Building the Business Case for an Inclusive Approach to Digital Health Measurement With a Web App (Market Opportunity Calculator): Instrument Development Study.

BACKGROUND: The use of digital health measurement tools has grown substantially in recent years. However, there are concerns that the promised benefits from these products will not be shared equitably. Underserved populations, such as those with lower education and income, racial and ethnic minorities, and those with disabilities, may find such tools poorly suited for their needs. Because underserved populations shoulder a disproportionate share of the US disease burden, they also represent a substantial share of digital health companies' target markets. Incorporating inclusive principles into the product development process can help ensure that the resulting tools are broadly accessible and effective. In this context, inclusivity not only maximizes societal benefit but also leads to greater commercial success. OBJECTIVE: A critical element in fostering inclusive product development is building the business case for why it is worthwhile. The Digital Health Measurement Collaborative Community (DATAcc) Market Opportunity Calculator was developed as an open-access resource to enable digital health measurement product developers to build a business case for incorporating inclusive practices into their research and development processes. METHODS: The DATAcc Market Opportunity Calculator combines data on population demographics and disease prevalence and health status from the US Census Bureau and the US Centers for Disease Control and Prevention (CDC). Together, these data are used to calculate the share of US adults with specific conditions (eg, diabetes) falling into various population segments along key "inclusion vectors" (eg, race and ethnicity). RESULTS: A free and open resource, the DATAcc Market Opportunity Calculator can be accessed from the DATAcc website. Users first select the target health condition addressed by their product, and then an inclusion vector to segment the patient population. The calculator displays each segment as a share of the overall US adult population and its share specifically among adults with the target condition, quantifying the importance of underserved patient segments to the target market. The calculator also estimates the value of improvements to product inclusivity by modeling the downstream impact on the accessible market size. For example, simplifying prompts on a hypertension-focused product to make it more accessible for adults with lower educational attainment is shown by the calculator to increase the target market by 2 million people and the total addressable market opportunity by US $200 million. CONCLUSIONS: Digital health measurement is still in its infancy. Now is the time to establish a precedent for inclusive product development to maximize societal benefit and build sustainable commercial returns. The Market Opportunity Calculator can help build the business case for "why"-showing how inclusivity can translate to financial opportunity. Once the decision has been made to pursue inclusive design, other components of the broader DATAcc toolkit for inclusive product development can support the "how."

Conflict or Collaboration-The Impact of Knowledge Endowment Heterogeneity on Remix in Open Collaborative Communities.

With the emergence of online open platforms and communities, remix has drawn much attention as an essential source of innovation whereby the knowledge endowment of online community users plays a crucial role. This study constructs a structural equation model to explore the impact of user knowledge endowment heterogeneity on remix through the mediating effect of their collaborative psychology. In this empirical study, we collected 25,032 pieces of data from Thingiverse (a 3D printing community) users and their published designs. The findings are as follows. Explicit knowledge endowment heterogeneity has a positive impact on the quantity of remix but a negative impact on its quality. Likewise, the implicit knowledge endowment heterogeneity positively affects the quantity of remix but has no significant effect on its quality. Users' conflicting psychology plays a mediating role between knowledge endowment heterogeneity and remix, while their collaborative psychology negatively mediates merely between explicit knowledge endowment heterogeneity and remix quality. By unraveling the relationship between user knowledge endowment heterogeneity, collaborative psychology, and remix, this study is significant in understanding users' remix process in open collaborative communities and illuminating their psychological mechanism in this process.

Opportunities and challenges in heart rhythm research: Rationale and development of an electrophysiology collaboratory.

There are many challenges in the current landscape of electrophysiology (EP) clinical and translational research, including increasing costs and complexity, competing demands, regulatory requirements, and challenges with study implementation. This review seeks to broadly discuss the state of EP research, including challenges and opportunities. Included here are results from a Heart Rhythm Society (HRS) Research Committee member survey detailing HRS members' perspectives regarding both barriers to clinical and translational research and opportunities to address these challenges. We also provide stakeholder perspectives on barriers and opportunities for future EP research, including input from representatives of the U.S. Food and Drug Administration, industry, and research funding institutions that participated in a Research Collaboratory Summit convened by HRS. This review further summarizes the experiences of the heart failure and heart valve communities and how they have approached similar challenges in their own fields. We then explore potential solutions, including various models of research ecosystems designed to identify research challenges and to coordinate ways to address them in a collaborative fashion in order to optimize innovation, increase efficiency of evidence generation, and advance the development of new therapeutic products. The objectives of the proposed collaborative cardiac EP research community are to encourage and support scientific discourse, research efficiency, and evidence generation by exploring collaborative and equitable solutions in which stakeholders within the EP community can interact to address knowledge gaps, innovate, and advance new therapies.

