The effect of telemedicine in critically ill patients: systematic review and meta-analysis

High-intensity physician staffing in intensive care units (ICUs), known as a closed ICU model, is defined as mandatory transfer of responsibility for the care of every critically ill patient to an intensivist-led team or mandatory consultation by an intensivist [1]. This model of staffing is associated with an increased use of evidence-based treatments [2] and significant reductions in mortality and length of stay (LOS) [3, 4]. However, projected population demands for intensive care will exceed the number of available intensivists, implying that many critically ill patients will be cared for in low-intensity staffing ICUs (an open model), in which any physician can admit and care for patients without the involvement of an intensivist [5].

Telemedicine, broadly defined as the exchange of medical information via electronic communication, may help to fill gaps in intensivist coverage and give all patients access to specialty care 24 hours per day, 7 days per week [6]. It allows real-time exchange of clinical data and direct interaction among critical care providers across long distances and provides decision support to underserviced rural areas, small hospitals without access to intensivists [7], and large hospitals with low-intensity physician-staffing models or nocturnal physician shortages. Some applications also contain decision-support tools to facilitate implementation of best practices and alarms to alert providers to sudden changes in patient status [8‐12].

A recent systematic review found that telemedicine, as compared with standard of care, decreased mortality in patients admitted to ICUs [13]. However, it remains unclear whether an active telemedicine system (for example, one with continuous monitoring of patient data with computer-generated alerts) is required for beneficial clinical effects or whether more-passive systems (such as remote intensivist consultation alone) would suffice. The objective of our systematic review was to determine the effect of telemedicine on ICU mortality in critically ill patients, focusing on subgroup effects related to the intensity of the intervention and quality of the study.

In this systematic review and meta-analysis, we found 11 before/after observational studies, including 49,457 patients, that examined the effect of telemedicine on clinically important outcomes. Our main findings are that telemedicine reduced ICU and hospital mortality and lengths of stay in critically ill patients. Although the effect of telemedicine on ICU mortality was similar among active and passive systems, this subgroup analysis was underpowered to detect a true dose-response effect. Notwithstanding the methodologic limitations of observational studies and meta-analyses of unadjusted data, telemedicine appears to be a promising intervention to improve outcomes in the ICU and should be studied further.

Telemedicine systems may improve clinical outcomes by improving adherence to best practices in the ICU, which has been demonstrated to be poor [33]. One study [29] in this review found that telemedicine increased adherence to four best practices and reduced complications of ventilator-associated pneumonia and catheter-related bloodstream infections. Other studies not meeting inclusion criteria for this review have also shown improved adherence to best practices with telemedicine. For example, a recent cluster-randomized trial showed that a multifaceted knowledge-translation intervention that included education via telemedicine increased the adoption of targeted best practices in community hospitals with few resources dedicated to quality improvement [34]. Similarly, a before/after study found a significant increase in the percentage of patients who received a daily sedative interruption with tele-ICU pharmacy support [35]. Last, one study reported improved nursing-staff satisfaction after the implementation of robotic tele-ICU [36]. However, with this exception [29], the studies in this review did not report process-of-care measures sufficiently to address the hypothesis that lower mortality was associated with improved adherence to best practices.

Our results are similar to those of Young et al. [13], who found that telemedicine is associated with a reduction in ICU mortality (pooled odds ratio, 0.80; 95% CI, 0.66 to 0.97; P = 0.02), but not hospital mortality. Whereas Young et al. explored subgroup effects on the basis of vendor affiliation, our objective was to determine whether more technologically advanced telemedicine systems, with or without continuous patient-data monitoring, were associated with a statistically significant benefit on ICU mortality compared with less-advanced systems. Our subgroup analysis did not confirm a differential effect between these types of systems, even when the advanced-technology group was restricted to active systems with continuous patient-data monitoring and alerts. In addition to lack of statistical power in this analysis, the interventions used in included studies may have been misclassified because of the lack of a commonly adopted conceptual framework and vocabulary to describe components of the intervention, the intensity with which they were deployed, and the clinical actions attributable to their deployment [37].

Besides the lack of evidence to guide selection of telemedicine features important for clinical benefit, other issues should mitigate against widespread implementation. First, generalizability is limited, as studies were conducted in few hospitals in one country. Second, the impact of telemedicine likely depends on characteristics of the environment in which it is deployed, including ICU organization (such as physician-staffing model and use of protocols) and patient case mix. Studies generally reported limited relevant contextual details. Third, the costs of installation and maintenance [38], potential for malfunction and downtime, and impact of redeployment of intensivists away from bedside clinical care during labor shortages have not been analyzed. Fourth, telemedicine has been primarily examined in before/after observational studies, from which conclusions regarding causality may be confounded by secular trends in case-mix and other interventions. These issues, although shared by healthcare technology in general [39], imply that universal adoption of telemedicine should be depend on the results of future studies, the design of which should be informed by a robust understanding of system design and organizational factors associated with patient benefit.

Strengths of this review include several methods to minimize bias, including a comprehensive literature search, duplicate outcomes abstraction, consideration of important clinical outcomes, and use of an established method to assess study quality specific to nonrandomized studies [22]. Our review also has weaknesses. In the absence of any randomized trials of telemedicine, we included observational studies, which tend to overestimate the effects of an intervention [40] even with standard methods to adjust for differences between groups [40‐42]. Our meta-analyses used unadjusted data and may have further exaggerated treatment effects. Although we believed the interventions were sufficiently similar in concept and execution to permit statistical aggregation, major differences occur in the components of this intervention, methods of deployment, and rates of adoption in the included studies. Moderate statistical heterogeneity was seen in our primary outcome that persisted in subgroups defined by study quality and telemedicine technology. Therefore, even among studies using advanced telemedicine interventions, our review cannot identify with certainty the components essential to success. Last, our subgroup analyses had few studies; for example, the lower-technology (low-intensity passive) telemedicine subgroup had only three studies. The power to detect clinically important subgroup effects was therefore limited.

Telemedicine is a promising technology to reduce mortality in the critically ill. Recently, the Critical Care Societies Collaborative proposed a comprehensive research agenda in ICU telemedicine, including development of a conceptual framework to describe the telemedicine system and the recipient ICUs and elucidation of mechanisms of telemedicine's effects on downstream clinical outcomes by analyzing effects on structure and process-of-care variables [37]. We believe that this complex intervention, similar to others in the ICU, warrants eventual evaluation in a cluster-randomized trial. Important areas of research that would inform the design of such a trial, in addition to those described, include individual patient meta-analysis of existing studies to permit adjustment for hospital and patient-level characteristics to identify patients and centers most likely to benefit, assessment of clinical equipoise (physician and nursing attitudes to ICU telemedicine) by using qualitative methods [43], and pilot observational studies to establish the optimal telemedicine technology configuration and dose tailored to ICU organization and case mix.