Perceived Versus Actual Risks of 30-Day Readmission in Patients With Cardiovascular Disease

Reducing rehospitalization in cardiac patients: a randomized, controlled trial of a cardiac care management program ("Cardiolotse") in Germany

BACKGROUND

We conducted a prospective, randomized, controlled, two-group parallel trial investigating the effectiveness of a care management program employing cardiac care navigators providing post-discharge support to patients compared to standard care.

METHODS

The intervention commenced in 2019/2020 for 2862 patients hospitalized with heart failure, coronary heart disease, or cardiac arrhythmias in departments of cardiology across eight participating sites of a hospital group in Berlin, Germany. We analyzed the results using an intention-to-treat approach. The primary outcome was the all-cause rehospitalization rate after 12 months. Secondary outcomes included rehospitalizations due to one of the qualifying cardiac diagnoses, duration of rehospitalization, mortality, health-related quality of life, and several process indicators. Trial data were collected from a combination of face-to-face and phone interviews conducted by hospital staff throughout the 12-month follow-up period using standardized questionnaires. Administrative claims data were provided by a large statutory health insurer. Outcomes for the intervention and control groups were compared using logistic regression, generalized linear models (GLMs) with a negative binomial distribution, ordinary least squares, and Cox proportional hazards regression.

RESULTS

Compared to the control group (N = 1294), the intervention group (N = 1256) had a lower rate of all-cause rehospitalizations (62.6% vs. 66.4%, p = 0.05) and shorter lengths of stay (14.49 vs. 16.89 days, p = 0.02) during the 12-month follow-up period. These differences were also present for rehospitalizations due to the cardiac diseases qualifying for study recruitment, with rehospitalization rates for the intervention and control groups being 58.0% vs. 61.4% (p = 0.08) and particularly pronounced for lengths of rehospitalization stay of 12.97 vs. 15.40 days (p = 0.01), respectively. Subgroup analyses indicated positive effects of the intervention for patients 70 years and older (p = 0.05), females (p = 0.06), and those with little or no German language proficiency (p = 0.03). Furthermore, we found positive effects on patients' adherence to health-related behavioral recommendations (81.91% vs. 73.95%, p = 0.000).

CONCLUSIONS

This study adds to the body of evidence indicating that care management interventions supporting patients as they transition from the inpatient to the outpatient sector can lower rehospitalizations, decrease length of rehospitalization stays, and improve adherence to post-discharge recommendations.

TRIAL REGISTRATION

German Clinical Trial Register, DRKS00020424 . Registered 2020-06-18. (retrospectively registered).

Predictors of 30-Day Re-admission in Cardiac Patients at Heart Hospital, Qatar

Background

Cardiovascular disease patients are more likely to be readmitted within 30 days of being discharged alive. This causes an enormous burden on health-care systems in terms of poor care of patients and misutilization of resources.

Aims and Objective

This study aims to find out the risk factors associated with 30-day readmission in cardiac patients at Heart Hospital, Qatar.

Methods

A total of 10,550 cardiac patients who were discharged alive within 30 days at the heart hospital in Doha, Qatar, from January 2015 and December 2019 were analyzed. The bootstrap method, an internal validation statistical technique, was applied to present representative estimates for the population.

Results

Out of the 10,550 cardiac patients, there were 8418 (79.8%) index admissions and 2132 (20.2%) re-admitted at least once within 30 days after the index admission. The re-admissions group was older than the index admission group (65.6 ± 13.2 vs. 56.0 ± 13.5, P = 0.001). Multinomial regression analysis showed that females were 30% more likely to be re-admitted than males (adjusted odds ratio [aOR] 1.30, 95% confidence interval [CI]: 1.11-1.50, P = 0.001). Diabetes (aOR 1.36, 95% CI: 1.20-1.53, P = 0.001), chronic renal failure (aOR 1.93, 95% CI: 1.66-2.24, P = 0.001), previous MI (aOR 3.22, 95% CI: 2.85-3.64, P = 0.001), atrial fibrillation (aOR 2.17, 95% C.I. : 1.10-2.67, P = 0.01), cardiomyopathy (aOR 1.72, 95% CI 1.47-2.02, P = 0.001), and chronic heart failure (aOR 1.56, 95% C.I.: 1.33-1.82, P = 0.001) were also independent predictors for re-admission in the regression model. C-statistics showed these variables could predict 82% accurately hospital readmissions within 30 days after being discharged alive.

