Risk-adjusted Readmission Rates Research Articles

Reducing Length of Stay is not Associated with Increased Readmission Rates Following Lower Extremity Arterial Bypass

Objective: 
 Traditional fee-for-service reimbursement models for medical services have been increasingly replaced with the merit-based and efficiency-driven pay-for-performance initiatives. Financial incentives to decrease expenditures have added pressure on hospitals and providers to reduce length of stay (LOS). Concern has been raised that this strategy may unwittingly increase readmission rates. We sought to better understand potential trade-offs between these two outcome measures for hospitals performing lower extremity arterial bypass (LEAB). 
 Methods: 
 We performed a retrospective observational cohort study of 479,366 Medicare beneficiaries undergoing LEAB in 1,708 hospitals from 2005-2009. Using LOS quintiles and a multiple logistic regression model, we generated risk-adjusted readmission rates (RARR) accounting for age, gender, pre-existing comorbidities, non-elective admission status, post-operative complications, and discharge destination. We then compared RARRs across LOS quintiles. Finally, we evaluated the association between hospital LOS on readmissions performance after adjusting for hospital volume, location, teaching status, bed size, and non-home discharges. 
 Results: 
 The mean hospital 30-day RARR was 14.5% (SD 3.5%) and the median LOS 4 days (range 3-6 days). Hospitals with the shortest median LOS (2.3 days) had slightly lower readmission rates compared to those with the highest median LOS (9.2 days) (13.3% vs 15.8%, p <0.001). The Spearman correlation coefficient was 0.15 (p < 0.001), indicating a very weak correlation between LOS and RARR. 
 Conclusion and Potential Implications: 
 At the hospital-level, there appears to be little tradeoff between LOS and RARR, implying these outcomes measure different domains of hospital quality and can be used as indicators of care quality and the likelihood for post-discharge adverse events. As it is possible for hospitals to perform well on both measures, pay-for-performance initiatives may consider incentivizing reducing LOS and readmissions.

Variation in Surgical Spending Among the Highest Quality Hospitals for Cancer Surgery.

This study evaluates the variation in spending by the highest-quality hospitals performing complex cancer surgery in the United States. As mortality rates for high-risk cancer surgery have improved, increased attention has focused on other elements of quality, such as complications. However, high-value surgical care requires both high-quality care and cost savings. Therefore, understanding any residual cost variation among high-quality hospitals is essential to better direct efforts to achieve efficient, high-value care. Medicare beneficiaries age 65 to 99 who underwent surgery for pancreas, esophageal, lung, rectal, and colon cancer from 2014 to 2016 were identified. The highest-quality hospitals were identified as those in the quintile with the lowest risk- and reliability-adjusted serious complication rates for each operation. Within this cohort of high-quality hospitals, 30-day total episode, index hospitalization, physician, postacute care, and readmis-sion spending were analyzed. Logistic regression models were utilized to estimate the probability of postoperative outcomes and post-discharge resource utilization. A total of 43,007 Medicare patients underwent either pancreas, esophageal, lung, rectal, or colon resection for cancer at a hospital within the highest-quality quintile. Among the highest quality hospitals, total episode spending ranged from $18,712 for colectomy to $38,054 for esophagectomy. Spending between the lowest- and highest spending hospitals varied from $1207 [confidence intervals (CI 95% ) $1195-$1220] or 6.6% of total episode spending in the lowest tertile for colectomy to $5706 (CI 95% $5,506-$5906) or 16.1% of total episode spending in the lowest tertile for esophagectomy. The largest component of variation was from postacute care spending followed by readmission. For all operations, the risk-adjusted rate of postacute care facility utilization was lower among the lowest spending hospitals compared to the highest spending hospitals. For example, for pancreas the lowest-spending hospitals on average discharged patients to a postacute care facility at a rate of 18,6% (CI 95% 16.2-20.9) compared to 31.0% (CI 95% 28.2-33.9) in the highest-spending hospitals. In all operations, the risk-adjusted readmission rate was lower among the lowest-spending hospitals compared to the highest-spending hospitals. For instance, within the esophagus cohort, the lowest-spending hospitals had an average risk-adjusted readmission rate of 17.3% compared to 29.4% in the highest spending hospitals ( P < .001). Even among the highest-quality hospitals, significant cost variation persists among cancer operations. Postacute care variation, rather than residual variation in complication rates, explains the majority of this variation and represents an immediately actionable target for increased cost-efficiency.

