creative problem solving design thinking in health and social care

Design Thinking in Health Care

SYSTEMATIC REVIEW — Volume 15 — September 27, 2018

Myra Altman, PhD 1 ,2,3 ; Terry T.K. Huang, PhD, MPH, MBA 4 ; Jessica Y. Breland, PhD 2 ( View author affiliations )

Suggested citation for this article: Altman M, Huang TT, Breland JY. Design Thinking in Health Care. Prev Chronic Dis 2018;15:180128. DOI: http://dx.doi.org/10.5888/pcd15.180128 external icon .

PEER REVIEWED

Introduction

Acknowledgments, author information.

Applying Design Thinking to health care could enhance innovation, efficiency, and effectiveness by increasing focus on patient and provider needs. The objective of this review is to determine how Design Thinking has been used in health care and whether it is effective.

We searched online databases (PubMed, Medline, Web of Science, CINAHL, and PyscINFO) for articles published through March 31, 2017, using the terms “health,” “health care,” or “healthcare”; and “Design Thinking,” “design science,” “design approach,” “user centered design,” or “human centered design.” Studies were included if they were written in English, were published in a peer-reviewed journal, provided outcome data on a health-related intervention, and used Design Thinking in intervention development, implementation, or both. Data were collected on target users, health conditions, intervention, Design Thinking approach, study design or sample, and health outcomes. Studies were categorized as being successful (all outcomes improved), having mixed success (at least one outcome improved), or being not successful (no outcomes improved).

Twenty-four studies using Design Thinking were included across 19 physical health conditions, 2 mental health conditions, and 3 systems processes. Twelve were successful, 11 reported mixed success, and one was not successful. All 4 studies comparing Design Thinking interventions to traditional interventions showed greater satisfaction, usability, and effectiveness.

Design Thinking is being used in varied health care settings and conditions, although application varies. Design Thinking may result in usable, acceptable, and effective interventions, although there are methodological and quality limitations. More research is needed, including studies to isolate critical components of Design Thinking and compare Design Thinking–based interventions with traditionally developed interventions.

Health care systems require continuous innovation to meet the needs of patients and providers (1,2). However, these stakeholders are not always considered when new interventions or system processes are designed, which results in products that remain unused because they do not account for human context, need, or fallibility (3,4). This approach also likely contributes to the decades-long gaps between intervention development and implementation (5). Design Thinking offers a way to close that gap by helping investigators incorporate user needs and feedback throughout the development process.

Design Thinking is an approach that prioritizes developing empathy for users, working in collaborative multidisciplinary teams, and using “action-oriented rapid prototyping” of solutions (2,6). It is an iterative process, with innovation emerging only after cycling through several rounds of ideation, prototyping, and testing, which distinguishes it from the traditional linear and often top-down approach to health intervention design (Figure 1) (1,2,4). Design Thinking has been used across sectors to solve complex problems, including the redesign of an elementary school curriculum to enhance student engagement (7), and in domains such as aviation (8) that, like health care, have high levels of risk. Design Thinking is similar to both “user-centered design” and “human-centered design,” which are both referred to as “Design Thinking” in this article.

Figure 1. Design Thinking process, stages of design thinking and examples of exercises used and questions asked in each stage, systematic review on Design Thinking in health care, search results through March 31, 2017. [A text description of this figure is available.]

There is much enthusiasm for the use of Design Thinking in health care, from intervention development to large-scale organizational and systems changes (9). However, health care settings present different challenges than do other domains, so it is important to consider these challenges in assessing whether Design Thinking provides added benefit over traditional approaches. With this in mind, the purpose of this review was to answer the questions, “How has Design Thinking been used to design interventions in health care settings, and have these interventions been effective?”

Data sources

Studies published through March 31, 2017, were identified through searches of online databases (PubMed, Medline, Web of Science, CINAHL, and PyscINFO) using the following search terms: “health,” “health care,” or “healthcare”; and “Design Thinking,” “design science,” “design approach,” “user centered design,” or “human centered design.” Additional articles were included if they were referenced as original research articles in existing articles. To provide an overview of the range of uses of the Design Thinking approach, we did not limit our review to specific populations or conditions and included articles addressing multiple health promotion and disease prevention topics. Given the search terms, the likely target populations for inclusion were patients and health care professionals and the settings in which they work or seek care.

Study selection

We reviewed selected articles using PRISMA guidelines (10,11) and entered citations into a reference manager, which removed duplicates. To be eligible for inclusion, studies had to be written in English, be published in a peer-reviewed journal, provide outcome data on a health-related intervention, and use Design Thinking in intervention development, implementation or both.

There are multiple definitions of Design Thinking, so we focused on the key principles common to most descriptions of the approach; thus, the list of Design Thinking approaches is not exhaustive. Studies were considered to use Design Thinking if they 1) described user/needs assessment, 2) involved iterative prototyping/testing of the intervention with user feedback, and 3) tested the intervention with target users (2,4). The user/needs assessment could include contextual observation of users in the setting in which they would interact with the innovation, interviews, narrative accounts, and documentation from users, gathering extreme user/outlier stories or a review of existing literature and work (2,6). Prototyping included activities such as creating a series of low-fidelity and high-fidelity prototypes of the potential innovation and refining it multiple times through iterative cycles of feedback from end users, stakeholders, and experts. Testing the intervention with target users included implementing and testing the innovation while continuing to refine it on the basis of user feedback and data (1,2,4). Design Thinking is also similar to other techniques, such as plan-do-study-act cycles and formative evaluations. We considered the emphasis on empathizing with the user and the use of low-fidelity prototyping to be key distinguishing features of Design Thinking, so only articles that explicitly indicate their use of these approaches were included. Initial screening was completed for all selected abstracts, and a second round of screening was completed on eligible full-text articles.

Data abstraction

Data were collected on target users, health conditions, objective of the intervention, details on the Design Thinking process, study design and sample, and reported health outcomes. If information was not reported in the article, we contacted the study authors. Studies were also evaluated to determine whether the intervention improved all targeted outcomes (successful), at least one targeted outcome (mixed success), or no targeted outcomes (not successful). Data quality was assessed using the National Institutes of Health’s (NIH’s) National Heart, Lung, and Blood Institute Study Quality Assessment Tools (12).