RESCUE Collaborative Community: A New Initiative to Reduce Rates of Intended Self-Injury and Suicide Among People with Diabetes.

Suicide is the leading cause of death among young people aged 20-34 and the second leading cause of death in adolescents aged 15-19. In the general population, among those attempting suicide 7% die by suicide and 23% reattempt with nonfatal consequences. Depression, closely associated with suicidal ideation, is diagnosed in 7%-25% of the United States and European populations. Individuals with type 1 diabetes (T1D) have a two to three times higher prevalence of depression and approximately double the rate of suicide compared to the general population. Rates of self-harm and suicide among people with diabetes are likely to be considerably underestimated due to poor identification. This information is critical to create interventions to decrease rates of suicide and self-harm. This is particularly important in the setting of advanced technologies in T1D, which offer both easier methods of self-injurious behaviors through insulin misuse and can act as identification tools to identify risk insulin behaviors and provide opportunities to develop interventions and prevention efforts in those with depression and suicidal ideation/behavior/acts. To this end, our goal was to identify any literature on coding diabetes correctly in individuals who die by suicide or engage in intentional self-harm. Furthermore, to describe the Reducing Suicide Rates Among Individuals with Diabetes (RESCUE) Collaborative Community and its goals of using multiple approaches to reduce rates of intended self-injury and suicide among people with diabetes. These include detection of cases, understanding support needs, identification of risk factors, and early intervention for individuals at risk.

Building trust in American hospital-community development projects: a scoping review.

Although it has become increasingly common for hospitals to engage in development projects aimed at improving the social determinants of health in surrounding communities, scholarly literature examining the establishment of trust between hospitals and communities is sparse. Because of an extensive and complex history of abuse suffered by marginalized populations at the hands of medical institutions, trust building is critical to the pursuit of equitable health outcomes in these communities. A scoping review was conducted to assess the current base of knowledge for building trust between hospital systems and community members. The review identified only 13 relevant articles addressing this topic, centered on six key themes: with whom to form partnerships; how to form partnerships; conceptualizing and defining trust; questions about investment and hiring; effective communication with communities; and, understanding communities.

Two-year effects of the community-based overweight and obesity intervention program Gezond Onderweg! (GO!) in children and adolescents living in a low socioeconomic status and multi-ethnic district on Body Mass Index-Standard Deviation Score and quality of life.

BACKGROUND: In most childhood obesity interventions, disadvantaged groups are underrepresented, and results are modest and not maintained. A long-term collaborative community-based approach is necessary to reach out to children from multi-ethnic backgrounds and achieve sustainable behavior change, resulting in sustained Body Mass Index-Standard Deviation Score (BMI-SDS) reductions. The objective is to determine the effects of GO! on BMI-SDS and Health-Related Quality of Life (HRQoL) for children and adolescents having overweight or obesity. METHODS: A prospective, longitudinal cohort study was used to collect two-year follow-up data from November 2014 to July 2019. Children and adolescents (4-19 years old) from the low socioeconomic status and multi-ethnic district of Malburgen in the Dutch city of Arnhem were included. 178 children having overweight or obesity were recruited, with 155 children measured at baseline and after two years as a minimum, while 23 were lost to follow up. Participants attending the program for over six months were defined as completers (n=107) and participants attending the program for less than six months were defined as non-completers (n=48). The child health coach (CHC) acts as a central care provider in the collaborative community with healthcare providers from both medical and social fields. This coach coordinates, monitors and coaches healthy lifestyles, while increasing self-management for both children and parents. This is done in a customized and neighborhood-oriented manner and provided by all the stakeholders involved in GO!. The main outcomes are the change in BMI-SDS scores and HRQoL scores reported by participants. FINDINGS: After 24 months, completers showed a decrease in BMI-SDS of -0·32 [95% CI: -0·42, -0·21], compared with -0·14 [95% CI: -0·29, 0·01] for non-completers (adjusted for gender and ethnicity; P=0.036). While 25% suffered from overweight and 75% from obesity at the start, following the intervention 5% showed normal weight, with 33% overweight and 62% with obesity. HRQoL reported by participants improved over time, showing no differences between completers and non-completers, gender and ethnicity after two years. INTERPRETATION: Our results suggest that the GO! program might be effective in reaching out and reducing BMI-SDS for participants in a low socioeconomic status and multi-ethnic district over a two-year period. We noticed also trends to beneficial shifts in obesity grades. HRQoL improved regardless of the participation rate, gender and ethnic background. In light of the study limitations, further studies are needed to corroborate our observations. FUNDING: Dullerts-foundation, Nicolai Broederschap foundation, Burger en Nieuwe weeshuis foundation, Rijnkind foundation, Arnhems Achterstandswijken foundation, Menzis-foundation, the municipalities of Arnhem, Rheden, Overbetuwe and Lingewaard, the Association of Dutch municipalities, and Province of Gelderland.

