Evaluating the Effect of Monitoring through Telephone (Tele-Monitoring) on Self-Care Behaviors and Readmission of Patients with Heart Failure after Discharge

Comparative effectiveness of ehealth self-management interventions for patients with heart failure: A Bayesian network meta-analysis

OBJECTIVE

This study evaluated the effectiveness of electronic self-management support interventions in reducing all-cause mortality, cardiovascular mortality, readmission rates, and HF-related readmission in heart failure patients.

METHODS

Following the PRISMA-P guidelines and PRISMS taxonomy, we searched Pubmed, Cochrane Library, and Embase for RCTs and trials of electronic health technologies for heart failure interventions. Develop support programs in advance for education, monitoring, reminders, or a combination of these to screen and categorize studies. The Cochrane ROB2 tool was used to assess the risk of bias.

RESULTS

The monitoring interventions may improve all-cause mortality (OR 0.77, 95% CI 0.63 to 0.93) and cardiovascular mortality (OR 0.75, 95% CI 0.61 to 0.93) compared to usual care. Reminder interventions were associated with significantly reducing readmission rates (OR 0.07, 95% CI 0.00 to 0.94). Mixed interventions were most effective in reducing HF-related readmission rates (OR 0.75, 95% CI 0.56 to 0.99).

CONCLUSION

Electronic self-management interventions, particularly monitoring and reminders, can potentially improve outcomes of heart failure patients, including reducing all-cause mortality, cardiovascular mortality, and readmission rates.

PRACTICE IMPLICATIONS

The eHealth model and the combination of self-management are significant for long-term intervention in patients with HF to improve their quality of life and prognosis.

Telehealth-based transitional care management programme to improve access to care

BACKGROUND

The transition from hospital to home is a vulnerable time for patients and families that can be improved through care coordination and structured discharge planning.

LOCAL PROBLEM

Our organisation aimed to develop and expand a programme that could improve 30-day readmission rates on overall and disease-specific populations by assessing the impact of a telehealth outreach by a registered nurse (RN) after discharge from an acute care setting on 30-day hospital readmission.

METHODS

This is a prospective observational design conducted from May 2021 to December 2022 with an urban, non-academic, acute care hospital in Westchester County, New York. Outcomes for patients discharged home following inpatient hospitalisation were analysed within this study. We analysed overall and disease-specific populations (congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD) and pneumonia (PNA)) as compared with a 40-month prestudy cohort.

INTERVENTIONS

Patients were identified in a non-random fashion meeting criterion of being discharged home after an inpatient admission. Participants received a telephonic outreach by an RN within 72 hours of discharge. Contacted patients were asked questions addressing discharge instructions, medication access, follow-up appointments and social needs. Patients were offered services and resources based on their individual needs in response to the survey.

RESULTS

68.2% of the 24 808 patients were contacted to assess and offer services. Median readmission rates for these patients were 1.2% less than the prestudy cohort (11.0% to 9.8%). Decreases were also noted for disease-specific conditions (CHF (14.3% to 9.1%), COPD (20.0% to 13.4%) and PNA (14.9% to 14.0%)). Among those in the study period, those that were contacted between 24 and 48 hours after discharge were 1.2 times less likely to be readmitted than if unable to be contacted (254/3742 (6.8%) vs 647/7866 (8.2%); p=0.005).

CONCLUSIONS

Using a multifaceted telehealth approach to improve patient engagement and access reduced 30-day hospital readmission for patients discharged from the acute care setting.

Transitional Care Interventions From Hospital to Community to Reduce Health Care Use and Improve Patient Outcomes: A Systematic Review and Network Meta-Analysis

Importance

Discharge from the hospital to the community has been associated with serious patient risks and excess service costs.

Objective

To evaluate the comparative effectiveness associated with transitional care interventions with different complexity levels at improving health care utilization and patient outcomes in the transition from the hospital to the community.

Data Sources

CENTRAL, Embase, MEDLINE, and PsycINFO were searched from inception until August 2022.

Study Selection

Randomized clinical trials evaluating transitional care interventions from hospitals to the community were identified.

Data Extraction and Synthesis

At least 2 reviewers were involved in all data screening and extraction. Random-effects network meta-analyses and meta-regressions were applied. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines were followed.

Main Outcomes and Measures

The primary outcomes were readmission at 30, 90, and 180 days after discharge. Secondary outcomes included emergency department visits, mortality, quality of life, patient satisfaction, medication adherence, length of stay, primary care and outpatient visits, and intervention uptake.