Effects of post-discharge telemonitoring on 30-day chronic obstructive pulmonary disease readmissions and mortality

Introduction Much attention has been focused on decreasing chronic obstructive pulmonary disease (COPD) hospital readmissions. The US health system has struggled to meet this goal. The objective of this study was to assess the efficacy of telehealth services on the reduction of hospital readmission and mortality rates for COPD. Methods We used a cross-sectional design to examine the association between hospital risk-adjusted readmission and mortality rates for COPD and hospital use of post-discharge telemonitoring (TM). Data for 777 hospitals were sourced from the Centers for Medicare & Medicaid Services and the American Hospital Association annual surveys. Propensity score matching using the kennel weights method was applied to calculate the weighted probability of being a hospital that offers post-discharge TM services. Results Hospitals with post-discharge TM had about 34% significantly higher odds (adjusted odds ratio (AOR) = 1.34; 95% confidence interval (CI) 1.06–1.70) of 30-day COPD readmission and 33% significantly lower odds (AOR = 0.67; 95% CI 0.50–0.90) of 30-day COPD mortality compared to hospitals without post-discharge TM services. Discussion Overall, hospitals that offer post-discharge TM services have seen an improvement in 30-day COPD mortality rates. However, those same hospitals have also experienced a significant increase in 30-day COPD readmissions. TM can potentially decrease mortality in patients recently admitted for acute exacerbation of COPD. The results provide further evidence that readmissions present a problematic assessment of health-care quality, as the need for readmission may or may not be directly related to the quality of care received while in hospital.

Trends in 30-Day Readmission for Medicaid and Privately Insured Pediatric Patients: 2010-2017.

Children insured by Medicaid have higher readmission rates than privately insured children. However, little is known about whether this disparity has changed over time. Data from the 2010 to 2017 Healthcare Cost and Utilization Project Nationwide Readmissions Database were used to compare trends in 30-day readmission rates for children insured by Medicaid and private insurers. Patient-level crude and risk-adjusted readmission rates were compared by using Poisson regression. Hospital-level risk-adjusted readmission rates were compared between Medicaid- and privately insured patients within a hospital by using linear regression. Approximately 60% of pediatric admissions were covered by Medicaid. From 2010 to 2017, the percentage of children with a complex or chronic condition increased for both Medicaid- and privately insured patients. Readmission rates were consistently higher for Medicaid beneficiaries from 2010 to 2017. Readmission rates declined slightly for both Medicaid- and privately insured patients; however, they declined faster for privately insured patients (rate ratio: 0.988 [95% confidence interval: 0.986-0.989] vs 0.995 [95% confidence interval: 0.994-0.996], P for interaction <.001]). After adjustment, readmission rates for Medicaid- and privately insured patients declined at a similar rate (P for interaction = .87). Risk-adjusted hospital readmission rates were also consistently higher for Medicaid beneficiaries. The within-hospital difference in readmission rates for Medicaid versus privately insured patients remained stable over time (slope for difference: 0.015 [SE 0.011], P = .019). Readmission rates for Medicaid- and privately insured pediatric patients declined slightly from 2010 to 2017 but remained substantially higher among Medicaid beneficiaries suggesting a persistence of the disparity by insurance status.

Association of Medicaid Eligibility With Surgical Readmission Among Medicare Beneficiaries

The Centers for Medicare & Medicaid Services is beginning to consider adjusting for social risk factors, such as dual eligibility for Medicare and Medicaid, when evaluating hospital performance under value-based purchasing programs. It is unknown whether dual eligibility represents a unique domain of social risk or instead represents clinical risk unmeasured by variables available in traditional Medicare claims. To assess how dual eligibility for Medicare and Medicaid is associated with risk-adjusted readmission rates after surgery. A retrospective cohort study was conducted of 55 651 Medicare beneficiaries undergoing general, vascular, and gynecologic surgery at 62 hospitals in Michigan between January 1, 2014, and December 1, 2016. Representative cohorts were derived from traditional Medicare claims (n = 29 710) and the Michigan Surgical Quality Collaborative (MSQC) clinical registry (n = 25 941), which includes additional measures of clinical risk. Statistical analysis was conducted between April 10 and July 15, 2019. The association between dual eligibility and risk-adjusted 30-day readmission rates after surgery was compared between models inclusive and exclusive of additional measurements of clinical risk. The study also examined how dual eligibility is associated with hospital profiling using risk-adjusted readmission rates. Dual eligibility for Medicare and Medicaid. Risk-adjusted all-cause 30-day readmission after surgery. There were a total of 3986 dual-eligible beneficiaries in the Medicare claims cohort (2554 women; mean [SD] age, 72.9 [6.9] years) and 1608 dual-eligible beneficiaries in the MSQC cohort (990 women; mean [SD] age, 72.9 [6.8] years). In both data sets, higher proportions of dual-eligible beneficiaries were younger, female, and nonwhite than Medicare-only beneficiaries (Medicare claims cohort: female, 2554 of 3986 [64.1%] vs 12 879 of 25 724 [50.1%]; nonwhite, 1225 of 3986 [30.7%] vs 2783 of 25 724 [10.8%]; MSQC cohort: female, 990 of 1608 [61.6%] vs 12 578 of 24 333 [51.7%]; nonwhite, 416 of 1608 [25.9%] vs 2176 of 24 333 [8.9%]). In the Medicare claims cohort, dual-eligible beneficiaries were more likely to be readmitted (15.5% [95% CI, 13.7%-17.3%]) than Medicare-only beneficiaries (13.3% [95% CI, 12.7%-13.9%]; difference, 2.2 percentage points [95% CI, 0.4-3.9 percentage points]). In the MSQC cohort, after adjustment for more granular measures of clinical risk, dual eligibility was not significantly associated with readmission (difference, 0.6 percentage points [95% CI, -1.0 to 2.2 percentage points]). In both the Medicare claims and MSQC cohorts, adding dual eligibility to risk-adjustment models had little association with hospital ranking using risk-adjusted readmission rates. This study suggests that dual eligibility for Medicare and Medicaid may reflect unmeasured clinical risk of readmission in claims data. Policy makers should consider incorporating more robust measures of social risk into risk-adjustment models used by value-based purchasing programs.

