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Design knowledge for digital health implementation: a scoping review based on citation analysis

Published online by Cambridge University Press:  31 July 2025

Fredrik Kjell Bodell Open the ORCID record for Fredrik Kjell Bodell [Opens in a new window] ,
Valeria Pannunzio Open the ORCID record for Valeria Pannunzio [Opens in a new window] ,
Julian Houwen Open the ORCID record for Julian Houwen [Opens in a new window] ,
Guillaume Lamé Open the ORCID record for Guillaume Lamé [Opens in a new window] ,
Dirk Snelders  and
Maaike Kleinsmann
Fredrik Kjell Bodell*
Affiliation:
Department of Design Organisation and Strategy, Faculty of Industrial Design Engineering, Delft University of Technology, Delft, The Netherlands
Valeria Pannunzio
Affiliation:
Department of Design Organisation and Strategy, Faculty of Industrial Design Engineering, Delft University of Technology, Delft, The Netherlands
Julian Houwen
Affiliation:
Department of Design Organisation and Strategy, Faculty of Industrial Design Engineering, Delft University of Technology, Delft, The Netherlands Department of Cardiology, Leiden University Medical Center , Leiden, The Netherlands
Guillaume Lamé
Affiliation:
Laboratoire de Génie Industriel, CentraleSupélec, Université Paris Saclay , 91190 Gif-sur-Yvette, Paris, France
Dirk Snelders
Affiliation:
Department of Design Organisation and Strategy, Faculty of Industrial Design Engineering, Delft University of Technology, Delft, The Netherlands
Maaike Kleinsmann
Affiliation:
Department of Design Organisation and Strategy, Faculty of Industrial Design Engineering, Delft University of Technology, Delft, The Netherlands
*
Corresponding author Fredrik Kjell Bodell F.K.Bodell@tudelft.nl
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Abstract

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.

Keywords

design researchdigital healthhealthcare designimplementationscoping review

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Type
Review Article
Information
Design Science , Volume 11 , 2025 , e31
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Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press

1. Introduction

Herbert Simon famously wrote “Everyone designs who devises courses of action aimed at changing existing situations into preferred ones” (as cited in Simon Reference Simon1996, p. 111). To change a situation into a preferred one and realize the proposed benefits of the new situation, the developed ideas for change have to be implemented in real-life contexts. In this article, we will explore how design knowledge can contribute to this process of implementation.

Design knowledge has been described by Horváth (Reference Horváth2004) as both knowledge about design and knowledge for (i.e used in) design. Since design is both a field of investigation and a human practice, there is a general consensus that design knowledge exists in many forms, such as in artifacts, tacit knowledge within practitioners and scientific knowledge in published research (Cross Reference Cross1982; Horváth Reference Horváth2004; Stolterman Reference Stolterman2021). As we are interested in sharing knowledge between fields, we will focus on the formal design knowledge that the academic design research community publishes. Building formal design knowledge in the form of theories, ideas and concepts has been described as a way to challenge and inspire current practice to improve it (Stolterman Reference Stolterman2021). By continuing to build a rich body of knowledge on implementation, we can improve implementation processes and maximize the impact of investments in using new innovations (Bauer et al. Reference Bauer, Damschroder, Hagedorn, Smith and Kilbourne2015; Cabassa Reference Cabassa2016).

In this article, we will focus on the digital health domain and illustrate how researchers in digital health implementation use design knowledge in their published contributions. This is because implementation is a particularly prominent topic in healthcare. In this domain, Chambers, Glasgow, & Stange (Reference Chambers, Glasgow and Stange2013, p. 3) define implementation as the “initial process of embedding interventions within settings.” An example could be the implementation of video calling (an intervention) to a general practice office (a specific setting) to connect with patients remotely. The intervention, video calling, is employed to achieve an intended purpose, and the context of application is defined by the general practice staff, the patients, the technological infrastructure and other elements. Here, the starting point is different from that of a design project. When designing, the starting point is a setting that is to be improved; in contrast, implementation starts with an intervention that is meant to improve the setting but still needs to be adapted and embedded in the context.

Digital health covers various technologies, such as wearables, patient record systems, video conferencing, mobile applications and artificial intelligence. These technologies are currently used to increase the quality of care, reduce inefficiencies, improve access to care and improve patient personalization (U.S. FDA 2020). Although there are clear potential benefits to these technologies, realizing them has often been slower than anticipated due to difficulties in implementation (Wachter Reference Wachter2016). For example, digital health implementations are often planned around an oversimplified model of the condition, with unclear value propositions, and plausible reasons for users to reject the intervention; in addition, there is often an inability to adapt and evolve these technologies over time to continue to meet the intended needs (Greenhalgh et al. Reference Greenhalgh, Wherton, Papoutsi, Lynch, Hughes, Hinder, Fahy, Procter and Shaw2017). Digital health solutions are also often incompatible with existing systems, work practices (Ross et al. Reference Ross, Stevenson, Lau and Murray2016) and system-level complexities such as financial, regulatory, legal and policy constraints (Greenhalgh et al. Reference Greenhalgh, Wherton, Papoutsi, Lynch, Hughes, Hinder, Fahy, Procter and Shaw2017; Bente et al. Reference Bente, Van Dongen, Verdaasdonk and van Gemert-Pijnen2024). To address some of these implementation issues, methods and approaches from the design field can help, for example, by identifying and designing for the needs of different stakeholders (Clarkson Reference Clarkson2018; Heiss & Kokshagina Reference Heiss and Kokshagina2021) while keeping into consideration the broader system (da Costa Junior, Diehl, & Snelders Reference da Costa Junior, Diehl and Snelders2019). Given the increasingly constrained healthcare landscape and the many challenges digital health faces, establishing and improving implementation processes is crucial for realizing the benefits that digital health solutions can bring. This makes digital health a good candidate for exemplifying the use of design knowledge in implementation.