Results

Overall, 126 trials with 97 408 participants were included, 86 (68%) of which were of low risk of bias. Low-complexity interventions were associated with the most efficacy for reducing hospital readmissions at 30 days (odds ratio [OR], 0.78; 95% CI, 0.66 to 0.92) and 180 days (OR, 0.45; 95% CI, 0.30 to 0.66) and emergency department visits (OR, 0.68; 95% CI, 0.48 to 0.96). Medium-complexity interventions were associated with the most efficacy at reducing hospital readmissions at 90 days (OR, 0.64; 95% CI, 0.45 to 0.92), reducing adverse events (OR, 0.42; 95% CI, 0.24 to 0.75), and improving medication adherence (standardized mean difference [SMD], 0.49; 95% CI, 0.30 to 0.67) but were associated with less efficacy than low-complexity interventions for reducing readmissions at 30 and 180 days. High-complexity interventions were most effective for reducing length of hospital stay (SMD, -0.20; 95% CI, -0.38 to -0.03) and increasing patient satisfaction (SMD, 0.52; 95% CI, 0.22 to 0.82) but were least effective for reducing readmissions at all time periods. None of the interventions were associated with improved uptake, quality of life (general, mental, or physical), or primary care and outpatient visits.

Conclusions and Relevance

These findings suggest that low- and medium-complexity transitional care interventions were associated with reducing health care utilization for patients transitioning from hospitals to the community. Comprehensive and consistent outcome measures are needed to capture the patient benefits of transitional care interventions.

Telemonitoring for heart failure: a meta-analysis

AIMS

Telemonitoring modalities in heart failure (HF) have been proposed as being essential for future organization and transition of HF care, however, efficacy has not been proven. A comprehensive meta-analysis of studies on home telemonitoring systems (hTMS) in HF and the effect on clinical outcomes are provided.

METHODS AND RESULTS

A systematic literature search was performed in four bibliographic databases, including randomized trials and observational studies that were published during January 1996-July 2022. A random-effects meta-analysis was carried out comparing hTMS with standard of care. All-cause mortality, first HF hospitalization, and total HF hospitalizations were evaluated as study endpoints. Sixty-five non-invasive hTMS studies and 27 invasive hTMS studies enrolled 36 549 HF patients, with a mean follow-up of 11.5 months. In patients using hTMS compared with standard of care, a significant 16% reduction in all-cause mortality was observed [pooled odds ratio (OR): 0.84, 95% confidence interval (CI): 0.77-0.93, I2: 24%], as well as a significant 19% reduction in first HF hospitalization (OR: 0.81, 95% CI 0.74-0.88, I2: 22%) and a 15% reduction in total HF hospitalizations (pooled incidence rate ratio: 0.85, 95% CI 0.76-0.96, I2: 70%).

CONCLUSION

These results are an advocacy for the use of hTMS in HF patients to reduce all-cause mortality and HF-related hospitalizations. Still, the methods of hTMS remain diverse, so future research should strive to standardize modes of effective hTMS.

Effectiveness of eHealth Self-management Interventions in Patients With Heart Failure: Systematic Review and Meta-analysis

Background

Heart failure (HF) is a common clinical syndrome associated with substantial morbidity, a heavy economic burden, and high risk of readmission. eHealth self-management interventions may be an effective way to improve HF clinical outcomes.

Objective

The aim of this study was to systematically review the evidence for the effectiveness of eHealth self-management in patients with HF.

Methods

This study included only randomized controlled trials (RCTs) that compared the effects of eHealth interventions with usual care in adult patients with HF using searches of the EMBASE, PubMed, CENTRAL (Cochrane Central Register of Controlled Trials), and CINAHL databases from January 1, 2011, to July 12, 2022. The Cochrane Risk of Bias tool (RoB 2) was used to assess the risk of bias for each study. The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) criteria were used to rate the certainty of the evidence for each outcome of interest. Meta-analyses were performed using Review Manager (RevMan v.5.4) and R (v.4.1.0 x64) software.

Results

In total, 24 RCTs with 9634 participants met the inclusion criteria. Compared with the usual-care group, eHealth self-management interventions could significantly reduce all-cause mortality (odds ratio [OR] 0.83, 95% CI 0.71-0.98, P=.03; GRADE: low quality) and cardiovascular mortality (OR 0.74, 95% CI 0.59-0.92, P=.008; GRADE: moderate quality), as well as all-cause readmissions (OR 0.82, 95% CI 0.73-0.93, P=.002; GRADE: low quality) and HF-related readmissions (OR 0.77, 95% CI 0.66-0.90, P<.001; GRADE: moderate quality). The meta-analyses also showed that eHealth interventions could increase patients’ knowledge of HF and improve their quality of life, but there were no statistically significant effects. However, eHealth interventions could significantly increase medication adherence (OR 1.82, 95% CI 1.42-2.34, P<.001; GRADE: low quality) and improve self-care behaviors (standardized mean difference –1.34, 95% CI –2.46 to –0.22, P=.02; GRADE: very low quality). A subgroup analysis of primary outcomes regarding the enrolled population setting found that eHealth interventions were more effective in patients with HF after discharge compared with those in the ambulatory clinic setting.

