Incentivizing Cost-Effective Reductions in Hospital Readmission Rates.
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ABSTRACT:
SUBMITTER: Cox JC
PROVIDER: S-EPMC5319438 | biostudies-literature | 2016 Nov
REPOSITORIES: biostudies-literature
Publications
Incentivizing Cost-Effective Reductions in Hospital Readmission Rates.
Cox James C JC Sadiraj Vjollca V Schnier Kurt E KE Sweeney John F JF
Journal of economic behavior & organization 20150403 B
The recent regulatory changes enacted by the Centers for Medicare and Medicaid Services (CMS) have identified hospital readmission rates as a critical healthcare quality metric. This research focuses on the utilization of pay-for-performance (P4P) mechanisms to cost effectively reduce hospital readmission rates and meet the regulatory standards set by CMS. Using the experimental economics laboratory we find that both of the P4P mechanisms researched, bonus and bundled payments, cost-effectively ...[more]
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Project description:BackgroundDespite recent reductions in national unplanned readmission rates, we have relatively little understanding of which hospital strategies are most associated with changes in risk-standardized readmission rates (RSRR).ObjectiveWe examined associations between the change in hospital 30-day RSRR for patients with heart failure and the uptake of strategies over 12-18 months in a national sample of hospitals.DesignWe conducted a prospective study of hospitals using a Web-based survey at baseline (November 2010-May 2011, n = 599, 91.0% response rate) and 12-18 months later (November 2011-October 2012, n = 501, 83.6% response rate), with RSRR measured at the same time points. The final analytic sample included 478 hospitals.ParticipantsThe study included hospitals participating in the Hospital-to-Home (H2H) and State Action on Avoidable Rehospitalizations (STAAR) initiatives.Main measuresWe examined associations between change in hospital 30-day RSRR for patients with heart failure and the uptake of strategies previously demonstrated to have increased between baseline and follow-up, using unadjusted and adjusted linear regression.Key resultsThe average number of strategies taken up from baseline to follow-up was 1.6 (SE = 0.06); approximately one-quarter (25.3%) of hospitals took up at least three new strategies. Hospitals that adopted the strategy of routinely discharging patients with a follow-up appointment already scheduled experienced significant reductions in RSRR (reduction of 0.63 percentage point, p value < 0.05). Hospitals that took up three or more strategies had significantly greater reductions in RSRR compared to hospitals that took up only zero to two strategies (reduction of 1.29 versus 0.57 percentage point, p value < 0.05). Among the 117 hospitals that took up three or more strategies, 93 unique combinations of strategies were used.ConclusionsAlthough most individual strategies were not associated with RSRR reduction, hospitals that took up any three or more strategies showed significantly greater reduction in RSRR compared to hospitals that took up fewer than three strategies.
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Project description:ObjectiveTo examine the relationship between community factors and hospital readmission rates.Data sources/study settingWe examined all hospitals with publicly reported 30-day readmission rates for patients discharged during July 1, 2007, to June 30, 2010, with acute myocardial infarction (AMI), heart failure (HF), or pneumonia (PN). We linked these to publicly available county data from the Area Resource File, the Census, Nursing Home Compare, and the Neilsen PopFacts datasets.Study designWe used hierarchical linear models to assess the effect of county demographic, access to care, and nursing home quality characteristics on the pooled 30-day risk-standardized readmission rate.Data collection/extraction methodsNot applicable.Principal findingsThe study sample included 4,073 hospitals. Fifty-eight percent of national variation in hospital readmission rates was explained by the county in which the hospital was located. In multivariable analysis, a number of county characteristics were found to be independently associated with higher readmission rates, the strongest associations being for measures of access to care. These county characteristics explained almost half of the total variation across counties.ConclusionsCommunity factors, as measured by county characteristics, explain a substantial amount of variation in hospital readmission rates.
