Readmission rates in not-for-profit vs. proprietary hospitals before and after the hospital readmission reduction program implementation

Immediate outcome assessment of the rapid response team of home health care services at King Abdulaziz Medical City in Riyadh

Background

Paediatrics rapid response team (RRT) is a newly developed service under paediatrics home health care (HHC) programme which is a standby visiting team that responds to non-critical emergency calls. The current study aimed to compare the total emergency visits and hospital admissions before and after implementation of RRT project.

Method

A retrospective chart review was conducted from December 2018 to December 2020. Paediatric patients registered under the home health care (HHC) programme were the target population. The admission and hospitalization rates were assessed before and after the implantation of an RRT. The variables related to patient profile were assessed to explore the association between hospitalization and admission.

Result

Data for 117 patients and a total of 114 calls attended under HHC covered by RRT were analysed. In the first year after the implementation of RRT, the mean number of ER visits per patient per year was reduced from 4.78 ± 6.10 to 3.93 ± 4.12 with (P value, 0.06). Also, a slight decrease in the mean number of admissions from 3.74 ± 4.43 to a mean of 3.46 ± 4.1 with (P value, 0.29). Follow-up after receiving an RRT call for an initial complaint was statistically significant in reducing both ER visits and hospital admissions within 7 days with a P value of 0.03 and 0.04, respectively.

Conclusion

The RRT was effective in decreasing the ER visits and hospital admissions for a very special group of patients. Additionally, the emplacement of proper triaging code at the time of attending to patients helped in reducing unnecessary ER visit and hospital admission.

Does Geographic Location Affect the Quality of Care? The Difference in Readmission Rates Between the Border and Non-Border Hospitals in Texas

Purpose

Materials and Methods

Results

Conclusion

Hospital Readmissions Reduction Program and Post-Acute Care: Implications for Service Delivery and 30-Day Hospital Readmission

OBJECTIVES

Examine whether the introduction of the Hospital Readmissions Reduction Program (HRRP) is associated with changes in post-acute care (PAC) use and 30-day readmission.

DESIGN

A retrospective cohort study examined data prepassage, preimplementation, and postimplementation of the HRRP.

SETTING AND PARTICIPANTS

In total, 7,851,430 Medicare beneficiaries discharged from 5116 acute hospitals to PAC settings including inpatient rehabilitation, skilled nursing, home health, or a long-term care hospital during 2007‒2015. We examined HRRP-targeted conditions (acute myocardial infarction, heart failure, and pneumonia) and nontargeted conditions (ischemic stroke, total hip arthroplasty/total knee arthroplasty, and hip/femur fractures).

MEASURES

The hospital-level of quarterly PAC use and the association with 30-day risk-standardized readmission rates. Outcomes were calculated for HRRP-targeted and nontargeted conditions/diagnoses across 3 phases of HRRP implementation.

RESULTS

An increase in quarterly PAC use was significantly (P < .001) associated with a decrease in 30-day risk-standardized readmission rates for acute myocardial infarction, heart failure, and hip/femur fracture. In contrast, an increase in quarterly PAC use was significantly associated with an increase in readmission rate for total hip arthroplasty/total knee arthroplasty (P < 001). PAC quarterly use and readmission rates varied significantly during implementation periods for HRRP- targeted and nontargeted conditions.

CONCLUSIONS AND IMPLICATIONS

The impact on readmission after PAC for selected impairment groups may be mediated by the type of PAC services received and whether the diagnoses is included in the HRRP. Additional research is necessary to determine if a reduction in readmission is associated with inclusion in the HRRP or is a side effect related to diagnostic group and/or type of PAC services received.

The Effect of Centers for Medicare and Medicaid's Inpatient Psychiatric Facility Quality Reporting Program on the Use of Restraint and Seclusion

BACKGROUND

Patients in inpatient psychiatry settings are uniquely vulnerable to harm. As sources of harm, research and policy efforts have specifically focused on minimizing and eliminating restraint and seclusion. The Centers for Medicare and Medicaid's Inpatient Psychiatric Facility Quality Reporting (IPFQR) program attempts to systematically measure and reduce restraint and seclusion. We evaluated facilities' response to the IPFQR program and differences by ownership, hypothesizing that facilities reporting these measures for the first time will show a greater reduction and that ownership will moderate this effect.

METHODS

Using a difference-in-differences design and exploiting variation among facilities that previously reported on these measures to The Joint Commission, we examined the effect of the IPFQR public reporting program on the use and duration of restraint and seclusion from the end of 2012 through 2017.

RESULTS

There were a total of 9705 observations of facilities among 1841 unique facilities. Results suggest the IPFQR program reduced duration of restraint by 48.96% [95% confidence interval (95% CI), 16.69%-68.73%] and seclusion by 53.54% (95% CI, 19.71%-73.12%). There was no change in odds of zero restraint and, among for-profits only, a decrease of 36.89% (95% CI, 9.32%-56.07%) in the odds of zero seclusion.