Conclusions

eHealth self-management interventions could benefit the health of patients with HF in various ways. However, the clinical effects of eHealth interventions in patients with HF are affected by multiple aspects, and more high-quality studies are needed to demonstrate effectiveness.

Text Messaging, Telephone, or In-Person Outpatient Visit to the Surgical Clinic: A Randomized Trial

INTRODUCTION

Routine outpatient follow-up visits for surgical patients are a source of strain on health-care resources and patients. With the COVID-19 pandemic adding a new urgency to finding the safest follow-up arrangement, text message follow-up might prove an acceptable alternative to a phone call or an in-person clinic visit.

METHODS

An open-label, three-arm, parallel randomized trial was conducted. The interventions were traditional in-person appointment, a telephone call, or a text message. The primary outcome was the number of postdischarge complications identified. The secondary outcomes were patient satisfaction with follow-up, future preference, default to follow-up, and preference to receiving medical information by text message.

RESULTS

Two hundred eight patients underwent randomization: 50 in the in-person group, 80 in the telephone group, and 78 in the text message group. There was no difference in the number of reported complications: 5 (10%) patients in the in-person group, 7 (9%) patients in the text group, and 11 (14%) patients in the telephone group (P = 0.613). The preferred method of follow-up was by telephone (106, 61.6%). The least preferred was the in-person follow-up (15, 8.7%, P = 0.002), which also had the highest default rate (44%).

CONCLUSIONS

There was no evidence that text messages and telephone calls are unsafe and ineffective methods of follow-up. Although most patients are happy to receive results by text message, the majority of patients would prefer a telephone follow-up and are less likely to default by this method. Health-care systems should develop telehealth initiatives when planning health-care services in the wake of the COVID-19 pandemic.

A telehealth program benefits discharged patients with heart failure

BACKGROUND

Heart failure (HF) remains a major cause of mortality, hospitalisations, and poor quality of life. The mortality and readmission rate of HF patients after discharge are still high due to poor self-care and adherence, or inability to detect signs of deterioration. Telehealth programs may benefit a broad range of patients and reduce the suffering from HF. We aimed to investigate the impact of a 12-week telehealth program on outcomes among discharged patients with HF.

METHODS

Study population was consisted of 425 patients discharged between Jan 2020 to Aug 2020. All enrolled participants were diagnosed as HF and underwent standard treatments. At discharge, they were randomised into the telehealth or control group. The intervention was based on telephone support biweekly. After 12-week follow-up, patients' outcomes including mortality, readmission, disease condition, adherence, self-care behaviours, and mental health were compared between the groups.

RESULTS

The telehealth program significantly improved the HF symptoms in patients (p < 0.001). Patients in telehealth group showed better adherence compared to control (p = 0.002). Moreover, the intervention enhanced patients' self-care skills, indicated by the increased ratio of individuals knowing how to evaluate the cardiac function (p = 0.009) and purchasing medicines (p = 0.03). In addition, the telehealth program significantly improved the mental health status of patients (p = 0.03).

CONCLUSION

The telehealth program is beneficial for improving HF symptoms, adherence, self-care skills and mental health status of discharged patients and support the future use of this program to manage patients and reduce the burden attributed to the condition.

Continuous Remote Patient Monitoring: Evaluation of the Heart Failure Cascade Soft Launch

OBJECTIVE

We report on our experience of deploying a continuous remote patient monitoring (CRPM) study soft launch with structured cascading and escalation pathways on heart failure (HF) patients post-discharge. The lessons learned from the soft launch are used to modify and fine-tune the workflow process and study protocol.

METHODS

This soft launch was conducted at NorthShore University HealthSystem's Evanston Hospital from December 2020 to March 2021. Patients were provided with non-invasive wearable biosensors that continuously collect ambulatory physiological data, and a study phone that collects patient-reported outcomes. The physiological data are analyzed by machine learning algorithms, potentially identifying physiological perturbation in HF patients. Alerts from this algorithm may be cascaded with other patient status data to inform home health nurses' (HHNs') management via a structured protocol. HHNs review the monitoring platform daily. If the patient's status meets specific criteria, HHNs perform assessments and escalate patient cases to the HF team for further guidance on early intervention.

RESULTS

We enrolled five patients into the soft launch. Four participants adhered to study activities. Two out of five patients were readmitted, one due to HF, one due to infection. Observed miscommunication and protocol gaps were noted for protocol amendment. The study team adopted an organizational development method from change management theory to reconfigure the study protocol.

