RESUMO
A key component of primary care pediatrics is health promotion through screening: applying a test or procedure to detect a previously unrecognized disease or disease risk. How do we decide whether to screen? In 1965, Wilson and Jungner published an influential set of screening principles focused on the health problem's importance, the screening tool's performance, and the evidence for treatment efficacy. However, if we want realistic estimates of the population effects of routine screening, we must also account for the health care system's real-world functioning and disparities in care. We offer revised principles to guide discussions about routine screening in the primary care setting. We add to Wilson and Jungner's principles: 1. A focus on life course epidemiology and its consequences for population health, 2. A need to screen for the early stages of chronic health problems, 3. A concern for screening's acceptability to providers and the community, 4. A recommendation for estimating the uncertainty in benefits and harms in evaluating screening, 5. Inclusion of systematic plans for population data collection and monitoring, and 6. Recognition that achieving population health improvement requires a high-performing system with sufficient throughput and monitoring to deliver accessible, affordable, and effective care, especially for the groups experiencing the greatest inequities in access. Above all, instead of assuming best practices in treatment delivery and monitoring after screening, we argue for realism about the health care system functioning in routine practice.
Assuntos
Programas de Rastreamento , Saúde da População , Atenção Primária à Saúde , Humanos , Criança , Pediatria , Promoção da Saúde/métodos , Doença CrônicaRESUMO
BACKGROUND AND OBJECTIVES: Race-based medicine, which falsely assumes that race is biological, is common in the published medical literature. We analyzed trends in the use of race in Pediatrics articles over a 75-year period. METHODS: We analyzed a random sample of 50 original research articles published each decade in Pediatrics from 1948 to 2022. RESULTS: Of 375 articles, 39% (n = 147) included race. Among articles, 85% (n = 116) used race only to describe study subjects, 7% (n = 9) described race as a social construct, and 11% (n = 15) described race as a biological construct. Only 7% (n = 10) of studies provided a reason for including race. Statements reflective of racial bias or discrimination were identified in 22% (n = 30) of the articles that mentioned race. Although statements concerning for explicit racial bias were uncommon, with none identified in the most recent decade, statements suggestive of implicit racial bias still occurred (22%, 5 of 23). Race was presented as a dichotomy, such as "white/nonwhite," in 9% of studies (n = 12). Regarding currently nonrecommended terminology, the term "minorities" was used in 13% of studies (n = 18); 25% of studies used the term "others" (n = 34), and among these, 91% (n = 31 of 34) did not provide any definition, an occurrence that increased over time at a rate of 0.9%/year. CONCLUSIONS: Although there has been improvement over the past 75 years in the reporting of race in published studies in Pediatrics, significant opportunities for further improvement remain.
Assuntos
Pediatria , Grupos Raciais , Racismo , Humanos , Pediatria/tendências , Publicações Periódicas como Assunto/tendênciasRESUMO
BACKGROUND: Health outcomes are significantly influenced by unmet social needs. Although screening for social needs has become common in health care settings, there is often poor linkage to resources after needs are identified. The structural barriers (eg, staffing, time, and space) to helping address social needs could be overcome by a technology-based solution. OBJECTIVE: This study aims to present the design and evaluation of a chatbot, DAPHNE (Dialog-Based Assistant Platform for Healthcare and Needs Ecosystem), which screens for social needs and links patients and families to resources. METHODS: This research used a three-stage study approach: (1) an end-user survey to understand unmet needs and perception toward chatbots, (2) iterative design with interdisciplinary stakeholder groups, and (3) a feasibility and usability assessment. In study 1, a web-based survey was conducted with low-income US resident households (n=201). Following that, in study 2, web-based sessions were held with an interdisciplinary group of stakeholders (n=10) using thematic and content analysis to inform the chatbot's design and development. Finally, in study 3, the assessment on feasibility and usability was completed via a mix of a web-based survey and focus group interviews following scenario-based usability testing with community health workers (family advocates; n=4) and social workers (n=9). We reported descriptive statistics and chi-square test results for the household survey. Content analysis and thematic analysis were used to analyze qualitative data. Usability score was descriptively reported. RESULTS: Among the survey participants, employed and younger individuals reported a higher likelihood of using a chatbot to address social needs, in contrast to the oldest age group. Regarding designing the chatbot, the stakeholders emphasized the importance of provider-technology collaboration, inclusive conversational design, and user education. The participants found that the chatbot's capabilities met expectations and that the chatbot was easy to use (System Usability Scale score=72/100). However, there were common concerns about the accuracy of suggested resources, electronic health record integration, and trust with a chatbot. CONCLUSIONS: Chatbots can provide personalized feedback for families to identify and meet social needs. Our study highlights the importance of user-centered iterative design and development of chatbots for social needs. Future research should examine the efficacy, cost-effectiveness, and scalability of chatbot interventions to address social needs.