The topic of designers and design research taking part in implementation has previously been brought to attention by Norman & Stappers (Reference Norman and Stappers2015), who suggest that designers should contribute to implementation when dealing with complex sociotechnical problems. Karlsson et al. (Reference Karlsson, Pannunzio, Snelders and Kleinsmann2024) also argue that design practices such as co-creation, prototyping and user research can potentially be beneficial during implementation. More generally, implementation issues can be seen as examples of ill-defined or ‘wicked’ problems that often arise in social systems, with multiple stakeholders with conflicting interests and different perspectives (Buchanan Reference Buchanan1992). One of the fundamental roles of design is to tackle such ill-defined problems (Cross Reference Cross1982) by creating and reflecting on additions and changes to the artificial world (Cross Reference Cross2001). Treating implementation processes as ill-defined problems and attempts to change the artificial world suggests that design can contribute to implementation processes. Design methods and approaches also have the potential to create more implementable solutions through understanding users and changing and evaluating the intervention iteratively (Simonsen & Hertzum Reference Simonsen and Hertzum2012; Wiltschnig, Christensen, & Ball Reference Wiltschnig, Christensen and Ball2013), which can help to adapt the intervention to improve the integration with the target context.

Research question

To explore the potential contribution of design knowledge in digital health implementation, we have limited ourselves to formal design knowledge published in the academic literature, as this literature often seeks to reveal knowledge within design. Starting from design research literature, we aimed to illustrate how its insights have already made their way into the literature on digital health implementationFootnote 1. The intention is to understand current areas where the design field contributes to the implementation of digital health and use this as a basis to discuss future steps. To explore this, we sought to answer the following research question: How is design literature cited in digital health implementation literature? We looked at this from three perspectives: (1) the purpose of citing the design literature, (2) the concept from the design literature that is referred to and (3) the characteristics of the design articles that are cited. The first two perspectives will be explored by examining digital health implementation articles, while the third one will be explored by examining the design articles being cited. This will provide insights into how design knowledge is thought to contribute to digital health implementation and which design approaches or methods are considered to be valuable for digital health implementation. This, in turn, can help the design research community understand how to shape its research to be beneficial for the digital health implementation research audience.

The structure of the article is as follows. First, we present the methodological approach of the study. We then present the results and discuss the potential of design to contribute to digital health implementation and what the design community could do to improve its impact on implementation.

2. Method

To investigate how design knowledge contributes to digital health implementation, we are limiting ourselves to formal knowledge published in academic design research. In this study, ‘design knowledge’ thus means formal knowledge shared in the academic design research community, in the form of academic publications.

In this investigation, we explored how design articles are cited through a scoping review. This type of review appears to be suitable for our scope, as this study aims to provide an overview of existing literature (Munn et al. Reference Munn, Peters, Stern, Tufanaru, McArthur and Aromataris2018). To structure our review process, we used the five steps from Arksey and O’Malley’s (Reference Arksey and O’Malley2005) framework. The first step in conducting the scoping review was to create a research question. This was a collaborative effort among all co-authors, where the starting point was to understand how design knowledge makes its way into digital health implementation and how we can gather insights about this through literature. However, this scoping review differs from traditional scoping reviews, as we use a set of journals as a starting point for our search. By using journals, we did not have to limit the search to specific keywords and could be open to any topics that might occur. Using this approach, we first examined the digital health implementation publications that cite design articles, and second, we examined the design articles that were cited by these publications, creating two sets of publications. The process was structured as follows:

Steps relating to digital health implementation journals.

  1. 1. Define key design journals to represent the design literature (explained in 2.1).

  2. 2. Search for digital health implementation records that cite publications from the selected design journals (explained in 2.2).

  3. 3. Screen the records abstracts and full text (explained in 2.3)

  4. 4. Collect and analyze data from the digital health implementation publications (explained in 2.4).

Step relating to design journals.

  1. 5. Collect and analyze data from the cited design publications (explained in 2.5).

These steps will be elaborated upon in the next section. When reporting the process and results of the scoping review, we followed the PRISMA Extension for Scoping Reviews (PRISMA-ScR) guidelines (Tricco et al. Reference Tricco, Lillie, Zarin, O’Brien, Colquhoun, Levac, Moher, Peters, Horsley, Weeks, Hempel, Akl, Chang, McGowan, Stewart, Hartling, Aldcroft, Wilson, Garritty, Lewin, Godfrey, Macdonald, Langlois, Soares-Weiser, Moriarty, Clifford, Tunçalp and Straus2018).