Study extraction

Figure 2 presents study flow based on the PRISMA study guidelines (10,11). After the initial search, the authors separately screened all abstracts based on the eligibility criteria. One author reviewed all full-text articles (N = 297), and a second author reviewed roughly 15% as a reliability check. Agreement on inclusion/exclusion was more than 80%. Any abstracts or articles for which there was disagreement or uncertainty were reviewed by 2 authors and discussed until consensus was reached. A total of 26 papers representing 24 interventions were included in the analysis. Two authors reviewed all included studies.

Figure 2. PRISMA 2009 flow diagram, systematic review on Design Thinking in health care, search results through March 31, 2017. [A text description of this figure is available.]

Study characteristics

A summary of all included studies is provided in ( Table 1 ). Eleven studies were successful (13–25), 12 reported mixed success (26–37), and one reported no success (38) (Table 1 and Table 2 ). Sample sizes of included studies ranged from 12 to 291, but most studies were small; 14 studies had fewer than 40 participants. Eleven (45.8%) used a control group (15,17,18,24,26–29,31,33,35,38,42), and 4 (16.6%) compared a design-thinking intervention to an intervention designed using traditional methods (17,18,24,26,35). Two of the studies included were “good” quality, 13 were “fair” quality, and 9 were “poor” quality. All studies used Design Thinking methodology in intervention development, and 3 also used it for implementation (16,20,25,43)

The 24 included interventions targeted a range of conditions, including 19 related to physical health (17 unique conditions), 2 related to mental health, and 3 related to systems processes. Approximately two-thirds of the interventions were mobile telephone–based or tablet-based.

Summary of findings by target user

Patient-facing interventions (n = 11). Five interventions were successful: 4 with a pre/post design (13,19,22,23,44) and 1 pilot randomized control trial (RCT) (15). Five reported mixed success, including one pre/post design (31), one pilot RCT (29), one RCT (28), one cohort study (47), and one unblinded, randomized crossover design (33). One, a pilot RCT, was not successful (46).

Provider-facing interventions (n = 9). Six were successful, including 3 studies using a pre/post design (16,20,25), one field experiment (14), one using a quasi-experimental crossover design (24), and one cross-sectional study (21). Three had mixed success, including 2 studies with an experimental crossover design (17,18,26) and one with primarily a pre/post design, one portion of which was a randomized crossover design (35).

Patient-facing and provider-facing interventions (n = 2). Both reported mixed success and were pre/post designs (30,34,45).

Caregiver-facing or family-facing interventions (n = 2). Both reported mixed success, one in a pilot RCT (27,39) and one using a pre/post design (32).

Summary of Randomized-Controlled Trials (K = 5). Of the RCTs and pilot RCTs reviewed, one demonstrated success on all outcomes (15,40), 3 showed mixed success (27–29,39,41), and one reported no enduring significant results (38,46).

Summary of studies directly testing Design Thinking methodology

Four studies directly compared interventions created with Design Thinking to interventions created with traditional methods. In one study with a within-sample experimental crossover design (26), a Design Thinking–based graphical information display to improve nurses’ ability to detect changes in patients’ physiological states in an intensive care unit (ICU) was compared with a conventional display in commercial, electronic ICU charting systems. The Design Thinking intervention resulted in improved detection of changes in patient states and greater ease of use, usefulness, satisfaction, and support of understanding, but no differences in workload for nurses (26). Another study using an experimental crossover design compared 2 computer interfaces designed to display drug interaction alerts, one developed using Design Thinking and one using traditional software (17,18). Whereas the design of the traditional software was not described, the traditional display included only basic text information. In this study, users (ICU nurses) were more efficient and effective, and reported higher satisfaction with the Design Thinking interface. Another study using a quasi-experimental crossover design used Design Thinking to develop an application to guide clinicians in detecting and scoring the severity of graft versus host disease (GvHD) (24). When compared with paper-based NIH guidelines, users of the application (app) signficantly improved diagnostic and scoring accuracy. A final study compared a Design Thinking–based app that provided nurses with information about antibiotic use with regular information sources (which were not described) (35). In the randomized portion of this study, nurses using the app found information on antibiotic use more quickly; however, the app did not enhance their ability to improve antibiotic-related behaviors. (Only 7 participants were included in the randomized portion of the study.) Whereas the development of the control intervention was not fully described in these papers, based on the limited descriptions given, it is likely that it did not include key elements of Design Thinking such as user feedback and prototyping.

The 24 interventions summarized in this review provide an overview of the breadth of Design Thinking’s applicability in health care and demonstrate that it is feasible and applicable to multiple health care domains. It has been applied across a range of diverse patient populations and conditions, including chronic obstructive pulmonary disease (28,34), diabetes (34,47), caregiver stress (27), and posttraumatic stress disorder (22). It also has been applied to systems process changes, such as nursing handoffs (16) and drug–drug interaction alerts (17,18). Results also demonstrate that, although it is often applied to electronic interventions, Design Thinking is feasible for use in other modalities (eg, on paper, in person).

Initial results of the interventions included in this review are promising; all but one demonstrated positive effects on at least one identified outcome, and half showed positive effects on all measured outcomes. In addition, in the studies that directly compared the Design Thinking intervention with a traditional intervention, the Design Thinking intervention generally demonstrated improved outcomes and higher usability and satisfaction.

However, none of these studies were RCTs with large sample sizes. Design Thinking interventions have been tested primarily in pre/post designs or pilot RCTs with small samples. Furthermore, most studies included were poor or fair quality, with only 2 being considered good quality. Importantly, the criteria used to assess quality were based on traditional research approaches, and many of the features of poor-quality studies were included by design; some had small sample sizes to generate insights and to test assumptions rapidly, and some were pilot studies. This feature of Design Thinking also may account for the limited use of large RCTs; however, this poses a challenge when evaluating the effectiveness of the approach. More work in this area using more rigorous methods and larger samples is critical to fully understanding the benefits of Design Thinking. Although many studies that used Design Thinking were excluded from our review because they did not include sufficient outcome data (n = 131), full-scale trials of many of these interventions are under way, results of which will provide more evidence about the effectiveness of this approach in health care. In addition, no studies measured Design Thinking directly to explain how or what components of Design Thinking lead to improved usability and effectiveness, limiting the field’s ability to disseminate the most effective components and refine the Design Thinking approach for health care.

Design Thinking methods varied among the studies reviewed. For example, only 6 studies conducted contextual observations of users during the needs assessment phase, no studies reported a brainstorming stage, 10 studies did not use low-fidelity prototypes, and some reported a small number of iterations (eg, one mixed-success trial had 4 intervention iterations, but only 2 iterations were evaluated with target users [27]). Using more thorough and structured Design Thinking methodology may have resulted in more consistent and enhanced outcomes. At the same time, Design Thinking is meant to be flexibly applied. Future work should balance that flexibility with the potential benefits of a more systematic approach.

