Determinants of the implementation of an artificial intelligence-supported device for the screening of diabetic retinopathy in primary care – a qualitative study

Abstract

Diabetic retinopathy is a microvascular complication of diabetes mellitus that is usually asymptomatic in the early stages. Therefore, its timely detection and treatment are essential. First pilot projects exist to establish a smartphone-based and AI-supported screening of DR in primary care. This study explored health professionals’ perceptions of potential barriers and enablers of using a screening such as this in primary care to understand the mechanisms that could influence implementation into routine clinical practice. Semi-structured telephone interviews were conducted and analysed with the help of qualitative analysis of Mayring. The following main influencing factors to implementation have been identified: personal attitude, organisation, time, financial factors, education, support, technical requirement, influence on profession and patient welfare. Most determinants could be relocated in the behaviour change wheel, a validated implementation model. Further research on the patients’ perspective and a ranking of the determinants found is needed.

Stakeholder perspectives towards diagnostic artificial intelligence: a co-produced qualitative evidence synthesis

“…Across 44 studies, 689 participants were interviewed and 402 participated in focus groups. 31 studies conducted interviews, 16 , 24 , 25 , 31 , 32 , 34 , 36 , 37 , 38 , 40 , 41 , 42 , 43 , 44 , 45 , 48 , 49 , 50 , 51 , 53 , 55 , 57 , 59 , 60 , 61 , 62 , 63 , 64 nine conducted focus groups, 18 , 26 , 27 , 29 , 30 , 33 , 52 , 56 , 58 , 65 five conducted ethnographic studies with interviews, 17 , 46 , 47 , 54 , 66 and two conducted both interviews and focus groups. 35 , 47 The mean number of participants in interview studies was 20 (IQR 15–24), and in focus groups 40(IQR 15–37).…”

“…(2022) 41 Qualitative, NR Semi-structured interviews Membership of the “Minerva Consortium” and personal contacts of the study authors, convenience/snowballing sampling 20 Expertise: 9 (45%) clinical genetics, 2 (10%) paediatric genetics, 5 (25%) bioinformatics, 2 (10%) commercial, 3 (15%) other Rare disease Hypothetical AI used in diagnosing facial dysmorphology Discussion of the value of trust in using AI for dysmorphology, concluding that trust in AI is grounded in its reliability, competence and “intentions.” Held et al. (2022) 42 Qualitative, thematic content analysis Semi-structured interviews Mixed group of clinicians in Germany, convenience sampling 24 10 (42%) female; average year of birth 1971; 16 (67%) general practitioner, 3 (13) medical assistant, 5 (21%) ophthalmologists Ophthalmology Hypothetical AI used to diagnose diabetic retinopathy Main determinants of implementation have been identified: personal attitude, organisation, time, financial factors, education, support, technical requirement, influence on profession and patient welfare. Helenason et al.…”

“…Four distinct stakeholder groups were described: patients/the public, clinicians, researchers, and healthcare leaders. Twenty studies focussed on clinician perspectives, 17 , 18 , 29 , 32 , 35 , 42 , 44 , 46 , 48 , 50 , 52 , 54 , 55 , 60 , 61 , 63 eight on patients, 16 , 26 , 27 , 30 , 33 , 40 , 53 , 57 , 58 and one on researchers 59 and healthcare leaders/experts. 45 Fourteen focussed on mixed groups.…”

Evaluation of Synchronous and Asynchronous Telemedical Applications in Primary Care in Rural Regions of Northern Germany—Results and Lessons Learned from a Pilot Study

“…Applications should be market-ready, robust, and easy to use. Time for identifying and testing those applications is well spent [ 5 , 34 ].…”

Determinants of the implementation of artificial intelligence-based screening for diabetic retinopathy—a cross-sectional study with general practitioners in Germany

“…The questionnaire was developed on the grounds of a previously conducted qualitative study 22 and the experiences of the researchers (Director of the Institute of General Medicine, economic engineer, and GP). The questionnaire used in this study has not been previously validated.…”