CONCLUSION

We sought to automate the monitoring aspects of post-discharge care by aligning a new technology that generates streaming data from a wearable device with a complex, multi-provider workflow into a novel protocol using iterative design, implementation, and evaluation methods to monitor post-discharge HF patients. CRPM with structured escalation and telemonitoring protocol shows potential to maintain patients in their home environment and reduce HF-related readmissions. Our results suggest that further education to engage and empower frontline workers using advanced technology is essential to scale up the approach.

Effects of nurse-led transitional care interventions for patients with heart failure on healthcare utilization: A meta-analysis of randomized controlled trials

BACKGROUND

Heart failure (HF) imposes a substantial burden on patients and healthcare systems. Hospital-to-home transitional care, involving time-limited interventions delivered predominantly by nurses, was introduced to lighten this burden. This study aimed to examine the effectiveness and dose-response of nurse-led transitional care interventions (TCIs) on healthcare utilization among patients with HF.

METHODS

Health-related databases were systematically searched for articles published from January 2000 to June 2020. We included randomized controlled trials (RCTs) that compared nurse-led TCIs with usual care for adults hospitalized with HF and reported the following healthcare utilization outcomes: all-cause readmissions, HF-specific readmissions, emergency department visits, or length of hospital stay. Random-effects meta-analysis, meta-regression analysis, and dose-response analysis were performed to estimate the treatment effects and explain the heterogeneity.

RESULTS

Twenty-five RCTs including 8422 patients with HF were included. Nurse-led TCIs for patients with HF resulted in a mean 9% (RR = 0.91; 95% CI = 0.82 to 0.99; p = 0.04; I2 = 46%) and 29% (RR = 0.71; 95% CI = 0.60 to 0.84; p < 0.0001; I2 = 0%) reduction in all-cause and HF-specific readmission risks respectively compared to usual care. The interventions were also effective in shortening the length of hospital stay (MD = -2.37; 95% CI = -3.16 to -1.58; p < 0.0001; I2 = 14%). However, no significant reduction was found for emergency department visits (RR = 0.96; 95% CI = 0.84 to 1.10; p = 0.58; I2 = 0%). The effect of meta-regression coefficients on all-cause and HF-specific readmissions was not statistically significant for any prespecified trial-level characteristic. Dose-response analysis revealed that the HF-specific readmission risk decreased in a dose-dependent manner with the complexity and intensity of nurse-led TCIs.

CONCLUSIONS

Nurse-led TCIs were effective in decreasing all-cause and HF-specific readmission risks, as well as in reducing the length of hospital stay; however, the interventions were not effective in reducing the frequency of emergency department visits.

Effect of nurse-led hospital-to-home transitional care interventions on mortality and psychosocial outcomes in adults with heart failure: a meta-analysis

AIMS

To determine the effectiveness and dose-response of nurse-led hospital-to-home transitional care interventions (TCIs) on patient mortality and psychosocial outcomes of health-related quality of life (HRQoL), self-care behaviours, and emotional well-being in adults hospitalized with heart failure (HF) and to recognize pertinent characteristics that potentially affect the overall effectiveness.

METHODS AND RESULTS

Relevant studies were identified through electronic database searches, including MEDLINE, Embase, CINAHL, and Cochrane Library from January 2000 until January 2021. Two independent authors performed study selection, data abstraction, and risk-of-bias assessment. When appropriate, we used random-effects meta-analysis to derive pooled effect estimates, investigated dose-response relationships, and ran meta-regressions to locate the source of heterogeneity. A total of 27 studies with 7635 participants were included. Our findings revealed that nurse-led hospital-to-home TCIs reduced the risk of all-cause mortality by 21% [risk ratio = 0.79; 95% confidence interval (CI) 0.68-0.92; P = 0.003] and improved HRQoL (mean difference = -3.29; 95% CI -6.51 to -0.07; P = 0.04) compared to usual care, but non-significant effects were found for emotional well-being. The narrative summary of evidence for self-care behaviours showed positive intervention effects. Meta-regression did not find any covariates that were significantly related to mortality or HRQoL. Dose-response analysis showed that mortality risk was reduced with increased intensity and complexity of the nurse-led TCIs.

CONCLUSION

Generally, nurse-led hospital-to-home TCIs may play a beneficial role in decreasing mortality, and improving HRQoL and self-care behaviours for adults with HF. Additional studies are warranted to characterize the optimal nurse-led TCIs for HF management.

Predicting Hospital Readmission in Heart Failure Patients in Iran: A Comparison of Various Machine Learning Methods

Objectives

Heart failure (HF) is a common disease with a high hospital readmission rate. This study considered class imbalance and missing data, which are two common issues in medical data. The current study’s main goal was to compare the performance of six machine learning (ML) methods for predicting hospital readmission in HF patients.

