Patient Readmission Rates For All Insurance Types After Implementation Of The Hospital Readmissions Reduction Program

Improvements in Transitional Care Among Medicaid-Insured Patients With Serious Mental Illness

BACKGROUND

The Thrive program is an evidenced-based care model for Medicaid-insured adults in the hospital-to-home transition. A substantial portion of Thrive participants live with serious mental illness (SMI), yet Thrive's efficacy has not been tested among these patients.

PURPOSE

To compare 30-day postdischarge outcomes between Thrive participants with and without SMI and explore Thrive's appropriateness and acceptability among participants with SMI.

METHODS

We conducted a sequential explanatory mixed-methods study of 252 (62 with SMI) Thrive participants discharged from an academic medical center from February 2021 to August 2023. Interviews of participants with SMI were analyzed using rapid qualitative analysis.

RESULTS

Participants with and without SMI experienced similar rates of 30-day readmissions, emergency room visits, and postdischarge follow-up visits, with these differences being nonsignificant. Participants with SMI were highly satisfied with Thrive's care coordination and attention to social needs, yet participants suggested stronger connections to behavioral health care.

CONCLUSIONS

Participants with and without SMI benefit equitably from Thrive.

Impact of Insurance on Readmission Rates, Healthcare Expenditures, and Length of Hospital Stay among Patients with Chronic Ambulatory Care Sensitive Conditions in China

Background: The disparities in healthcare access due to varying insurance coverage significantly impact hospital outcomes, yet what is unclear is the role of insurance in providing care once the patient is in the hospital for a preventable admission, particularly in a weak gatekeeping environment. This study aimed to investigate the association between insurance types and readmission rates, healthcare expenditures, and length of hospital stay among patients with chronic ambulatory care sensitive conditions (ACSCs) in China. Methods: This retrospective observational study utilized hospitalization data collected from the Nanhai District, Foshan City, between 2016 and 2020. Generalized linear models (GLMs) were employed to analyze the relationship between medical insurance types and readmission rates, lengths of hospital stay, total medical expenses, out-of-pocket expenses, and insurance-covered expenses. Results: A total of 185,384 records were included. Among these, the participants covered by urban employee basic medical insurance (UEBMI) with 44,415 records and urban and rural resident basic medical insurance (URRBMI) with 80,752 records generally experienced more favorable outcomes compared to self-pay patients. Specifically, they had lower readmission rates (OR = 0.57, 95% CI: 0.36 to 0.90; OR = 0.59, 95% CI: 0.42 to 0.84) and reduced out-of-pocket expenses (β = -0.54, 95% CI: -0.94 to -0.14; β = -0.41, 95% CI: -0.78 to -0.05). However, they also experienced slightly longer lengths of hospital stay (IRR = 1.08, 95% CI: 1.03 to 1.14; IRR = 1.11, 95% CI: 1.04 to 1.18) and higher total medical expenses (β = 0.26, 95% CI: 0.09 to 0.44; β = 0.25, 95% CI: 0.10 to 0.40). Conclusions: This study found that different types of health insurance were associated with varying clinical outcomes among patients with chronic ambulatory care sensitive conditions (ACSCs) in China. Since the hospitalization of these patients was initially avoidable, disparities in readmission rates, lengths of hospital stay, and medical expenses among avoidable inpatient cases exacerbated the health gap between different insurance types. Addressing the disparities among different types of insurance can help reduce unplanned hospitalizations and promote health equity.

Prevalence of Healthcare Barriers Among US Adults With Chronic Liver Disease Compared to Other Chronic Diseases

Background and Aims

The extent of healthcare barriers and its association with acute care use among adults with chronic liver disease (CLD) relative to other chronic conditions remains understudied. We compared the probability of barriers and recurrent acute care use among persons with CLD and persons with chronic obstructive pulmonary disease (COPD) and/or cardiovascular disease (CVD).

Methods

We assembled a population-based, cross-sectional study using pooled self-reported National Health Interview Survey data (2011-2017) among community-dwelling persons. Probability of barriers by disease group (CLD vs COPD/CVD) was assessed using hurdle negative binomial regression.

