Ninety-Day Readmissions of Bundled Valve Patients: Implications for Healthcare Policy.

Medicare's Bundle Payment for Care Improvement (BPCI) Model 2 groups reimbursement for valve surgery into 90-day episodes of care, which include operative costs, inpatient stay, physician fees, postacute care, and readmissions up to 90 days postprocedure. We analyzed our BPCI patients' 90-day outcomes to understand the late financial risks and implications of the bundle payment system for valve patients. All BPCI valve patients from October 2013 (start of risk-sharing phase) to December 2015 were included. Readmissions were categorized as early (≤30 days) or late (31-90 days). Data were collected from institutional databases as well as Medicare claims. Analysis included 376 BPCI valve patients: 202 open and 174 transcatheter aortic valves (TAVR). TAVR patients were older (83.6 vs 73.8 years; P = 0.001) and had higher Society of Thoracic Surgery predicted risk (7.1% vs 2.8%; P = 0.001). Overall, 18.6% of patients (70/376) had one-or-more 90-day readmission, and total claim was on average 51% greater for these patients. Overall readmissions were more common among TAVR patients (22.4% (39/174) vs 15.3% (31/202), P = 0.052) as was late readmission. TAVR patients had significantly higher late readmission claims, and early readmission was predictive of late readmission for TAVR patients only (P = 0.04). Bundled claims for a 90-day episode of care are significantly increased in patients with readmissions. TAVR patients represent a high-risk group for late readmission, possibly a reflection of their chronic disease processes. Being able to identify patients at highest risk for 90-day readmission and the associated claims will be valuable as we enter into risk-bearing episodes of care agreements with Medicare.

Vulnerable Hospitals and Cancer Surgery Readmissions: Insights into the Unintended Consequences of the Patient Protection and Affordable Care Act.

BACKGROUND: Penalties from the Hospital Readmission Reduction Program can push financially strained, vulnerable patient-serving hospitals into additional hardship. In this study, we quantified the association between vulnerable hospitals and readmissions and examined the respective contributions of patient- and hospital-related factors. METHODS: A total of 110,857 patients who underwent major cancer operations were identified from the 2004-2011 State Inpatient Database of California. Vulnerable hospitals were defined as either self-identified safety net hospitals (SNHs) or hospitals with a high percentage of Medicaid patients (high Medicaid hospitals [HMHs]). We used multivariable logistic regression to determine the association between vulnerable hospitals and readmission. Patient and hospital contributions to the elevation in odds of readmission were assessed by comparing estimates from models with different subsets of predictors. RESULTS: Of the 355 hospitals, 13 were SNHs and 31 were HMHs. After adjusting for Hospital Readmission Reduction Program variables, SNHs had higher 30-day (odds ratio [OR] = 1.32; 95% CI, 1.18-1.47), 90-day (OR = 1.28; 95% CI, 1.18-1.38), and repeated readmissions (OR = 1.33; 95% CI, 1.18-1.49); HMHs also had higher 30-day (OR = 1.18; 95% CI, 1.05-1.32), 90-day (OR = 1.28; 95% CI, 1.16-1.42), and repeated readmissions (OR = 1.24; 95% CI, 1.01-1.54). Compared with patient characteristics, hospital factors accounted for a larger proportion of the increase in odds of readmission among SNHs (60% to 93% vs 24% to 39%), but a smaller proportion among HMHs (9% to 15% vs 60% to 115%). CONCLUSIONS: Vulnerable status of hospitals is associated with higher readmission rates after major cancer surgery. These findings reinforce the call to account for socioeconomic variables in risk adjustments for hospitals who serve a disproportionate share of disadvantaged patients.

Quantifying and Predicting Surgeon Work Input in Primary vs Revision Total Hip Arthroplasty.

BACKGROUND: Primary total hip arthroplasties (THAs) performed annually are projected to increase 174% by 2030, causing a parallel increase for revision THA. Increased surgical effort and readmission rates associated with revision THA may discourage surgeons from performing them. Although revision THA Medicare reimbursement is greater, it may be disproportionate to time and effort. We examined work input between primary and revision THA, assessing predictive factors. We also compared surgeon work input to current reimbursement. METHODS: A total of 156 patients were identified, 80 primary and 76 revision THA. Demographic, clinical, and radiographic data were collected. Radiographic data were collected from the most recent preoperative radiographs taken before primary or revision THA. Multiple linear and logistic regression models were used to identify patient factors contributing to select outcome variables by a stepwise method, with a probability value for entry (P = .05) and removal (P = .10). Residual analysis was performed, confirming validity of these models. RESULTS: Average age, body mass index, and percentage of female patients were similar between cohorts. There was no statistically significant difference between the demographic variables, although data revealed patient variables contributing to statistically significant increases in surgical time, length of stay, blood loss, and complications with revision THA. CONCLUSION: Despite a 66% increase in "percent effort" and 3-fold higher readmission rate, revision THA requires at least a 2-fold increase because of nonquantifiable factors. Revision THA demonstrates a substantial increase in work effort not commensurate with current Medicare reimbursement, which may force surgeons to limit or eliminate revision arthroplasties performed reducing access to patient care.