The Hospital Readmissions Reduction Program and Readmissions for Chronic Obstructive Pulmonary Disease, 2006-2015.

Rationale: In October 2012, the initial phase of the Hospital Readmission Reduction Program imposed financial penalties on hospitals with higher-than-expected risk-adjusted 30-day readmission rates for Medicare beneficiaries with congestive heart failure, myocardial infarction, and pneumonia. We hypothesized that these penalties may also be associated with decreased readmissions for chronic obstructive pulmonary disease (COPD) in the general population before COPD became a target condition (October 2014).Objectives: To determine if implementation of the initial financial penalties for other conditions was associated with a decrease in hospital readmissions for COPD.Methods: We used population-level data to examine patients readmitted for any reason or for COPD within 30 days after an initial hospitalization for COPD. The data source was seven states in the State Inpatient Database. The preimplementation period included calendar years 2006 to 2012. The postimplementation period included 2013 to 2015. Using interrupted time series, the level change was examined, which reflected the difference between the expected and actual readmission rates in 2013. The difference in slopes between the pre- and postimplementation periods was also examined.Results: We identified 805,764 hospitalizations for COPD from 904 hospitals. Overall, 26% of patients had primary insurance other than Medicare. After the intervention, patients had lower rates of all-cause 30-day readmissions (level change, -0.93%; 95% confidence interval [CI], -1.44% to -0.43%; P = 0.004), which was driven by fewer early readmissions (0-7 d). The postimplementation slope became positive; the difference in slopes was 0.39% (95% CI, 0.28% to 0.50%; P < 0.001). Patients also had lower rates of COPD-related readmissions (level decrease, -0.52%; 95% CI, -0.93% to -0.12%; P = 0.02), which was due to decreases in both early and late (8-30 d) readmissions. The postimplementation slope was negative; the difference in slopes was -0.21% (95% CI, -0.35% to -0.07%; P = 0.009).Conclusions: In patients with COPD and any insurance status, there was an association between the initial phase of the Hospital Readmission Reduction Program and a decrease in both all-cause and COPD-related readmissions even before COPD became a target diagnosis. The large amount of money at risk to hospitals likely resulted in broad behavioral change. Future research is needed to test which levers can effectively reduce readmission rates for COPD.

Care coordination for veterans with COPD: a positive deviance study.

Improving chronic obstructive pulmonary disease (COPD) care and reducing hospital readmissions is an urgent healthcare system priority. However, little is known about the organizational factors that underlie intersite variation in readmission rates. Evidence from other chronic diseases points to care coordination as one such factor. To understand whether intersite differences in care coordination may be one of the organizational factors contributing to the variation in readmission rates, we examined provider perspectives on COPD care at Veterans Affairs (VA) sites. In this mixed-methods positive deviance study, we selected 3 VA sites in the lowest quartile and 3 in the highest quartile for 2016 risk-adjusted COPD readmission rates. During June to October 2017, we conducted semistructured interviews with primary and specialty care providers involved in COPD care at VA sites with low (n = 14) and high (n = 11) readmission rates. Although providers at all sites referenced ongoing readmission reduction initiatives, only providers at low-readmission sites described practice environments characterized by high relational coordination (ie, high-quality work relationships and high-quality communication). They also reported fewer significant structural barriers to collaboration in areas like patient volume. The most notable differences between high- and low-readmission sites were related to the quality of relational coordination and the presence of structural barriers to coordination, rather than specific readmission reduction initiatives. Implementing organizational reforms aimed at enhancing relational coordination and removing structural barriers would enhance care for COPD and may improve quality of care for other chronic conditions.

Readmission and Mortality After Hospitalization for Myocardial Infarction and Heart Failure

BackgroundReadmission rates after acute myocardial infarction (AMI) and heart failure (HF) hospitalizations have decreased in the United States since the implementation of the Hospital Readmissions Reduction Program. ObjectivesThis study was designed to examine the temporal trends of readmission and mortality after AMI and HF in Ontario, Canada, where reducing hospital readmissions has not had a policy incentive. MethodsThe cohort was comprised of AMI or HF patients 65 years of age or older who had been hospitalized from 2006 to 2017. Primary outcomes were 30-day readmission and post-discharge mortality. Secondary outcomes included in-hospital mortality, 30-day mortality from admission, and in-hospital mortality or 30-day mortality post-discharge. Adjusted monthly trends for each outcome were examined over the study period. ResultsOur cohorts included 152,808 AMI and 223,283 HF patients. Age- and sex-standardized AMI hospitalization rates in Ontario declined 32% from 2006 to 2017 while HF hospitalization rates declined slightly (9.1%). For AMI, risk-adjusted 30-day readmission rates declined from 17.4% in 2006 to 14.7% in 2017. All AMI risk-adjusted mortality rates also declined from 2006 to 2017 with 30-day post-discharge mortality from 5.1% to 4.4%. For HF, overall risk-adjusted 30-day readmission was largely unchanged from 2006 to 2014 at 21.9%, followed by a decline to 20.8% in 2017. Risk-adjusted 30-day post-discharge mortality declined from 7.1% in 2006 to 6.6% in 2017. ConclusionsThe patterns of outcomes in Ontario are consistent with the United States for AMI, but diverge for HF. For AMI and HF, admissions, readmissions, and mortality rates declined over this period. The reasons for the country-specific patterns for HF need further exploration.

