COPD indicates chronic obstructive pulmonary disease.
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Chauhan U, McAlister FA. Comparison of Mortality and Hospital Readmissions Among Patients Receiving Virtual Ward Transitional Care vs Usual Postdischarge Care: A Systematic Review and Meta-analysis. JAMA Netw Open. 2022;5(6):e2219113. doi:10.1001/jamanetworkopen.2022.19113
Is virtual ward transitional care following medical discharge to home associated with better outcomes compared with usual postdischarge care?
In this systematic review and meta-analysis of 24 randomized clinical trials including 10 876 patients, virtual ward transition systems were associated with significantly fewer deaths and hospital readmissions in patients with heart failure. Across all diseases, virtual wards were also associated with fewer emergency department visits, shorter length of stay during readmissions, and lower health care costs.
In this study, although virtual ward interventions were associated with some better outcomes and lower costs, fewer deaths and readmissions were seen only in trials enrolling patients with heart failure.
Virtual wards (VWs) include patient assessment in their homes by health care personnel and offer ongoing assessment and case management via home, telephone, and/or clinic visits. The association between VWs and patient outcomes during the transition from the hospital to home are unclear; earlier reviews on this topic have often conflated telemonitoring programs with VW models.
To evaluate the use of VW transition systems for community-dwelling individuals after medical discharge.
English-language articles indexed in PubMed or Cochrane and published between January 1, 2000, and June 15, 2021.
Randomized clinical trials comparing VW care with usual postdischarge care. Studies were stratified by diagnosis.
Data Extraction and Synthesis
Following the Preferred Reporting Items for Systematic Reviews and Meta-analyses guideline, 2 reviewers independently identified studies and extracted data. DerSimonian-Laird inverse variance weighted random-effects models were used to compute relative risks (RRs) for dichotomous outcomes and mean differences for continuous outcomes.
Main Outcomes and Measures
All-cause mortality, hospital readmissions, emergency department visits, health care costs, readmission length of stay, quality of life, and functional status.
Twenty-four randomized clinical trials (11 in patients with heart failure, 3 in patients with chronic obstructive pulmonary disease, 4 in patients at high-risk for readmission, and 6 in mixed patient populations) with 10 876 patients were included (20 more trials than earlier reviews). In patients with heart failure, VWs were associated with fewer deaths (RR, 0.86; 95% CI, 0.76-0.97) and fewer readmissions (RR, 0.84; 95% CI, 0.74-0.96). However, similar associations were not seen in randomized clinical trials enrolling patients with other diagnoses (RR, 0.93; 95% CI, 0.83-1.04 for mortality and RR, 0.96; 95% CI, 0.88-1.05 for readmissions). Across all studies, VWs were associated with fewer emergency department visits (RR, 0.83; 95% CI, 0.70-0.98) and shorter readmission lengths of stay (mean difference, −1.94 days; 95% CI, −3.28 to −0.60 days). Three of 7 studies that evaluated health care expenses reported statistically significant lower costs with VW transition systems.
Conclusions and Relevance
Although postdischarge VW interventions appear to be associated with fewer subsequent emergency department visits, shorter readmission lengths of stay, and lower health care costs, fewer deaths and readmissions were seen only in trials enrolling patients with heart failure.