Results

The sample included 47,037 adults (5062 with CLD, 41,975 with COPD/CVD). The CLD group was younger (median age 55 vs 62 years) and included more Hispanics (17.5% vs 8.6%) and persons with poverty (20.1% vs 15.3%) than the COPD/CVD group. More respondents with CLD vs COPD/CVD reported barriers (44.7% vs 34.4%), including unaffordability (27.5% vs 18.8%), transportation-related (6.1% vs 4.1%), and organizational barriers at entry to (17.6% vs 13.0%) and within healthcare (19.5% vs 14.2%). While adults with CLD were more likely to experience at least 1 barrier (adjusted incident rate ratio, 1.12 [1.01-1.24], P = .03), they were not associated with more (1.05 [1.00-2.71], P = .06). Probability of recurrent acute care use was associated with more healthcare barriers.

Conclusion

Findings from this nationally representative sample of over 43 million US adults reveal that persons with CLD have increased probability of healthcare barriers, likely related to their higher prevalence of socioeconomic vulnerabilities compared to persons with COPD/CVD. CLD warrants attention as a priority condition in public policies that direct resources towards high-risk populations.

Disparities in 30-Day Readmission Between Medicare/Medicaid and Private Insurance Among Patients With Heart Failure Screened for Cognitive Impairment

BACKGROUND

Racial disparities exist among patients with heart failure (HF). HF is often comorbid with cognitive impairment. Appropriate self-care can prevent HF hospital readmissions but requires access to resources through insurance. Racial differences exist between insurance types, and this may influence the disparity between races and patients with HF and cognitive impairment.

OBJECTIVE

The objectives of this study were to examine the relationships between insurance type and self-care stratified by race and to assess for differences in time-to-30-day readmission among patients with HF with cognitive impairment.

METHODS

This is a secondary analysis of data collected among hospitalized patients with HF with cognitive impairment. Patients completed surveys on self-care (Self-Care of Heart Failure Index), HF knowledge (Dutch Heart Failure Knowledge Scale), depression (Geriatric Depression Scale), and social support (Enhancing Recovery in Coronary Heart Disease Social Support Inventory). Socioeconomic data were collected. Linear models were created to examine the relationships between insurance type and self-care by race. Kaplan-Meier curves and Cox regression were used to assess readmission.

RESULTS

The sample of 125 patients with HF with cognitive impairment was predominantly Black (68%, n = 85) and male (53%, n = 66). The sample had either Medicare/Medicaid (62%, n = 78) or private insurance (38%, n = 47). Black patients with HF with cognitive impairment and private insurance reported higher self-care confidence compared with Black patients with HF with cognitive impairment and Medicare/Medicaid ( P < .05). Medicare/Medicaid was associated with a higher frequency of 30-day readmission and a faster time-to-readmission.

CONCLUSIONS

Patients with HF with cognitive impairment and Medicare/Medicaid insurance reported lower self-care confidence and more likely to be readmitted within 30 days.

Multifactorial risk factors for hospital readmissions among patients with symptoms of advanced heart failure

AIMS

Economic burden of heart failure is attributed to hospital readmissions. Previous studies assessing risk factors for readmissions have focused on single group of risk factors, were limited to 30-day readmissions, or did not account for competing risk of mortality. This study investigates the biological, socio-economic, and behavioural risk factors predicting hospital readmissions while accounting for the competing risk of mortality.

