A systematic review on the effectiveness and impact of clinical decision support systems for breathlessness

Abstract

Breathlessness is a common presenting symptom in practice. This systematic review aimed to evaluate the impact of CDSS on breathlessness and associated diseases in real-world clinical settings. Studies published between 1 January 2000 to 10 September 2021 were systematically obtained from 14 electronic research databases including CENTRAL, Embase, Pubmed, and clinical trial registries. Main outcomes of interest were patient health outcomes, provider use, diagnostic concordance, economic evaluation, and unintended consequences. The review protocol was prospectively registered in PROSPERO (CRD42020163141). A total of 4294 records were screened and 37 studies included of which 30 were RCTs. Twenty studies were in primary care, 13 in hospital outpatient/emergency department (ED), and the remainder mixed. Study duration ranged from 2 weeks to 5 years. Most were adults (58%). Five CDSS were focused on assessment, one on assessment and management, and the rest on disease-specific management. Most studies were disease-specific, predominantly focused on asthma (17 studies), COPD (2 studies), or asthma and COPD (3 studies). CDSS for COPD, heart failure, and asthma in adults reported clinical benefits such as reduced exacerbations, improved quality of life, improved patient-reported outcomes or reduced mortality. Studies identified low usage as the main barrier to effectiveness. Clinicians identified dissonance between CDSS recommendations and real-world practice as a major barrier. This review identified potential benefits of CDSS implementation in primary care and outpatient services for adults with heart failure, COPD, and asthma in improving diagnosis, compliance with guideline recommendations, promotion of non-pharmacological interventions, and improved clinical outcomes including mortality.

Management of chronic breathlessness in primary care: what do GPs, non-GP specialists, and allied health professionals think?

“…This issue is one that has also been identified by the World Health Organization in primary care, but remains unresolved, including in Australia (World Health Organization 2016;Harrison and Siriwardena 2018). The use of electronic clinical decision support systems that synthesise relevant diagnostic criteria and guidelines, including leveraging emerging technologies such as artificial intelligence, presents an opportunity to empower GPs to do more by providing them the support to navigate diagnostic uncertainties, as well as ensure their management aligns with best practice (Sunjaya 2022;Sunjaya et al 2022b).…”

Low Vision Rehabilitation Service Utilization Before and After Implementation of a Clinical Decision Support System in Ophthalmology

“…Across medical specialties, CDSSs have been shown to be effective at improving health care delivery processes and outcomes . Endocrinology, primary care, radiology, and other specialties have initiated CDSS and associated quality improvement efforts, but to date, despite preliminary interest, there are no published works that we know of in ophthalmology examining the use of CDSSs.…”

“…7,17,18,20 Across medical specialties, CDSSs have been shown to be effective at improving health care delivery processes and outcomes. [21][22][23][24] Endocrinology, primary care, radiology, and other specialties have initiated CDSS and associated quality improvement efforts, but to date, despite preliminary interest, 25 there are no published works that we know of in ophthalmology examining the use of CDSSs. In fairly high-volume ophthalmology clinics, the CDSS not only provided a reliable tracking mechanism for auditing service referral and utilization, but also served as a practice guideline reminder to ophthalmologists.…”

Application and Prospects of Artificial Intelligence Technology in Early Screening of Chronic Obstructive Pulmonary Disease at Primary Healthcare Institutions in China

“…Although the World Health Organization (WHO) has identified the development of health information systems and digital technologies (including CDSS) as one of the priorities for strengthening primary healthcare, the application of CDSS for evaluating patients with respiratory distress in primary healthcare and outpatient services in China has not yet become widespread. 24 Another study published in “CHEST” explored the use of AI as a predictive tool to identify high-risk COPD patients. 25 Certain AI systems use sensor data collected from wearable devices to assist in diagnosing COPD by analyzing changes in breathing patterns, such as frequency, depth, and rhythm.…”