Temporal Trends in Racial Differences in 30-Day Readmission and Mortality Rates After Acute Myocardial Infarction Among Medicare Beneficiaries

The association of the Hospital Readmission Reduction Program (HRRP) with reductions in racial disparities in 30-day outcomes for myocardial infarction (MI), is unknown, including whether this varies by HRRP hospital penalty status. To assess temporal trends in 30-day readmission and mortality rates among black and nonblack patients discharged after hospitalization for acute MI at low-performing and high-performing hospitals, as defined by readmission penalty status after HRRP implementation. This observational cohort analysis used data from the multicenter National Cardiovascular Data Registry Chest Pain-MI Registry centers that were subject to the first cycle of HRRP, between January 1, 2008, and November 30, 2016. All patients hospitalized with MI who were included in National Cardiovascular Data Registry Chest Pain-MI Registry were included in the analysis. Data were analyzed from April 2018 to September 2019. Hospital performance category and race (black compared with nonblack patients). Centers were classified as high performing or low performing based on the excess readmission ratio (predicted to expected 30-day risk adjusted readmission rate) for MI during the first HRRP cycle (in October 2012). Thirty-day all-cause readmission and mortality rates. Among 753 hospitals that treated 155 397 patients with acute MI (of whom 11 280 [7.3%] were black), 399 hospitals (53.0%) were high performing. Thirty-day readmission rates declined over time in both black and nonblack patients (annualized 30-day readmission rate: 17.9% vs 20.8%). Black (compared with nonblack) race was associated with higher unadjusted odds of 30-day readmission in both low-performing and high-performing centers (odds ratios: before HRRP: low-performing hospitals, 1.14 [95% CI, 1.03-1.26]; P = .01; high-performing hospitals, 1.17 [95% CI, 1.04-1.32]; P = .01; after HRRP: low-performing hospitals, 1.23 [95% CI, 1.13-1.34]; P < .001; high-performing hospitals, 1.25 [95% CI, 1.12-1.39]; P < .001). However, these racial differences were not significant after adjustment for patient characteristics. The 30-day mortality rates declined significantly over time in nonblack patients, with stable (nonsignificant) temporal trends among black patients. Adjusted associations between race and 30-day mortality showed that 30-day mortality rates were significantly lower among black (compared with nonblack) patients in the low-performing hospitals (odds ratios: pre-HRRP, 0.79 [95% CI, 0.63-0.97]; P = .03; post-HRRP, 0.80 [95% CI, 0.68-0.95]; P = .01) but not in high-performing hospitals. Finally, the association between race and 30-day outcomes did not vary after the HRRP period began in either high-performing or low-performing hospitals. In this analysis, 30-day readmission rates among patients with MI declined over time for both black and nonblack patients. Differences in race-specific 30-day readmission rates persisted but appeared to be attributable to patient-level factors. The 30-day mortality rates have declined for nonblack patients and remained stable among black patients. Implementation of the HRRP was not associated with improvement or worsening of racial disparities in readmission and mortality rates.

Reliability of the American Community Survey Estimates of Risk-Adjusted Readmission Rankings for Hospitals Before and After Peer Group Stratification