| S-EPMC4319869 | biostudies-literature
Project description:ImportanceThe Affordable Care Act has led to US national reductions in hospital 30-day readmission rates for heart failure (HF), acute myocardial infarction (AMI), and pneumonia. Whether readmission reductions have had the unintended consequence of increasing mortality after hospitalization is unknown.ObjectiveTo examine the correlation of paired trends in hospital 30-day readmission rates and hospital 30-day mortality rates after discharge.Design, setting, and participantsRetrospective study of Medicare fee-for-service beneficiaries aged 65 years or older hospitalized with HF, AMI, or pneumonia from January 1, 2008, through December 31, 2014.ExposureThirty-day risk-adjusted readmission rate (RARR).Main outcomes and measuresThirty-day RARRs and 30-day risk-adjusted mortality rates (RAMRs) after discharge were calculated for each condition in each month at each hospital in 2008 through 2014. Monthly trends in each hospital's 30-day RARRs and 30-day RAMRs after discharge were examined for each condition. The weighted Pearson correlation coefficient was calculated for hospitals' paired monthly trends in 30-day RARRs and 30-day RAMRs after discharge for each condition.ResultsIn 2008 through 2014, 2 962 554 hospitalizations for HF, 1 229 939 for AMI, and 2 544 530 for pneumonia were identified at 5016, 4772, and 5057 hospitals, respectively. In January 2008, mean hospital 30-day RARRs and 30-day RAMRs after discharge were 24.6% and 8.4% for HF, 19.3% and 7.6% for AMI, and 18.3% and 8.5% for pneumonia. Hospital 30-day RARRs declined in the aggregate across hospitals from 2008 through 2014; monthly changes in RARRs were -0.053% (95% CI, -0.055% to -0.051%) for HF, -0.044% (95% CI, -0.047% to -0.041%) for AMI, and -0.033% (95% CI, -0.035% to -0.031%) for pneumonia. In contrast, monthly aggregate changes across hospitals in hospital 30-day RAMRs after discharge varied by condition: HF, 0.008% (95% CI, 0.007% to 0.010%); AMI, -0.003% (95% CI, -0.005% to -0.001%); and pneumonia, 0.001% (95% CI, -0.001% to 0.003%). However, correlation coefficients in hospitals' paired monthly changes in 30-day RARRs and 30-day RAMRs after discharge were weakly positive: HF, 0.066 (95% CI, 0.036 to 0.096); AMI, 0.067 (95% CI, 0.027 to 0.106); and pneumonia, 0.108 (95% CI, 0.079 to 0.137). Findings were similar in secondary analyses, including with alternate definitions of hospital mortality.Conclusions and relevanceAmong Medicare fee-for-service beneficiaries hospitalized for heart failure, acute myocardial infarction, or pneumonia, reductions in hospital 30-day readmission rates were weakly but significantly correlated with reductions in hospital 30-day mortality rates after discharge. These findings do not support increasing postdischarge mortality related to reducing hospital readmissions.
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Project description:Healthcare-associated infections (HAIs) pose a significant burden to patient safety. Institutions can implement hospital infection control (HIC) measures to reduce the impact of HAIs. Since patients can carry pathogens between institutions, there is an economic incentive for hospitals to free ride on the HIC investments of other facilities. Subsidies for infection control by public health authorities could encourage regional spending on HIC. We develop coupled mathematical models of epidemiology and hospital behavior in a game-theoretic framework to investigate how hospitals may change spending behavior in response to subsidies. We demonstrate that under a limited budget, a dollar-for-dollar matching grant outperforms both a fixed-amount subsidy and a subsidy on uninfected patients in reducing the number of HAIs in a single institution. Additionally, when multiple hospitals serve a community, funding priority should go to the hospital with a lower transmission rate. Overall, subsidies incentivize HIC spending and reduce the overall prevalence of HAIs.
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Project description:Safety-net and teaching hospitals are somewhat more likely to be penalized for excess readmissions, but the association of other hospital characteristics with readmission rates is uncertain and may have relevance for hospital-centered interventions.To examine the independent association of 8 hospital characteristics with hospital-wide 30-day risk-standardized readmission rate (RSRR).This is a retrospective cross-sectional multivariable analysis.US hospitals.Centers for Medicare and Medicaid Services specification of hospital-wide RSRR from July 1, 2013 through June 30, 2014 with race and Medicaid dual-eligibility added.We included 6,789,839 admissions to 4474 hospitals of Medicare fee-for-service beneficiaries aged over 64 years. In multivariable analyses, there was regional variation: hospitals in the mid-Atlantic region had the highest RSRRs [0.98 percentage points higher than hospitals in the Mountain region; 95% confidence interval (CI), 0.84-1.12]. For-profit hospitals had an average RSRR 0.38 percentage points (95% CI, 0.24-0.53) higher than public hospitals. Both urban and rural hospitals had higher RSRRs than those in medium metropolitan areas. Hospitals without advanced cardiac surgery capability had an average RSRR 0.27 percentage points (95% CI, 0.18-0.36) higher than those with. The ratio of registered nurses per hospital bed was not associated with RSRR. Variability in RSRRs among hospitals of similar type was much larger than aggregate differences between types of hospitals.Overall, larger, urban, academic facilities had modestly higher RSRRs than smaller, suburban, community hospitals, although there was a wide range of performance. The strong regional effect suggests that local practice patterns are an important influence. Disproportionately high readmission rates at for-profit hospitals may highlight the role of financial incentives favoring utilization.
