Conquering CHD
Conquering CHD, formerly the Pediatric Congenital Heart Association, is a congenital heart disease (CHD) patient advocacy organisation in the United States of America. Conquering CHD exists to conquer the most common birth defect. This is accomplished through awareness, knowledge, community, and research. One of the pillars of this organisation is patient and family engagement. This tenet extends into research as well. Beginning in 2013, Conquering CHD has strived to involve the patient and family voice in decision-making and prioritising of advocacy resources. With this in mind, it was the aim of Conquering CHD to inform the landscape of research priorities important to patients and families through the development of a patient-driven research agenda.
Participatory design in healthcare
Participatory design is an approach to problem-solving that utilises the knowledge and opinions of groups of people to generate plans and new ideas. This method has proven particularly fruitful in industries that have enabled their employees to provide input on system-wide decisions. Reference Marshall, Cain and Payne1 Crowdsourcing, an approach within the realm of participatory design, describes the outsourcing of a problem or task to a community of individuals rather than to specific individuals. Reference Weiner2 The process of crowdsourcing can generally be described by three main components – identification of tasks, an online or open call for work, and a large group of distributed people. Reference McCartney3 Though healthcare is typically a patient- or family-centered delivery model, the use of this method of data and thought acquisition represents a powerful tool in the identification of patient- and family-centered research priorities. Reference Weiner2 This also offers the opportunity to engage with patients and empower them to shape the systems that affect their health. Reference Donetto, Pierri, Tsianakas and Robert4 Patient and family participation in such data mining may prove critical in shaping health policy and decisions. Reference Weiner2
Crowdsourcing is becoming an increasingly popular tool in medical research. Several applications, including clinical and translational research, study recruitment, medication and genomic data, and community feedback and engagement have all demonstrated effectiveness. Reference Tucker, Day, Tang and Bayus5 This method offers a low-cost opportunity to collect massive amounts of data, but is not without its shortcomings, particularly generalizability to the general population. Reference Tucker, Day, Tang and Bayus5 However, this approach is not frequently utilised in paediatrics or CHD. This cross-sectional study and literature review aim to assess the priorities of patients and families in CHD research and to determine the reflection of these areas in the current body of scientific literature. In addition, this evaluation seeks to demonstrate the effectiveness and feasibility of crowdsourcing in CHD. It is anticipated that more patient-centered items including valve replacement, psychological/emotional effects, and access to care will score more favourably and likely will not reflect a correlation with current scientific literature.
Materials and methods
Survey design and distribution
After years of informal discussion, Conquering CHD planned a digital survey asking patients and families to rank the importance of specific types of research as it related to CHD in their lives. To generate the list of items included in the survey, Conquering CHD staff, volunteers, patients, and their families had informal discussions. These conversations blossomed into more robust discussions amongst the same populations and eventually garnered a preliminary list of research objectives. This was launched as an online survey, the “PCHA Research Priorities Poll” which contained an opening explanatory paragraph with definitions, five required questions, and six voluntary demographic questions. The survey took respondents an average of 7 minutes to complete.
The crowdsourcing tool was publicly released on September 6, 2019, and closed on October 1, 2019. During that time, the survey garnered 527 responses. Using Conquering CHD social media platforms on Facebook, Twitter, and Instagram, the digital survey targeted any individual with a patient or family connection to CHD. It is important to note that there was no age restriction on the tool and respondents may have included teenagers completing the survey on their own behalf. Posts included the survey link, QR code graphic, and a call to patients and families, which were shared on September 6, 2019, September 17, 2019, September 23, 2019, and September 30, 2019. The questionnaire was distributed through social media and email to 43,168 accounts across all platforms.
The tool was available only in English and asked participants to rank items within broader categories including “Technology Advances,” “Genetic and Cellular Research,” “Broad Understanding of CHD,” and “Psychosocial Outcomes” in order of importance, with “1” representing the most preferred item. The items provided are as follows: in “Technology Advances”, valve replacement, circulation assist devices, paediatric devices and pacemaker alternatives; in “Genetic and Cellular Research”, stem cell research, tissue culture, predicting CHD, genome association screening, genome engineering, and animal models; in “Broad Understanding of CHD”, access to care, long-term impact and early detection; in “Psychosocial Outcomes”, psychological/emotional effects, neuropsychological issues, and access to medical records. In addition, the survey queried general demographic data, including relationship to CHD, age, level of education, income, and race/ethnicity. Anyone engaged with Conquering CHD was eligible to complete the study, including patients and families.
Statistical analysis
Data analysis was done with the R software. 6 Inferential analysis was done to compare the mean rank between options for each category of Technology; Genetic and Cellular Research; Broad Understanding of CHD; and Psychosocial Outcomes. Among each category, we compare the mean rank between the different options to help represent the magnitude of predilection among them. For this, we use Bayesian Multilevel random intercept ANOVA with the brms R package. Reference Bürkner7 Bayesian inference allows to state direct inferences for the parameters of interest without needing a null hypothesis, and this is done by conditioning the model by the observed data. Reference Kaplan8,Reference Gelman, Carlin, Stern, Dunson, Vehtari and Rubin9 Bayesian inference is described by a point estimate and the respective 95% credible interval. Multilevel modelling is applied to account for the same subject ranking all options within each category. Reference Hox, Moerbeek and Van de Schoot10 This model enables accounting for dependent responses, making direct inferences, and comparing the mean ranks between options.