Since the transition to the American Community Survey, data uncertainty has complicated its use for policy making and research, despite the ongoing need to identify disparities in health care outcomes. The US Centers for Medicare & Medicaid Services' new, stratified payment adjustment method for its Hospital Readmissions Reduction Program may be able to reduce the reliance on data linkages to socioeconomic survey estimates. To determine whether there are differences in the reliability of socioeconomically risk-adjusted hospital readmission rates among hospitals that serve a disproportionate share of low-income populations after stratifying hospitals into peer group-based classification groups. This cross-sectional study uses data from the 2014 New York State Health Cost and Utilization Project State Inpatient Database for 96 278 hospital admissions for acute myocardial infarction, pneumonia, and congestive heart failure. The analysis included patients aged 18 years and older who were not transferred to another hospital, who were discharged alive, who did not leave the hospital against medical advice, and who were discharged before December 2014. The main outcomes were 30-day hospital readmissions after acute myocardial infarction, pneumonia, and congestive heart failure assessed using hierarchical logistic regression. The mean (SD) age of the patients was 69.6 (16.0) years for the safety-net hospitals and 74.9 (14.7) years for the non-safety-net hospitals; 9382 (48.8%) and 7003 (48.5%) patients, respectively, were female. For safety net designations, 20% (3 of 15) of all evaluations concealed and distorted differences in risk, with factors such as poverty failing to identify similar risk of acute myocardial infarction readmission until unreliable estimates were excluded from the analysis (OR, 1.23 [95% CI, 1.00-1.52], P = .02; vs OR, 1.17 [95% CI, 0.94-1.46], P = .15). By comparison, 2 of the 60 models (3%) for the peer group-based classification altered the association between socioeconomic status and readmission risk, concealing similarities in congestive heart failure readmission when adjusted using high school completion rates (OR, 1.27 [95% CI 1.02-1.58], P = .04; vs OR, 1.23 [95% CI, 0.98-1.53], P = .06) and distorting similarities in pneumonia readmissions when accounting for the proportion of lone-parent families (OR, 1.27 [95% CI, 0.98-1.66], P = .07; vs OR, 1.35 [95% CI, 1.02-1.80], P = .04) between the lowest and highest socioeconomic status hospitals in quartile 1. There was greater precision in socioeconomic adjusted readmission estimates when hospitals were stratified into the new payment adjustment criteria compared with safety net designations. A contributing factor for improved reliability of American Community Survey estimates under the new payment criteria was the merging of patients from low-income neighborhoods with greater homogeneity in survey estimates into groupings similar to those for higher-income patients, whose neighborhoods often exhibit greater estimate variability. Additional efforts are needed to explore the effect of measurement error on American Community Survey-adjusted readmissions using the new peer group-based classification methods.

Risk Adjusting Health Care Provider Collaboration Networks.

The quality of hospital discharge care and patient factors (health and sociodemographic) impact the rates of unplanned readmissions. This study aims to measure the effects of controlling for the patient factors when using readmission rates to quantify the weighted edges between health care providers in a collaboration network. This improved understanding may inform strategies to reduce hospital readmissions, and facilitate quality-improvement initiatives. We extracted 4 years of patient, provider, and activity data related to cardiology discharge workflow. A Weibull model was developed to predict the risk of unplanned 30-day readmission. A provider-patient bipartite network was used to connect providers by shared patient encounters. We built collaboration networks and calculated the Shared Positive Outcome Ratio (SPOR) to quantify the relationship between providers by the relative rate of patient outcomes, using both risk-adjusted readmission rates and unadjusted readmission rates. The effect of risk adjustment on the calculation of the SPOR metric was quantified using a permutation test and descriptive statistics. Comparing the collaboration networks consisting of 2,359 provider pairs, we found that SPOR values with risk-adjusted outcomes are significantly different than unadjusted readmission as an outcome measure (p-value = 0.025). The two networks classified the same provider pairs as high-scoring 51.5% of the time, and the same low scoring provider pairs 85.6% of the time. The observed differences in patient demographics and disease characteristics between high-scoring and low-scoring provider pairs were reduced by applying the risk-adjusted model. The risk-adjusted model reduced the average variation across each individual's SPOR scored provider connections. Risk adjusting unplanned readmission in a collaboration network has an effect on SPOR-weighted edges, especially on classifying high-scoring SPOR provider pairs. The risk-adjusted model reduces the variance of providers' connections and balances shared patient characteristics between low- and high-scoring provider pairs. This indicates that the risk-adjusted SPOR edges better measure the impact of collaboration on readmissions by accounting for patients' risk of readmission.

Hospital Readmission Rates in Medicare Advantage and Traditional Medicare: A Retrospective Population-Based Analysis.

Medicare's Hospital Readmissions Reduction Program reports risk-standardized readmission rates for traditional Medicare but not Medicare Advantage beneficiaries. To compare readmission rates between Medicare Advantage and traditional Medicare. Retrospective cohort study linking the Medicare Provider Analysis and Review (MedPAR) file with the Healthcare Effectiveness Data and Information Set (HEDIS). 4748 U.S. acute care hospitals. Patients aged 65 years or older hospitalized for acute myocardial infarction (AMI) (n= 841613), congestive heart failure (CHF) (n= 1458652), or pneumonia (n= 2020365) between 2011 and 2014. 30-day readmissions. Among admissions for AMI, CHF, and pneumonia identified in MedPAR, 29.2%, 38.0%, and 37.2%, respectively, did not have a corresponding record in HEDIS. Of these, 18.9% for AMI, 23.7% for CHF, and 18.3% for pneumonia resulted in a readmission that was identified in MedPAR. However, among index admissions appearing in HEDIS, 14.4% for AMI, 18.4% for CHF, and 13.9% for pneumonia resulted in a readmission. Patients in Medicare Advantage had lower unadjusted readmission rates than those in traditional Medicare for all 3 conditions (16.6% vs. 17.1% for AMI, 21.4% vs. 21.7% for CHF, and 16.3% vs. 16.4% for pneumonia). However, after standardization, patients in Medicare Advantage had higher readmission rates than patients in traditional Medicare for AMI (17.2% vs. 16.9%; difference, 0.3 percentage point [95% CI, 0.1 to 0.5 percentage point]), CHF (21.7% vs. 21.4%; difference, 0.3 percentage point [CI, 0.2 to 0.5 percentage point]), and pneumonia (16.5% vs. 16.0%; difference, 0.5 percentage point [95% CI, 0.4 to 0.6 percentage point]). Rate differences increased between 2011 and 2014. Potential unobserved differences between populations. The HEDIS data underreported hospital admissions for 3 common medical conditions, and readmission rates were higher among patients with underreported admissions. Medicare Advantage beneficiaries had higher risk-adjusted 30-day readmission rates than traditional Medicare beneficiaries. National Institute on Aging.