Our results suggest that one area where Design Thinking could be especially useful is in designing interventions for underserved populations whose needs may be overlooked by other approaches. For example, the study of a mobile health tool for detecting and managing cardiovascular disease in rural India required significant feedback from the end users — minimally trained health workers — to ensure that the intervention was suited to their level of technological familiarity as well as the inconsistent technical infrastructure (eg, creating a one-touch navigation system) (21). Using Design Thinking allowed the multidisciplinary team to question assumptions and biases and develop an intervention that was successful, acceptable, and feasible to the actual users, an outcome that may not have been possible using traditional methods (21). Another study evaluated the impact of an education tool to enhance long-acting contraceptive use in a clinic serving mostly African American patients who were included early in the usability testing process to ensure the tool met their needs. Several changes were made as a result, such as including more peer testimonials, which likely increased the tool’s impact and relevance (29). In this way, Design Thinking could also pair well with other approaches that prioritize the inclusion of users in service of reducing health disparities, such as community-based participatory research (48).

Tensions when using Design Thinking in health care

In their text and through our analysis, the studies included in this review show several challenges to consider when applying Design Thinking to health care. First, there is the possibility of tension between what users want and what providers and researchers believe to be beneficial based on research and expertise (49). Whereas in industry, where an innovation designer may prioritize customers’ preferences to maximize profits, in health care a balance must be struck between creating interventions that are effective and sufficiently palatable and feasible so that they will be used by providers and patients.

Second, tension may exist between the needs assessment, a fundamental step of Design Thinking, and existing literature and evidence base for some conditions. That is, given the evidence, intervention developers may not be willing or see it necessary to conduct their own needs assessment using observation or interview strategies or to brainstorm creative solutions. Indeed, 7 of the studies included in this review reported literature reviews, and possibly expert consultation, as their only needs assessment steps, and none reported brainstorming. One way to overcome this tension is to view evidence as a set of design constraints in which needs assessment, brainstorming, ideation, and prototyping should occur.

A third possible tension relates to balancing the Design Thinking approach of understanding the narrative of outliers with traditional health research methods that prioritize statistics on large samples to produce generalizable results. Conclusions drawn from small user samples should be tested in broader populations to ensure their applicability. Mixed-methods approaches that use both strategies may reduce this tension. For example, a research team that uses a qualitative Design Thinking approach early in the research process (eg, user observations, focus groups, and usability tests with small groups of target users) may be able to generate insights into the key needs of the target population. This approach may also find ways to address these needs, and subsequent quantitative testing of the developed interventions in broader samples will allow the group to evaluate whether their assumptions generalize to the broader population, and the intervention will be more effective as a result.

Fourth, there is inherent tension between a central philosophy of the prototyping process in Design Thinking — to rapidly move through low-fidelity then high-fidelity iterations to fail early and often to more quickly reach a better design (50) — and the risk of serious negative outcomes due to health care failures (eg, death). Many of the studies did not use low-fidelity prototyping or multiple rapid iterations, perhaps because of this tension. However, although there may be some reluctance to experiment with low-fidelity prototypes in health care where morbidity and mortality are at stake, there are low-stakes approaches to low-fidelity prototyping that may minimize risk and improve the pace of innovation (eg, storyboards to illustrate a new clinic process).

Intervention development and implementation: case example

Considering the role of Design Thinking is important, not only in efficacious intervention development but also in effective implementation into practice (5). Only 3 of the included interventions addressed implementation, but this limited implementation provides insights. For example, in designing a new process for facilitating nurse handoffs between shifts, Lin and colleagues conducted an extensive 6-month intervention development design process that was user-focused and empathic and had rapid iteration in pilot sites (43). However, despite this strong preliminary work, the intervention was not readily accepted when implemented in other clinics. As a participant stated:

After the concepts had been co-developed and field tested with our pilot units . . . we assumed the units were “bought in” to the idea of the change. . . . Surprisingly, our approach to the training resulted in criticism and created skepticism [at other clinics]. . . . They attributed this to “not made here” sentiments from those units not involved in the original design.

To overcome this tension, the team involved additional stakeholders to develop a more user-centered process for the implementation of their Design Thinking innovation, after which they successfully implemented the innovation across 125 nursing units in 14 hospitals over 2 years (16). This study highlights the importance of understanding the context of the setting and users, both when developing and implementing an intervention using a Design Thinking approach. It should also be noted that this process required significant time and energy from stakeholders. One stakeholder commented, “Don’t get me wrong. What we did was fantastic. But it took a lot out of us” (43). This study highlights the importance of staying true to the user-centered nature of Design Thinking throughout the process — from development to implementation — to maximize implementation success. It also highlights the challenges in using this approach. Teams using Design Thinking should be prepared for a more intensive process than traditional, less iterative and user-centered methods.

Limitations

Given the varied outcomes included in the review and the inconsistent reporting of qualitative outcomes it was difficult to make comparisons across studies. The range of study types and limited number of large scale RCTs testing intervention effects also made it difficult to draw definitive conclusions about effectiveness. At the same time, given that there was only one study with a null result, there was likely publication bias, which may have led to overestimation of the effectiveness of Design Thinking. It is also possible that investigators used methods but did not report them (eg, prototyping). In addition, we did not assess the use of Design Thinking in other health care areas where it may be beneficial, such as the design of physical spaces. Finally, Design Thinking–based health care innovations that were developed and implemented outside research contexts may exist and are thus not reported in the literature.

Conclusions

Design Thinking is being used in varied health care settings and health conditions, and more studies are forthcoming. This review suggests that Design Thinking may result in more usable, acceptable, and effective interventions compared with traditional expert-driven methods. However, there is inconsistent use of the methodology and significant limitations inherent in the studies, which limits our ability to draw conclusions about this approach. Future studies may benefit from focusing on comparing interventions developed using Design Thinking methods with traditionally developed interventions, including those with RCT designs, and identifying the most useful components of Design Thinking methods.

Overall, Design Thinking is a promising approach to intervention development, implementation, and dissemination that may increase the acceptability and effectiveness of health care interventions by actively engaging patients and providers in the design process and rapidly iterating innovation prototypes to maximize success.