Evaluation of correlation of priorities with current literature
The largest medical databases utilising Boolean search were identified including PubMed, Scopus, and ScienceDirect. These were queried for all articles in “congenital heart disease” alone over the past 5 years as of June 1, 2020. Then each database was queried for each identified research item using Boolean operators (i.e. (congenital heart disease) AND (valve replacement)) to generate the number of articles published under each topic. The relative percentage of total articles per topic was then obtained. Subsequently, Spearman’s correlation was performed comparing the raw survey results to the number of articles obtained per topic to determine if there is concordance between priorities identified by crowdsourcing participants and the current body of literature on CHD.
Results
Demographic data of the survey participants are summarised in Table 1. The summarised rank of research items within each category is described in Table 2.
Table 1. Participant demographics and characteristics
Table 2. Mean rank comparisons by subcategory
Regarding the mean rank comparison for “Technology Advances” preferences, pacemaker alternatives present the higher mean rank (M = 3.13, SD = 0.99), followed by paediatric devices (M = 2.57, SD = 0.89), circulation assistance devices (M = 2.22, SD = 1.12), and valve replacement (M = 2.07, SD = 1.14). When comparing the mean rank between circulation devices versus pacemaker alternatives, we find circulation being preferred with 95% confidence interval (M = 0.91, SE = 0.06, 95% CI = 0.79, 1.04). Similarly, when comparing circulation devices versus paediatric devices, the circulation devices are preferred with 95% confidence interval (M = 0.35, SE = 0.06, 95% CI = 0.22, 0.47). On the other hand, valve replacement was preferred over circulation devices with 95% confidence interval (M = −0.15, SE = 0.06, 95% CI = −0.28, −0.03). Comparing pacemaker alternatives with paediatric devices, we find that paediatric devices were preferred with 95% confidence interval (M = 0.57, SE = 0.06, 95% CI = 0.44, 0.69). Similarly valve replacement was preferred with 95% confidence interval over pacemaker alternatives (M = 1.06, SE = 0.06, 95% CI = 0.94, 1.19). Lastly, by comparing paediatric devices with valve replacement, valves were preferred with 95% confidence interval (M = 0.50, SE = 0.06, 95% CI = 0.38, 0.62).
In the area of “Genetic and Cellular Research,” the topic with the lowest mean rank is stem cell research (M = 2.53, SD = 1.44), followed by tissue culture (M = 2.94, SD = 1.62), predicting CHD (M = 3.16, SD = 1.74), genome association screening (M = 3.35, SD = 1.44), genome engineering (M = 3.99, SD = 1.54), and animal models (M = 5.03, SD = 1.18). When comparing animal models with any other topic, we are 95% confident that any other topic is preferred. The mean rank differences are as follows: genome association screening (M = −1.68, SE = 0.09, 95% CI = −1.86, −1.49), genome engineering (M = −1.04, SE = 0.09, 95% CI = −1.22, −0.86), predicting CHD (M = −1.87, SE = 0.09, 95% CI = −2.05, −1.70), stem cell (M = −2.50, SE = 0.09, 95% CI = −2.69, −2.31), and tissue culture (M = −2.09, SE = 0.09, 95% CI = −2.28, −1.91). When comparing genome association screening, we are 95% confident that it has a lower mean rank than genome engineering (M = −0.64, SE = 0.09, 95% CI = −0.82, −0.46), and present a higher mean rank than the other topics: predicting CHD (M = 0.20, SE = 0.09, 95% CI = 0.02, 0.37), stem cell (M = 0.83, SE = 0.09, 95% CI = 0.64, 1.01), and tissue culture (M = 0.42, SE = 0.09, 95% CI = 0.23, 0.61). When comparing genome engineering with predicting CHD (M = 0.83, SE = 0.09, 95% CI = 0.66, 1.01), stem cell (M = 1.47, SE = 0.09, 95% CI = 1.28, 1.64), and with tissue culture (M = 1.06, SE = 0.09, 95% CI = 0.87, 1.24), we are 95% confident that genome engineering has a higher mean rank score than the other three topics. When comparing predicting CHD compared to stem cell (M = 0.63, SE = 0.09, 95% CI = 0.45, 0.81) and tissue culture (M = 0.22, SE = 0.09, 95% CI = 0.05, 0.4), we are 95% confident that predicting CHD has a higher mean rank. Lastly, comparing stem cell and tissue culture (M = 09.41, SE = 0.09, 95% CI = −0.59, −0.22) we are 95% confident that stem cell research has the lowest mean rank score.
