Family Medicine and Community Health最新文献

focused Rapid Assessment Process (fRAP) 2.0 is a community engagement approach combining geospatial mapping with rapid qualitative assessment in cyclical fashion within communities to capture multifactorial and multilevel features impacting primary care problems. fRAP 2.0 offers primary care researchers a methodology framework for exploring complex community features that impact primary healthcare delivery and outcomes. The fRAP 2.0 study design expands the fRAP from a sequential design to a cyclical process of geospatial mapping and rapid qualitative assessment in search of modifiable contextual factors. Research participants are stakeholders from various socioecological levels whose perspectives inform study outcomes that they may use to then become the agents of change for the very problems they helped explore. Here, we present a proof-of-concept study for fRAP 2.0 examining disparities in cervical cancer mortality rates among Hispanic women in Texas. The primary outcomes of interest are features at the community level, medical health system level and regional government policy levels that offer opportunities for collaborative interventions to improve cervical cancer outcomes. In this study, geospatial mapping of county and ZIP code-level variables impacting postdiagnosis cervical cancer care at community, medical and policy levels were created using publicly available data and then overlaid with maps created with Texas Cancer Registry data for cervical cancer cases in three of the largest population counties. Geographically disparate areas were then qualitatively explored using participant observation and ethnographic field work, alongside 39 key informant interviews. Roundtable discussion groups and stakeholder engagement existed at every phase of the study. Applying the fRAP 2.0 method, we created an action-oriented roadmap of next steps to improve cervical cancer care disparities in the three Texas counties with emphasis on the high disparity county. We identified local change targets for advocacy and the results helped convene a stakeholder group that continues to actively create on-the-ground change in the high-disparity county to improve cervical cancer outcomes for Hispanic women.

Objective: To extract key lessons on primary healthcare (PHC) service delivery strategies for non-communicable diseases (NCD) from the work of researchers funded by the Global Alliance for Chronic Diseases (GACD).

Design: A convergent mixed methods study that extracted data using a standardised template from research projects funded by the GACD that focused on PHC. The strategies implemented in these studies were mapped onto the PHC Performance Initiative framework. Semistructured qualitative interviews were conducted with researchers from purposefully selected projects to understand the strategies and contextual factors in more depth.

Setting: PHC contexts from low or middle-income countries (LMIC) as well as vulnerable groups within high-income countries. Projects came from all regions of the world, particularly East Asia and Pacific, sub-Saharan Africa, South Asia, Latin America and Caribbean.

Participants: The study extracted data on 84 research projects and interviewed researchers from 16 research projects.

Results: Research projects came from all regions of the world, and mainly focused on diabetes (35.3%), hypertension (28.3%) and mental health (27.6%). Mapped onto the PHC Performance Initiative framework: 49.4% focused on high-quality PHC (particularly the comprehensiveness of NCD care, 41.2%); 41.2% on the availability of PHC services (particularly the competence of healthcare workers, 36.5%); 35.3% on population health management (particularly community-based services, 35.3%); 34.1% on facility organisation and management (particularly team-based care, 20.0%) and 31.8% on access (particularly digital technology, 23.5%). Most common strategies were task shifting and training to improve the comprehensiveness of NCD care through community-based services. Contextual factors related to inputs: infrastructure, equipment and medication, workforce (particularly community health workers), finances, health information systems and digital technology.

Conclusion: Key strategies and contextual factors to improve PHC service delivery for NCDs in LMICs were identified. These strategies should combine with other strategies to strengthen the PHC system as a whole, while improving care for NCDs.

Background: Colorectal cancer (CRC) is the second leading cause of cancer death in US adults but can be reduced by screening. The roles of individual and contextual factors, and especially physician supply, in attaining universal CRC screening remains uncertain.

Methods: We used data from adults 50-75 years old participating in the 2018 New York (NY) Behavioural Risk Factor Surveillance System linked to county-level covariates, including primary care physician (PCP) density and gastroenterologist (GI) density. Data were analysed in 2023-2024. Our analyses included (1) ecological and geospatial analyses of county-level CRC screening prevalence and (2) individual-level Poisson regression models of receipt of screening, adjusted for socioeconomic and county-level contextual variables.