Up to one-fifth of patients discharged from the hospital are readmitted within 30 days and up to one-third are readmitted within 3 months.1 Although many approaches to reducing readmissions have been tested, the results have often been disappointing, and those that have achieved reduction have been beneficial only in certain contexts.2 The virtual ward (VW), a model first developed in England in 2006, uses a multidisciplinary case-management model to provide short-term transitional care to community-dwelling patients after hospital discharge to prevent unplanned readmissions.3 The VW differs from the hospital at home concept, which seeks to deliver inpatient type care in patient homes, by focusing on the period after hospital discharge as patients transition to community care. Virtual ward models include patient assessment within their home by skilled health care professionals, care coordination, and multidisciplinary team-based case management by combinations of telehealth, in-home, and/or clinic visits. Despite the theoretical appeal of the model, 2 systematic reviews identified that the evidence on the use of VWs is mixed and limited (most studies were small and reported context-specific initiatives), and benefits were only seen in studies of patients with heart failure (HF).4,5 However, most of the studies included in those 2 reviews (6 of 10 in one4 and 26 of 31 in the other5) evaluated telemonitoring programs (ongoing telephone or video follow-up with or without transmission of patient-recorded vital signs) without the key component of the 2006 VW model: patient assessment within their homes by skilled health care personnel. As telemonitoring has been shown to be efficacious for patients with HF in a number of randomized clinical trials (RCTs),6 whether VW transitional care models are beneficial after hospital discharge remains unknown.
We conducted a systematic review and meta-analysis to evaluate the use of VW interventions in a wide range of patient outcomes after discharge, including mortality, hospital readmission, emergency department visits, health care costs, quality of life, and functional status. We compared outcomes stratified by characteristics of the patient population enrolled. Patient populations were classified a priori as HF, chronic obstructive pulmonary disease (COPD), high risk for readmission, and mixed medical diagnoses.
We searched the PubMed database for English full-text articles published between January 1, 2000, and June 15, 2021. The search algorithm incorporated common terms for postdischarge transitional care interventions of interest, including virtual ward, hospital at home, and transitional care, and several terms addressing outcomes such as mortality, readmission, and cost (eMethods in the Supplement). This study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. We hand-searched the reference lists of included articles and relevant reviews from the Cochrane Library.
Publications were eligible for inclusion if they were studies in adult that compared a postdischarge VW in the community (involving at least 1 home visit by a health care practitioner after discharge with ongoing home visitations, care coordination, and daily case management with a multidisciplinary team) with usual postdischarge care in RCTs, studied patients discharged from a medical ward to home (as opposed to those needing postsurgical rehabilitation or were discharged to a skilled nursing facility), and evaluated outcomes such as all-cause mortality, hospital readmission, emergency department visits, length of stay, health care costs, quality of life, or functional status. Two reviewers (U.C. and F.A.M.) independently screened abstracts and full-text articles for inclusion. Systematic review software (Covidence, version; [Covidence]) was used to blind reviewer voting, identify conflicts, and support reaching consensus.7
One reviewer (U.C.) extracted information about study and patient characteristics, elements of each VW intervention, outcomes, and study quality, using the Cochrane Risk of Bias Tool,8 with confirmation by the second reviewer (F.A.M.). Conflicts were resolved via consensus.
We conducted our primary meta-analyses by categorizing data by patient population (HF, COPD, high risk for readmission, or mixed medical diagnoses). For dichotomous outcomes, we followed the intention-to-treat principle to compute relative risks (RRs) and used DerSimonian-Laird random-effects models with inverse-variance weights.9 For continuous outcomes, we computed mean differences using an inverse variance random-effects model. Results included in the meta-analyses correspond to outcomes reported for the maximum length of follow-up time in each study.
Studies that evaluated cost, quality of life, and functional status were too heterogeneous in their assessment methods and outcome measures to permit formal pooling; these outcomes are reported by the proportion of trials that found statistically significant benefit (reduced cost, increased quality of life) in the intervention group. We originally planned to conduct a meta-regression to see whether efficacy varied by type of VW care (including but not restricted to frequency and intensity of home visits); however, there was insufficient detail in the published studies or from authors we contacted to permit this analysis. Although we had also planned to evaluate for efficacy differences across geographic regions, there were too few studies in each region and too much heterogeneity in the results even within regions for this analysis to be done. All statistical analysis and forest plot synthesis was performed using Cochrane Review Manager, version.10 Two-sided significance testing was conducted with the significance threshold set at P < .05.
We identified 1008 unique citations, of which 24 RCTs (10 876 participants; 23 RCTs with low risk of bias) met eligibility criteria (eFigure 1 in the Supplement). Overall, 11 studies reported nursing care–dominant VW interventions and 13 used multidisciplinary team care.