2.1. Journal selection

To identify publications on digital health implementation that cite design literature, the design field had to be defined. To represent the design research field, we chose to select a number of key design journals. The starting point for this selection was an article by Gemser et al. (Reference Gemser, de Bont, Hekkert and Friedman2012) that divides design journals into general design journals and journals that are specialized in a subdiscipline of design. We chose to use the general design journals as they publish articles across subdisciplines. Cash (Reference Cash2018) and Huynh-Dagher et al. (Reference Huynh-Dagher, Lamé, Duong and Jankovic2022) have taken a similar approach and also added journals to the initial list by Gemser et al. Together, they added Design Science and Research in Engineering Design as general design journals. We added those two journals as well. Additionally, we chose to include She Ji, as it can be regarded as a new general design journal, which did not yet exist at the time of the publication of the article by Gemser et al. The complete list of selected journals thus includes Design Studies, International Journal of Design, the Design Journal, Design Issues, Journal of Engineering Design, Research in Engineering Design, She Ji, Journal of Design Research and Design Science.

2.2. Search strategy for digital health implementation records

To find digital health implementation records, we conducted searches in Scopus and Web of Science (WoS). These databases contain both design and digital health articles, and they also make it possible to conduct searches that start from pre-specified journals, which was required for our two-step method. We searched for digital health implementation records that cite each of the selected design journals by:

  1. a. Searching for the name of each design journal as source title (Scopus) or publication title (WoS).

  2. b. For Scopus, selecting all articles from the journal and choosing “View cited by” to present all records that cited the design journal.

    For WoS, selecting “Citation Report” and then the total number of articles citing the papers from the journal under “Citing Articles.”

  3. c. Using the search query below to find all records about digital health implementation that cited the selected design journals. TITLE-ABS-KEY (“eHealth” OR “e-Health” OR “Telehealth*” OR “Tele-health*” OR “telemedicine” OR “tele-medicine” OR “mHealth” OR “m-health” OR “mobile health” OR “health information technolog*” OR “health informat*” OR “digital health*” OR “digital medicine”) AND TITLE-ABS-KEY (“implement*” OR “embed*” OR “integrat*” OR “realiz*” OR “realis*” OR “adopt*”)

    This search query was used in Scopus, and the same, but removing ‘TITLE-ABS-KEY’ from both parts of the query, was used in WoS.

These three steps were conducted for all nine of the selected design journals in both databases. For each step, we also noted the number of publications from each publication, the number of publications that cited the journal in total and the number of publications that cited the journal and were about digital health implementation. The initial search and data collection were conducted on the 5th of January 2024, and the search query and data collection were revised on the 9th of July 2024. The search was then updated on the 17th of March 2025 after peer review.

2.3. Abstract screening and eligibility assessment

We used the Rayyan.ai online platform to support the screening process, which was based on three inclusion criteria (Table 1). After uploading all records to Rayyan, we removed duplicates and checked for inclusion criterion 1. Three researchers (FB, VP and JH) then screened the publications’ titles, abstracts and keywords for inclusion criterion 2. At least two researchers independently screened the titles and abstracts for each publication, and disagreements were resolved through discussion among the three researchers. After the abstract screening, full texts were checked for eligibility using criteria 2 and 3 (see Table 1). After full-text screening, 70 publications on digital health implementation were included for data collection and analysis.

Table 1.

Criteria used for eligibility assessment

Note: After full-text screening, we also excluded a publication written by many of the authors of this publication (self-authored), as the two were written in parallel, and the results of this publication might have influenced that publication.

2.4. Data collection and data analysis of digital health implementation publications

We extracted the first author’s country, year of publication, journal name, publication category (i.e., position paper, review, or original research) and publication type (i.e., conference paper, book chapter or journal article) from the included articles on digital health implementation. Additionally, we searched Scopus for the journal’s subject area using the journal name.

To extract data from the records, we identified the fragments of text that referenced one of the selected design journals. The fragments consisted of pieces of text (one to four sentences long) in which one of the selected design journals was cited. All fragments were coded in ATLAS.ti (v23.2.1). We then followed the Reflexive Thematic Analysis method, with a constructivist epistemology view (Braun & Clarke Reference Braun and Clarke2012), to analyze the data inductively. We identified patterns and grouped them into themes related to the use of design knowledge in implementing digital health. This process was conducted through the following steps. To begin with, the first author collated the coded fragments into potential themes and topics (sub-themes) based on shared characteristics. Four other co-authors then reviewed the themes and topics, and each discussed their feedback with the first author. These discussions primarily addressed the alignment between codes and categories and the relations between the categories. The analysis developed through each revision, where the discussions primarily focused on enhancing the analysis rather than discussing different opinions on categorizing codes and categories. Initially, the discussions resulted in significant changes to the themes. Later revisions focused on smaller adjustments to the labelling of the topics and quotes. Lastly, the first author prepared a written presentation using selected data extracts to illustrate the themes. All co-authors reviewed and annotated this document, after which they discussed their comments with the first author. After two iterations, consensus was achieved.