The research was supported by the Department of Veterans Affairs (VA), Veterans Health Administration, Health Services Research and Development Service (HSR&D). Dr Breland is a VA HSR&D Career Development awardee at the VA Palo Alto (15-257). The views expressed in this article are those of the authors and do not necessarily represent the views of the Department of Veterans Affairs. There is no copyrighted material used in this article, and no copyrighted surveys, instruments, or tools were used in this article.

The authors thank Ms Elon Hailu for her help editing the manuscript. At the time of the research, Dr Altman was affiliated with the Department of Psychology, Washington University in St. Louis, St. Louis, Missouri, and the VA Palo Alto Health Care System, Menlo Park, California.

Corresponding Author: Myra Altman, PhD, Postdoctoral Design Fellow, Clinical Excellence Research Center, Stanford University, 75 Alta Rd, Stanford, CA 94305. Telephone: 603-306-6231. Email: [email protected] .

Author Affiliations: 1 Washington University in St. Louis, St. Louis, Missouri. 2 VA Palo Alto Health Care System, Menlo Park, California. 3 Stanford University, Stanford, California. 4 Center for Systems and Community Design, Graduate School of Public Health and Health Policy, City University of New York, New York, New York.

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Abbreviation: DNR, did not report; NA, not applicable; RCT, randomized control trial; a If 2 studies are cited, the earlier article is the intervention development methodology and the later article is the evaluation study.

Abbreviations: App, application; CI, confidence interval; COPD, chronic obstructive pulmonary disease; GvHD, graft vs host disease; HBA1c, hemoglobin A1c; HCAHPS, Hospital Consumer Assessment of Healthcare Providers and Systems; HRQOL, health-related quality of life; IGID, integrated graphical information display; IUD, intrauterine device; NKE, nurse knowledge exchange plus; PTSD, posttraumatic stress disorder; SD, standard deviation a All results significant at P < .05.

The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the U.S. Department of Health and Human Services, the Public Health Service, the Centers for Disease Control and Prevention, or the authors’ affiliated institutions.

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Design Thinking to Improve Implementation of Public Health Interventions: An Exploratory Case Study on Enhancing Park Use

Terry t-k huang.

a Center for Systems and Community Design, Graduate School of Public Health and Health Policy, City University of New York, New York, United States of America

Jonathan Aitken

b Tacit Design Strategy, Vancouver, BC, Canada

Emily Ferris

Nevin cohen.

Design thinking, a human-centred, iterative process to innovate solutions aligned with communities’ tacit knowledge, has the potential to augment public health interventions. This paper presents a case study of a design thinking workshop to illustrate the process and methods to train public health researchers. A workshop was conducted to engage participants in a systematic, non-linear process of design thinking to design possible interventions to enhance use of renovated New York City parks.

Participants engaged in exercises to rapidly craft proposals for park re-design. The process involved learning about design methods to overcome limitations of linear thinking and how design thinking can be applied to public health problems that require community input.

The case study demonstrated the feasibility of training public health researchers in design thinking methods that can be applied to public health problems. With increased capacity, public health researchers could apply design thinking to community collaborations to develop solutions embedded in the unique contexts of the community.

Introduction

Despite increasing recognition of the need for environmental and policy changes to address complex health issues such as obesity and health disparities ( Gortmaker et al. 2011 ; Swinburn et al. 2011 ; National Center for Chronic Disease Prevention and Health Promotion 2015 ), data on the effects of these interventions remain limited. Some studies suggest that while introducing parks or supermarkets in under-served neighbourhoods may have many neighbourhood benefits, they do not necessarily lead to an uptake of the health behaviour the intervention was designed to address, such as increased fruit and vegetable consumption or increased physical activity ( Boone-Heinonen et al. 2011 ; Cohen et al. 2009 ). Changing availability and accessibility alone may be inadequate to change specific health behaviours ( Boone-Heinonen et al. 2011 ; Cohen et al. 2009 ). Issues within the design phase of an intervention, such as poor alignment with true community needs, relying on faulty or partial theories of change or lack of prototyping and testing, may exacerbate this disconnect between the specific aims of the intervention and the actual impact on the ground. This suggests the need for different methods of intervention design and implementation.

More intensive community input and involvement may help ensure the effectiveness and relevance of interventions to those receiving them. One method embraced by public health to address this issue is community-based participatory research (CBPR), which engages community members in the research process to ensure that researchers study the right questions, use appropriate research methods, and increase knowledge and capacity among community residents. CBPR calls for the equitable inclusion of community stakeholders – those affected by the public health issue in question – to be active partners in all stages of research. CBPR has been shown to increase trust in the research process and improve the quality of research, intervention design, and implementation ( Israel et al. 2013 ). Despite these benefits of CBPR, the research process, however participatory, remains limited to conventional tools such as surveys, interviews and focus groups that attempt to identify needs and design interventions through a linear (deductive or inductive) form of logic. These research techniques may be insufficient to innovate bottom-up solutions owned by the community from the outset which more directly align with the local context and thus are more effective and sustainable ( Mahr, Lievens, and Blazevic 2014 ).

From a systems science perspective, bridging the gap between the individual and the environment is crucial ( Huang and Yaroch 2009 ; Huang and Ferris 2016 ). Innovative approaches are needed to optimize the implementation of environmental or policy change so individuals adopt the intervention. One such innovative approach is design thinking, a problem solving framework and set of methods for developing an understanding of those affected by an issue, reframing the issue to generate creative ideas, and rapidly prototyping these ideas and learning from them in an iterative manner. The prioritization of user insights distinguishes design thinking from conventional technocratic design or problem-solving methods. It is well-aligned with CBPR principles but uses a non-linear, creative process that underlines many product and service design innovations in other fields ( Brown 2009 ; Lockwood and Walton 2008 ; Kolfschoten and de Vreede 2009 ).

Largely developed and implemented in the design field, design thinking is relatively uncommon in the health field ( Altman, Huang, and Breland In press .) and is not a standard method taught in public health schools, in part due to the strong positivist, linear cause-and-effect tradition that dominates public health. Because our research team is involved in the evaluation of a large natural experiment on the impact of citywide park redesign and renovation on New York City residents’ physical activity, mental health and quality of life ( Huang et al. 2016 ), we sought to build internal capacity to use design thinking to generate ideas about how to increase park usage among community residents post-renovation. We aimed to gauge the feasibility of training public health researchers in design thinking by conducting a workshop with our own colleagues ( d.school 2017 ; Brown 2009 ). We did not cover the full scope of prototyping and testing, due to time constraints, but focused on the ideation of design concepts. The goal of this paper is to illustrate the potential utility of integrating design thinking as a tool that could complement traditional public health methods to enhance innovation, while recognizing that the scope of the design thinking process depends on the design challenge.