Methods

In this retrospective cohort study, information of 1,856 HF patients was analyzed. These patients were hospitalized in Farshchian Heart Center in Hamadan Province in Western Iran, from October 2015 to July 2019. The support vector machine (SVM), least-square SVM (LS-SVM), bagging, random forest (RF), AdaBoost, and naïve Bayes (NB) methods were used to predict hospital readmission. These methods’ performance was evaluated using sensitivity, specificity, positive predictive value, negative predictive value, and accuracy. Two imputation methods were also used to deal with missing data.

Results

Of the 1,856 HF patients, 29.9% had at least one hospital readmission. Among the ML methods, LS-SVM performed the worst, with accuracy in the range of 0.57–0.60, while RF performed the best, with the highest accuracy (range, 0.90–0.91). Other ML methods showed relatively good performance, with accuracy exceeding 0.84 in the test datasets. Furthermore, the performance of the SVM and LS-SVM methods in terms of accuracy was higher with the multiple imputation method than with the median imputation method.

Conclusions

This study showed that RF performed better, in terms of accuracy, than other methods for predicting hospital readmission in HF patients.

Association Between Access to Specialists and History of Cellulitis Among Patients with Lymphedema: Secondary Analysis Using the National LIMPRINT Database

Background: Cellulitis is frequently encountered in patients with lymphedema despite existing prevention protocols. To resolve this issue, social aspects surrounding patients, such as communication with patients and professionals, are necessary to consider new approaches. This study aimed to clarify the association between the history of cellulitis in patients with lymphedema and access to specialists after adjustment for relevant confounding factors. Methods and Results: This study was a secondary analysis of the Lymphoedema IMpact and PRevalence-INTernational (LIMPRINT) study using a national Japanese database of adult lymphedema compiled between 2014 and 2015 (n = 113). Descriptive data were collected for patient characteristics. Multivariate logistic regression analysis was conducted to explore possible risk factors for patients having experienced cellulitis. The duration of edema ranged from <6 months (16.2%) to 10 years or longer (25.2%), with varying severity. History of cellulitis was observed in 31.9% of patients. The prevalent treatment techniques within the context of complex decongestive therapy included skin care advice (52.2%), compression garments (55.8%), exercise advice (41.6%), multilayer bandages (38.1%), cellulitis advice (49.6%), and massage (61.1%). Overall, 57.1% of patients had access to lymphedema specialists. Longer duration of lymphedema (adjusted odds ratio [AOR] = 4.10, p = 0.005) and access to lymphedema specialists (AOR = 0.28, p = 0.009) were significantly associated with a history of cellulitis. Conclusions: A history of cellulitis in patients with lymphedema is associated with limited access to specialists. To support self-care in this patient population, reasonable consideration systems, including telehealth, should be developed to facilitate communication between specialists and patients and decrease the occurrence of cellulitis in lymphedema.

Effect of Educational Interventions to Reduce Readmissions due to Heart Failure Decompensation in Adults: a Systematic Review and Meta-analysis

OBJECTIVES

To estimate the combined effect of educational interventions (EI) on decreased readmissions and time of hospital stay in adults with heart failure, compared with usual care.

METHODS

Systematic review (SR) and meta-analysis (MA) of randomized controlled trials that followed the recommendations of the PRISMA statement. The protocol was registered on PROSPERO (CRD42019139321). Searches were made from inception until July 2019 in the databases of PubMed/Medline, Embase, Cochrane CENTRAL, Lilacs, Web of Science, and Scopus. The MA was conducted through the random effects model. The effect measure used for the dichotomous outcomes was relative risk (RR) and for continuous outcomes the mean difference (MD) was used, with 95% confidence intervals (CI). Heterogeneity was evaluated through the inconsistency statistic (I2).

RESULTS

Of 2369 studies identified, 45 were included in the SR and 43 in the MA. The MA of studies with follow-up at six months showed a decrease in readmissions of 30% (RR: 0.70; 95% CI: 0.58 to 0.84; I2: 0%) and the 12-month follow-up evidenced a reduction of 33% (RR: 0.67; 95% CI: 0.58 to 0.76; I2: 52%); both analyses in favor of the EI group. Regarding the time of hospital stay, a reduction was found of approximately two days in patients who received the EI (MD: -1.98; 95% CI: -3.27 to -0.69; I2: 7%).

CONCLUSIONS

The findings support the benefits of EI to reduce readmissions and days of hospital stay in adult patients with heart failure.

Strategies to prevent hospital readmission and death in patients with chronic heart failure, chronic obstructive pulmonary disease, and chronic kidney disease: A systematic review and meta-analysis

BACKGROUND

Readmission following hospital discharge is common and is a major financial burden on healthcare systems.