Comparison of Hospital Readmission After Total Hip and Total Knee Arthroplasty vs Spinal Surgery After Implementation of the Hospital Readmissions Reduction Program

The Hospital Readmissions Reduction Program (HRRP) was recently expanded to penalize excessive readmissions after total hip arthroplasty (THA) and total knee arthroplasty (TKA). These are the first surgical procedures to be included in the HRRP. To determine whether the HRRP was associated with a greater decrease in readmissions after targeted procedures (THA and TKA) compared with similar nontargeted procedures (lumbar spine fusion and laminectomy). A retrospective cohort study was conducted of patients 50 years or older among all payers in the Nationwide Readmissions Database who underwent THA, TKA, lumbar spine fusion, or laminectomy between January 1, 2010, and September 30, 2015. Multivariable logistic regression and interrupted time-series models were used to calculate and compare 30-day readmission trends in 3 periods associated with the HRRP: preimplementation (January 2010-September 2012), implementation (October 2012-September 2014), and penalty (October 2014-September 2015). Statistical analysis was performed from January 1, 2010, to September 30, 2015. Announcement and implementation of the HRRP. Readmission within 30 days after hospitalization for THA, TKA, lumbar spine fusion, or laminectomy surgery. The study included 6 687 077 (58.3% women and 41.7% men; mean age, 66.7 years; 95% CI, 66.7-66.8 years) weighted hospitalizations for THA, TKA, lumbar spine fusion, and laminectomy surgery: 4 765 466 hospitalizations for targeted conditions and 1 921 611 for nontargeted conditions. After passage of the Patient Protection and Affordable Care Act, the risk-adjusted rates of readmission after all procedures decreased in a similar fashion. Implementation of the HRRP was associated with a 0.018% per month decrease in the rate of readmission (95% CI, -0.025% to -0.010%) after targeted procedures, which was not observed after nontargeted procedures (slope per month, -0.003%; 95% CI, -0.016% to 0.010%). Penalties were not associated with a greater decrease in readmission for either targeted or nontargeted procedures. These results appear to be consistent with hospitals responding to the future possibility of penalties by reducing readmissions after surgical procedures targeted by the HRRP.

Association Between Hospital Participation in Medicare Shared Savings Program Accountable Care Organizations and Readmission Following Major Surgery.

To evaluate the effect of Medicare Shared Savings Program accountable care organizations (ACOs) on hospital readmission after common surgical procedures. Hospital readmissions following surgery lead to worse patient outcomes and wasteful spending. ACOs, and their associated hospitals, have strong incentives to reduce readmissions from 2 distinct Centers for Medicare and Medicaid Services policies. We performed a retrospective cohort study using a 20% national Medicare sample to identify beneficiaries undergoing 1 of 7 common surgical procedures-abdominal aortic aneurysm repair, colectomy, cystectomy, prostatectomy, lung resection, total knee arthroplasty, and total hip arthroplasty-between 2010 and 2014. The primary outcome was 30-day risk-adjusted readmission rate. We performed difference-in-differences analyses using multilevel logistic regression models to quantify the effect of hospital ACO affiliation on readmissions following these procedures. Patients underwent a procedure at one of 2974 hospitals, of which 389 were ACO affiliated. The 30-day risk-adjusted readmission rate decreased from 8.4% (95% CI, 8.1-8.7%) to 7.0% (95% CI, 6.7-7.3%) for ACO affiliated hospitals (P < 0.001) and from 7.9% (95% CI, 7.8-8.0%) to 7.1% (95% CI, 6.9-7.2%) for non-ACO hospitals (P < 0.001). The difference-in-differences of the 2 trends demonstrated an additional 0.52% (95% CI, 0.97-0.078%) absolute reduction in readmissions at ACO hospitals (P = 0.021), which would translate to 4410 hospitalizations avoided. Readmissions following common procedures decreased significantly from 2010 to 2014. Hospital affiliation with Shared Savings ACOs was associated with significant additional reductions in readmissions. This emphasis on readmission reduction is 1 mechanism through which ACOs improve value in a surgical population.

