Dataset Information

The integrated nuclear medicine and radiology residency program in the Netherlands: strengths and potential areas for improvement according to nuclear medicine physicians and radiologists.

ABSTRACT:

Purpose

To evaluate the Dutch integrated nuclear medicine and radiology residency program from the perspective of nuclear medicine physicians and radiologists.

Methods

A survey was distributed among nuclear medicine physicians and radiologists in hospitals that participate in the Dutch integrated nuclear medicine and radiology training program.

Results

A total of 139 completed questionnaires were included. Nuclear medicine physicians (n = 36) assigned a mean score of 5.7 ± 2.0, and radiologists (n = 103) assigned a mean score of 6.5 ± 2.8 (on a 1-10 scale) to the success of the integrated training program in their hospital. On multiple regression, female gender of the survey participant (B = 2.22, P = 0.034), musculoskeletal radiology as subspecialty of the survey participant (B = 3.36, P = 0.032), and the survey participant's expectancy of resident's ability to handle workload after completion of residency were significantly associated with perceived success of the integrated training program (B = 1.16, P = 0.023). Perceived strengths of the integrated training program included broadening of expertise, a better preparation of future imaging specialists for hybrid imaging, increased efficiency in training residents, and increased efficiency in multidisciplinary meetings. Perceived weaknesses of the integrated training program included reduced exposure to nuclear medicine, less time for research and innovation, and concerns about its international recognition.

Conclusion

This study provided insights into the experiences of nuclear medicine physicians and radiologists with the Dutch integrated nuclear medicine and radiology residency program, which may be helpful to improve the program and similar residency programs in other countries.

SUBMITTER: Velleman T

PROVIDER: S-EPMC9250465 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:ImportanceContraception and abortion services are essential health care, and family medicine (FM) physicians are an important part of the workforce providing this care. Residency could inform the reproductive health services FM physicians provide.ObjectiveTo determine which residency training factors are associated with FM physicians' provision of reproductive health services to Medicaid beneficiaries.Design, setting, and participantsThis cross-sectional, population-based observational study of inpatient and outpatient FM physicians who completed residency between 2008 and 2018 and treated at least 1 Medicaid beneficiary in 2019 was conducted from November 2022 to March 2023. The study used 2019 American Medical Association Masterfile and Historical Residency file, as well as the 2019 Transformed Medicaid Statistical Information System claims.ExposuresResidency training in community-based or reproductive health-focused programs.Main outcomes and measuresThe outcomes were providing the following to at least 1 Medicaid beneficiary in 2019: prescription contraception (pill, patch, and/or ring), intrauterine device (IUD) and/or contraceptive implant, and dilation and curettage (D&C). Odds of providing each outcome were measured using correlated random-effects regression models adjusted for physician, residency program, and county characteristics.ResultsIn the sample of 21 904 FM physician graduates from 410 FM residency programs, 12 307 were female (56.3%). More than half prescribed contraception to Medicaid beneficiaries (13 373 physicians [61.1%]), with lower proportions providing IUD or implant (4059 physicians [18.5%]) and D&C (152 physicians [.7%]). FM physicians who graduated from a Reproductive Health Education in Family Medicine program, which fully integrates family planning into residency training, had significantly greater odds of providing prescription contraception (odds ratio [OR], 1.23; 95% CI, 1.07-1.42), IUD or implant (OR, 1.79; 95% CI, 1.28-2.48), and D&C (OR, 3.61; 95% CI, 2.02-6.44). Physicians who completed residency at a Teaching Health Center, which emphasizes community-based care, had higher odds of providing an IUD or implant (OR, 1.51; 95% CI, 1.19-1.91).Conclusions and relevanceIn this cross-sectional study of FM physicians providing Medicaid service, characteristics of residency training including community-based care and integration of family planning training are associated with greater odds of providing reproductive health services. With growing reproductive health policy restrictions, providing adequate training in reproductive health is critical to maintaining access to care, especially for underserved populations.

Project description:Rationale and objectivesVirtual residency interviews have become crucial in maintaining CDC-recommended precautionary measures throughout the ongoing COVID-era. However, scant literature exists regarding the direct impact the pandemic has had on the radiology program selection process, including preferred modalities of residency interviews and social media utilization. This survey aimed to understand how radiology programs adapted to changes in the 2020-2021 virtual application cycle.Materials and methodsA 32-question survey was distributed to 194 residency programs between July and August of 2021. Data were analyzed primarily by using descriptive statistics and Paired Student's T-testing.ResultsA total of 31 programs completed the survey, yielding a response rate of 16%. When queried about the perceived success of virtual interviews during the 2020-2021 application cycle, 21 programs (68%) said the new interview format was very successful. Twenty-seven of the programs (87%) believed they were able to adequately gauge applicants through virtual interviews. However, when surveyed about personal preferences for interviews, the responses were more evenly distributed between virtual (11/31, 35%) and in-person (14/31, 45%). Pre-COVID, the top three criteria programs used to rank candidates were USMLE Step 1 score (20/31, 65%), letters of recommendation (17/31, 55%), and MSPE (12/31, 39%). Within the virtual, COVID-19 era, these criteria remained statistically unchanged (p = 0.22): USMLE Step 1 score (21/31, 68%), letters of recommendation (17/31, 55%), and MSPE (14/31, 45%). About half of programs who had not previously utilized social media (12 of 23, 52%) created accounts, mostly via Twitter or Instagram.ConclusionThe primary findings indicate that programs perceived success with virtually interviewing and ranking applicants, the criteria to rank applicants remain unchanged despite the virtual environment, and programs' social media utilization increased.