Conclusion

The model was more than 80% accurate in predicting 30-day readmission after being discharged alive. The presence of five or more risk factors was found to be crucial for readmissions within 30 days. The study may help design interventions that may result in better outcomes with fewer resources in the population.

Effectiveness of Telemedicine Visits in Reducing 30-Day Readmissions Among Patients With Heart Failure During the COVID-19 Pandemic

Background The COVID-19 pandemic resulted in a rapid implementation of telemedicine into clinical practice. This study examined whether early outpatient follow-up via telemedicine is as effective as in-person visits for reducing 30-day readmissions in patients with heart failure. Methods and Results Using electronic health records from a large health system, we included patients with heart failure living in North Carolina (N=6918) who were hospitalized between March 16, 2020 and March 14, 2021. All-cause readmission within 30 days after discharge was examined using weighted logistic regression models. Overall, 7.6% (N=526) of patients received early telemedicine follow-up, 38.8% (N=2681) received early in-person follow-up, and 53.6% (N=3711) did not receive follow-up within 14 days of discharge. Compared with patients without early follow-up, those who received early follow-up were younger, were more likely to be Medicare beneficiaries, had more comorbidities, and were less likely to live in an disadvantaged neighborhood. Relative to in-person visits, those with telemedicine follow-up were of similar age, sex, and race but with generally fewer comorbidities. Overall, the 30-day readmission rate (19.0%) varied among patients who received telemedicine visits (15.0%), in-person visits (14.0%), or no follow-up (23.1%). After covariate adjustment, patients who received either telemedicine (odds ratio [OR], 0.55; 95% CI, 0.44-0.72) or in-person (OR, 0.52; 95% CI, 0.45-0.60) visits were similarly less likely to be readmitted within 30 days compared with patients with no follow-up. Conclusions During the COVID-19 pandemic, the use of telemedicine visits for early follow-up increased rapidly. Patients with heart failure who received outpatient follow-up either via telemedicine or in-person had better outcomes than those who received no follow-up.

What CVD risk factors predict self-perceived risk of having a myocardial infarction? A cross-sectional study

Background

This study aims to identify predictors of self-perceived risk of myocardial infarction (MI).

Methods

Among 564 men and women (50–65 years; randomly selected from the Swedish population), we assessed risk perception as relative self-perceived risk compared to others (lower, same, higher) and percentage ten-year absolute risk. Predictors (added blockwise) were identified using multinomial or linear regression, providing odds ratios (ORs) or β coefficients with their 95% confidence intervals (CI).

Results

The mean of self-perceived 10-year MI risk was 12%. Lower BMI (AOR 0.57, 95% CI: 0.44–0.75), low stress (AOR 2.51, 95% CI: 1.39–4.52), high level of physical activity (AOR 1.66, 95% CI:1.01–2.74), hypertension (AOR 0.42, 95% CI: 0.23–0.76), family history (AOR 0.38, 95% CI: 0.21–0.69), and poor general health (AOR 0.41, 95% CI: 0.19–0.89) predicted if respondents perceived their MI risk as lower. Poor general health (AOR 1.94, 95% CI: 1.01–3.73), family history (AOR 2.72, 95% CI: 1.57–4.72), and high cholesterol (AOR 2.45, 95% CI: 1.18–5.09) predicted if respondents perceived their MI risk as higher. Low level of self-perceived CVD knowledge and low numeracy predicted if respondents perceived their MI risk as the same as others. High cholesterol (B 6.85, 95% CI: 2.47–11.32) and poor general health (B 8.75, 95% CI: 4.58–13.00) predicted a higher percentage of perceived ten-year risk.

Conclusion

General health was a common predictor of self-perceived MI risk. Lifestyle factors (BMI, physical activity) and stress dominated the predictors for perceiving MI risk as lower than others, while high cholesterol predicted perception of high risk.