Hospital Variation in 30-Day Readmissions Following Transcatheter Aortic Valve Replacement

Call for Action to Target Interhospital Variation in Cardiovascular Mortality, Readmissions, and Length-of-Stay: Results of a National Population Analysis

BACKGROUND

Excessive interhospital variation threatens healthcare quality. Data on variation in patient outcomes across the whole cardiovascular spectrum are lacking. We aimed to examine interhospital variability for 28 cardiovascular All Patient Refined-Diagnosis-related Groups (APR-DRGs).

METHODS

We studied 103,299 cardiovascular admissions in 99 (98%) Belgian acute-care hospitals between 2012 and 2018. Using generalized linear mixed models, we estimated hospital-specific and APR-DRG-specific risk-standardized rates for in-hospital mortality, 30-day readmissions, and length-of-stay above the APR-DRG-specific 90th percentile. Interhospital variation was assessed based on estimated variance components and time trends between the 2012-2014 and 2016-2018 periods were examined.

RESULTS

There was strong evidence of interhospital variation, with statistically significant variation across the 3 outcomes for 5 APR-DRGs after accounting for patient and hospital factors: percutaneous cardiovascular procedures with acute myocardial infarction, heart failure, hypertension, angina pectoris, and arrhythmia. Medical diagnoses, with in particular hypertension, heart failure, angina pectoris, and cardiac arrest, showed strongest variability, with hypertension displaying the largest median odds ratio for mortality (2.51). Overall, hospitals performing at the upper-quartile level should achieve improvements to the median level, and an annual 633 deaths, 322 readmissions, and 1578 extended hospital stays could potentially be avoided.

CONCLUSIONS

Analysis of interhospital variation highlights important outcome differences that are not explained by known patient or hospital characteristics. Targeting variation is therefore a promising strategy to improve cardiovascular care. Considering their treatment in multidisciplinary teams, policy makers, and managers should prioritize heart failure, hypertension, cardiac arrest, and angina pectoris improvements by targeting guideline implementation outside the cardiology department.

Prognostic impact of remote dielectric sensing value following TAVR

Remote dielectric sensing (ReDS) system non-invasively quantifies pulmonary congestion. Re-admission following trans-catheter aortic valve replacement (TAVR) remains an unsolved matter. Residual pulmonary congestion is a strong risk factor of worse clinical outcomes in patients with heart failure. ReDS system may have a prognostic impact in patients undergoing TAVR. Patients who received TAVR and ReDS measurements during index hospitalization between 2021 and 2022 were included. The prognostic impact of ReDS value on the composite endpoint of death or re-admission following index discharge was investigated. Totally, 42 patients (median 84 years, 14 men) were included. Median ReDS value at index discharge was 27% (24%, 30%) and 10 patients had ReDS values > 30%. During a median of 316 (282, 354) days following index discharge, a higher ReDS value at baseline was independently associated with the incidence of composite endpoint with an adjusted hazard ratio of 1.32 (95% confidence interval between 1.10 and 1.58) with a calculated cutoff of 30%, which significantly stratified the cumulative incidence of the composite endpoint (78% in the high ReDS group [N = 10] and 36% in the normal ReDS group [N = 32], p = 0.002). ReDS technology may be a promising tool to predict future clinical outcomes following TAVR by quantifying residual pulmonary congestion. The clinical implication of ReDS-guided aggressive intervention following TAVR remains the next concern.

A Readmission Risk Score for Transcatheter Aortic Valve Replacement: An Analysis of 200,000 Patients

OBJECTIVE

The objective of this study was to leverage a national database of TAVR procedures to create a risk model for 30-day readmissions.

METHODS

The National Readmissions Database was reviewed for all TAVR procedures from 2011 to 2018. Previous ICD coding paradigms created comorbidity and complication variables from the index admission. Univariate analysis included any variables with a P-value of ≤0.2. A bootstrapped mixed-effects logistic regression was run using the hospital ID as a random effect variable. By bootstrapping, a more robust estimate of the variables' effect can be generated, reducing the risk of model overfitting. The odds ratio of variables with a P-value <0.1 was turned into a risk score following the Johnson scoring method. A mixed-effect logistic regression was run using the total risk score, and a calibration plot of the observed to expected readmission was generated.