Ten of the RCTs investigated patients with HF,11-21 3 evaluated patients with COPD,22-24 4 investigated patients with high risk of readmission (either by LACE [risk scoring criteria based on length of stay, acuity of the admission, comorbidities, and emergency department use 6 months before admission] scoring or local hospitalization/complexity metrics),25-28 and 6 RCTs included patients with a mix of diagnoses.29-34 Five of the RCTs were conducted in the US, 5 in Asia, 4 in Australia, 5 in Europe, 3 in Canada, and 1 in South America, and 1 trial was multinational. Canadian studies contributed the largest weight to analyses (4579 participants; 43% of the RCT total). The Table provides characteristics of the included RCTs. Risk of bias assessments are reported in the eTable in the Supplement.
Postdischarge VW transitional care was associated with fewer deaths in 10 RCTs enrolling patients with a primary diagnosis of HF (RR, 0.86; 95% CI, 0.76-0.97) (Figure 1).11-20 There was no significant difference in all-cause mortality in the non-HF RCTs (RR, 0.93; 95% CI, 0.83-1.04): 3 RCTs in patients with COPD (RR, 1.11; 95% CI, 0.69-1.79),22-24 2 in patients considered high risk for readmission (RR, 0.97; 95% CI, 0.84-1.12),25,26 and 4 in patients with a variety of diagnoses (RR, 0.84; 95% CI, 0.68-1.02).29-32
Twenty-three RCTs evaluated postdischarge hospital readmission.11-33 Virtual ward care was associated with fewer hospital readmissions in patients with a primary diagnosis of HF (RR, 0.84; 95% CI, 0.74-0.96) (Figure 2).11-21 However, the data from non-HF RCTs did not detect any significant difference in hospital readmissions (RR, 0.96; 95% CI, 0.88-1.05): 3 RCTs in patients with COPD (RR, 0.97; 95% CI, 0.62-1.51),22-24 4 in patients considered high risk for readmission (RR, 1.00; 95% CI, 0.95-1.06; with McWilliams et al27 excluded from statistical aggregation owing to 75% participant attrition),25-28 and 5 in patients with a variety of diagnoses (RR, 0.91; 95% CI, 0.73-1.14).29-33
Across all 11 trials, VW systems were associated with significantly fewer subsequent emergency department visits (RR, 0.83; 95% CI, 0.70-0.98) (Figure 3), although the results were very heterogeneous.12,16,18,22,23,25,27-29,31,33 Three of these trials were conducted in patients with a primary diagnosis of HF (RR, 0.65; 95% CI, 0.39-1.11),12,16,18 2 in patients with COPD (RR, 0.67; 95% CI, 0.17-2.57),22,23 3 in patients considered high risk for readmission (RR, 0.91; 95% CI, 0.68-1.22; with McWilliams et al27 excluded from statistical aggregation owing to 75% crossover to usual care),25,27,28 and 3 in patients with various mixed diagnoses (RR, 0.85; 95% CI, 0.55-1.33).29,31,33
Seven RCTs compared total health care expenses between the VW intervention and usual care.11-14,26,30,34 Three RCTs reported significant cost-savings of $5000 to $10 000 per patient11,12,14 and 4 were cost-neutral.13,26,30,34 All RCTs reporting significant cost-savings enrolled HF cohorts.