2.5. Data collection and data analysis of the cited design articles

Aside from analyzing how design concepts are used in articles on digital health implementation, we also wanted to understand the type of design articles that get cited by digital health implementation researchers. We identified the cited design articles by looking at the reference list of the included digital health implementation records. By doing this, 58 design articles were included. To chart them, we read the design articles and classified them into three types:

  • • Original research, based on the collection and analysis of primary or secondary data.

  • • Position papers, which present and discuss new concepts or the author’s opinion.

  • • Literature reviews, which report the state of the art of academic knowledge in a given topic.

The design articles were also classified by open access status and focus on healthcare, to see if these two variables affect the extent to which they are cited in the digital health implementation literature. The article’s healthcare focus was classified by examining the title, abstract and keywords and by reading any included case studies. Here, we categorized them as healthcare-focused if they were related to a type of illnesses, such as mental health, diabetes or cardiovascular disease. We also categorized them as healthcare-focused if the articles focused on health service delivery in general or on medical devices. We did not classify the articles as healthcare-related if they, for example, focused on well-being, mood or delivering services to elderly people who were not mentioned to have any illnesses.

3. Results

The results from this scoping review are presented in four subchapters: Section 3.1 describes the number of records for each step of the selection process. Section 3.2 presents the general characteristics of included digital health implementation records. Section 3.3 presents the characteristics of citations from design literature, and Section 3.4 presents characteristics of the cited design articles. A complete overview of the characteristics of the included articles is available in supplementary file 1.

3.1. The number of records for each step of the selection process

The database search yielded 382 digital health implementation records that cited work from the selected design journals. The number of articles from each journal can be found in Table 2. After screening the records, 70 publications were included in the first part of the analysis (Figure 1).

Table 2.

Number of records in each journal, citing the journal in total and after the search query

Note: Obtained from Scopus and Web of Science on the 17th of March 2025.

Figure 1.

Flow diagram for the publication selection process.

3.2. General characteristics of included digital health implementation records

The list of study characteristics is presented in Table 3. In it, we can see that the publications came from 18 countries based on the first author’s affiliation. It also shows how many included publications are original empirical research, viewpoints or position papers, protocols, literature reviews, book chapters and editorials. The records included journal articles, conference papers and book chapters. It also shows the topics of the included journals. The included publications were primarily published after 2017 (87%), see Figure 2.

Table 3.

Characteristics of the included digital health implementation records

a For each country to the left of the number.

b The ‘Journal subject’ total is greater than 62 because Scopus can list multiple subjects per journal.

Figure 2.

The number of digital health implementation records citing at least one of the selected design journals per year of publication.

3.3. Characteristics of citations by digital health implementation records

In the 70 included records on digital health implementation, we identified 101 fragments that cited the selected design journals. Through thematic analysis, we identified 27 topics, 21 of which fit within two larger themes. These themes describe the purpose of citing a design article. In the first theme, the design literature is cited to show the potential benefit of an approach or method. In the second theme, the design literature is cited to explain the process of using an approach or method. Six topics did not fit the two larger themes. Table 4 shows how the topics are divided across the themes.

Table 4.

Publications and coded fragments per theme and topic

3.3.1. Theme 1: Show the potential benefit of an approach or method

Fifty of the included 70 publications cited the selected design journals to show the potential benefit of an approach or method. These cited approaches and methods are primarily related to co-design, human-centered design or understanding user needs. The cited benefits of these methods and approaches in digital health implementation, with supporting quotes, can be found in Table 5.

Table 5.

Theme 1: Benefits of approaches and methods (with supporting quotes)

3.3.2. Theme 2: Explain the process of using an approach or method

28 of the included 70 publications cited at least one of the selected design journals to describe a method or approach. What they describe is primarily co-design, human-centered design and prototyping. Quotes that illustrate how the design literature is referenced can be found in Table 6.

Table 6.

Theme 2: Descriptions of approaches and methods cited from design records (with supporting quotes)

3.3.3. Other topics

Ten coded fragments, out of the 101 total coded fragments, did not fit into the two main themes above. Two topics that had at least two citations were technology acceptance and evaluation of the implementation, and four had only one. Quotes to show how each is cited can be found in Table 7.

Table 7.

Topics that are cited for other reasons

3.4. Characteristics of cited design articles

In total, 58 articles from the selected design journals were cited by the 70 publications on digital health implementation. Of these 58 design articles, 45 were cited once, and 13 were cited more than once (see Table 8).

Table 8.

Number of citations from the digital health implementation literature for the selected design journals

Out of the eight most cited design articles, four described co-design, and three were published in the Design Journal. All articles cited more than twice can be seen in Table 9 with the number of citations, title and the journal in which it was published.

Table 9.

Design articles that were cited more than twice by digital health implementation literature

The types of articles cited were primarily original research and position papers. Literature reviews were the least cited type of research. Average citations per paper were 2 for original research, 1.3 for position papers and 1.1 for literature reviews. Of the cited design articles, a third were healthcare-related. The healthcare-related articles were cited 2.2 times per article, against 1.3 for the not healthcare-related articles. For an overview of research type, year, open access status, and healthcare focus, see Table 10.

