Insights from semi-structured interviews on integrating artificial intelligence in clinical chemistry laboratory practices.

BACKGROUND: Artificial intelligence (AI) is gradually transforming the practises of healthcare providers. Over the last two decades, the advent of AI into numerous aspects of pathology has opened transformative possibilities in how we practise laboratory medicine. Objectives of this study were to explore how AI could impact the clinical practices of professionals working in Clinical Chemistry laboratories, while also identifying effective strategies in medical education to facilitate the required changes. METHODS: From March to August 2022, an exploratory qualitative study was conducted at the Section of Clinical Chemistry, Department of Pathology and Laboratory Medicine, Aga Khan University, Karachi, Pakistan, in collaboration with Keele University, Newcastle, United Kingdom. Semi-structured interviews were conducted to collect information from diverse group of professionals working in Clinical Chemistry laboratories. All interviews were audio recorded and transcribed verbatim. They were asked what changes AI would involve in the laboratory, what resources would be necessary, and how medical education would assist them in adapting to the change. A content analysis was conducted, resulting in the development of codes and themes based on the analyzed data. RESULTS: The interviews were analysed to identify three primary themes: perspectives and considerations for AI adoption, educational and curriculum adjustments, and implementation techniques. Although the use of diagnostic algorithms is currently limited in Pakistani Clinical Chemistry laboratories, the application of AI is expanding. All thirteen participants stated their reasons for being hesitant to use AI. Participants stressed the importance of critical aspects for effective AI deployment, the need of a collaborative integrative approach, and the need for constant horizon scanning to keep up with AI developments. CONCLUSIONS: Three primary themes related to AI adoption were identified: perspectives and considerations, educational and curriculum adjustments, and implementation techniques. The study's findings give a sound foundation for making suggestions to clinical laboratories, scientific bodies, and national and international Clinical Chemistry and laboratory medicine organisations on how to manage pathologists' shifting practises because of AI.

Tradução, Adaptação, Validação e Avaliação para Uso no Brasil de um Instrumento Britânico de Auxílio à Escolha da Especialidade Médica / Translation, Adaptation, Validation and Evaluation for use in Brazil of a British Inventory to Assist in the Choice of Medical Specialty

RESUMO O objetivo deste estudo foi traduzir, validar e avaliar um instrumento britânico de auxílio à escolha da especialidade médica. Esse instrumento processa as respostas a 130 questões e fornece uma classificação de 59 especialidades médicas, em ordem decrescente de recomendação, em função do ajuste do perfil do candidato às características das especialidades. As dez primeiras recomendações são consideradas positivas, e as dez últimas, negativas. A tradução e a adaptação semântica seguiram os passos técnicos recomendados para esse tipo de trabalho, resultando no instrumento em português denominado SCIB (Special Choice Inventory - Brasil). A melhor versão das questões traduzidas foi escolhida. Em seguida, o instrumento foi aplicado a 120 médicos brasileiros (85 médicos especialistas e 35 médicos residentes), representando 38 diferentes especialidades. Foi também aplicado a 79 estudantes dos dois últimos anos do curso de graduação em Medicina. Os participantes da amostra de médicos responderam a um questionário no qual indicavam duas outras especialidades que cogitariam exercer além da atual, bem como outras três que dificilmente exerceriam. O instrumento foi considerado adequado ou muito adequado à realidade brasileira por 85,8% (103/120) dos médicos e por 73,4% (58/79) dos estudantes. Entre estes últimos, 60,8% (48/79) consideraram a escala útil ou muito útil. Os resultados da aplicação do SCIB permitiram verificar que a concordância global das recomendações positivas do instrumento foi de 67,5% (81/120) com a especialidade atualmente exercida e de 72,5% (87/120) com as especialidades que os participantes cogitaram exercer. A concordância entre as recomendações negativas da escala e as especialidades que os médicos dificilmente exerceriam foi de 87,5% (105/120). Os dados das etapas de tradução e adaptação do instrumento original trouxeram elementos para a validação de face, de conteúdo e semântica do instrumento. As respostas dos 120 médicos e os dados da reaplicação da escala a 40 deles permitiram verificar que o SCIB tem homogeneidade, consistência interna e reprodutibilidade satisfatórias. Em conclusão, a tradução e a adaptação de uma escala britânica de auxílio à escolha da especialidade médica no Brasil foram bem-sucedidas. O instrumento resultante teve desempenho muito satisfatório quando aplicado a médicos especialistas e residentes. O SCIB deve, então, constituir uma promissora ferramenta de apoio na escolha da especialidade médica, além de poder ser utilizado na investigação científica nessa área.

ABSTRACT The purpose of this study was to translate, validate and evaluate a British specialty choice inventory. This tool processes the answers to 130 items and returns a 59-medical specialty ranking, in decreasing order of recommendation, based on the candidate's profile adjustments to specialty characteristics. The top 10 and the bottom 10 recommendations are considered positive and negative ones, respectively. Translation and semantic adaptation followed the standard procedures described in the specialized literature, and resulted in a Brazilian Portuguese version named SCIB (Special Choice Inventory — Brasil). The best version of each translated item was chosen. SCIB was then applied to 120 Brazilian physicians (85 specialists and 35 residents) representing 38 different specialties. SCIB was also applied to 79 senior medical students. Participant physicians indicated in a structured questionnaire two specialties they could have chosen apart from the current one, as well as three specialties they would unlikely choose. SCIB was regarded as adequate or very adequate to the Brazilian conditions by 85.8% (103/120) of the physicians and 73.4% (58/79) of the students. Among the latter, 60.8% (48/79) regarded the inventory useful or very useful. For the physicians, SCIB positive recommendations included their current specialty in 67.5% (81/120) of the cases, and any of the specialties they could have chosen in 72.5% (87/120) of the cases. SCIB negative recommendations included any of the specialties that participants would unlikely choose in 87.5% (105/120) of the cases. The translation and adaptation procedures provided data for SCIB validation concerning the face, content and semantic aspects. Answers from the 120 physicians and data from a test-retest study involving 40 participants showed that SCIB has satisfactory levels of homogeneity, internal consistency and reproducibility. In conclusion, translation and adaptation for use in Brazil of the Sci59, a British inventory for assisting medical specialty choice, was successful and resulted in the, SCIB, a tool whose performance was very satisfactory. SCIB can thus be seen as a promising tool for assisting medical specialty choice, as well as for research in this field.

Sci45: the development of a specialty choice inventory.

OBJECTIVE: To devise a valid career selection instrument to help doctors in training choose from a range of specialties that match their attributes and aspirations and to help selection interviewers focus on the key issues pertaining to the suitability of candidates for particular training opportunities. DESIGN: A psychometric instrument of 130 4-response choice items was developed to match individual personal and professional preferences to possible career specialty choices. The development process involved semi-structured interviews with consultants in 35 specialties, a national postal survey of consultants in 45 specialties, factor analysis of the results, design of the pilot instruments, testing on 450 senior house officers (doctors in basic specialist training within 2-5 years of leaving medical school), and further item analysis to derive the final instrument. A scoring system and software were developed to indicate the best and worst fit specialties for the respondent. PARTICIPANTS: The participants were hospital consultants, general practitioners and senior house officers (SHOs) in basic specialist training. OUTCOME MEASURE: The successful construction of a valid and accessible career choice instrument (Specialty Choice Inventory/Sci45). CONCLUSIONS: This project has yielded a psychometrically valid computer- or paper-based instrument that can be used by doctors at any stage of training to assist in career choice. It can be used as part of the selection process, for careers guidance, for analysis of career problems, for research or to validate a particular range of career options.