Results: Mean prevalence of up-to-date CRC screening was 71% (95% CI 70% to 73%) across NY's 62 counties. County-level CRC screening demonstrated significant spatial patterning (Global Moran's I=0.14, p=0.04), consistent with the existence of county-level contextual factors. In both county-level and individual-level analyses, lack of health insurance was associated with lower likelihood of up-to-date screening (ß=-1.09 (95% CI -2.00 to -0.19); adjusted prevalence ratio 0.68 (95% CI 0.60 to 0.77)), even accounting for age, race/ethnicity and education. In contrast, county-level densities of both PCPs and GIs were completely unassociated with screening at either the county or individual level. As expected, other determinants at the individual level included education status and age.

Conclusion: In this state-wide representative analysis, physician density was completely unassociated with CRC screening, although health insurance status remains strongly related. In similar screening environments, broadened insurance coverage for CRC screening is likely to improve screening far more effectively than increased physician supply.

Introduction: The application of large language models such as generative pre-trained transformers (GPTs) has been promising in medical education, and its performance has been tested for different medical exams. This study aims to assess the performance of GPTs in responding to a set of sample questions of short-answer management problems (SAMPs) from the certification exam of the College of Family Physicians of Canada (CFPC).

Method: Between August 8th and 25th, 2023, we used GPT-3.5 and GPT-4 in five rounds to answer a sample of 77 SAMPs questions from the CFPC website. Two independent certified family physician reviewers scored AI-generated responses twice: first, according to the CFPC answer key (ie, CFPC score), and second, based on their knowledge and other references (ie, Reviews' score). An ordinal logistic generalised estimating equations (GEE) model was applied to analyse repeated measures across the five rounds.

Result: According to the CFPC answer key, 607 (73.6%) lines of answers by GPT-3.5 and 691 (81%) by GPT-4 were deemed accurate. Reviewer's scoring suggested that about 84% of the lines of answers provided by GPT-3.5 and 93% of GPT-4 were correct. The GEE analysis confirmed that over five rounds, the likelihood of achieving a higher CFPC Score Percentage for GPT-4 was 2.31 times more than GPT-3.5 (OR: 2.31; 95% CI: 1.53 to 3.47; p<0.001). Similarly, the Reviewers' Score percentage for responses provided by GPT-4 over 5 rounds were 2.23 times more likely to exceed those of GPT-3.5 (OR: 2.23; 95% CI: 1.22 to 4.06; p=0.009). Running the GPTs after a one week interval, regeneration of the prompt or using or not using the prompt did not significantly change the CFPC score percentage.

Conclusion: In our study, we used GPT-3.5 and GPT-4 to answer complex, open-ended sample questions of the CFPC exam and showed that more than 70% of the answers were accurate, and GPT-4 outperformed GPT-3.5 in responding to the questions. Large language models such as GPTs seem promising for assisting candidates of the CFPC exam by providing potential answers. However, their use for family medicine education and exam preparation needs further studies.

Background: As populations age globally, effectively managing geriatric health poses challenges for primary care. Comprehensive geriatric assessments (CGAs) aim to address these challenges through multidisciplinary screening and coordinated care planning. However, most CGA tools and workflows have not been optimised for routine primary care delivery.

Objective: This study aimed to evaluate the impact of a computerised CGA tool, called the Golden Age Visit, implemented in primary care in Israel.

Methods: This study employed a quasiexperimental mixed-methods design to evaluate outcomes associated with the Golden Age electronic health assessment tool. Quantitative analysis used electronic medical records data from Maccabi Healthcare Services, the second largest health management organisation (HMO) in Israel. Patients aged 75 and older were included in analyses from January 2017 to December 2019 and January 2021 to December 2022. For patients, data were also collected on controls who did not participate in the Golden Age Visit programme during the same time period, to allow for comparison of outcomes. For physicians, qualitative data were collected via surveys and interviews with primary care physicians who used the Golden Age Visit SMARTEST e-assessment tool.

Results: A total of 9022 community-dwelling adults aged 75 and older were included in the study: 1421 patients received a Golden Age Visit CGA (intervention group), and 7601 patients did not receive the assessment (control group). After CGAs, diagnosis rates increased significantly for neuropsychiatric conditions and falls. Referrals to physiotherapy, occupational therapy, dietetics and geriatric outpatient clinics also rose substantially. However, no differences were found in rates of hip fracture or relocation to long-term care between groups. Surveys among physicians (n=151) found high satisfaction with the programme.

Conclusion: Implementation of a large-scale primary care CGA programme was associated with improved diagnosis and management of geriatric conditions. Physicians were also satisfied, suggesting good uptake and feasibility within usual care. Further high-quality studies are still needed but these results provide real-world support for proactively addressing geriatric health needs through structured screening models.