Table 10.

Study characteristics of design articles

4. Discussion

This study investigated what type of design knowledge is used in digital health implementation publications. By analyzing how digital health implementation publications have cited a corpus of preselected design journals, we distinguished two main themes. Through charting the data from the cited design articles, we also identified metrics that show what type of design articles digital health implementation publications cite most often. Next, we will offer a set of reflections regarding selected topics in these themes, followed by a discussion on the defining characteristics of the cited design articles. Thereafter, we will discuss the strengths and limitations of the study and finally present some future directions for how design knowledge can contribute to digital health implementation.

4.1. How digital health implementation publications cite the design literature

Based on our analysis, we found two main themes for how digital health implementation literature cites design literature.

  • • To show the potential benefit of an approach or method, justifying why it is chosen in their study on digital health implementation

  • • To explain the process of using an approach or method, describing how to use it and describe conditions for using it in their study on digital health implementation.

These two themes point to how design knowledge can contribute to digital health implementation in addressing some of the barriers to implementing digital health solutions, mentioned by Greenhalgh et al. (Reference Greenhalgh, Wherton, Papoutsi, Lynch, Hughes, Hinder, Fahy, Procter and Shaw2017), Ross et al. (Reference Ross, Stevenson, Lau and Murray2016), and Bente et al. (Reference Bente, Van Dongen, Verdaasdonk and van Gemert-Pijnen2024). By virtue of creating, describing and evaluating methods and approaches that can address barriers to digital health implementation, design knowledge can contribute to improving the fit between intervention and context. This role is in line with the purpose of creating knowledge, being to challenge current practice and inspire ways of improving it (Stolterman Reference Stolterman2021), which can also be used to challenge and inspire implementation practice.

Across the two overarching themes in which design knowledge contributes, we found several recurring topics. Combining the topics from both themes, the three most cited topics were:

  • • Co-design, which was cited to show that it can improve adoption and communication with users. Citations were also made to explain co-design and the challenges of involving users.

  • • Human-centered design, which was cited to show that it can improve user experience and usability, as well as take people and systems into consideration when making changes to interventions and contexts. Citations were also made to explain what it is and how it is viewed.

  • • Prototyping, which was cited to show that it contributes to engaging stakeholders in discussions on user needs, prioritizing changes and enhancing creativity. Citations were also made to explain how to use prototypes and the risks of using them.

In the first theme, where citations were used to show the benefit of an approach or method, additional topics were found: understanding user needs, service design, design thinking, personas, wicked problems, design for healthcare, systems integration, systems thinking, design for behavior change and considering the context. Looking at the design topics cited in the digital health implementation literature, design knowledge seems to be primarily used to understand the needs and perspectives of the people involved in the implementation. This is seen in multiple of the cited topics, such as co-design, human-centered design, prototyping, understanding user needs, personas and service design. Additionally, some of these topics contribute to how to move towards implementation in collaboration with the involved stakeholders. The following discussion will focus on the role of design knowledge in relation to the three most cited topics: co-design, human-centered design and prototyping.

4.1.1. Co-design

Co-design was the most cited topic from the design literature. Co-designing with relevant stakeholders in the implementation process is, for instance, seen as a means to understand the patients (Lewis et al. Reference Lewis, Palmer, Kotevski, Densley, O’Donnell, Johnson, Wohlgezogen, Gray, Robins-Browne and Burchill2021) and create collective ownership (Gillam et al. Reference Gillam, Evans, Aworinde, Ellis-Smith, Ross and Davies2023). Both are described as essential aspects for a successful implementation. Co-design was also cited as a way to create a more efficient implementation process by improving communication and adoption from the users.

From reading the digital health implementation publications, we notice that different sources view co-design differently. Some see co-design as an approach where users take part in creating the service, including the implementation process. For example, the paper by Bevan Jones et al. (Reference Bevan Jones, Stallard, Agha, Rice, Werner-Seidler, Stasiak, Kahn, Simpson, Alvarez-Jimenez, Rice, Evans and Merry2020) describe co-design as an active involvement of stakeholders throughout the process. Others see co-design as gathering feedback from stakeholders, primarily end-users, through methods such as focus groups or interviews. For example, Manski-Nankervis et al. (Reference Manski-Nankervis, Alexander, Biezen, Jones, Hunter, Emery, Lumsden, Boyle, Gunn, McMorrow, Prictor, Taylor, Hallinan, Chondros, Janus, McIntosh and Nelson2021) describe how they gathered feedback from end-users and other stakeholders on prototypes in an iterative way. Another example is Pickering et al. (Reference Pickering, Serafimovska, Cho, Blaszczynski and Gainsbury2022) who present a focus group study where participants were asked to provide their thoughts on the problem and ideas for features to include in a possible solution. Liang et al. (Reference Liang, Melcer, Khotchasing and Hoang2024), on the other hand, describe that in co-design, the stakeholders are treated as equal collaborators; however, their method describes three of the same type of workshops as the only form of outside stakeholder participation. This lack of consensus on what constitutes co-design in implementation practice can create issues. If articles on co-design suggest that certain benefits will come from using co-design, the way co-design is used certainly affects the degree to which those benefits will be achieved. With an existing strong link to co-design, future research directions within design research could be dedicated to establishing more specific links between types of co-design and their implementation benefits. To do this, it could help to differentiate studies using co-design longitudinally or to gather insights at distinct points.

