Decision support tools in low back pain

Coupé, Veerle M.H.; Hooff, Miranda L. van; Kleuver, Marinus de; Ostelo, Raymond

doi:10.1016/j.berh.2017.07.002

Cited by 16 publications

(21 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…An application of predictive analytics which is nowadays finding a wide use in the clinical practice is the decision support tool (DST), which exploits the predictive power of the models to support clinical decisions by providing personalized predictions. A recent example of DST in spine care is the Nijmegen Decision Tool for Chronic Low Back Pain, which is based on predictors covering various aspects of the patient's health (namely, sociodemographic, pain, somatic, psychological, functioning, and quality of life) to suggest either surgical treatment, conservative care, or no intervention. This DST is still under development, and the technical implementation of the decision has not been finalized yet.…”

Section: Applications Of Ai and ML In Spine Researchmentioning

confidence: 99%

Artificial intelligence and machine learning in spine research

2019

View full text Add to dashboard Cite

Artificial intelligence (AI) and machine learning (ML) techniques are revolutionizing several industrial and research fields like computer vision, autonomous driving, natural language processing, and speech recognition. These novel tools are already having a major impact in radiology, diagnostics, and many other fields in which the availability of automated solution may benefit the accuracy and repeatability of the execution of critical tasks. In this narrative review, we first present a brief description of the various techniques that are being developed nowadays, with special focus on those used in spine research. Then, we describe the applications of AI and ML to problems related to the spine which have been published so far, including the localization of vertebrae and discs in radiological images, image segmentation, computer‐aided diagnosis, prediction of clinical outcomes and complications, decision support systems, content‐based image retrieval, biomechanics, and motion analysis. Finally, we briefly discuss major ethical issues related to the use of AI in healthcare, namely, accountability, risk of biased decisions as well as data privacy and security, which are nowadays being debated in the scientific community and by regulatory agencies.

show abstract

Section: Applications Of Ai and ML In Spine Researchmentioning

confidence: 99%

Artificial intelligence and machine learning in spine research

2019

View full text Add to dashboard Cite

show abstract

“…Finally, the development and provision of decision support tools to assist patients in reflecting on their feelings about certain types of treatment is essential. The planning and design of these for a complex condition such as low back pain will be challenging [45], the first for example for chronic low back pain has recently been published [46]. Ideally these tools will equally support both practitioner and patient in the SDM journey.…”

Section: Discussionmentioning

confidence: 99%

Shared decision making by United Kingdom osteopathic students: an observational study using the OPTION-12 instrument

Rajendran¹,

Beazley²,

Bright³

2019

Chiropr Man Therap

View full text Add to dashboard Cite

Background At the crux of patient centred care is Shared Decision Making (SDM), which benefits patient and practitioner. Despite external pressures, studies indicate that SDM remains poorly practised across a variety of healthcare professions. The degree of SDM engagement within United Kingdom osteopathic undergraduate teaching clinics is currently unknown. Methods In 2014 we used the reliable and validated OPTION-12 (O12) instrument to calculate a score that reflected the degree of SDM utility in one United Kingdom Osteopathic Educational Institute’s teaching clinic. We also aimed to compare these scores with those previously obtained for physiotherapists working within the United Kingdom’s National Health Service. Student-patient initial and follow-up encounters were audio recorded, transcribed and scored using the O12. Comparisons between the following O12 scores were performed: the Osteopathic Educational Institute’s 4th and 3rd year students; the Osteopathic Educational Institute’s student’s initial and follow-up patient encounters; the Osteopathic Educational Institute’s students and National Health Service physiotherapists. Results We analysed 35.5 h of transcribed data from 30 student-patient encounters (7 initial: 23 follow-up). An O12 score of 0.6% (range 0–10.4%) was calculated. No significant differences were found between year groups or encounter types. Significant differences were found compared to National Health Service physiotherapist (score = 24.4%): (U = 144, z = 4.25, p < 0.0005); although both scores are below the 60% threshold for competent SDM behaviour. Conclusions Undergraduate osteopaths did not appear to engage in competent SDM behaviours, implying traditional and paternalistic styles of decision making that align with results from other manual therapy professions. Students in this study did not practise competent SDM behaviours. Effective educational strategies are required to ensure SDM behaviours reach competent levels.

show abstract

“…In the context of the conservative management of patients with NSLBP with or without associated psychosocial factors, a plethora of original and review studies exist, and an increasing number of knowledge tools including EBCPGs have become available (Coupé, van Hooff, de Kleuver, Steyerberg, & Ostelo, 2016;Fairbank et al, 2011;Foster, Hill, O'Sullivan, & Hancock, 2013;Sepucha et al, 2016;Wong et al, 2017). Therefore, it would appear, with some reservations regarding quality and adequacy, that NSLBP treatment knowledge has been successfully refined through all three stages.…”

Section: Attitudesmentioning

confidence: 99%

Evidence-Based Practice for Non-Specific Low Back Pain: Canadian Physiotherapists’ Adherence, Beliefs, and Perspectives

Prado

Parsons

Ripat

2022

Physiotherapy Canada

View full text Add to dashboard Cite

Purpose: Physiotherapists are key providers of care for patients with low back pain (LBP); however, information on Canadian physiotherapists’ use of evidence-based clinical practice guidelines (EBCPGs) for LBP is lacking. We aimed to (1) describe Canadian physiotherapists’ adherence to EBCPGs for LBP; (2) compare beliefs and attitudes of physiotherapists with higher and lower adherence; (3) identify predictors of adherence; and (4) gather physiotherapists’ perceptions about the care provided to patients with LBP. Method: This mixed methods study involved two phases: (1) a survey containing a LBP clinical scenario and (2) qualitative semi-structured interviews with physiotherapists. Results: A total of 406 (77%) of the 525 survey respondents demonstrated higher adherence (score of 3 or 4) to EBCPGs; however, only 29.5% chose interventions to address psychosocial issues. Postgraduate training was the strongest predictor of higher adherence. Interviewed physiotherapists reported being highly satisfied with the care provided to patients with LBP even when psychosocial issues are present, despite low confidence in addressing those issues. Conclusions:Although overall adherence was high, Canadian physiotherapists do not frequently address psychosocial issues with LBP patients, and often do not feel confident or competent in that aspect of practice. This suggests an opportunity for developing additional training for addressing psychosocial issues in LBP patients.

show abstract

Decision support tools in low back pain

Cited by 16 publications

References 39 publications

Artificial intelligence and machine learning in spine research

Artificial intelligence and machine learning in spine research

Shared decision making by United Kingdom osteopathic students: an observational study using the OPTION-12 instrument

Evidence-Based Practice for Non-Specific Low Back Pain: Canadian Physiotherapists’ Adherence, Beliefs, and Perspectives

Contact Info

Product

Resources

About