We assembled a team of nine researchers, including five public health faculty and four graduate students, in a day-long design thinking workshop in November 2016. The goal was to engage in a series of exercises that demonstrated key design thinking concepts and, through a hypothetical project, applied design thinking to a public health problem: creating the physical space and programming that would increase park use and thereby increase physical activity. This public health problem was selected because of the research team’s existing work evaluating the impact of citywide park redesign and renovation. The workshop was led by one of the authors who is a designer with extensive experience in implementing collaborative design thinking projects (JA). The co-authors, along with six other colleagues, were participants in order to build internal capacity and gain a basic understanding of the feasibility of incorporating design thinking into public health research before engaging with outside community members. Participants, all design thinking novices, were clustered into two groups of 4–5 people. Participants included both regular park users and non-users. While demographic information was not collected, the participants were university students and faculty and therefore had a number of years of higher education.

The workshop adapted the critical steps from the Stanford Design School’s protocol for design thinking: empathizing, defining the problem, ideating, prototyping, and testing (d.school). This protocol was selected as the Stanford Design School is considered a leader in design thinking. The first two steps represent ‘need-finding’ and involve a deep exploration into ‘tacit knowledge’ that may be hidden from the stakeholders. Tacit knowledge is knowledge that everyone has but is so taken for granted that few of us even realize that we have it. This knowledge comes from experience, perception, emotions, visceral senses, attitudes and values to which we are trained to avoid paying attention as scientists ( Polanyi 1967 ; Nonaka 1994 ; Mareis 2012 ; Kothari et al. 2012 ). Tacit knowledge can inform solutions that better fit stakeholders’ needs. Following need finding, ideating, prototyping and testing design solutions constitutes an iterative rather than linear process, unlike conventional public health methods. As opposed to moving from hypothesis to test, design moves from need to multiple ideas, then prototypes and tests (and often back to revising ideas). The ideas come from a creative process, not purely from previous results. Outputs do not need to perfectly represent the ideas. The cycle from ideas to prototypes, tests and new ideas moves rapidly, as the most important thing is to fail often and rapidly, so that the most innovative, promising solutions can emerge ( Brown 2009 ).

The workshop involved engaging the researchers in a sequence of exercises to introduce the concept of design and design thinking and to engage the researchers in the process.

Introduction to Tacit Knowledge

To illustrate the value of tacit knowledge to the design process, the researchers were led through a 45-minute long activity, Stanford’s ‘wallet exercise.’ Participants were asked to spend a few minutes developing wallet design ideas, without preparation. Next they were directed to identify the characteristics of an ideal wallet for one specific person by asking open-ended questions that probed for emotions, values and needs. Based on this information, they were asked to create a new personalized design. They worked individually and sketched their designs and then discussed the designs with the group. The goal was to orient participants to consider how tacit knowledge can affect design outcomes, and to experience the value of rough prototypes in generating understanding and feedback.

Recognizing limits of implicit assumptions

Two ‘mini exercises’ (the ‘9-dots’ exercise and ‘dividing-a-square’ exercise) were assigned to illustrate the assumptions we bring to problems and how assumptions often limit our ability to devise a solution. Participants were given 5 minutes to connect 9 dots arranged in a square (3 by 3) without lifting the pen from paper, with 4 straight connected lines. The only solution is to allow the lines to extend past the implied boundaries of the rectangle, yet most people assume that lines must fit within the square and don’t question the parameters.

Value of Iterative Design

In the third exercise, participants were asked to divide a square into 4 identical and equal-sized shapes, within 5 minutes. This activity illustrates how initial solutions to problems are obvious—most people quickly reach the same results. When pushed to further iterate, participants generated additional solutions, demonstrating the power of iteration and how quickly generating variations on a solution requires and encourages creative thinking. This process illustrated opportunities in moving beyond obvious designs to a wider range of choices, and that the same solution set could be arrived at through different cognitive and physical pathways.

Identifying Design Assumptions

The fourth exercise required participants to spend 20 minutes to consider current uses of parks and assumptions the participants held about park design. The aim was to make explicit the usually implicit constraints people might apply to a more complex design problem, such as a whole-park redesign.

Several exercises illustrated the ideation process. The participants were asked to reimagine parks and how they connect to communities. Participants were asked to consider open-ended questions designed to elicit different approaches to the problem space. These included probing for emotions, values and attitudes around parks to move participants beyond preconceived notions of parks. Participants had 90 minutes to consider such questions as:

• Do parks play a role in local social networks?
• What does that connection look like?
• How do I want to feel in a park?
• What do parks represent to me?
• What values do parks embody?

Participants visualized the answers on paper, an iterative process that itself involves thinking, drawing, discussing, stepping back and explaining, receiving feedback, and revising. This step allowed participants to respond to each other and make direct connections among concepts. In 30 minutes, the groups developed mission statements encapsulating their collective understanding of parks and community.

The final activity required the participants to use the mission statement to brainstorm and generate multiple ideas for community parks as quick sketches in 90 minutes, without judging or evaluating the ideas, and disregarding practicality. They considered the social context of the park, and how changes to that network might affect park usage.

Wallet Exercise

By providing a contrast in experience from an ‘expert led’ design process to a ‘human-centred’ process, the wallet exercise effectively demonstrated the power of tacit knowledge in designing a product that ‘fits’ a user. In all cases, the intended user preferred the second wallet over the first.

Mini-exercises

As expected, only one participant solved the ‘9-dots’ exercise. One participant generated 5 designs in the ‘dividing the box’ exercise, but most developed 3–4 designs. While there is an infinite number of designs possible in this exercise, most people did not consider the possibility of dividing lines in the box that were not straight ( Figure 1 ). In discussing this possibility participants noted the constraints of prior assumptions and the value of forcing multiple iterations of design solutions.

The ‘9 dots’ and the ‘Dividing a square’ exercise

Probing exercises

The open-ended exercises which probed for values, emotions and attitudes around parks generated the following results.

The participants identified the following park uses ( Table 1 ): diverse individual and group activities; a space for physical activity and passive recreation; engagement with nature; a space for organized events and organic social gatherings; to facilitate structured activities and programming such as concerts; as spaces for illicit activities; and as a facilitator of social connections and networks by providing gathering space for different groups such as parents/caretakers and as venues for informal social gatherings including pick-up sports.

