Interventions to reduce low-value imaging – a systematic review of interventions and outcomes

Abstract

Background It is estimated that 20–50% of all radiological examinations are of low value. Many attempts have been made to reduce the use of low-value imaging. However, the comparative effectiveness of interventions to reduce low-value imaging is unclear. Thus, the objective of this systematic review was to provide an overview and evaluate the outcomes of interventions aimed at reducing low-value imaging. Methods An electronic database search was completed in Medline – Ovid, Embase-Ovid, Scopus, and Cochrane Library for citations between 2010 and 2020. The search was built from medical subject headings for Diagnostic imaging/Radiology, Health service misuse or medical overuse, and Health planning. Keywords were used for the concept of reduction and avoidance. Reference lists of included articles were also hand-searched for relevant citations. Only articles written in English, German, Danish, Norwegian, Dutch, and Swedish were included. The Mixed Methods Appraisal Tool was used to appraise the quality of the included articles. A narrative synthesis of the final included articles was completed. Results The search identified 15,659 records. After abstract and full-text screening, 95 studies of varying quality were included in the final analysis, containing 45 studies found through hand-searching techniques. Both controlled and uncontrolled before-and-after studies, time series, chart reviews, and cohort studies were included. Most interventions were aimed at referring physicians. Clinical practice guidelines (n = 28) and education (n = 28) were most commonly evaluated interventions, either alone or in combination with other components. Multi-component interventions were often more effective than single-component interventions showing a reduction in the use of low-value imaging in 94 and 74% of the studies, respectively. The most addressed types of imaging were musculoskeletal (n = 26), neurological (n = 23) and vascular (n = 16) imaging. Seventy-seven studies reported reduced low-value imaging, while 3 studies reported an increase. Conclusions Multi-component interventions that include education were often more effective than single-component interventions. The contextual and cultural factors in the health care systems seem to be vital for successful reduction of low-value imaging. Further research should focus on assessing the impact of the context in interventions reducing low-value imaging and how interventions can be adapted to different contexts.

Understanding the multilevel determinants of clinicians’ imaging decision-making: Setting the stage for de-implementation of low-value imaging

“…This approach enabled a more systematic assessment of multilevel determinants of imaging, including its contextual determinants for deimplementation. Despite being crucial to identifying and developing effective de-implementation strategies, contextual determinants are often are overlooked in studies that focus on identifying determinants of, speci cally, low-value imaging (31). Moreover, we examined imaging in two different clinical conditions in which low-value imaging is common and investigated the similarities and differences of the determinants in different disease contexts.…”

Visualizing the Invisible: Invisible Waste in Diagnostic Imaging

“…Moreover, we can promote efficiency and justice, as low-value care resources are freed up to provide high-value care. Many measures for reducing waste are available [ 21 ], but it is crucial that they are adapted to the specific context.…”

“…This article is not a systematic review, and it is not exhaustive in referencing the literature. However, many references stem from one scoping review [ 15 ] and a systematic review [ 21 ], which is supplemented with relevant references from related academic fields. Nonetheless, this study can be of great value for further research, including systematic reviews of waste in imaging.…”

“…While this paradox is well known, and a recent systematic review provides an overview of the many interventions available to reduce low-value imaging and their outcomes [ 21 ], the problem prevails. Accordingly, the objective of this study is to investigate various types of waste in imaging and why they are so persistent in today’s health services.…”

Paying for artificial intelligence in medicine

“…Reimbursement of AI is nascent, and it may take years to evaluate whether CMS’s initial per-use reimbursement policies have led to the overuse of medical AI. However, experience with other devices related to imaging and procedural services suggests that per-use reimbursement encourages overuse 13 , 14 . For example, reductions in fee-for-service reimbursement have been shown to be associated with decreases in unnecessary radiology utilization in chronic diseases such as stroke 15 .…”