| S-EPMC5426655 | biostudies-literature
Project description:Medicare penalizes hospitals with higher than expected readmission rates by up to 3% of annual inpatient payments. Expected rates are adjusted only for patients' age, sex, discharge diagnosis, and recent diagnoses.To assess the extent to which a comprehensive set of patient characteristics accounts for differences in hospital readmission rates.Using survey data from the nationally representative Health and Retirement Study (HRS) and linked Medicare claims for HRS participants enrolled in Medicare who were hospitalized from 2009 to 2012 (n = 8067 admissions), we assessed 29 patient characteristics from survey data and claims as potential predictors of 30-day readmission when added to standard Medicare adjustments of hospital readmission rates. We then compared the distribution of these characteristics between participants admitted to hospitals with higher vs lower hospital-wide readmission rates reported by Medicare. Finally, we estimated differences in the probability of readmission between these groups of participants before vs after adjusting for the additional patient characteristics.All-cause readmission within 30 days of discharge.Of the additional 29 patient characteristics assessed, 22 significantly predicted readmission beyond standard adjustments, and 17 of these were distributed differently between hospitals in the highest vs lowest quintiles of publicly reported hospital-wide readmission rates (P ? .04 for all comparisons). Almost all of these differences (16 of 17) indicated that participants admitted to hospitals in the highest quintile of readmission rates were more likely to have characteristics that were associated with a higher probability of readmission. The difference in the probability of readmission between participants admitted to hospitals in the highest vs lowest quintile of hospital-wide readmission rates was reduced by 48% from 4.41 percentage points with standard adjustments used by Medicare to 2.29 percentage points after adjustment for all patient characteristics assessed (reduction in difference: -2.12; 95% CI, -3.33 to -0.67; P =?.003).Patient characteristics not included in Medicare's current risk-adjustment methods explained much of the difference in readmission risk between patients admitted to hospitals with higher vs lower readmission rates. Hospitals with high readmission rates may be penalized to a large extent based on the patients they serve.
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Project description:Addressing social determinants of health may help hospitals improve population health and outcomes that are tied to financial incentives, such as readmission rates. Whether this strategy is effective remains unknown. The authors measure the association between nonprofit hospital spending on their community's social needs and Medicare readmission rates. This is a retrospective cohort study (July 2013 to June 2014) that combines Internal Revenue Service tax reports of community benefit spending by private, acute care, nonprofit hospitals with Medicare readmissions data for residents of their surrounding community, the hospital's zip code. Total community benefit spending and 2 of the largest subsets of spending-health care-related and community-directed spending-were measured and normalized as the proportion of each hospital's total expenditure. Associations between quintiles of community benefit spending and Medicare readmission rates were measured using discharge-level multivariate linear regression, adjusting for patient, hospital, community characteristics, and local public health department spending. The sample consisted of 1405 nonprofit hospitals with 341,913 discharges. Associations between readmission rates and total community benefit spending and the health care-related subset were not statistically significant. Discharges from hospitals in the upper quintiles of community-directed spending were associated with lower readmission rates by 0.82 to 1.21 absolute percentage points (P?=?0.01 to <0.001) compared to the lowest quintile. The magnitude of associations between community-directed spending and readmissions was larger for preventable readmissions and smaller when including beneficiaries beyond the hospital's zip code. These associations suggest that community-directed spending may be associated with better health care outcomes.