RESULTS

A total of 237,507 TAVRs were identified, with an in-hospital mortality of 2.2 %. A total of 17.4 % % of TAVR patients were readmitted within 30 days. The median age was 82 with 46 % of the population being women. The risk score values ranged from -3 to 37 corresponding to a predicted readmission risk between 4.6 % and 80.4 %, respectively. Discharge to a short-term facility and being a resident of the hospital state were the most significant predictors of readmission. The calibration plot shows good agreement between the observed and expected readmission rates with an underestimation at higher probabilities.

CONCLUSION

The readmission risk model agrees with the observed readmissions throughout the study period. The most significant risk factors were being a resident of the hospital state and discharge to a short-term facility. This suggests that using this risk score in conjunction with enhanced post-operative care in these patients could reduce readmissions and associated hospital costs, improving outcomes.

Modeling the Association of Volume vs Composite Outcome Thresholds With Outcomes and Access to Transcatheter Aortic Valve Implantation in the US

Importance

Professional societies and the Centers for Medicare & Medicaid Services suggest volume thresholds to ensure quality in transcatheter aortic valve implantation (TAVI).

Objective

To model the association of volume thresholds vs spoke-and-hub implementation of outcome thresholds with TAVI outcomes and geographic access.

Design, Setting, and Participants

This cohort study included patients who enrolled in the US Society of Thoracic Surgeons/American College of Cardiology Transcatheter Valve Therapy registry. Site volume and outcomes were determined from a baseline cohort of adults undergoing TAVI between July 1, 2017, and June 30, 2020.

Exposures

Within each hospital referral region, TAVI sites were categorized by volume (<50 or ≥50 TAVIs per year) and separately by risk-adjusted outcome on the Society of Thoracic Surgeons/American College of Cardiology Transcatheter Valve Therapy 30-day TAVI composite during the baseline period (July 2017 to June 2020). Outcomes of patients undergoing TAVIs from July 1, 2020, to March 31, 2022, were then modeled as though the patients had been treated at (1) the nearest higher volume (≥50 TAVIs per year) or (2) the best outcome site within the hospital referral region.

Main Outcomes and Measures

The primary outcome was the absolute difference in events between the adjusted observed and modeled 30-day composite of death, stroke, major bleeding, stage III acute kidney injury, and paravalvular leak. Data are presented as the number of events reduced under the above scenarios with 95% bayesian credible intervals (CrIs) and median (IQR) driving distance.

Results

The overall cohort included 166 248 patients with a mean (SD) age of 79.5 (8.6) years; 74 699 (47.3%) were female and 6657 (4.2%) were Black; 158 025 (95%) were treated in higher-volume sites (≥50 TAVIs) and 75 088 (45%) were treated in best-outcome sites. Modeling a volume threshold, there was no significant reduction in estimated adverse events (-34; 95% CrI, -75 to 8), while the median (IQR) driving time from the existing site to the alternate site was 22 (15-66) minutes. Transitioning care to the best outcome site in a hospital referral region resulted in an estimated 1261 fewer adverse outcomes (95% CrI, 1013-1500), while the median (IQR) driving time from the original site to the best site was 23 (15-41) minutes. Directionally similar findings were observed for Black individuals, Hispanic individuals, and individuals from rural areas.

Conclusions and Relevance

In this study, compared with the current system of care, a modeled outcome-based spoke-and-hub paradigm of TAVI care improved national outcomes to a greater extent than a simulated volume threshold, at the cost of increased driving time. To improve quality while maintaining geographic access, efforts should focus on reducing site variation in outcomes.

The safety of early discharge following transfemoral transcatheter aortic valve replacement under general anesthesia

Background

There is growing evidence of the safety of same-day discharge for low-risk conscious sedated TAVR patients. However, the evidence supporting the safety of early discharge following GA-TAVR with routine transesophageal echocardiography (TEE) is limited.