Current park uses and implicit assumptions regarding park design

Participants discussed the assumptions they were making during the park design process. They noted that current park functions underpin many of the implicit assumptions held when re-designing or renovating parks ( Table 1 ). These implicit assumptions related to park design include the value of parks as places to experience nature, engage in physical activity or passive recreation, and socialize. Additional implied assumptions focused on the possible impacts of parks beyond their borders, including the potential to raise adjacent property values and the potential for dangerous or illegal activity. Participants noted that their own class, race, gender and cultural backgrounds influenced their implicit assumptions.

Participants explored the connections that exist between parks, local social networks and communities. As they sketched the elements of the park they were designing, each participant explored how he/she wanted to feel in the park, what the park would look like, what it represented, and the values that it embodied. Parks and local social networks might connect in several ways ( Table 2 ), including as a space for existing networks or defined groups to meet. Existing communities could use, appropriate and transform parks to meet their needs and help to strengthen or grow the community. Alternatively, parks could serve as a setting for communities to develop organically through the common use of park features. For example, communities of parents/caretakers might form around their children’s use of playgrounds.

Connections between parks and social networks

Participants discussed how parks could embody a community’s values or represent different emotions or attitudes for different residents. Further, parks could play a role in shaping a community’s identity. Parks could contribute to a neighbourhood’s sense of safety and the natural landscape might add to the neighbourhood’s liveability. Residents might be exposed to different people, activities and cultures through their local park. Moving beyond parks as a place to connect with nature, socialize or engage in physical activity, parks could also serve as a focal point for neighbourhood pride and as a representation of civic engagement, neighbourhood vitality or community ownership. Additionally, parks could reflect the culture or history of a neighbourhood.

Participants developed mission statements that articulated what feelings they wanted the park to foster, the activities that could engender these feelings, and how the park could embody the values that lead to such feelings ( Table 3 ). The mission statements included goals at both the individual and community level. Some mission statements focused on individual growth fostered through park programming and space for solitude and reflection. Mission statements focused on the broader community including goals such as civic engagement, community belongingness, pride and ownership. For example, some supporting activities and features generated included inviting spaces for people to sit together, provision of refreshments, or culturally relevant programming. Incorporating features or programming designed for a diverse age range was thought to increase accessibility and further the goal of belongingness.

Mission statements and supporting activities for redesigning parks

Designing your park

The wallet and ‘mini-exercises’ helped participants consider design from an emotion/value based perspective and encouraged innovation and iteration. Based on this newly established framework, participants applied a similar process towards designing parks. Before iteration began, groups considered community-based values, and supporting activities. This was then distilled into an overarching design principle or mission statement to guide participants in the iterative stage. Examples of the links between these values and the designs they fostered can be seen in Figure 2 . Civic engagement, for example, was established as a value early in the iterative process and its influence on proposed activities, mission statement and design outcomes is clear. Another group considered that spaces that facilitated networks was an important way to link communities to parks. This concept was reflected throughout the process, and manifested as collective and market spaces in a park. Another example showed that a community might feel more ‘ownership’ of a park if there was a natural connection to the neighbourhood through a blurred sense of park edges, rather than rigid boundaries or fences.

Examples of the links between the values around parks and the associated park designs

While prevalent in other fields, public health practitioners rarely use design thinking. Design thinking is non-linear and iterative. It emphasizes hands-on doing, not just thinking. It encourages failing often and quickly as a key path to innovation. This contrasts with conventional problem solving approaches in public health. This paper illustrates that it is feasible to train public health researchers to begin to think in design terms, and that within a one-day workshop a research team can generate diverse ideas that could inform future implementation strategies of park renovation interventions. Workshop participants identified the diverse emotions and values associated with parks, and a wide range of activities that might help foster these emotions or values. By incorporating deeply held emotions and values in the design of park prototypes, the public health researchers were able to imagine ways design thinking might enhance the impact of parks’ physical renovation. Furthermore, examples from the ‘Designing your park’ exercise suggested that considering community values as an integral part of the design process directly affected design outcomes.

Design thinking by non-designers

Design thinking encompasses a wide range of activities focused on providing a replicable process-oriented approach to creativity and innovation. This emphasis on a systematic process rather than on an expert-driven model allows its application to various disciplines by non-design research practitioners. Edward de Bono championed lateral thinking as a useful method of problem solving that is ‘concerned with breaking out of the concept prisons of old ideas… [leading]…to changes in attitude and approach’ ( De Bono 1983 ). de Bono pioneered this as a process learnable by anyone. Many design thinkers have extended de Bono’s ideas. Sanders and Stappers base their ideas of co-creation around the assumption that everyone is creative, and that given the right tools, lay people can contribute to the design process ( Sanders and Stappers 2012 ; Sanders and Stappers 2008 ). Design thinking could potentially facilitate implementation science and health disparities research. Public health interventions often fail to translate into the real world due to misalignment with the context in which they are delivered ( Lobb and Colditz 2013 ). Community participation in human-centred design may ameliorate this, ensuring that intervention strategies address the tacit knowledge held by target audiences of interventions from conception. This could represent a novel way of undertaking CBPR and of improving intervention implementation outcomes, but future research is needed to explore this approach further. Though incorporating community feedback is out of the scope of this case study, there are many examples from other fields demonstrating how the inclusion of design thinking into the community setting can help enable community stakeholders to be in the driver seat to generate bottom-up solutions that would be truly tailored to the specific needs of a community ( IDEO. 2018 ; Center for Systems and Community Design 2018 ).

Design thinking applied to health

Design thinking has only recently been applied to solving complex health problems, though there is growing interest in doing so from the design and healthcare sectors( Altman, Huang, and Breland In press. ). These collaborations demonstrate how systematic approaches to creative innovation can be applied to issues in diverse healthcare contexts. Previous projects have incorporated design thinking to improve employee workflow ( Shaikh et al. 2017 ) and patient experience ( IDEO, 2012 ; MindLab n.d. ). Other researchers incorporated elements of design thinking to increase the uptake and efficacy of mobile health behaviour change interventions ( Fjeldsoe et al. 2012 ; Mummah, King, et al. 2016 ). The Alameda County Public Health Department underwent a human-centred design pilot to increase internal capacity and to innovate strategies to stimulate the local economy as part of Oakland Best Babies Zone, a place-based initiative to reduce infant mortality inequities ( Vechakul, Shrimali, and Sandhu 2015 ). Recognizing gaps in the health sector’s capacity to implement design thinking models, frameworks for co-creation and learning ( Elg et al. 2012 ; Mummah et al. 2016 ) have been advanced to help healthcare professionals operationalize these models. Researchers have started to examine outcomes of interventions developed with design thinking. For example, based on an iterative, co-design process, a hand hygiene compliance (HHC) intervention modified alcohol-based-rub dispensers to monitor frequency of use and centrally project the frequency data, providing real-time feedback to hospital staff and visitors. Use was higher on dispensers with data visualization, and staff reported increased motivation for HHC ( Kupis et al. 2017 ). Further research is needed to better understand and measure how the inclusion of design thinking processes in healthcare interventions impacts health outcomes.

