain is reviewed to answer the research question: 'in which measure has design research contributed to each of the 'four aims' of eHealth innovation in the past five years?'. The results of the review are presented and employed to draw three main observations: 1) design researchers in eHealth seem to be largely focused on improving experiences of care, either patients' or health professionals'; 2) design researchers' contribution on reducing per capita costs of care appears to be less pronounced, which is outlined as a point for improvement; and 3) in a considerable amount of reviewed contributions, design researchers appear to be contributing to multiple 'aims' at once. In this subgroup of reviewed contributions, several disciplinary areas and types of stakeholders interact and integrate through design research activities. The latter observation leads to a reflection on the strategic role of design research in the contexts of the convergence revolution and of the non-communicable disease crisis. Implications of this reflection for design researchers are recognized in the opportunity and timeliness to develop eHealth-specific ways to orchestrate design integration. A direction for further research in this sense is identified in the use of sensory and self-monitored data as a boundary object for eHealth innovation. The prospective value of this direction is finally exemplified through the case of blood pressure.
...
The Quadruple Aim is a framework which prioritizes four 'aims', or dimensions of performance, for innovating in the healthcare domain, respectively: 1) enhancing the individual experience of care; 2) improving the work life of health care clinicians and staff; 3) improving the health of populations; and 4) reducing the per capita cost of care. In this contribution, recent literature providing examples of design research in the eHealth domain is reviewed to answer the research question: 'in which measure has design research contributed to each of the 'four aims' of eHealth innovation in the past five years?'. The results of the review are presented and employed to draw three main observations: 1) design researchers in eHealth seem to be largely focused on improving experiences of care, either patients' or health professionals'; 2) design researchers' contribution on reducing per capita costs of care appears to be less pronounced, which is outlined as a point for improvement; and 3) in a considerable amount of reviewed contributions, design researchers appear to be contributing to multiple 'aims' at once. In this subgroup of reviewed contributions, several disciplinary areas and types of stakeholders interact and integrate through design research activities. The latter observation leads to a reflection on the strategic role of design research in the contexts of the convergence revolution and of the non-communicable disease crisis. Implications of this reflection for design researchers are recognized in the opportunity and timeliness to develop eHealth-specific ways to orchestrate design integration. A direction for further research in this sense is identified in the use of sensory and self-monitored data as a boundary object for eHealth innovation. The prospective value of this direction is finally exemplified through the case of blood pressure.