Effectiveness of clinical dashboards as audit and feedback or clinical decision support tools on medication use and test ordering: a systematic review of randomized controlled trials

Abstract

Background Clinical dashboards used as audit and feedback (A&F) or clinical decision support systems (CDSS) are increasingly adopted in healthcare. However, their effectiveness in changing the behavior of clinicians or patients is still unclear. This systematic review aims to investigate the effectiveness of clinical dashboards used as CDSS or A&F tools (as a standalone intervention or part of a multifaceted intervention) in primary care or hospital settings on medication prescription/adherence and test ordering. Methods Seven major databases were searched for relevant studies, from inception to August 2021. Two authors independently extracted data, assessed the risk of bias using the Cochrane RoB II scale, and evaluated the certainty of evidence using GRADE. Data on trial characteristics and intervention effect sizes were extracted. A narrative synthesis was performed to summarize the findings of the included trials. Results Eleven randomized trials were included. Eight trials evaluated clinical dashboards as standalone interventions and provided conflicting evidence on changes in antibiotic prescribing and no effects on statin prescribing compared to usual care. Dashboards increased medication adherence in patients with inflammatory arthritis but not in kidney transplant recipients. Three trials investigated dashboards as part of multicomponent interventions revealing decreased use of opioids for low back pain, increased proportion of patients receiving cardiovascular risk screening, and reduced antibiotic prescribing for upper respiratory tract infections. Conclusion There is limited evidence that dashboards integrated into electronic medical record systems and used as feedback or decision support tools may be associated with improvements in medication use and test ordering.

What is the quantity, quality and type of systematic review evidence available to inform the optimal prescribing of statins and antihypertensives? A systematic umbrella review and evidence and gap map

“…Nine of the reviews synthesised qualitative evidence,27 31 42 50 55 58 60 61 83 104 four of which also included quantitative evidence in a mixed evidence synthesis 42 50 58 61. Of the reviews synthesising quantitative evidence evaluating interventions, interventions focused on: enhancing patient adherence to medication as prescribed (n=57),25 30 32–35 37–41 43–46 48 49 51 53 54 56 57 59 62 63 65–71 73–81 86 87 89–96 98–103 105 deprescribing a prescribed medication (n=6)36 46 72 80 88 93 or optimising the prescribing of medication to meet the needs of the patient (n=13) 26 28 29 38 52 64 71 84 85 87 90 100 106. Three of these reviews were judged by reviewers to have dual aims 71 87 90.…”

“…Two high quality,27 72 and seven ‘critically low’ quality,31 33 50 55 80 105 106 reviews of qualitative evidence included in the ‘pretreatment/initiation’ part of pathway, were also relevant here.…”

“…Four ‘critically low’ quality synthesised quantitative evidence to optimise the prescribing of medications, including statins and antihypertensives 85 87 90 106. One ‘high’ quality review evaluated interventions to optimise adherence to both groups of medication 98 99.…”

“… 29 85 87 One ‘critically low’ quality review synthesised quantitative evidence evaluating interventions to reduce the prescribing of fall risk increasing drugs in older adults. 47 The medication of interest within one ‘critically low’ quality review was both statins and antihypertensives, 106 and antihypertensives alone in a high-quality review. 72 …”

A TOGAF based interoperable health information system needs assessment for practitioner–patient interaction

“…Such applications, in turn, tend to make it possible for tertiary healthcare decision support and intelligence dashboards to be met for better patient care and public health administration activities (Blazek et al, 2022). The activities may include healthcare indicators dashboards, data analytics platforms, and patient self‐care portals which support clinical decisions at an end‐user level offering expert advice from a healthcare expert system, for example, dashboards for electronic medical records and clinical decision support and other healthcare quality indicators (Xie et al, 2022).…”