Background and Significance Falls in community-dwelling older adults are common, and there is a lack of clinical decision support (CDS) to provide health care providers with effective, individualized fall prevention recommendations. Objectives The goal of this research is to identify end-user (primary care staff and patients) needs through a human-centered design process for a tool that will generate CDS to protect older adults from falls and injuries. Methods Primary care staff (primary care providers, care coordinator nurses, licensed practical nurses, and medical assistants) and community-dwelling patients aged 60 years or older associated with Brigham & Women's Hospital-affiliated primary care clinics and the University of Florida Health Archer Family Health Care primary care clinic were eligible to participate in this study. Through semi-structured and exploratory interviews with participants, our team identified end-user needs through content analysis. Results User needs for primary care staff (n = 24) and patients (n = 18) were categorized under the following themes: workload burden; systematic communication; in-person assessment of patient condition; personal support networks; motivational tools; patient understanding of fall risk; individualized resources; and evidence-based safe exercises and expert guidance. While some of these themes are specific to either primary care staff or patients, several address needs expressed by both groups of end-users. Conclusion Our findings suggest that there are many care gaps in fall prevention management in primary care and that personalized, actionable, and evidence-based CDS has the potential to address some of these gaps.

Background: Falls are a widespread and persistent problem for community-dwelling older-adults. Use of fall prevention guidelines in the primary care setting has been suboptimal. Interoperable computerized clinical decision support systems have the potential to increase engagement with fall risk management at scale. To support fall risk management across organizations our team developed the ASPIRE tool for use in differing primary care clinics using interoperable standards. Objectives: Usability testing of ASPIRE was conducted to measure, ease of access, overall usability, learnability, and acceptability prior to pilot . Methods: Participants were recruited using purposive sampling from two sites with different electronic health records and different clinical organizations. Formative testing rooted in user-centered design was followed by summative testing using a simulation approach. During summative testing participants used ASPIRE across two clinical scenarios and were randomized to determine which scenario they saw first. Single ease question and system usability scale were used in addition to analysis of recorded sessions in NVivo. Results: All 14 participants rated the usability of ASPIRE as above average based on usability benchmarks for the system usability scale metric. Time on task decreased significantly between the first and second scenarios indicating good learnability. However, acceptability data was more mixed with some recommendations being consistently accepted while others were adopted less frequently. Conclusions: This study described the usability testing of the ASPIRE system within two different organizations using different electronic health records. Overall, the system was rated well, and further pilot testing should be done to validate that these positive results translate into clinical practice. Due to its interoperable design ASPIRE could be integrated into diverse organizations allowing a tailored implementation without the need to build a new system for each organization. This distinction makes ASPIRE well positioned to impact the challenge of falls at scale.

Purpose: Disparities in cancer outcomes still remain in low-and-middle income countries (LMICs), where less than 30% of children living with cancer survive. In this context, the Global Initiative for Childhood Cancer has set the goal of achieving at least 60% survival for all countries by 2030. The aim of this study was to describe trends in childhood mortality rates for LMICs over time and evaluate their association with the health system metrics related to the WHO CureAll framework. Methods: In this ecological study, childhood cancer was defined as all-cancers for the age group of 0-14 years old. Data were collected from public data sources including the Global Burden of Disease, WHO cancer profiles and World Bank. Descriptive analyses were performed to investigate mortality rate patterns over time (1990-2019). Exposure variables including density of hospital beds, density of CT scanners, density of MRI scanners, density of density of external beam radiotherapy, out-of-pocket expenditure, and universal health coverage index were evaluated against percent change of mortality of cancer rates (1990-2019). Smooth regression lines were used to visualize inflections points within income level groups. Results: A total of 134 LMICs were included in this study. Overall, low-income countries had the major decrease in childhood mortality rates from 1900 to 2019. The top three countries with the highest decrease in rates were Malawi, Ethiopia, and Zambia deaths (-22.6 to -9.1/100,000 population). The top three countries with the highest increase in rates were Botswana, Burkina Faso, and Dominica (+1.2 to +1.8 deaths/100,000 population). The factors associated the most with changes in the childhood cancer mortality rates over time were improvements in infrastructure, such as increasing hospital beds and the availability of cancer treatments, increasing universal coverage, and decreasing out-of-pocket expenditures for healthcare costs. Conclusion: An improved understanding of cancer mortality trends and their relation with health system variables in LMICs is important to monitor and evaluate progress in survival rates for children living with cancer in these countries. This study intends to provide insights on the use of health system metrics related to the WHO CureAll framework as priority interventions for childhood cancer in LMICs. Citation Format: Hannah Rice, Emily Smith, Cesia Cotache-Condor, Esther Majaliwa, Pamela Espinoza, Madeline Metcalf, Henry Rice. Correlation of Childhood Cancer Mortality Trends and CureAll Metrics for 134 LMICs [abstract]. In: Proceedings of the 11th Annual Symposium on Global Cancer Research; Closing the Research-to-Implementation Gap; 2023 Apr 4-6. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(6_Suppl):Abstract nr 26.

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