4.1.2. Human-centered design

Human-centered design (HCD) was the second most cited topic in the digital health implementation literature. However, how it was applied differed. For example, Stein et al. (Reference Stein, Strickland, Tabak, Dale, Colditz and Evanoff2019) interacted with different stakeholders to get their perspectives at multiple points in time throughout the process, while Choosri et al. (Reference Choosri, Jitmun, Lumpoon, Sitthithanasakul, Saralamba, Thongbunjob and Chumsang2022) focused on understanding the effectiveness of the intervention for different stakeholders by conducting interviews at one point in time. Both state that they adopted a human-centered design approach. The purpose of adopting this approach also varied. It was, for instance, presented as a way to enhance the user experience (Hardy et al. Reference Hardy, Ward, Emsley, Greenwood, Freeman, Fowler, Kuipers, Bebbington and Garety2022), help understand the context, not to disrupt it when implementing a change (Choosri et al. Reference Choosri, Jitmun, Lumpoon, Sitthithanasakul, Saralamba, Thongbunjob and Chumsang2022), and foster more equitable implementations (Holeman & Kane Reference Holeman and Kane2020).

HCD has previously been presented as a valuable approach for redesigning care delivery systems to fit the needs of everyone within them (Erwin & Krishnan Reference Erwin and Krishnan2016). Here, we see potential in HCD to consider both human and system-level factors to help align digital health innovations with the lived realities of care delivery. From our findings, we see that adopting HCD can potentially improve the experience and usability for people in a care delivery system, and incorporate both people and system factors into making changes. In this sense, design knowledge contributes to digital health implementation by describing how to use HCD and its benefits to further its adoption. With digital health implementors experiencing many issues relating to aligning with human needs (Ross et al. Reference Ross, Stevenson, Lau and Murray2016; Greenhalgh et al. Reference Greenhalgh, Wherton, Papoutsi, Lynch, Hughes, Hinder, Fahy, Procter and Shaw2017), we suggest that furthering research efforts into the role of HCD in implementation could improve implementation practices while also improving the impact of design knowledge.

4.1.3. Prototyping

Prototyping was the third most cited topic from design knowledge in digital health implementation literature. Using prototypes was seen as a way to improve implementation by creating tangible representations with which to engage stakeholders (Scanzera et al. Reference Scanzera, Beversluis, Potharazu, Bai, Leifer, Cole, Du, Musick and Chan2023) and promote creative thinking among stakeholders (McCarthy et al. Reference McCarthy, O’Raghallaigh, Woodworth, Lim, Kenny and Adam2020). The diversity of prototyping tools in the included publications spans across scenarios, journey maps, paper mock-ups and high-fidelity physical prototypes. Most researchers in digital health implementation describe using these prototypes to test for potential issues with the implementation. This is done either by having users try out a prototype or by presenting the prototype to different stakeholders. Using prototypes in this way can help with collaboration and communication of ideas of future states (Blomkvist & Segelström Reference Blomkvist and Segelström2014). This can foster a better understanding of various perspectives on a digital health intervention during implementation.

As digital health implementation can experience barriers such as incompatibility with existing work practices (Ross et al. Reference Ross, Stevenson, Lau and Murray2016) and can benefit from methods that help understand the digital health solutions fit with its context before adoption (Greenhalgh et al. Reference Greenhalgh, Wherton, Papoutsi, Lynch, Hughes, Hinder, Fahy, Procter and Shaw2017), knowledge about how to create and use prototypes can be a potentially impactful contribution from design. Karlsson et al. (Reference Karlsson, Pannunzio, Snelders and Kleinsmann2024) have identified from interviews with design practitioners that they are using prototypes to create a common language with stakeholders and to understand end users through reflection or testing. As such, we can observe how a designerly, constructivist approach to understanding and involving different kinds of stakeholders with prototypes can be applied not only to the development and testing of new solutions but also to their implementation in context. Building additional knowledge about applying prototypes in relation to implementation could therefore contribute further to digital health implementation.

4.2. Design articles cited by digital health implementation

The analysis of the cited design articles reveals insights about the type of records being cited in digital health implementation publications. When it comes to the type of article, original research articles are the most cited, making up 56% of all citations, while position papers account for 33% of citations. This is possibly due to a preference for original studies from healthcare researchers. The healthcare-related design articles saw a greater amount of citations per article (about 1.7 times more) than the design articles that were not related to healthcare. This might suggest that they are easier to find for digital health researchers or might be seen as more relevant and applicable to improving health systems. Regarding the year of publishing, most cited design articles were published after 2010, and no design articles published after 2020 were cited. This could suggest either a lag in citation accumulation, a more established reliance on earlier foundational works, or that topics from this time are more interesting for digital health implementation researchers.

Our results also show that the selected design journals were cited by digital health implementation papers more and more every year from 2018 to 2022, but that there was a drop in 2023. This might have to do with Covid-19 and the shift in focus for what to publish during this time. A search on Scopus with the same digital health search query shows that there was generally a small decline in papers published on digital health in the same period.