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Project description:BackgroundLowering hospital readmission rates has become a primary target for the Centers for Medicare & Medicaid Services, but studies of the relationship between adherence to the recommended hospital care processes and readmission rates have provided inconsistent and inconclusive results.ObjectiveTo examine the association between hospital performance on Medicare's Hospital Compare process quality measures and 30-day readmission rates for patients with acute myocardial infarction (AMI), heart failure and pneumonia, and for those undergoing major surgery.Design, setting and participantsWe assessed hospital performance on process measures using the 2007 Hospital Inpatient Quality Reporting Program. The process measures for each condition were aggregated in two separate measures: Overall Measure (OM) and Appropriate Care Measure (ACM) scores. Readmission rates were calculated using Medicare claims.Main outcome measureRisk-standardized 30-day all-cause readmission rate was calculated as the ratio of predicted to expected rate standardized by the overall mean readmission rate. We calculated predicted readmission rate using hierarchical generalized linear models and adjusting for patient-level factors.ResultsAmong patients aged ≥ 66 years, the median OM score ranged from 79.4 % for abdominal surgery to 95.7 % for AMI, and the median ACM scores ranged from 45.8 % for abdominal surgery to 87.9 % for AMI. We observed a statistically significant, but weak, correlation between performance scores and readmission rates for pneumonia (correlation coefficient R = 0.07), AMI (R = 0.10), and orthopedic surgery (R = 0.06). The difference in the mean readmission rate between hospitals in the 1st and 4th quartiles of process measure performance was statistically significant only for AMI (0.25 percentage points) and pneumonia (0.31 percentage points). Performance on process measures explained less than 1 % of hospital-level variation in readmission rates.ConclusionsHospitals with greater adherence to recommended care processes did not achieve meaningfully better 30-day hospital readmission rates compared to those with lower levels of performance.
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Project description:Tracheostomy is frequently performed in patients with severe ischemic stroke, intracerebral hemorrhage, or subarachnoid hemorrhage. Little is known about readmission rates among stroke patients who undergo mechanical ventilation.We used previously validated International Classification of Diseases, Ninth Edition-Clinical Modification codes and data on all discharges from nonfederal acute care hospitals in 3 states. We compared readmission rates among mechanically ventilated patients with stroke who were discharged with or without a tracheostomy.Among 39,881 patients who underwent mechanical ventilation during the index stroke hospitalization and survived to discharge, 10,690 (26.8%; 95% confidence interval, 26.4%-27.2%) underwent tracheostomy. During a mean follow-up period of 3.4 (±2.0) years, the overall incidence rate of readmissions was 4.25 (95% confidence interval, 4.22-4.28) per 100 patients per 30 days. The rate of any readmissions within 30 days was 26.9% among patients with tracheostomy compared with 22.5% among those without a tracheostomy (absolute risk difference, 4.4%; 95% confidence interval, 3.5%-5.4%; P<0.001). After adjustment for potentially confounding variables, tracheostomy was associated with a slightly increased readmission rate (incidence rate ratio, 1.07; 95% confidence interval, 1.03-1.11).Approximately one quarter of mechanically ventilated patients with stroke who survive to discharge are readmitted to the hospital within 30 days. Readmission rates are significantly higher in patients with stroke who undergo tracheostomy, but the difference is not clinically meaningful. Thirty-day readmission rates among mechanically ventilated patients with stroke are similar to Medicare beneficiaries hospitalized with major medical diseases such as pneumonia.
| S-EPMC4589479 | biostudies-literature
Project description:ObjectiveTo assess variation among hospitals on pediatric readmission and revisit rates and to determine the number of high- and low-performing hospitals.MethodsIn a retrospective analysis using the State Inpatient and Emergency Department Databases from the Healthcare Cost and Utilization Project with revisit linkages available, we identified pediatric (ages 1-20 years) visits with 1 of 7 common inpatient pediatric conditions (asthma, dehydration, pneumonia, appendicitis, skin infections, mood disorders, and epilepsy). For each condition, we calculated rates of all-cause readmissions and rates of revisits (readmission or presentation to the emergency department) within 30 and 60 days of discharge. We used mixed logistic models to estimate hospital-level risk-standardized 30-day revisit rates and to identify hospitals that had performance statistically different from the group mean.ResultsThirty-day readmission rates were low (<10.0%) for all conditions. Thirty-day rates of revisit to the inpatient or emergency department setting ranged from 6.2% (appendicitis) to 11.0% (mood disorders). Study hospitals (n = 958) had low condition-specific visit volumes (37.0%-82.8% of hospitals had <25 visits). The only condition with >1% of hospitals labeled as different from the mean on 30-day risk-standardized revisit rates was mood disorders (4.2% of hospitals [n = 15], range of hospital performance 6.3%-15.9%).ConclusionsWe found that when comparing hospitals' performances to the average, few hospitals that care for children are identified as high- or low-performers for revisits, even for common pediatric diagnoses, likely due to low hospital volumes. This limits the usefulness of condition-specific readmission or revisit measures in pediatric quality measurement.
| S-EPMC3876751 | biostudies-literature