OBJECTIVES

Our objectives were to 1) identify studies describing post-discharge interventions and their efficacy with respect to reducing risk of mortality and rate of hospital readmission; and 2) identify intervention characteristics associated with efficacy.

METHODS

A systematic review of the literature was performed. We searched MEDLINE, PubMed, Cochrane, EMBASE and CINAHL. Our selection criteria included randomized controlled trials comparing post-discharge interventions with usual care on rates of hospital readmission and mortality in high-risk chronic disease patient populations. We used random effects meta-analyses to estimate pooled risk ratios for all-cause and cause-specific mortality as well as all-cause and cause-specific hospitalization.

RESULTS

We included 31 randomized controlled trials encompassing 9654 patients (24 studies in CHF, 4 in COPD, 1 in both CHF and COPD, 1 in CKD and 1 in an undifferentiated population). Meta-analysis showed post-discharge interventions reduced cause-specific (RR = 0.71, 95% CI = 0.63-0.80) and all cause (RR = 0.90, 95% CI = 0.81-0.99) hospitalization, all-cause (RR = 0.73, 95% CI = 0.65-0.83) and cause-specific mortality (RR = 0.68, 95% CI = 0.54-0.84) in CHF studies, and all-cause hospitalization (RR = 0.52, 95% CI = 0.32-0.83) in COPD studies. The inclusion of a cardiac nurse in the multidisciplinary team was associated with greater efficacy in reducing all-cause mortality among patients discharged after heart failure admission (HR = 0.64, 95% CI = 0.54-0.75 vs. HR = 0.87, 95% CI = 0.73-1.03).

CONCLUSIONS

Post-discharge interventions reduced all-cause mortality, cause-specific mortality, and cause-specific hospitalization in CHF patients and all-cause hospitalization in COPD patients. The presence of a cardiac nurse was associated with greater efficacy in included studies. Additional research is needed on the impact of post-discharge intervention strategies in COPD and CKD patients.

The effectiveness of transitional care interventions for adult people with heart failure on patient-centered health outcomes: A systematic review and meta-analysis including dose-response relationship

BACKGROUND

Transitional care interventions that bridge the care gap from hospital to home have proven to be effective in lessening the burden of healthcare systems by reducing hospital readmissions. Yet, the effects of transitional care interventions on patient-centered health outcomes of mortality, quality of life, and emotional distress remains unclear.

OBJECTIVES

To evaluate the effectiveness and dose-response of transitional care interventions on patient-centered health outcomes of mortality, quality of life, and emotional distress among individuals with heart failure and to identify the trial-level characteristics potentially affecting the overall effectiveness.

DESIGN

Systematic review with random-effects meta-analysis, meta-regression, and dose-response analysis of randomized controlled trials comparing transitional care interventions with usual care in adult people hospitalized with heart failure.

DATA SOURCES

Electronic databases including MEDLINE, Embase, Cochrane Library, and CINAHL were systematically searched from January 1, 2000 to June 31, 2020.

REVIEW METHODS

Authors independently reviewed the retrieved articles based on inclusion and exclusion criteria, extracted data, and assessed risk of bias using the Cochrane risk-of-bias tool version 2.0. We pooled data from each study using random-effects meta-analysis and performed meta-regression to explore the impact of pre-specified trial-level factors. Dose-response meta-analysis was conducted to examine the relationship between the intensity (i.e., frequency and duration of interventions) and complexity (i.e., number of intervention components) of transitional care interventions and the treatment effects.

RESULTS

Data were synthesized from 42 trials covering a total of 10,784 people with heart failure. Comparing to usual care, transitional care interventions achieved pooled evidence of a mean 18% risk reduction on mortality (0.82, 95% CI 0.71 to 0.95, P = 0.009) and better improvement in quality of life (-4.37, 95% CI -7.20 to -1.54, P = 0.002). There were insufficient data to determine with certainty the effects on anxiety and depression. Meta-regression showed greater efficacy in trials that delivered the intervention by a multidisciplinary team. Dose-response analyses demonstrated that mortality and quality of life were improved with increased intensity and complexity of the transitional care interventions.

CONCLUSIONS

Transitional care interventions were effective in reducing mortality and improving quality of life for adult people with heart failure. The effects on emotional distress were inconclusive due to insufficient data, highlighting the need for further research.

REGISTRATION NUMBER

CRD42019132732.

The Effectiveness of Transitional Care Interventions on Health Care Utilization in Patients Discharged From the Hospital With Heart Failure: A Systematic Review and Meta-Analysis

OBJECTIVES

Heart failure (HF) heavily burdens the global health system. Transitional care interventions attempt to streamline the hospital-to-home transition to ease the burden. This systematic review and meta-analysis aimed to evaluate the effectiveness of transitional care interventions on health care utilization after hospitalization for HF.