Comparing Self-Reported Infant Safe Sleep From Community- and Health Care-Based Settings.

OBJECTIVE: To compare self-reported safe sleep data from a community social service agency and primary care centers. DESIGN, SETTINGS, AND PARTICIPANTS: Cross-sectional Pregnancy Risk Assessment Monitoring System (PRAMS)-based survey data from a community social service agency and survey data from primary care centers were compared using descriptive statistics. There were 166 community survey respondents, average age of 25 years (SD = 5.4 years), and 79 primary care center respondents, average age of 24 years (SD = 5.4 years). Two binary logistic regressions were performed to examine the association between demographic differences and safe sleep position/bed sharing. RESULTS: Safe sleep position responses did not differ significantly between the community-based (n = 126, 85%) and primary care center-based (n = 62, 79%) samples, χ(2)(1) = 0.79, P = .372. Reported bed sharing was significantly higher in the community sample (n = 54, 36%) than the health care center sample (n = 4, 5%), Fisher's exact test, P< .001. Black race was determined to be significantly associated with increased unsafe sleep positioning (OR = 2.86, P = .022). The community center cohort was the only significant predictor of bed sharing (OR = 25.40, P = .002). CONCLUSION: Differences in reported safe sleep environments may be due to knowledge variances of safe sleep guidelines, or clinic-based respondents may have been more likely to provide socially desirable responses. The comparison data further highlight the need for continued targeted effort to improve safe sleep behaviors to improve infant health outcomes.

Social Deterministic Factors to Participation in the National Health Insurance Scheme in the Context of Rural Ghanaian Setting.

The primary purpose of this study is to identify predictors of complete household enrollment into the National Health Insurance Scheme (NHIS) among inhabitants of the Barekese sub-district in the Ashanti Region of Ghana. Heads of households in 20 communities from the Barekuma Collaborative Community Project site were interviewed to gather data on demographic, socioeconomic status (SES) indicators and complete household subscription in the NHIS. Logistic regression model was used to predict enrollment in the NHIS. Of the 3228 heads of households interviewed, 60 percent reported having all members of their respective households enrolled in the NHIS. Residents in the classified Middle and High SES brackets had 1.47 (95% CI: 1.21-1.77) and 1.66 (95% CI: 1.27-2.16) times higher odds, respectively, of complete household enrollment compared to their counterparts in the Low SES category. The odds of enrolling in the program tend to increase progressively with the highest level of education attained by the head of the family unit. Eight years after the introduction of the national health insurance policy in Ghana, the reported subscription rate for complete households was about 60 percent in the 20 rural communities that participated in the study. This finding calls for the need to step up further national strategies that will help increase enrollment coverage, especially among the poor and less educated in the rural communities.

Spatial Analysis of Factors Associated with Household Subscription to the National Health Insurance Scheme in Rural Ghana.

The use of health insurance schemes in financing healthcare delivery and to minimize the poverty gap is gaining considerable recognition among the least developed and resource challenged countries around the world. With the implementation of the socialized health insurance scheme, Ghana has taken the lead in Sub-Saharan Africa and now working out further strategies to gain universal coverage among her citizenry. The primary goal of this study is to explore the spatial relationship between the residential homes and demographic features of the people in the Barekese subdistrict in Ghana on the probability to enroll the entire household unit in the National Health Insurance Scheme (NHIS). Household level data were gathered from 20 communities on the enrollment status into the NHIS alongside demographic and socioeconomic indicators and the spatial location of every household that participated in the study. Kulldorff's purely spatial scan statistic was used to detect geographic clusters of areas with participatory households that have either higher or lower enrollment patterns in the insurance program. Logistic regression models on selected demographic and socioeconomic indicators were built to predict the effect on the odds of enrolling an entire household membership in the NHIS. Three clusters significantly stood out to have either high or low enrollment patterns in the health insurance program taking into accounts the number of households in those sub-zones of the study region. Households in the Cluster 1 insurance group have very high travel expenses compared to their counterparts in the other idenfied clusters. Travel cost and time to the NHIS registration center to enroll in the program were both significant predictors to participation in the program when controlling for cluster effect. Residents in the High socioeconomic group have about 1.66 [95% CI: 1.27-2.17] times the odds to enroll complete households in the insurance program compared to their counterparts in the Low socioeconomic group. The study demonstrated the use of spatial analytical tools to identify clusters of household enrollment pattern in the NHIS among residents in rural Ghana. In the face of limited resources, policy makers can therefore use the findings as guideline to strategically channel interventions to areas of most need. Furthermore, these analyses can be repeated annually to assess progress on improving insurance coverage.