The effect of telemedicine employing telemonitoring instruments on readmissions of patients with heart failure and/or COPD: a systematic review

Abstract

Background: Hospital readmissions pose a challenge for modern healthcare systems. Our aim was to assess the efficacy of telemedicine incorporating telemonitoring of patients' vital signs in decreasing readmissions with a focus on a specific patient population particularly prone to rehospitalization: patients with heart failure (HF) and/or chronic obstructive pulmonary disease (COPD) through a comparative effectiveness systematic review.

Methods: Three major electronic databases, including PubMed, Scopus, and ProQuest's ABI/INFORM, were searched for English-language articles published between 2012 and 2023. The studies included in the review employed telemedicine incorporating telemonitoring technologies and quantified the effect on hospital readmissions in the HF and/or COPD populations.

Results: Thirty scientific articles referencing twenty-nine clinical studies were identified (total of 4,326 patients) and were assessed for risk of bias using the RoB2 (nine moderate risk, six serious risk) and ROBINS-I tools (two moderate risk, two serious risk), and the Newcastle-Ottawa Scale (three good-quality, four fair-quality, two poor-quality). Regarding the primary outcome of our study which was readmissions: the readmission-related outcome most studied was all-cause readmissions followed by HF and acute exacerbation of COPD readmissions. Fourteen studies suggested that telemedicine using telemonitoring decreases the readmission-related burden, while most of the remaining studies suggested that it had a neutral effect on hospital readmissions. Examination of prospective studies focusing on all-cause readmission resulted in the observation of a clearer association in the reduction of all-cause readmissions in patients with COPD compared to patients with HF (100% vs. 8%).

Conclusions: This systematic review suggests that current telemedicine interventions employing telemonitoring instruments can decrease the readmission rates of patients with COPD, but most likely do not impact the readmission-related burden of the HF population. Implementation of novel telemonitoring technologies and conduct of more high-quality studies as well as studies of populations with ≥2 chronic disease are necessary to draw definitive conclusions.

Systematic review registration: This study is registered at the International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY), identifier (INPLASY202460097).

Keywords: ADHF -acute decompensated heart failure; AECOPD -acute exacerbation of chronic obstructive pulmonary disease; COPD; heart failure; readmission(s); telemedicine; telemonitoring.

Figure 1

PRISMA flowchart depicting the process of the literature search of the systematic review. PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses.

Figure 2

World map representing the countries where the identified studies were conducted.

Figure 3

Column charts depicting the percentages of identified studies using remote monitoring for each vital sign. (A) Proportion of heart failure (HF) studies telemonitoring for weight, heart rate (HR), blood pressure (BP), electrocardiograph (ECG) and oxygen saturation (Ox Sat). (B) Proportion of chronic obstructive pulmonary diseases (COPD) studies telemonitoring for Ox Sat, HR, weight, pulmonary volumes via spirometry, BP, temperature and respiratory rate (RR). BP, blood pressure; COPD, chronic obstructive pulmonary disease; ECG, Electrocardiograph; HF, heart failure; HR, heart rate; Ox Sat, oxygen saturation; RR, respiratory rate.

Figure 4

“Traffic light” plots of the domain-level judgements for each individual result and weighted bar plots of the distribution of risk-of-bias judgements within each bias domain for randomized controlled trials (RCTs) and non-RCTs. (A) For RCTs, the risk of bias tool for randomized trials (RoB2) was utilized. The majority of RCTs were generally categorized as having intermediate/unclear risk of bias. None of the studies was deemed as low risk due to the nature of telemedicine interventions, which precluded blinding of patients and healthcare professionals. (B) For non-RCTs, the risk of bias tool in non-randomized studies of interventions (ROBINS-I) was applied. Similar types of biases regarding the lack of blinding and pre-selection of the intervention population were encountered in all the studies. RCTs, randomized controlled trials; ROBINS-I, risk of bias tool in non-randomized studies of interventions; RoB2, risk of bias tool for randomized trials.