Eight RCTs compared the mean length of stay for hospital readmissions following discharge between the VW intervention and usual care.11,12,14,17,26,27,29,31 Four RCTs reported the mean (SD) length of stay (mean difference in length of stay, −1.94 days; 95% CI, −3.28 to −0.60 days) (Figure 4).13,15,25,30 Data from 4 RCTs could not be statistically aggregated because they only reported P values: 2 RCTs17,29 reported a significant reduction in length of stay with P < .001 and 2 studies found no significant difference between groups.11,27 Overall, 4 of 8 studies reported a significant reduction in length of stay; 3 of these 4 only enrolled patients with HF.12,14,17
Eleven RCTs compared changes in quality of life over time between the VW intervention and usual care.12,14,15,17,18,20-23,33,34 Scoring systems included the Edmonton Symptom Assessment Scale, St George’s Respiratory Questionnaire, and Euroquol 5 Dimensions of Health. Six RCTs reported changes in quality-of-life scores with means (SDs) (standardized mean difference in score improvement, 0.11; 95% CI, −0.01 to 0.24) (eFigure 2 in the Supplement).12,14,21-23,34 Four RCTs could not be statistically aggregated because they only reported P values: 1 demonstrated a significant increase in quality of life,15 1 showed a significant decrease,17 and 2 showed no or variable significance.20,33 One RCT had substantial attrition (45% attrition in the intervention group and 73% in the control group vs the intention-to-treat cohort) in quality-of-life reporting and was thus omitted from comparison.18
Five RCTs compared changes in functional status over time between the VW intervention and usual care.12,13,21,30,32 Scoring systems included the 6-minute walk test, the Palliative Performance Scale, and the Katz Index for Activities of Daily Living. No RCTs reported significant differences in the improvement or exacerbation of functional status between groups.
We found that, in patients with HF, postdischarge VW interventions were associated with fewer deaths, fewer readmissions, and shorter hospital stays for patients who were readmitted. However, the association of VW transitional care programs with those outcomes in patients with other medical conditions who were discharged remain uncertain. All VW interventions that examined costs were either cost-neutral or cost-saving. The cost-saving VW interventions all enrolled HF cohorts and reported that reduced hospitalization and length of stay in the intervention group greatly offset the added expense of home visits and clinic visits. All 4 trials enrolling patients deemed at high risk for readmission did not demonstrate any benefit across several outcomes. This lack of benefit may indicate these interventions did not meet the needs of patients with complex conditions, a relative lack or delay in responsiveness for non-HF diagnoses (eg, COPD) to short-term changes in management, or perhaps scoring systems, such as LACE or social complexity scores, select for patients whose readmissions are not preventable. These patients may well require hospital care regardless of what is done and may not have factors that can be prevented or altered. Others have suggested that only a minority of readmissions are preventable.35 Thus, it would be useful for physicians to be prepared to identify patients who stand to benefit from specialized palliative services rather than VW transitional care programs.36
Unlike earlier reviews on this topic,4,5 we did not conflate telemonitoring interventions with VW interventions: the key distinguishing factor is that the VW model proposed in 2006 has as a central tenet that patients be assessed in their homes by trained health care personnel. Most trials included in earlier reviews of VW models evaluated telemonitoring case management and not VW models. In addition, those earlier reviews included trials in patients treated and released from emergency departments or RCTs evaluating comprehensive geriatric assessments at home rather than VWs for patients transitioning from the hospital to home. As a result, only 4 trials in those 2 earlier reviews evaluated VW models for patients discharged from medical wards to home; in this systematic review and meta-analysis, we identified 20 RCTs of VW models not included in earlier reviews.
The estimates of hospital readmission and emergency department visit reductions associated with VW were heterogeneous across studies, suggesting that the effect of VW interventions on these outcomes may be more sensitive to particular elements of each program. These outcomes are also prone to more potential bias than mortality: if clinicians are aware a patient is receiving intensive VW care at home, they may be less likely to suggest they present to an emergency department or, if they are seen in the emergency department, the clinician there may be less likely to admit them. Furthermore, the patient’s threshold to go to an emergency department will probably be influenced by whether they already have follow-up with a health care professional in place.
Half of VW interventions were associated with reduced length of stay when patients were readmitted compared with patients readmitted after usual postdischarge care. This is a notable finding as it suggests that the reduction in readmission rates for patients receiving VW is not just owing to a higher threshold for readmission; in that case, one would expect the patients being readmitted to be sicker and thus have longer lengths of stay. It is interesting to speculate whether direct collaboration between VW staff and inpatient clinicians improves information transfer and continuity, thereby enhancing the quality of inpatient care.