DESIGN

Systematic review and meta-analysis including dose-response relationship.

SETTING AND PARTICIPANTS

Randomized controlled trials (RCTs) of transitional care interventions vs usual care in older patients discharged from the hospital with HF.

METHODS

Electronic databases including MEDLINE, Embase, Cochrane Library, and CINAHL, were systematically searched from January 2009 to October 2019 to locate relevant systematic reviews or meta-analyses. The original RCTs included in the review articles were identified, and an additional search for recently published RCTs was performed from January 2014 to June 2020. This systematic review focused on health care utilization outcomes, including hospital readmissions for HF or any cause, emergency department (ED) visits, and length of hospital stay (LOS).

RESULTS

Data were summarized from 38 RCTs covering 10,871 patients. Pooled evidence suggested a mean 11% [risk ratio (RR) 0.89, 95% confidence interval (CI) 0.82, 0.97] and 22% (RR 0.78, 95% CI 0.68, 0.89) risk reduction on all-cause and HF-specific readmissions, but no significant reduction (RR 0.94, 95% CI 0.83, 1.07) on ED visits. Findings were mixed for LOS. Subgroup analysis by different types of transitional care interventions indicated that multidisciplinary interventions currently have the best evidence for reducing readmissions up to 6 months post the index HF hospitalization. In addition, we observed an inverse linear dose-response relationship between intervention intensity (ie, frequency and duration of interventions) and complexity (ie, number of intervention components) and the risk of HF readmissions.

CONCLUSIONS AND IMPLICATIONS

Transitional care interventions for hospitalized patients with HF reduced all-cause and HF-specific readmissions, but did not decrease ED visits. Multidisciplinary interventions are highly recommended if adequate resources are available.

Implementation of Artificial Intelligence-Based Clinical Decision Support to Reduce Hospital Readmissions at a Regional Hospital

BACKGROUND

Hospital readmissions are a key quality metric, which has been tied to reimbursement. One strategy to reduce readmissions is to direct resources to patients at the highest risk of readmission. This strategy necessitates a robust predictive model coupled with effective, patient-centered interventions.

OBJECTIVE

The aim of this study was to reduce unplanned hospital readmissions through the use of artificial intelligence-based clinical decision support.

METHODS

A commercially vended artificial intelligence tool was implemented at a regional hospital in La Crosse, Wisconsin between November 2018 and April 2019. The tool assessed all patients admitted to general care units for risk of readmission and generated recommendations for interventions intended to decrease readmission risk. Similar hospitals were used as controls. Change in readmission rate was assessed by comparing the 6-month intervention period to the same months of the previous calendar year in exposure and control hospitals.

RESULTS

Among 2,460 hospitalizations assessed using the tool, 611 were designated by the tool as high risk. Sensitivity and specificity for risk assignment were 65% and 89%, respectively. Over 6 months following implementation, readmission rates decreased from 11.4% during the comparison period to 8.1% (p < 0.001). After accounting for the 0.5% decrease in readmission rates (from 9.3 to 8.8%) at control hospitals, the relative reduction in readmission rate was 25% (p < 0.001). Among patients designated as high risk, the number needed to treat to avoid one readmission was 11.

CONCLUSION

We observed a decrease in hospital readmission after implementing artificial intelligence-based clinical decision support. Our experience suggests that use of artificial intelligence to identify patients at the highest risk for readmission can reduce quality gaps when coupled with patient-centered interventions.

mHealth education interventions in heart failure

BACKGROUND

Heart failure (HF) is a chronic disease with significant impact on quality of life and presents many challenges to those diagnosed with the condition, due to a seemingly complex daily regimen of self-care which includes medications, monitoring of weight and symptoms, identification of signs of deterioration and follow-up and interaction with multiple healthcare services. Education is vital for understanding the importance of this regimen, and adhering to it. Traditionally, education has been provided to people with heart failure in a face-to-face manner, either in a community or a hospital setting, using paper-based materials or video/DVD presentations. In an age of rapidly-evolving technology and uptake of smartphones and tablet devices, mHealth-based technology (defined by the World Health Organization as mobile and wireless technologies to achieve health objectives) is an innovative way to provide health education which has the benefit of being able to reach people who are unable or unwilling to access traditional heart failure education programmes and services.

OBJECTIVES

To systematically review and quantify the potential benefits and harms of mHealth-delivered education for people with heart failure.

SEARCH METHODS

We performed an extensive search of bibliographic databases and registries (CENTRAL, MEDLINE, Embase, CINAHL, PsycINFO, IEEE Xplore, ClinicalTrials.gov and WHO International Clinical Trials Registry Platform (ICTRP) Search Portal), using terms to identify HF, education and mHealth. We searched all databases from their inception to October 2019 and imposed no restriction on language of publication.