Challenges using design thinking in public health

The workshop illustrated specific challenges in the application of design thinking in a public health setting. Largely developed by the design field, design thinking methodology has not been readily accessible to public health professionals. Those trained in traditional evidence-led processes may be suspicious of design thinking, and its emphasis on empathy, tacit knowledge and ‘disruptive change.’ As discussed by Jones in Design for Care , ‘Because change incurs both costs and risks, healthcare has significant incentives not to change the system’( Jones 2013 ) which discourages the adoption of new systems or disruption. This systemic conservatism maintains stability, but inhibits necessary changes. Public health professionals’ knowledge of existing systems and barriers to change inhibits new thinking. Furthermore, increasing ‘silo-ization’ and reduced budgets create an environment where change may indicate a subsequent loss of power—and protection of the status quo becomes the default. In the pilot workshop, though public health participants were engaged and enthusiastic, interesting limitations emerged. For example, while open-ended exercises generated rich discussions, participants seemed uncertain as to how to proceed, and outcomes were mostly simple lists. These participants, like most non-designers, were unaccustomed to thinking through sketching and may have been uncomfortable or unfamiliar with brainstorming and iteration; both essential components of design thinking. As discussed by Barbara Tversky, ‘drawings are an integral part of the dialogue a designer conducts with him or herself during design. They are a kind of external representation, a cognitive tool developed to facilitate information processing’( Tversky 1999 ). Designers spend years refining visual communication and iteration skills. Health professional workshop participants were more comfortable discussing ideas than sketching them.

Though participants were comfortable discussing questions, at the ideation phase, most drew independently without interacting or adding to each other’s ideas. In addition, the workshop revealed that public health professionals, like most non-designers, have some difficulty adapting to the non-linear needs of design thinking, which could be ameliorated with practice. Where possible, providing more physical materials could further stimulate creativity. If participants get stuck, workshop facilitators should de-emphasize the importance of the quality of drawings to allow participants to create quickly, without being limited by their sketching abilities.

Public Health Implications

The public health community generally is organized around the scientific method, which reflects a linear approach to problem solving. While the field has acknowledged the importance of engaging the community as participants in research, often the methods remain conventional, linear, and therefore limited in fostering innovation. This is necessary but not sufficient in public health, where many interventions - even those based in evidence-led strategies - do not achieve their desired impact due to poor or insufficient design. Linear thinking may be even more limited in addressing public health and community systems , which are complex and messy. Design thinking offers a way forward by providing a structured and replicable process for creative problem solving. This process allows for new connections between existing ideas and encourages rapid prototyping in order to identify issues or problems early on in the process. This paper shows that it is possible to increase public health researchers’ capacity to engage in design thinking, and challenges around visual thinking could potentially be overcome through further refinement of the design thinking tools used. With increased capacity, public health researchers could incorporate and adapt design thinking into the intervention design process as a tool to gather and employ greater community insight.

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Bringing Design Thinking to Public Health

Through creative problem solving and community collaboration, design thinking can help public health create targeted solutions to health challenges.

Design thinking, or human-centered design, is a creative approach to problem solving that began in product design but has broad, interdisciplinary applications in public health practice.

Liz Chen, PhD, MPH , assistant professor of health behavior, serves as the design thinking lead at Innovate Carolina and co-leads the Carolina Graduate Certificate in Innovation for the Public Good . Unlike other problem-solving approaches that use empirical data to move forward and find a single solution, Chen says design thinking involves going backward, in a sense, to further understand a problem in context alongside people who are impacted by the challenge before trying to solve it.

“We rely on building empathy and letting end users lead,” Chen says. Design thinking practitioners work with those experiencing a public health challenge to design multiple potential solutions. Constant data collection, iteration and learning from failures are built into the process.

Design thinking goes hand in hand with approaches like community-based participatory research, Chen says, where communities have more power in generating solutions than other public health approaches. Design thinking also involves small-batch, cyclical testing similar to implementation science and continuous quality improvement processes.

“Our students look for ways to engage directly with audiences so they aren’t the ones holding all the power and making decisions about how interventions look,” she says.

— Liz Chen, PhD, MPH

While a Master of Public Health (MPH) student in the health equity, social justice and human rights (EQUITY) concentration, Jared Bishop (’21) worked as one of Chen’s design thinking research assistants. He joined the Supplemental Nutrition Assistance Program-Education (SNAP-Ed) team at the UNC Center for Health Promotion and Disease Prevention’s Food, Fitness and Opportunity Research Collaborative (FFORC) to help design educational opportunities for caregivers of young children. They partnered with Cooking Matters, a national program that teaches participants to use nutrition information to make healthier choices and cook delicious, affordable meals.

The FFORC team’s multi-stage, multilayered process was grounded in design thinking. Bishop and colleagues identified places where caregivers would prefer to access food skills education: health care settings, schools or early childhood education centers, and food retail environments — specifically, grocery stores. They conducted separate design thinking processes for each.

Inside grocery stores, they held caregiver-only sessions to identify “pain points” and “happy points” about the shopping experience and then held cocreation sessions with managers who implement SNAP-Ed in different states. 

“We did design thinking with an equity focus,” Bishop says, “centering the voices of caregivers. Not only did we listen to their feedback — we made sure their voices were uplifted when we worked.”

The process made the caregivers feel seen and heard, Bishop says. “Hearing that other parents have the same concerns about navigating those areas was comforting for them, knowing they’re not alone.”

The FFORC team’s project resulted in a publicly available toolkit and roadmap to use design thinking to build SNAP-Ed plans.

Margaret Benson Nemitz, MPH, an alumna of the health behavior MPH program, and colleagues at the North Carolina Institute for Public Health (NCIPH) implemented design thinking with local health departments to plan how they might reach their annual goals better.