Reviewing the cited design articles, we can also see that the most cited articles have clearly described topics in the title and abstract. Titles of these papers are for example “The core of ‘design thinking”and its application” (Dorst Reference Dorst2011), “Benefits of co-design in service design projects” (Steen et al. Reference Steen, Manschot and De Koning2011) and “What is human-centred design?” (Giacomin Reference Giacomin2014). This might suggest that researchers in the digital health domain who seek knowledge from design have an easier time understanding if what they are looking for exists within an article, if it contains specific concept keywords and describes how it will present knowledge around that concept.

When discussing what health research might find applicable from design knowledge, it should also be noted that these different research communities value and legitimize knowledge differently. Particularly, design might not live up to the standard of evidence expected from health research (Lamé Reference Lamé2018). Health research tends to prioritize methodological rigor and consistency (often from a positivist point of view), while design often emphasizes contextual tailoring and flexibility (often from a constructivist point of view). The focus on rigor and consistency over flexibility may result in overlooking more diverse or practice-based forms of knowledge. This might harm the building of knowledge that challenges and inspires new practice, especially in complex systems where you cannot predict outcomes of change. We therefore argue that to improve implementation, we should develop knowledge using multiple epistemologies. A cross-disciplinary dialogue on what counts as valid knowledge to contribute to improving the implementation of digital health solutions is thus necessary.

In reading the cited design articles, we also noticed that few details are provided on the boundary conditions for when the explained methods and approaches will be appropriate. However, describing methods and approaches in context is crucial, as it permits the consideration of factors (such as the skills of the method users and the attributes of the environment) that might affect results (Gericke, Eckert, & Stacey Reference Gericke, Eckert and Stacey2022). This is discussed in Steen et al. (Reference Steen, Manschot and De Koning2011), one of the included design articles, which reports on tailoring co-design processes to each case, and characterizes this as a challenge for co-design. As implementations are very context-dependent, knowing how to use design methods and approaches depending on the context is essential for grasping how to adopt them. Clearly describing the context in which implementation methods and approaches are applicable could therefore support wider adoption of design knowledge.

4.3. Strengths and limitations

Searching for how design is cited in other domains by using sets of journals is, as far as we are aware, a novel approach to understanding the impact of design knowledge on another field. In this case, we used it for digital health implementation; however, it could also be used to understand, for example, how design knowledge has made its way into the literature on education, sustainability, policy, manufacturing, entrepreneurship, artificial intelligence or management. As it is sometimes difficult to show how design knowledge makes its way into other fields, we encourage other researchers to use similar methods to explore the impact of design knowledge.

However, we acknowledge that our method presents several limitations. First, a limitation in our study is that we have chosen to focus exclusively on design knowledge presented in academic journals rather than, for instance, tacit knowledge and knowledge within artifacts. To fill this knowledge gap, we will also submit a paper on how design professionals use their knowledge to contribute to digital health implementation in real-life projects. Secondly, we have included two major databases, limiting our results for both sets of articles (design and digital health implementation) to those indexed in Scopus and Web of Science.

Finally, to map the contribution of design knowledge to digital health implementation, we had to create a searchable scope. In doing so, we narrowed down the design literature to a set of nine general design journals, selecting journals similar to previous examples by Gemser et al. (Reference Gemser, de Bont, Hekkert and Friedman2012), Cash (Reference Cash2018), and Huynh-Dagher et al. (Reference Huynh-Dagher, Lamé, Duong and Jankovic2022). Using design journals made it possible not to limit the search to specific keywords that had to represent the broad design field, and instead kept it open for any topics that might occur. However, we used a relatively limited definition of design literature as we did not include journals focusing on specific design subdisciplines, such as CoDesign, AI-EDAM, International Journal of Design Creativity and Innovation, Design for Health, Human-Computer Interaction, Human Factors, Strategic Design Journal, Design and Culture, Design Management Journal, Applied Ergonomics and Journal of Mechanical Design, as well as conference publications. While we did this to avoid skewing our results towards any specific design subfields, we see that this choice constitutes a major limitation of our study, as it resulted in the exclusion of much potentially relevant design literature. To illustrate the potential scope of relevant literature in excluded journals, we conducted an additional search on April 29th using the same strategy, which showed 67 records for CoDesign, compared to 4 for Design and Culture and 491 for Human Factors before abstract screening. If other researchers would like to apply our method for a specific sub-topic within design, such as collaboration, we suggest adding specialized journals such as CoDesign for collaborative design or Human Factors for human factors-related design, in addition to the general design journals that we have used.

