Mandrola, John M

Shared decision making (SDM) has been advocated to improve patient care, patient decision acceptance, patient-provider communication, patient motivation, adherence, and patient reported outcomes. Documentation of SDM is endorsed in several society guidelines and is a condition of reimbursement for selected cardiovascular and cardiac arrhythmia procedures. However, many clinicians argue that SDM already occurs with clinical encounter discussions or the process of obtaining informed consent and note the additional imposed workload of using and documenting decision aids without validated tools or evidence that they improve clinical outcomes. In reality, SDM is a process and can be done without decision tools, although the process may be variable. Also, SDM advocates counter that the low-risk process of SDM need not be held to the high bar of demonstrating clinical benefit and that increasing the quality of decision making should be sufficient. Our review leverages a multidisciplinary group of experts in cardiology, cardiac electrophysiology, epidemiology, and SDM, as well as a patient advocate. Our goal is to examine and assess SDM methodology, tools, and available evidence on outcomes in patients with heart rhythm disorders to help determine the value of SDM, assess its possible impact on electrophysiological procedures and cardiac arrhythmia management, better inform regulatory requirements, and identify gaps in knowledge and future needs.

Background: Efficacy of an intervention is commonly evaluated using P values, in addition to effect size measures such as absolute risk reduction, relative risk reduction, and numbers needed to treat. However, these measures are not always intuitive to clinicians. The fragility index (FI) is a more intuitive number that can facilitate interpretation but can only be used with binary outcomes. FI is the minimum number of patients who must be moved from the nonevent group to the event group to turn a significant result nonsignificant. In this retrospective analysis, we assessed the robustness of cardiovascular randomized controlled trials (RCTs), which report a positive (statistically significant) primary outcome by using the FI. Methods and Results: We searched Medline from 2007 to 2017 to identify cardiovascular RCTs published in 6 high impact journals ( The Lancet , New England Journal of Medicine , Journal of the American Medical Association , Circulation , Journal of the American College of Cardiology and European Heart Journal ). Only RCTs with sample sizes >500 and a 2-by-2 factorial design or dichotomous primary outcomes were selected. FI was calculated using a defined approach. Among the cohort of 123 RCTs that met inclusion criteria, median FI was 13 (interquartile range, 5–26). In 28 trials (22.8%), FI ranged between 1 and 4. In 37 trials (30.1%), number of patients lost to follow-up was higher than the FI. Pharmaceutical interventions had higher FI compared with other interventions, FI=19 (7–52; P =0.002). Median FI varied according to subspecialty (electrophysiology=2; heart failure=11; interventional cardiology=8; P =0.020) and multiregional RCTs had higher FI=22 (12–53.25; P =0.023). FI did not differ based on risk of bias indicators, funding, or publication year. Conclusions: Considerable variations in FI were observed among cardiovascular trials, suggesting the need for careful interpretation of results, particularly when number of patients lost to follow-up exceeds FI.

Mobile technology has become a ubiquitous part of everyday life and is changing the way we offer clinical care and perform clinical research. We have unprecedented access to data for one’s self-care as well as for sharing with health care providers. Meeting the challenge posed by the influx of wearable device data requires a multidisciplinary team of researchers, clinicians, software developers, information technologists, and statisticians. Although the possibility of what can be achieved with the ever-evolving wearable technologies seems to be unlimited, regulatory agencies have provided a framework to establish standards for clinical applications, which will also affect research applications. Clinical programs and electronic medical records vendors should prepare to establish a framework to implement these technologies into clinicians’ workflow and to allow feedback to measure the impact on clinical outcome. In this article, we discuss how a new brand of multidisciplinary care is evolving around mobile health devices and present a vision of up-and-coming technology in this space.