Quality-of-life reporting varied greatly across studies, as did the nature of the interventions, making it difficult to define an average result of VW interventions. Although some participants reported feelings of satisfaction and security with VW care and associated improvements in health, negative factors cited by others included an inability to disconnect from the health care system, the invasive nature of home visits, deeper internalization of a sick role and their dependency on the health care system, and greater awareness of symptoms influencing symptom-based quality-of-life metrics.
This study has strengths. Our search strategy was broad and included hand searches of identified studies and review articles, we conducted our study as per PRISMA recommendations and focused on RCTs reporting objective outcomes, and we extracted several high-quality trials and stratified by patient population. Although some reviews limited investigation to the effects of VW interventions for patients with only 1 condition,37 we evaluated a wider array of outcomes and conditions to assess differential outcomes across patient populations.
The study has limitations. These include limited reporting of functional status, quality-of-life metrics, length of stay data, and lack of individual patient data that would permit meta-regression to evaluate for differences in efficacy over time or by more granular patient subgroups or specific elements of the interventions. In addition, although our interest was in all patients being discharged from medical wards, we found few RCTs of non-HF cohorts, particularly patients with COPD who make up a substantial proportion of readmitted patients. We are aware of VW programs for patients following stroke or surgical admissions and would encourage others to examine whether such programs demonstrate efficacy in those populations. This hypothesis should be tested rather than assumed based on our findings for non-HF populations in our systematic review and meta-analysis. With respect to our statistical analyses, we acknowledge that the DerSimonian-Laird random-effects model is limited in its consideration of study heterogeneity; it offers straightforward calculations but produces slightly narrower 95% CIs compared with more advanced statistical packages. In addition, VW programs in our study were heterogeneous in definition and intensity, which limits our ability to make specific recommendations about which VW elements are key for implementation.
In this systematic review and meta-analysis, VW transitional care programs for recently discharged patients were associated with clear benefits in patients with HF, but their association with mortality or readmissions in patients with other chronic medical conditions or complex social situations remains uncertain and thus requires further research. Just as a single approach is not sufficient for most interventions in health care, it is clear from our data that not all patients benefit from VW transitional programs, even in the optimized setting of RCTs. Based on earlier studies, we believe that all patients discharged from medical wards should have an outpatient follow-up appointment within 2 weeks of discharge with a familiar physician (either their regular primary care clinician or a physician who cared for them during their hospitalization).38-40 We believe that VW transitional care programs should be targeted toward patients most likely to derive benefit; however, the difficulty is in identifying such individuals as even experienced clinicians and many risk prediction tools cannot accurately do so.41,42 Moreover, targeting VW interventions toward patients who need a high level of care is unlikely to be the best approach since fewer than half of such patients continue to need that level of care in consecutive years.43 As the comorbidity burdens of discharged patients increase, the proportion of patients who might potentially benefit from VW transitional care programs is likely to change and we would suggest that any VW transitional care program should be implemented with a robust evaluation component.
Accepted for Publication: May 10, 2022.
Published: June 28, 2022. doi:10.1001/jamanetworkopen.2022.19113
Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2022 Chauhan U et al. JAMA Network Open.
Corresponding Author: Finlay A. McAlister, MD, MSc, Division of General Internal Medicine, University of Alberta, 5-134C Clinical Sciences Bldg, 11350 83 Ave, Edmonton, Alberta, Canada T6G 2G3 (firstname.lastname@example.org).
Author Contributions: Both authors had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Both authors.
Acquisition, analysis, or interpretation of data: Both authors.
Drafting of the manuscript: Both authors.
Critical revision of the manuscript for important intellectual content: Both authors.
Statistical analysis: Chauhan.
Administrative, technical, or material support: McAlister.
Conflict of Interest Disclosures: None reported.