“There are many similarities between what human-centered design teaches us and what strategic planning teaches us,” Benson Nemitz said.

They recruited six local health departments in N.C. to participate on a design team. They framed their challenge through a design thinking lens: “How might we design a support system for quality improvement for all local health departments while providing for differences among health departments?” The participants, all new to design thinking, met monthly from July to December 2021.

“No one knew what to expect. No one knew how to think in this way."

— Margaret Benson Nemitz, MPH, NCIPH community assessment coordinator

“No one knew what to expect. No one knew how to think in this way,” she said. “It was fun to watch representatives get comfortable drawing their ideas, asking big questions and us all being confused together.”

They spent time with a literal drawing board, Benson Nemitz said, even adding things they later determined wouldn’t work in practice alongside the ideas they thought would work. But that openness, creativity and quick feedback are built into design thinking. 

“It was interesting how foreign the process felt to the group,” she said, “and how much joy there was. How much freedom and fun and play.”

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Designing Creative Solutions to Health Care Challenges

A new UArizona Health Sciences class is preparing students from across the university to creatively solve health care challenges using design thinking.

Approximately 1 in 10 people will suffer from kidney stones at some point in their lives, experiencing symptoms such as severe lower back pain, blood in the urine, nausea, vomiting, and fever and chills as a result.

Having an opportunity to work on an actual health care problem like kidney stones was exactly what Bridget Slomka was looking for when she signed up for a new University of Arizona Health Sciences class that teaches students an innovative way to approach problem solving.

Tom Knapp and Bridget Slomka listen as Kasi Kiehlbaugh, PhD, talks through a concept during a Design for Care Workshop: Addressing Health Care Challenges with Design Thinking class.

“The treatment for kidney stones is so painful,” Slomka said. “It’s time consuming and repetitive. We said, ‘What if we prevented them in the first place?’”

Together with fellow biomedical engineering graduate student Tom Knapp , Slomka created a project that used design thinking to identify new solutions to reduce the risk of kidney stone development and recurrence. She was aware of a calcium plaque, known as Randall’s plaque, that is linked to the chronic formation of kidney stones.

“There is a whole field of medicine for people recurrently suffering from the condition, and there's a lot of potential for improvement,” Knapp said.

By applying design thinking skills, Slomka and Knapp arrived at their solution for kidney stones: targeted microbubble therapy. Microbubbles deliver drugs to targets in the body. Once they reach their intended target – in this case, the Randall’s plaque – ultrasound can be used to burst the bubbles and release a drug to reduce or prevent the plaque formation

Design in problem solving

“Design thinking is about learning how to creatively approach problems,” said Kasi Kiehlbaugh, PhD , director of the Health Sciences Design program.

Dr. Kiehlbaugh assists a student through the ideation process, which is one of the five basic concepts of design thinking: empathize, define, ideate, prototype and test.

Dr. Kiehlbaugh also teaches Design for Care Workshop: Addressing Healthcare Challenges with Design Thinking , which focuses on a human-centered process to creatively address unique problems. Undergraduate and graduate students learn how to apply design thinking principles, as well as experiential and project-based collaborative learning, to solve health and wellness challenges.

She structured the inaugural course as a workshop, meeting once a week for two-and-a-half hours. Her class of seven students included six biomedical engineering students and one speech, language and hearing sciences doctoral student. The first phase of the class covered the design thinking process, after which students focused on individual and team projects.

The design thinking toolkit

The basic principles of design thinking center on five concepts: empathize, define, ideate, prototype and test. However, there is not a rigid structure for how to approach a problem.

“Design thinking is about learning how to creatively approach problems.” Kasi Kiehlbaugh, PhD

“It’s definitely not a set of steps you follow,” Dr. Kiehlbaugh said. “It’s about giving students the confidence to know when, where and how to use these skills in any situation they encounter.”

At the heart of the design thinking process is the skill of empathy, the ability to fully understand the problem someone is facing. This can include why something is of concern to a person, how they face and encounter the problem, and how the problem affects that person. These answers then shape the ideating process, which is similar to brainstorming.

“Ideating is meant to be a broader understanding in that space where you’re trying to generate new ideas that encompass a lot of other tools,” Dr. Kiehlbaugh said.

Students utilize a variety of materials to develop prototypes and test ideas during the class.

Those tools include strategies such as lateral brainstorming, which uses a random word to stimulate new ideas. Another valuable method is journey mapping, a process Dr. Kiehlbaugh says allows students to “visually represent the emotional journey and the physical journey of the person at the center of the problem.”

Slomka and Knapp put these tools to use for their kidney stone team project.

“One of us took the patient's perspective, the other one took the physician's perspective,” Slomka said. “We would ask how this treatment integrates and how does it appear to both of these different groups?"

Making an impact

Some class projects, like Slomka and Knapp’s, were conceptual, some were carried out through prototyping, and others were ready to produce real-world solutions.

One group of students discussed some of the logistical challenges faced by COVID-19 vaccine point of distribution sites, such as the one at UArizona. They considered solutions to more efficiently train volunteers, such as using simple videos to cover basic on-boarding and procedures for various jobs.

The idea was accepted and implemented.

“This demonstrated they could work to create solutions to address specific needs and present them to university leadership or state-level leadership,” Dr. Kiehlbaugh said.

At the end of the semester, students present their projects to a panel of faculty members from different colleges and disciplines.

In future semesters, Dr. Kiehlbaugh envisions classes that include not only students from the five Health Sciences colleges, but also students from a variety of academic backgrounds, including English, humanities, drama, math and other departments across campus. The value of this kind of intellectual diversity was seen first-hand as students were brainstorming new ways to administer COVID-19 vaccines and reduce vaccine hesitancy.

The six biomedical engineering students approached the topic based on the continued use of a traditional injectable vaccine. But Bryan Wong, a student in the Department of Speech, Language and Hearing Sciences, looked at vaccine delivery differently and contributed a few more novel ideas: What if the vaccine could be administered as an inhalable shot or edible?

That is the kind of creative problem-solving needed to solve the biggest health care challenges, and Dr. Kiehlbaugh believes design thinking can help make it happen.

“Human health is a universal thing we all care about,” Dr. Kiehlbaugh said. “That is what is a great about an open program like this. It is a place where interprofessional education can happen in a really organic and exciting way.”

What Is Design Thinking?

Our Experts

Kasi Kiehlbaugh, PhD

Blair Willis 520-419-2979  [email protected]

Health Sciences Office of Communications 520-626-7301 [email protected]