CONCLUSIONS

This is the first examination of the effect of the IPFQR program on restraint and seclusion, suggesting the program was successful in reducing their use. We did not find support for ownership moderating this effect. Additional research is needed to understand mechanisms of response and the impact of the program on nontargeted aspects of quality.

Insurance patterns and instability from 2006 to 2016

Background

There is a rich literature on insurance coverage and its impacts on health care. Many recent studies have examined the impacts of the Affordable Care Act (ACA) and found that it had positive effects on health insurance coverage and health care usage. Most of the literature, however, has focused on insurance coverage at a single point in time, while research on insurance instability is underrepresented, even though it could significantly impact health outcomes. The aim of this study is to examine changes and implications of insurance instability among nonelderly adults from 2006 to 2016, covering the Great Recession and post-ACA periods.

Methods

Using 2006-to-2016 Medical Expenditure Panel Survey data, we identify seven insurance patterns and analyze them by race/ethnicity, age, geography, income, and medical conditions. We then use multivariable linear models to analyze the relationship between insurance instability and health care status, access, and utilization. Logistic, Poisson and nonlinear models test the robustness of our results.

Results

The post-ACA period 2015–2016 saw the lowest ever-uninsured rate (25.68% or 67.91 million). The largest decrease in insurance instability was among adults aged 19–25, low-income families, Hispanics, the western population, and the healthy population. Like the always-uninsured, those with other insurance gaps experienced a lack of access to care and decreased preventive care and other services.

Conclusions

Despite the post-ACA instability reduction, over 25% of the U.S. population continued to have insurance gaps over a two-year period. Disparities continued to exist between income groups, race/ethnicities, and regions. Repealing ACA could exacerbate insurance instability and disparities between different groups, which in turn could lead to adverse health outcomes.

Impact of the Medicare hospital readmissions reduction program on vulnerable populations

BACKGROUND

The Hospital Readmissions Reduction Program (HRRP) was established by the 2010 Patient Protection and Affordable Care Act (ACA) in an effort to reduce excess hospital readmissions, lower health care costs, and improve patient safety and outcomes. Although studies have examined the policy's overall impacts and differences by hospital types, research is limited on its effects for different types of vulnerable populations. The aim of this study was to analyze the impact of the HRRP on readmissions for three targeted conditions (acute myocardial infarction, heart failure, and pneumonia) among four types of vulnerable populations, including low-income patients, patients served by hospitals that serve a high percentage of low-income or Medicaid patients, and high-risk patients at the highest quartile of the Elixhauser comorbidity index score.

METHODS

Data on patient and hospital information came from the Nationwide Readmission Database (NRD), which contained all discharges from community hospitals in 27 states during 2010-2014. Using difference-in-difference (DD) models, linear probability regressions were conducted for the entire sample and sub-samples of patients and hospitals in order to isolate the effect of the HRRP on vulnerable populations. Multiple combinations of treatment and control groups and triple difference (DDD) methods were used for testing the robustness of the results. All models controlled for the patient and hospital characteristics.

RESULTS

There have been statistically significant reductions in readmission rates overall as well as for vulnerable populations, especially for acute myocardial infarction patients in hospitals serving the largest percentage of low-income patients and high-risk patients. There is also evidence of spillover effects for non-targeted conditions among Medicare patients compared to privately insured patients.

CONCLUSIONS

The HRRP appears to have created the right incentives for reducing readmissions not only overall but also for vulnerable populations, accruing societal benefits in addition to previously found reductions in costs. As the reduction in the rate of readmissions is not consistent across patient and hospital groups, there could be benefits to adjusting the policy according to the socioeconomic status of a hospital's patients and neighborhood.

Causes, Predictors, and Trends of Unplanned Readmissions after Elective Endovascular Embolization of Cerebral Aneurysms

BACKGROUND

30- and 90-day readmissions (dRA) are being increasingly scrutinized as quality metrics for hospital and provider performances. Little information regarding risk factors for readmission after elective endovascular treatment (EVT) of an unruptured cerebral aneurysm (UCA) is available.

METHODS

The Nationwide Readmissions Database was used to identify patients who underwent elective endovascular embolization of an unruptured aneurysm between 2010 and 2014. The primary outcomes of interest were unplanned readmissions occurring within 30 or 90 days of discharge. Binary logistic regressions were used to identify variables related to patients' demographics, comorbidities, and index hospital admission that were associated with 30dRA and 90dRA.

RESULTS

A total of 8588 patients met the inclusion criteria for 30dRA analysis and 7289 patients were eligible for 90dRA analysis. The 5-year 30dRA and 90dRA readmission rates were 7.1% and 13.5%, respectively. The annual incidences of 30dRAs and 90dRAs between 2010 and 2014 decreased significantly (pooled odds ratio (OR) for 30dRA: .874, 95% confidence interval (CI) .765-.998; pooled OR for 90dRA: .841, 95% CI .755-.938). Patients in higher income quartiles experienced decreased odds of 30dRA and 90dRA. Nonroutine disposition following the index admission and greater comorbidity burdens were associated with higher likelihoods of both 30dRA and 90dRA. The presence of pulmonary or cardiac complications was associated with increased odds of 90dRA.