SELECTION CRITERIA

We included studies if they were conducted as a randomised controlled trial (RCT), involving adults (≥ 18 years) with a diagnosis of HF. We included trials comparing mHealth-delivered education such as internet and web-based education programmes for use on smartphones and tablets (including apps) and other mobile devices, SMS messages and social media-delivered education programmes, versus usual HF care.

DATA COLLECTION AND ANALYSIS

Two review authors independently selected studies, assessed risks of bias, and extracted data from all included studies. We calculated the mean difference (MD) or standardised mean difference (SMD) for continuous data and the odds ratio (OR) for dichotomous data with a 95% confidence interval (CI). We assessed heterogeneity using the I² statistic and assessed the quality of evidence using GRADE criteria.

MAIN RESULTS

We include five RCTs (971 participants) of mHealth-delivered education interventions for people with HF in this review. The number of trial participants ranged from 28 to 512 participants. Mean age of participants ranged from 60 years to 75 years, and 63% of participants across the studies were men. Studies originated from Australia, China, Iran, Sweden, and The Netherlands. Most studies included participants with symptomatic HF, NYHA Class II - III. Three studies addressed HF knowledge, revealing that the use of mHealth-delivered education programmes showed no evidence of a difference in HF knowledge compared to usual care (MD 0.10, 95% CI -0.2 to 0.40, P = 0.51, I² = 0%; 3 studies, 411 participants; low-quality evidence). One study assessing self-efficacy reported that both study groups had high levels of self-efficacy at baseline and uncertainty in the evidence for the intervention (MD 0.60, 95% CI -0.57 to 1.77; P = 0.31; 1 study, 29 participants; very low-quality evidence).Three studies evaluated HF self-care using different scales. We did not pool the studies due to the heterogenous nature of the outcome measures, and the evidence is uncertain. None of the studies reported adverse events. Four studies examined health-related quality of life (HRQoL). There was uncertainty in the evidence for the use of mHealth-delivered education on HRQoL (MD -0.10, 95% CI -2.35 to 2.15; P = 0.93, I² = 61%; 4 studies, 942 participants; very low-quality evidence). Three studies reported on HF-related hospitalisation. The use of mHealth-delivered education may result in little to no difference in HF-related hospitalisation (OR 0.74, 95% CI 0.52 to 1.06; P = 0.10, I² = 0%; 3 studies, 894 participants; low-quality evidence). We downgraded the quality of the studies due to limitations in study design and execution, heterogeneity, wide confidence intervals and fewer than 500 participants in the analysis.

AUTHORS' CONCLUSIONS

We found that the use of mHealth-delivered educational interventions for people with HF shows no evidence of a difference in HF knowledge; uncertainty in the evidence for self-efficacy, self-care and health-related quality of life; and may result in little to no difference in HF-related hospitalisations. The identification of studies currently underway and those awaiting classification indicate that this is an area of research from which further evidence will emerge in the short and longer term.

Rapid Implementation of an Inpatient Telehealth Program during the COVID-19 Pandemic

BACKGROUND

 Relaxation of laws and regulations around privacy and billing during the COVID-19 pandemic provide expanded opportunities to use telehealth to provide patient care at a distance. Many health systems have transitioned to providing outpatient care via telehealth; however, there is an opportunity to utilize telehealth for inpatients to promote physical distancing.

OBJECTIVE

 This article evaluates the use of a rapidly implemented, secure inpatient telehealth program.

METHODS

 We assembled a multidisciplinary team to rapidly design, implement, and iteratively improve an inpatient telehealth quality improvement initiative using an existing videoconferencing system at our academic medical center. We assigned each hospital bed space a unique meeting link and updated the meeting password for each new patient. Patients and families were encouraged to use their own mobile devices to join meetings when possible.

RESULTS

 Within 7 weeks of go-live, we hosted 1,820 inpatient telehealth sessions (13.3 sessions per 100 bedded days). We logged 104,647 minutes of inpatient telehealth time with a median session duration of 22 minutes (range 1-1,961). There were 5,288 participant devices used with a mean of 3 devices per telehealth session (range 2-22). Clinicians found they were able to build rapport and perform a reasonable physical exam.

CONCLUSION

 We successfully implemented and scaled a secure inpatient telehealth program using an existing videoconferencing system in less than 1 week. Our implementation provided an intuitive naming convention for providers and capitalized on the broad availability of smartphones and tablets. Initial comments from clinicians suggest the system was useful; however, further work is needed to streamline initial setup for patients and families as well as care coordination to support clinician communication and workflows. Numerous use cases identified suggest a role for inpatient telehealth will remain after the COVID-19 crisis underscoring the importance of lasting regulatory reform.