Aims

To assess the safety of early discharge following transcatheter aortic valve replacement (TAVR) using General Anesthesia (GA-TAVR) and identify predictors for patient selection.

Materials and methods

We used data from 2,447 TEE-guided GA-TAVR patients performed at Cedars-Sinai between 2016 and 2021. Patients were categorized into three groups based on the discharge time from admission: 24 h, 24–48 h, and >48 h. Predictors for 30-day outcomes (cumulative adverse events and death) were validated on a matched cohort of 24 h vs. >24 h using the bootstrap model.

Results

The >48 h group had significantly worse baseline cardiovascular profile, higher surgical risk, low functional status, and higher procedural complications than the 24 h and the 24–48 h groups. The rate of 30-day outcomes was significantly lower in the 24 h than the >48 h but did not differ from the 24–48 h (11.3 vs. 15.5 vs. 11.7%, p = 0.003 and p = 0.71, respectively). Independent poor prognostic factors of 30-day outcomes had a high STS risk of ≥8 (OR 1.90, 95% CI 1.30–2.77, E-value = 3.2, P < 0.001), low left ventricle ejection fraction of <30% (OR 6.0, 95% CI 3.96–9.10, E-value = 11.5, P < 0.001), and life-threatening procedural complications (OR 2.65, 95% CI 1.20–5.89, E-value = 4.7, P = 0.04). Our formulated predictors showed a good discrimination ability for patient selection (AUC: 0.78, 95% CI 0.75–0.81).

Conclusion

Discharge within 24 h following GA-TAVR using TEE is safe for selected patients using our proposed validated predictors.

Unwarranted Between-hospital Variation in Mortality, Readmission, and Length of Stay of Urological Admissions: An Important Trigger for Prioritising Quality Targets

BACKGROUND

Unwarranted between-hospital variation is a persistent health care quality issue. It is unknown whether urology patients are prone to this variation.

OBJECTIVE

To examine between-hospital variation in mortality, readmission, and length of stay for all 22 urological All Patient Refined Diagnosis Related Groups (APR-DRGs).

DESIGN, SETTING, AND PARTICIPANTS

This study included administrative data from 320640 urological admissions in 99 (98%) Belgian acute-care hospitals between 2016 and 2018.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

We used hierarchical mixed-effect logistic regression models to estimate hospital-specific and APR-DRG-specific risk-standardised rates for in-hospital mortality, 30-d readmission, and length of stay above the APR-DRG-specific 90th percentile. Between-hospital variation was assessed based on the estimated variance components. Associations of outcomes with patient and hospital characteristics and time trends were examined.

RESULTS AND LIMITATIONS

Our analysis revealed important between-hospital variation in mortality, readmission, and length of stay for urological pathologies, particularly for medical diagnoses. Significant variation was shown in all three outcomes for kidney and urinary tract infections; other kidney and urinary tract diagnoses, signs, and symptoms; urinary stones and acquired upper urinary tract obstruction; and kidney and urinary tract procedures for nonmalignancy. Lowering of mortality rates in upper-quartile hospitals to the median could potentially save 41.5% of deaths in these hospitals, with the largest absolute gain for kidney and urinary tract infections and kidney and urinary tract malignancy. Limitations included a likely underestimation of readmission rates.

CONCLUSIONS

Urological patient outcomes are characterised by unwarranted between-hospital variation. We recommend improvement initiatives to prioritise kidney and urinary tract infections because of significant variation across the three outcomes and the largest potential gain in lives saved.

PATIENT SUMMARY

We found notable between-hospital variation in mortality, readmission, and length of stay for urological hospital admissions in Belgium. As much as 41.5% of deaths could potentially be avoided if underperforming hospitals improved. Targeting kidney and urinary tract infections could help reduce variation.