CONCLUSION

Readmission rates after elective EVT of UCAs decreased between 2010 and 2014. We identified several novel risk factors for both 30dRAs and 90dRAs that can be used to identify patients who are at highest risk of readmission.

Individual and Organizational Factors Associated With Hospital Readmission Rates: Evidence From a U.S. National Sample

Objective: Hospital readmission rate is an important indicator for assessing quality of care in the acute and postacute settings. Identifying factors that increase risk for hospital readmissions can aid in the recognition of potential targets for quality improvement efforts. The main objective of this brief report was to examine the factors that predict increased risk of 30-day readmissions. Method: We analyzed data from the 2013 National Readmission Database (NRD). Results: The main factors that predicted increased risk of 30-day readmission were number of chronic conditions, severity of illness, mortality risk, and hospital ownership. Unexpectedly, discharge from a for-profit hospital was associated with greater risk for hospital readmission in the United States. Discussion and Conclusion: These findings suggest that patients with severe physical illness and multiple chronic conditions should be the primary targets for hospital transitional care interventions to help reduce the rate of unnecessary hospital readmissions.

A Nationwide Analysis of 30-Day and 90-Day Readmissions After Elective Cerebral Aneurysm Clipping in the United States: Causes, Predictors, and Trends

BACKGROUND

Thirty-day readmissions (30dRAs) and 90-day readmissions (90dRAs) are being increasingly scrutinized as quality metrics for hospital and provider performances. Little information regarding risk factors for 30dRA and 90dRA after elective cerebral aneurysm clipping (CAC) of unruptured cerebral aneurysms is available. We sought to characterize risk factors with a nationally representative administrative database.

METHODS

The Nationwide Readmissions Database was used to identify patients who underwent elective CAC between 2010 and 2014. The outcomes of interest were unplanned readmissions occurring within 30 or 90 days of discharge. Binary logistic regression was used to identify variables related to patients' demographics, comorbidities, and index hospital admission that were associated with readmission. A Cochran-Mantel-Haenszel test was used to evaluate for changes in annual readmission rates.

RESULTS

A total of 1123 patients met the inclusion criteria for 30dRA analysis and 946 patients were eligible for 90dRA analysis. The 5-year 30dRA and 90dRA readmission rates were 9.1% and 14.9%, respectively. The annual rate of readmission between 2010 and 2014 did not change. Greater Charlson Comorbidity Index (odds ratio [OR], 2.68; 95% confidence interval [CI], 1.14-6.28) and nonroutine discharge after the index admission (OR, 1.81; 95% CI, 1.04-3.14) were associated with greater odds of 30dRA. Charlson Comorbidity Index (OR, 3.45; 95% CI, 1.57-7.56) and treatment at a metropolitan teaching hospital (OR, 2.21; 95% CI, 1.06-4.60) were associated with increased odds of 90dRA. Wound infection was the most common reason for readmission.

CONCLUSIONS

Readmission rates after elective CAC remained unchanged between 2010 and 2014, suggesting that improved methods for reducing unplanned readmissions after CAC are needed.

Readmission after pancreatic resection: causes, costs and cost-effectiveness analysis of high versus low quality hospitals using the Nationwide Readmission Database

BACKGROUND

Objectives were to determine the causes of readmission and assess the cost-effectiveness of high (HQ) and low quality (LQ) hospitals in performing pancreatic resection, by using readmission rates as the measure of quality.

METHODS

We identified 53,572 pancreatic resection cases from National Readmission Database from 2010 through 2014. Hospitals were risk adjusted and ranked based on readmission. Top 20% HQ hospitals having the lowest readmission rates were compared to the bottom 20% LQ hospitals with the highest readmission rates.

RESULTS

The 90-day readmission rate was 27.2% (HQ: 25.7%, LQ: 30.9%, p < 0.001). Compared to LQ, HQ hospitals had lower mortality (2.1% vs 10.2%, p < 0.001) and major complication (10.5% vs 53%, p < 0.001). Major complication during index operation was a major predictor of readmission (RR: 1.6, 95% CI: 1.6-1.7, p < 0.001). The optimal cut point of hospital volume associated with low mortality was 70 or more cases/year. Per year of survival benefit at HQ hospitals, the costs were lower by $9,293 with cost-savings of $6.98 million/year.

CONCLUSION

HQ hospitals were cost-effective at performing pancreatic resection and achieved substantial cost-savings by avoiding major complications during index operation and having lower rates of readmissions. Hospital readmission rate is a strong marker of quality of care.