4.4. Future directions

Some of the cited topics, such as co-design or HCD, are already quite prevalent in the healthcare innovation field. However, the use of prototypes to address barriers to implementation seems to be a less prevalent topic. This presents an opportunity for the increased contribution of design knowledge. In particular, there seems to be room for expanding the view of prototypes and how to use them. For example, using prototypes as a means for co-developing digital product service systems (Kleinsmann & Ten Bhömer Reference Kleinsmann and Ten Bhömer2020) could help the co-implementation of digital health solutions. Similarly, ‘service prototypes’ have been suggested to make the intangible parts of service delivery more accessible to discuss and share (Blomkvist & Segelström Reference Blomkvist and Segelström2014), which could prove useful in implementation processes. Camburn et al. (Reference Camburn, Viswanathan, Linsey, Anderson, Jensen, Crawford, Otto and Wood2017) show that there is not much research on using prototyping in advanced stages of development, when the product, service or system is being implemented. This presents an opportunity for prototyping to expand into implementation by using existing prototyping techniques and developing new ones.

Two topics that were less recognized, only being cited one and two times, respectively, but that we find interesting in relation to digital health implementation are systems approaches and design for behavior change. For the first topic, van der Bijl-Brouwer & Malcolm (Reference van der Bijl-Brouwer and Malcolm2020) were cited to highlight that taking a systems approach can help with addressing complexities. As implementors have to deal with many influencing factors, such as policy, technology, finance, workflow and organization (Greenhalgh et al. Reference Greenhalgh, Wherton, Papoutsi, Lynch, Hughes, Hinder, Fahy, Procter and Shaw2017; Bente et al. Reference Bente, Van Dongen, Verdaasdonk and van Gemert-Pijnen2024), different ways in which these complexities can be identified and addressed can help increase the chance of successful implementation. For example, systems approaches can help practitioners make intentional decisions on how to shape social structures and manage complexity (da Costa Junior et al. Reference da Costa Junior, Diehl and Snelders2019; Vink, Wetter-Edman, & Koskela-Huotari Reference Vink, Wetter-Edman and Koskela-Huotari2021).

Regarding design for behavior change, Cash et al. (Reference Cash, Hartlev and Durazo2017) were cited to exemplify that the design field is concerned with design for behavior change, and Visser et al. (Reference Visser, Vastenburg and Keyson2011) are cited to show how design can help create social connectedness which shapes behavior. Implementing a digital health solution often means transitioning from one way of working to another. By incorporating knowledge about how to design for shifting behavior, this transition might become easier. Behaviors have been suggested to, for example, be shaped by triggering specific experiences, improving knowledge or shifting attitudes (Fokkinga, Desmet, & Hekkert Reference Fokkinga, Desmet and Hekkert2020), which the design field can support. Bay Brix Nielsen, Cash, & Daalhuizen (Reference Bay Brix Nielsen, Cash and Daalhuizen2024) have also suggested that further iterations during implementation can help to fit behaviors with the intervention.

Overall, in light of the collected results, we urge design researchers, especially those working in healthcare, to consider whether or not their research might be beneficial for implementation processes. If that is the case, we suggest that those findings should be presented as such in their articles, so that they can be picked up more easily by implementation researchers and practitioners. Design researchers who address implementation should explicitly use the word ‘implementation’ in their abstracts to make their paper easier to find for researchers and practitioners. Additionally, we urge design professionals and design researchers to collaborate with researchers doing implementation work in order to guide, improve and spread the use of design knowledge as a way of supporting implementation. Hopefully, this research can also inspire designers and design researchers to focus more on implementation processes. Additionally, positioning design as a contributing field can be beneficial for increasing the impact of design research. Here, it is possible to strengthen and broaden the current contribution of design knowledge, not only for creating new products and services but also for implementing them.

5. Conclusions

This scoping review has shown how design knowledge contributes to the implementation of digital health solutions. If we see the aim of design as changing a situation to a preferred one, this study has provided some insights into how design can contribute to the later stages of realizing the change. Our results show that design research is primarily cited to provide insights about using approaches or methods and the benefits of using them. The cited topics primarily focus on the involvement of people in implementation processes and on how to create and evaluate potential changes together with the relevant stakeholders. With this contribution, we hope to inspire researchers in both fields to strengthen their relationship. In particular, there is great potential in the broader research field of design to contribute to implementation processes in ways that are yet unforeseen by implementation researchers working in the context of digital health. By continuing to strengthen the contribution of design knowledge to implementation, we can facilitate transitions toward positive change and, ultimately, contribute to improving systems of care.

Supplementary material

The supplementary material for this article can be found at http://doi.org/10.1017/dsj.2025.10022.

Footnotes

1 In another ongoing complementary study, we are interviewing designers doing digital health implementation to understand how they are contributing with their practices.

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Figure 0

Table 1. Criteria used for eligibility assessment

Figure 1

Table 2. Number of records in each journal, citing the journal in total and after the search query

Figure 2

Figure 1. Flow diagram for the publication selection process.

Figure 3

Table 3. Characteristics of the included digital health implementation records

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Figure 2. The number of digital health implementation records citing at least one of the selected design journals per year of publication.

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Table 4. Publications and coded fragments per theme and topic

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Table 5. Theme 1: Benefits of approaches and methods (with supporting quotes)

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Table 6. Theme 2: Descriptions of approaches and methods cited from design records (with supporting quotes)

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Table 7. Topics that are cited for other reasons

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Table 8. Number of citations from the digital health implementation literature for the selected design journals

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Table 9. Design articles that were cited more than twice by digital health implementation literature

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Table 10. Study characteristics of design articles

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