Project description:BackgroundArtificial Intelligence (AI) is recognized by emergency physicians (EPs) as an important technology that will affect clinical practice. Several AI-tools have already been developed to aid care delivery in emergency medicine (EM). However, many EM tools appear to have been developed without a cross-disciplinary needs assessment, making it difficult to understand their broader importance to general-practice. Clinician surveys about AI tools have been conducted within other medical specialties to help guide future design. This study aims to understand the needs of Canadian EPs for the apt use of AI-based tools.MethodsA national cross-sectional, two-stage, mixed-method electronic survey of Canadian EPs was conducted from January-May 2022. The survey includes demographic and physician practice-pattern data, clinicians' current use and perceptions of AI, and individual rankings of which EM work-activities most benefit from AI.ResultsThe primary outcome is a ranked list of high-priority AI-tools for EM that physicians want translated into general use within the next 10 years. When ranking specific AI examples, 'automated charting/report generation', 'clinical prediction rules' and 'monitoring vitals with early-warning detection' were the top items. When ranking by physician work-activities, 'AI-tools for documentation', 'AI-tools for computer use' and 'AI-tools for triaging patients' were the top items. For secondary outcomes, EPs indicated AI was 'likely' (43.1%) or 'extremely likely' (43.7%) to be able to complete the task of 'documentation' and indicated either 'a-great-deal' (32.8%) or 'quite-a-bit' (39.7%) of potential for AI in EM. Further, EPs were either 'strongly' (48.5%) or 'somewhat' (39.8%) interested in AI for EM.ConclusionsPhysician input on the design of AI is essential to ensure the uptake of this technology. Translation of AI-tools to facilitate documentation is considered a high-priority, and respondents had high confidence that AI could facilitate this task. This study will guide future directions regarding the use of AI for EM and help direct efforts to address prevailing technology-translation barriers such as access to high-quality application-specific data and developing reporting guidelines for specific AI-applications. With a prioritized list of high-need AI applications, decision-makers can develop focused strategies to address these larger obstacles.

Project description:ObjectivesRadiologists' perception is likely to influence the adoption of artificial intelligence (AI) into clinical practice. We investigated knowledge and attitude towards AI by radiologists and residents in Europe and beyond.MethodsBetween April and July 2019, a survey on fear of replacement, knowledge, and attitude towards AI was accessible to radiologists and residents. The survey was distributed through several radiological societies, author networks, and social media. Independent predictors of fear of replacement and a positive attitude towards AI were assessed using multivariable logistic regression.ResultsThe survey was completed by 1,041 respondents from 54 mostly European countries. Most respondents were male (n = 670, 65%), median age was 38 (24-74) years, n = 142 (35%) residents, and n = 471 (45%) worked in an academic center. Basic AI-specific knowledge was associated with fear (adjusted OR 1.56, 95% CI 1.10-2.21, p = 0.01), while intermediate AI-specific knowledge (adjusted OR 0.40, 95% CI 0.20-0.80, p = 0.01) or advanced AI-specific knowledge (adjusted OR 0.43, 95% CI 0.21-0.90, p = 0.03) was inversely associated with fear. A positive attitude towards AI was observed in 48% (n = 501) and was associated with only having heard of AI, intermediate (adjusted OR 11.65, 95% CI 4.25-31.92, p < 0.001), or advanced AI-specific knowledge (adjusted OR 17.65, 95% CI 6.16-50.54, p < 0.001).ConclusionsLimited AI-specific knowledge levels among radiology residents and radiologists are associated with fear, while intermediate to advanced AI-specific knowledge levels are associated with a positive attitude towards AI. Additional training may therefore improve clinical adoption.Key points• Forty-eight percent of radiologists and residents have an open and proactive attitude towards artificial intelligence (AI), while 38% fear of replacement by AI. • Intermediate and advanced AI-specific knowledge levels may enhance adoption of AI in clinical practice, while rudimentary knowledge levels appear to be inhibitive. • AI should be incorporated in radiology training curricula to help facilitate its clinical adoption.