TY - JOUR
T1 - Determinants of the implementation of an artificial intelligence-supported device for the screening of diabetic retinopathy in primary care – a qualitative study
AU - Held, Linda A.
AU - Wewetzer, Larisa
AU - Steinhäuser, Jost
N1 - Publisher Copyright:
© The Author(s) 2022.
PY - 2022/7
Y1 - 2022/7
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85135491464&partnerID=8YFLogxK
U2 - 10.1177/14604582221112816
DO - 10.1177/14604582221112816
M3 - Journal articles
C2 - 35921547
AN - SCOPUS:85135491464
SN - 1460-4582
VL - 28
JO - Health Informatics Journal
JF - Health Informatics Journal
IS - 3
ER -