The cost of preventing readmissions: why surgeons should lead the effort.

In accordance with the Affordable Care Act, Medicare has instituted financial penalties for hospitals with 30-day readmission rates that exceed a predetermined value. Currently, this value only considers "excess" readmissions for myocardial infarction, heart failure, and pneumonia with a maximum fine being one per cent of total Medicare reimbursements. In 2015, this penalty will increase to three per cent and encompass more surgical diagnoses. We retrospectively reviewed a database of adult patients undergoing cardiac surgery treated at our institution in 2012 to establish whether patients with readmissions within 30 days of the index operation could have been managed more cost-effectively without readmission. A calculation of cost efficiency was performed to compare the net hospital profit for two scenarios: admitting patients versus hypothetical preventative measures. Of the 576 patients during the study period, a total of 68 (11.8%) patients with unplanned 30-day readmissions were identified. Outpatient management was determined to have been feasible for 18 (26.5%) patients. Whereas the calculated net profit for readmission was $144,000, inclusion of Medicare's penalty resulted in a loss of $11,950. A readmission reduction program with an annual cost exceeding $11,950 would lead to financial loss. The financial implications of Medicare's readmission penalty alone necessitate the development of cost-effective strategies to reduce rehospitalization.

Applying STAAR interventions in incremental bundles: improving post-CABG surgical patient care.

BACKGROUND: Rehospitalization within 30 days of discharge after coronary artery bypass surgery (CABG) is a contributing factor to higher-than-acceptable overall hospital readmission rates throughout the United States. CABG rehospitalizations are of such concern that they are specifically targeted for action in 2015 under the Patient Protection and Affordable Care Act (2010). The phenomenon of increasing readmission rates has prompted the Institute for Healthcare Improvement to devise the Triple Aim initiative and the STate Action on Avoidable Rehospitalizations (STAAR) initiative to reduce 30-day readmission rates nationally. AIMS: This study explored the impact of implementing STAAR interventions delivered as part of a quality improvement project in incremental bundles on 30-day readmission rates and the experience of care in CABG patients. Specifically, the use of the teach-back patient education method and the scheduling of follow-up cardiology appointments prior to discharge using existing staff were examined. METHODS: A quantitative comparative study was conducted with 189 post-CABG patients at a tertiary care facility in the United States over a 2-year period, comparing outcomes between the group of patients prior to implementation of the STAAR interventions and those who later received them. Outcome variables included 30-day readmission rate and patient perception of experience of care. RESULTS: The overall 30-day readmission rate for CABG patients in the postintervention group was decreased to 12.0%, compared to 25.8% in the preintervention group. Of the demographic and health characteristics explored, only chronic lung disease was significantly related to 30-day readmission rates, and only in the postintervention group. LINKING EVIDENCE TO ACTION: Thirty-day readmission rates among CABG patients can be reduced and the experience of care can be enhanced through the use of targeted interventions utilizing existing staff and resources. The deliberate incremental implementation of bundled initiatives is an effective strategy in reducing 30-day readmissions in post-CABG patients.

Risk factors for unplanned hospital readmission in otolaryngology patients.

OBJECTIVE: Identify the risk factors that predict 30-day unplanned readmission in hospitalized otolaryngology patients. STUDY DESIGN: Retrospective cohort study. SETTING: Single academic hospital. SUBJECTS AND METHODS: All otolaryngology admissions for the 1-year period between January 1, 2011, and December 31, 2011, at an academic hospital were reviewed. Univariate logistic regression and multivariate logistic regression, employing a backward elimination stepwise approach, were performed to identify risk factors for unplanned readmission to the hospital within 30 days of discharge from the otolaryngology service. RESULTS: There were 1058 patients that accounted for 1271 hospital admissions. The 30-day unplanned readmission rate for patients discharged from the otolaryngology service was 7.3% (93/1271). Significant predictors identified on univariate analysis were used to build a multivariable logistic regression model of risk factors for unplanned readmission. These risk factors included presence of a complication (odds ratio [OR] = 11.60, 95% confidence interval [CI], 7.11-18.93), new total laryngectomy (OR = 4.72, 95% CI, 1.58-14.10), discharge destination of skilled nursing facility (OR = 2.70, 95% CI, 1.21-6.02), severe coronary artery disease or chronic lung disease (OR = 2.33, 95% CI, 1.38-3.93), and current illicit drug use (OR = 2.60, 95% CI, 1.27-5.34). The discriminative ability of the multivariate regression model to predict unplanned readmissions, as measured by the c-statistic, was 0.85. CONCLUSION: Otolaryngology patients have unique risk factors that predict unplanned readmission within 30 days of discharge. These data identify specific patient characteristics and care processes that can be targeted with quality improvement interventions to decrease unplanned readmissions.