Abstract 1: Readmission Rates Across All Insurance Types After Passage of the Hospital Readmissions Reduction Program: A Nationwide Analysis

Introduction: Since implementation of the Hospital Readmission Reduction Program (HRRP), readmission rates have declined among Medicare patients hospitalized with conditions targeted by the policy - myocardial infarction, heart failure, and pneumonia. It is unknown if similar reductions occurred for other insurance types (Medicaid, private). Methods: We conducted a difference-in-difference analysis using the Nationwide Readmission Database. First, we calculated quarterly readmission rates for each insurance type and target condition from 2010 to 2014. Second, we compared how quarterly readmission rates for target conditions changed before (2010-2012) and after HRRP implementation (2012-2014), using changes in readmissions for non-target conditions as controls. The analysis included 3,737,589 patients with target conditions and 31,096,617 patients with non-target conditions. Results: Following HRRP implementation, readmission rates declined for both Medicare and Medicaid patients. Medicaid readmissions for patients with target conditions declined at a significantly greater rate compared to non-target conditions, both in aggregate (change in slope between pre- and post-HRRP periods, -0.044%/quarter [95% CI -0.061; -0.027]), and for each condition: acute myocardial infarction (-0.098 [-0.132; -0.064]), heart failure (-0.030 [-0.055; -0.005]) and pneumonia (-0.079 [-0.107;-0.051]). Composite Medicaid readmission rates, however, remained higher than Medicare. Privately-insured patients had the lowest aggregate readmission rates throughout the study period, with no additional decline after HRRP implementation. Conclusions: The HRRP was associated with reductions in readmissions that extended to the Medicaid population. These findings may reflect the effect of system-wide efforts to reduce readmissions in response to the policy. Medicaid readmission rates, however, remained greater compared to other insurers, and should be considered a focus for future readmission reduction initiatives. Figure. Change in Readmission Rates for All Target Conditions, Across Insurance Types Points represent quarterly risk-adjusted readmission rates. Solid lines were generated from these points through a piecewise linear model. The dashed line separates the pre- and post-HRRP periods.

Trends in Hospital Readmission of Medicare-Covered Patients With Heart Failure

BackgroundThe Medicare Hospital Readmissions Reduction Program has led to fewer readmissions following hospitalizations with a principal diagnosis of heart failure (HF). Patients with HF are frequently hospitalized for other causes. ObjectivesThis study sought to compare trends in Medicare risk-adjusted, 30-day readmissions following principal HF hospitalizations and other hospitalizations with HF. MethodsThis was a retrospective study of 12,973,853 Medicare hospitalizations with a principal or secondary diagnosis of HF between January 2008 and June 2015. Hospitalizations were categorized as follows: principal HF hospitalizations; principal acute myocardial infarction or pneumonia hospitalizations with secondary HF; and other hospitalizations with secondary HF. The study examined trends in risk-adjusted, 30-day, all-cause readmission rates for each cohort and trends in differences in readmission rates among cohorts by using linear spline regression models. ResultsBefore passage of the Affordable Care Act in March 2010, risk-adjusted, 30-day readmission rates were stable for all 3 cohorts, with mean monthly rates of 26.1%, 24.9%, and 24.4%, respectively. Risk-adjusted readmission rates started declining after passage of the Affordable Care Act by 1.09% (95% confidence interval [CI]: 0.51% to 1.68%), 1.24% (95% CI: 0.92% to 1.57%), and 1.05% (95% CI: 0.52% to 1.58%) per year, respectively, until implementation of the Hospital Readmissions Reduction Program in October 2012 and then stabilized for all 3 cohorts. ConclusionsPatients with HF are often hospitalized for other causes, and these hospitalizations have high readmission rates. Policy changes led to decreases in readmission rates for both principal and secondary HF hospitalizations. Readmission rates in both groups remain high, suggesting that initiatives targeting all hospitalized patients with HF continue to be warranted.

Association of the Swiss Diagnosis-Related Group Reimbursement System With Length of Stay, Mortality, and Readmission Rates in Hospitalized Adult Patients

In 2012, hospital reimbursement in Switzerland changed from a fee-for-service per diem system to a diagnosis-related group (SwissDRG) system. Whether this change in reimbursement is associated with harmful implications for quality of care and patient outcomes remains unclear. To examine the association of the SwissDRG implementation with length of hospital stay (LOS), in-hospital mortality, and 30-day readmission rates in the overall adult inpatient population and stratified by 5 individual diagnoses. This cohort study used administrative data from the Swiss Federal Statistical Office to investigate medical hospitalizations in Switzerland from January 1, 2009, through December 31, 2015. All hospitalizations for adult medical inpatients were included in the main analysis. Patients who presented with 1 of the 5 common medical diagnoses were included in the subanalyses: community-acquired pneumonia, exacerbation of chronic obstructive pulmonary disease, acute myocardial infarction, acute heart failure, and pulmonary embolism. An interrupted time series model was used to determine changes in time trends for risk-adjusted LOS, in-hospital mortality, and 30-day readmission after the implementation of SwissDRG in 2012. Analyses were performed from March 1, 2018, to June 30, 2018, and from November 1, 2018, to December 18, 2018. Monthly patient-level data for LOS, in-hospital mortality, and 30-day readmission rates. The sample included a total of 2 426 722 hospitalized adult patients. Of this total, 1 018 404 patients (41.9%; 531 226 [52.2%] male, median [interquartile range (IQR)] age of 69 [55-80] years) composed the before-SwissDRG period; 1 408 318 patients (58.0%; 730 228 [51.9%] male, median [IQR] age of 70 [56-81] years) composed the after-SwissDRG period. The overall LOS gradually decreased from unadjusted mean (SD) 8.0 (12.7) days in 2009 to 7.2 (17.3) days in 2015. This reduction in LOS, however, was not substantially greater with the implementation of SwissDRG in 2012 (risk-adjusted slope, -0.0166 days; 95% CI, -0.0223 to -0.0110 days), with an adjusted difference in slopes of 0.0000 days (95% CI, -0.0072 to 0.0072 days). Risk-adjusted all-cause in-hospital mortality declined from 4.9% in 2009 to 4.6% in 2015, with a substantially greater decline after implementation of SwissDRG (difference between monthly slopes before and after implementation, -0.0115%; 95% CI, -0.0190% to -0.0039%). In the same period, risk-adjusted 30-day readmission rates increased from 14.4% in 2009 to 15.0% in 2015, with a greater increase after SwissDRG implementation (change in monthly slope, 0.0339%; 95% CI, 0.0254%-0.0423%). Patients with acute myocardial infarction were found to have a substantially greater increase after SwissDRG implementation in 30-day readmission rates (adjusted difference in slopes, 0.1144%; 95% CI, 0.0617%-0.1671%). Among medical hospitalizations in Switzerland, SwissDRG implementation appeared to be associated with an increase in readmission rates and a decrease in in-hospital mortality but not with the gradual decrease in LOS observed in the historical control period.