The 30-Day Readmission Rate of Same-Day Discharge Following Transcatheter Aortic Valve Implantation (from National Readmission Database 2015 to 2019)

The length of hospital stay after transcatheter aortic valve implantation (TAVI) has decreased over the years, and next-day discharge is being increasingly adopted in clinical practice. Whether further expediting discharge after TAVI by allowing same-day discharge (SDD) in selected patients is safe or derives additional benefits remains unanswered. Using the United States Nationwide Readmission Database 2015 to 2019, we identified 196,618 patients who received TAVI (mean age 79.5 8.4 years, 45.0% female). Of these, 245 patients (0.12%) were discharged on the same day they received TAVI (SDD group), and the remaining 196,373 were discharged on a different day (different-day discharge [DDD] group). A propensity score-matched analysis was done. The rate of unplanned readmission within 30 days of discharge was not significantly different between the SDD and DDD groups (11.0% vs 10.6%, hazard ratio 1.03, 95% confidence interval 0.56 to 1.90, p = 0.921). Hospitalization costs were significantly lower in the SDD group than the DDD group ($37,811 ± 18,029 vs $49,130 ± 27,007, p <0.001). In conclusion, the 30-day readmission rate was similar for patients discharged on the same day after TAVI and for patients discharged at a later time point.

Clinical implications of troponin-T elevations following TAVR: Troponin Increase Following TAVR

BACKGROUND

Baseline and post-procedural elevations in serum troponin-T levels are associated with increased morbidity and mortality following transcatheter aortic valve replacement (TAVR). However, the prognostic impact of change in serum troponin-T level following TAVR remains unknown.

METHODS

Among the patients with severe aortic stenosis who underwent TAVR, those with baseline serum troponin-T level ≥51.5 ng/L were excluded. The impact of increases in serum troponin-T level to an abnormally high range (≥51.5 ng/L) following TAVR on 2-year cardiovascular death or heart failure readmissions was investigated.

RESULTS

Among 189 included patients (median 86 years old, 28% men), serum troponin-T level increased in 79 patients following TAVR. An increase in serum troponin-T was associated with a higher rate of 30-day adverse events, predominantly due to pacemaker implantation for complete atrio-ventricular block, and a higher 2-year cumulative incidence of the primary endpoint (hazard ratio 5.24, 95% confidence interval 1.64-16.8, p = 0.005) adjusted for the potential confounders.

CONCLUSION

Post-procedural increase in serum troponin-T level was associated with adverse clinical outcomes following TAVR.

Hospital Variation in 30-Day Readmissions Following Transcatheter Aortic Valve Replacement

Background Data on hospital variation in 30-day readmission rates after transcatheter aortic valve replacement (TAVR) are limited. Further, whether such variation is explained by differences in hospital characteristics and hospital practice patterns remains unknown. Methods and Results We used the 2017 Nationwide Readmissions Database to identify hospitals that performed at least 5 TAVRs. Hierarchical logistic regression models were used to examine between-hospital variation in 30-day all-cause risk-standardized readmission rate (RSRR) after TAVR and to explore reasons underlying hospital variation in 30-day RSRR. The study included 27 091 index TAVRs performed across 325 hospitals. The median (interquartile range) hospital-level 30-day RSRR was 11.9% (11.1%-12.8%) ranging from 8.8% to 16.5%. After adjusting for differences in patient characteristics, there was significant between-hospital variation in 30-day RSRR (hospital odds ratio, 1.59; 95% CI, 1.39-1.77). Differences in length of stay and discharge disposition accounted for 15% of the between-hospital variance in RSRRs. There was no significant association between hospital characteristics and 30-day readmission rates after TAVR. There was statistically significant but weak correlation between 30-day RSRR after TAVR and that after surgical aortic valve replacement, percutaneous coronary intervention, acute myocardial infarction, heart failure, and pneumonia (r=0.132-0.298; P<0.001 for all). Causes of 30-day readmission varied across hospitals, with noncardiac readmissions being more common at the bottom 5% hospitals (ie, those with the highest RSRRs). Conclusions There is significant variation in 30-day RSRR after TAVR across hospitals that is not entirely explained by differences in patient or hospital characteristics as well as hospital-wide practice patterns. Noncardiac readmissions are more common in hospitals with the highest RSRRs.