The next area was “Broad Understanding of CHD,” with the options to rank improvement of early detection (M = 1.94, SD = 0.86), long-term Impact of medications and treatments (M = 1.81, SD = 0.75), and access to care/health disparities (M = 2.24, SD = 0.77). Looking at the mean rank comparisons, between health disparities and improving early detection, we are 95% confident that health disparities is the less preferred topic (M = −0.30, SE = 0.05, 95% CI = −0.40, −0.21), the same conclusion shows when comparing health disparities with long-term impact, as health disparities is the less preferred topic (M = −0.43, SE = 0.05, 95% CI = −0.52, −0.34). Finally, when comparing improving early detection and long-term impact, long-term impact is the preferred topic, but for slight margin (M = 0.13, SE = 0.05, 95% CI = 0.03, 0.22).
The last area was “Psychosocial Outcomes,” with psychological/emotional effects of CHD (M = 1.46, SD = 0.64), intervention for neuropsychological issues in CHD (M = 1.95, SD = 0.68), and benefits of patient access to medical records (M = 2.59, SD = 0.69). In the mean rank comparisons, we find that benefits of patient access to medical records is the least desired topic as we are 95% confident that intervention for neuropsychological issues in CHD has a lower rank mean (M = −0.63, SE = 0.04, 95% CI = −0.72, −0.56), as well as psychological/emotional effects of CHD have lower rank (M = −1.13, SE = 0.04, 95% CI = −1.22, −1.05). Lastly, when comparing Intervention for neuropsychological issues in CHD and psychological/emotional effects of CHD (M = 0.5, SE = 0.04, 95% CI = 0.42, 0.58), we are 95% confident that psychological/emotional effects of CHD is the preferred topic.
The raw data from the literature search are presented in Table 3 and aggregated in Table 4. “Query 1” for each entry was “congenital heart disease”. A Spearman’s correlation was used to assess the relationship between ‘mean rank scores on patient/parent preferred domains of CHD research’ and ‘total number of articles published from years 2015 to 2020 on PubMed, SCOPUS, and ScienceDirect for that domain’ using a sample of 528 participants. There was no correlation between the preferred domain of CHD research and the number of articles published for that domain, statistically not significant, rs = 0.02, p = 0.94.
Table 3. Research output by topic area
Table 4. Aggregate research output across all databases
Discussion
In this study, participatory design was applied in two stages – the generation of proposed research objectives and the critical evaluation and stratification of these areas of focus. This proved to be an effective model of data acquisition and evaluation but was not without its pitfalls. The demographic data of our respondents did not mirror that of the population affected by CHD, as the prevalence of CHD is roughly equivalent in all ethnicities in the United States of America. Reference Gilboa, Devine and Kucik11 This reflects a disparity between membership in Conquering CHD and participation in the survey among non-Caucasian patients and families. Further, as the survey was published only in English, this may also have limited respondents more comfortable in other languages. In addition, the response rate may also be limited in resource-poor areas, where lack of access to reliable internet service or devices would also present an obstacle. This study was also presented only to those already engaged with Conquering CHD, therefore limiting the sample to those interested in CHD advocacy and education, which may not necessarily reflect the general population affected by CHD.
In turn, this identifies an area of improvement in the recruitment and engagement of minority patients and families to benefit from the services, education, and support offered by Conquering CHD. Additionally, since the distribution of this survey, Conquering CHD is working to provide educational materials in both English and Spanish in order to offer more equitable engagement and information. This also speaks to the pervasive racial and ethnic disparities affecting paediatric healthcare. Reference Flores12
These data offer a stratified rank of the items of interest identified by the first focus groups. In this manner, the topics have been prioritised based on the preferences of affected patients and families. Dissemination of this data set enables clinicians and scientists to further target their own initiatives towards those that matter the most to patients. As researchers continue to pursue projects that support the health and well-being of patients and families affected by CHD, these formal objectives, identified by the individuals that their work supports, may offer valuable insight in the prioritisation of research agendas in laboratories, universities, and hospitals across the United States of America.
The Spearman’s correlation fails to demonstrate a relationship between patient identified research priorities and current research output in CHD. This is to say that the current body of literature does not represent the research priorities of patients and families affected by CHD. However, this view is inherently biased by personal experiences and this survey does not necessarily reflect the views of the entire population affected by CHD. Further, the structure of the survey limited respondents to a predetermined listing of choices without the option to add areas of interest of importance to them. In addition, the methodology does not discern between quantitative and qualitative research which may have also considered patient priorities. With clinical and scientific advances, these identified areas of interest will certainly change. It is imperative to re-evaluate this association and continue to involve patients and families in the development of research agendas to integrate areas of importance of those affected by CHD in the research that will ultimately affect their lives.
This intervention offered a unique opportunity to engage with the membership of Conquering CHD to formally delineate research objectives supported by the broader organisation. This fosters a sense of commitment to the organisational objectives and allows each member to have a voice. It is in this manner that Conquering CHD strives to truly advocate for patient-centered research, beginning with the identification of investigation priorities.
Acknowledgements
The authors would like to acknowledge the support of Dr Brett Anderson in the completion of this study. This piece is written in support of all of the families affected by CHD and in gratitude to those who treat them.
Financial support
This research received no specific grant from any funding agency, commercial, or not-for-profit sectors.
Conflicts of interest
None.