Trends in Pediatric Hospitalizations and Readmissions: 2010-2016.

Health reform and policy initiatives over the last 2 decades have led to significant changes in pediatric clinical practice. However, little is known about recent trends in pediatric hospitalizations and readmissions at a national level. Data from the 2010-2016 Healthcare Cost and Utilization Project Nationwide Readmissions Database and National Inpatient Sample were analyzed to characterize patient-level and hospital-level trends in annual pediatric (ages 1-17 years) admissions and 30-day readmissions. Poisson regression was used to evaluate trends in pediatric readmissions over time. From 2010 to 2016, the total number of index admissions decreased by 21.3%, but the percentage of admissions for children with complex chronic conditions increased by 5.7%. Unadjusted pediatric 30-day readmission rates increased over time from 6.26% in 2010 to 7.02% in 2016 with a corresponding increase in numbers of admissions for patients with complex chronic conditions. When stratified by complex or chronic conditions, readmission rates declined or remained stable across patient subgroups. Mean risk-adjusted hospital readmission rates increased over time overall (6.46% in 2010 to 7.14% in 2016) and in most hospital subgroups but decreased over time in metropolitan teaching hospitals. Pediatric admissions declined from 2010 to 2016 as 30-day readmission rates increased. The increase in readmission rates was associated with greater numbers of admissions for children with chronic conditions. Hospitals serving pediatric patients need to account for the rising complexity of pediatric admissions and develop strategies for reducing readmissions in this high-risk population.

Decreases In Readmissions Credited To Medicare's Program To Reduce Hospital Readmissions Have Been Overstated.

Medicare's Hospital Readmissions Reduction Program (HRRP) has been credited with lowering risk-adjusted readmission rates for targeted conditions at general acute care hospitals. However, these reductions appear to be illusory or overstated. This is because a concurrent change in electronic transaction standards allowed hospitals to document a larger number of diagnoses per claim, which had the effect of reducing risk-adjusted patient readmission rates. Prior studies of the HRRP relied upon control groups' having lower baseline readmission rates, which could falsely create the appearance that readmission rates are changing more in the treatment than in the control group. Accounting for the revised standards reduced the decline in risk-adjusted readmission rates for targeted conditions by 48percent. After further adjusting for differences in pre-HRRP readmission rates across samples, we found that declines for targeted conditions at general acute care hospitals were statistically indistinguishable from declines in two control samples. Either the HRRP had no effect on readmissions, or it led to a systemwide reduction in readmissions that was roughly half as large as prior estimates have suggested.

Variance of rates and Costs of Unplanned readmissions in tertiary Hospitals in south Korea

This study attempted to estimate rates and costs of unplanned readmissions of high level hospitals Korea.Unplanned readmissions are used as a proxy of the quality of medical services. Korean Health Insurancereimburses tertiary hospitals 5% more fees than general hospitals. The gaps of the health insurancereimbursement rates are not based on the difference in quality of medical services among the level ofhospitals. It needs to be reviewed whether the gaps are reflecting difference of the quality of medical services.The Health Insurance Claims Data of patients readmitted within 28 days after discharge from tertiaryhospitals in 2014 were classified into unplanned claims. Unplanned readmissions were compared withplanned readmissions.The risk-adjusted average readmission rate was 6.4% in all tertiary hospitals, but 5.7% in general hospitalswith 500 beds or more. Coefficient of variance (CV) of readmission rate was higher in tertiary hospitals(32.8) than general hospitals with 500 beds or more (17.5). However, there was no significant difference inmean medical fees per unplanned readmission between two groups of hospitals. It was 3,810 Won in thetertiary hospitals and 3,834 Won in general hospitals with 500 beds or more.The findings of this study showed that higher costs did not necessarily yield higher quality of care, suggestingthat quality control measures should be required to reduce unplanned readmissions in tertiary hospitals.