METHODS AND RESULTS

In this prospective cohort study, we recruited 250 patients hospitalized with symptoms of advanced heart failure [New York Heart Association (NYHA) Class III and IV] between July 2017 and April 2019. We analysed their baseline survey data and their hospitalization records over the next 4.5 years (July 2017 to January 2022). We used a joint-frailty model to determine the multifactorial risk factors for all-cause and unplanned hospital readmissions and mortality. At the time of recruitment, patients' mean (SD) age was 66 (12) years, majority being male (72%) and NYHA class IV (68%) with reduced ejection fraction (72%). 87% of the patients had poor self-care behaviours, 51% had diabetes and 56% had weak grip strength. Within 2 years of a hospital admission, 74% of the patients had at least one readmission. Among all readmissions during follow-up, 68% were unplanned. Results from the multivariable regression analysis shows that the independent risk factors for hospital readmissions were biologic-weak grip strength [hazard ratio (95% CI): 1.59 (1.06, 2.13)], poor functional status [1.79 (0.98, 2.61)], diabetes [1.42 (0.97, 1.86)]; behavioural-poor self-care [1.66 (0.84, 2.49)], and socio-economic-preference for maximal life extension at high cost for those with high education [1.98 (1.17, 2.80)]. Risk factors for unplanned hospital readmissions were similar. A higher hospital readmission rate increased the risk of mortality [1.86 (1.23, 2.50)]. Other risk factors for mortality were biologic-weak grip strength [3.65 (0.57, 6.73)], diabetes [2.52 (0.62, 4.42)], socio-economic-lower education [2.45 (0.37, 4.53)], and being married [2.53 (0.37, 4.69)]. Having a private health insurance [0.40 (0.08, 0.73)] lowered the risk for mortality.

CONCLUSIONS

Risk factors for hospital readmissions and mortality are multifactorial. Many of these factors, such as weak grip strength, diabetes, poor self-care behaviours, are potentially modifiable and should be routinely assessed and managed in cardiac clinics and hospital admissions.

How to further develop quality competition in the German healthcare system? Results of a Delphi expert study

INTRODUCTION

Many international healthcare systems use quality competition to improve the quality of care. The corresponding instruments include quality measurement, public reporting, selective contracting, and pay for performance. The German healthcare system clearly shows that the possibilities are often limited in the status quo. Therefore, a need for practicable and evidence-based proposals are necessary to further the development of quality competition.

METHODS

We conducted a national analysis and an international comparison (Switzerland, Netherlands and USA) as a pre-study to derive recommendations. On this basis, we designed a Delphi study with a consensus objective. Experts from relevant stakeholder groups in the German healthcare system were selected using purposive sampling for this study.

RESULTS

The experts saw potential for quality improvement in the further development of quality competition. Quality measurement and public reporting were rated as empowering tools. There was mostly disagreement on whether quality competition should be further developed in a more regulatory or entrepreneur-based manner. However, there was a clear consensus that further development must be coordinated between the stakeholders, step-by-step and scientifically supported. In addition, the impulse should be supported by a legislatively introduced reform.

CONCLUSIONS

Finally, these empirically based recommendations highlight the need for a coordinated coexistence of a top-down and a bottom-up approach. The developed blueprint proposal serves as an impetus for practical considerations of implementation.

Predictors of 30-Day Readmission in Patients Hospitalized With Heart Failure as a Primary Versus Secondary Diagnosis

Short-term rehospitalizations are common, costly, and detrimental to patients with heart failure (HF). Current research and policy have focused primarily on 30-day readmissions for patients with HF as a primary diagnosis at index hospitalization, whereas a much larger population of patients are admitted with HF as a secondary diagnosis. This study aims to compare patients initially hospitalized for HF as either a primary or a secondary diagnosis, and to identify the most important factors in predicting 30-day readmission. Patients admitted with HF between 2014 and 2016 in the Nationwide Readmissions Database were included and divided into 2 cohorts: those admitted with a primary and secondary diagnosis of HF. Multivariable logistic regression was performed to predict 30-day readmission. Statistically significant predictors in multivariable logistic regression were used for dominance analysis to rank these factors by relative importance. Co-morbidities were the major driver of increased risk of 30-day readmission in both groups. Individual Elixhauser co-morbidities and the Elixhauser co-morbidity indexes were significantly associated with an increase in 30-day readmission. The 5 most important predictors of 30-day readmission according to dominance analysis were age, Elixhauser co-morbidity indexes of co-morbidity complications and readmission, number of diagnoses, and renal failure. These 5 factors accounted for 68% of the 30-day readmission risk. Measures of patient co-morbidities were among the strongest predictors of readmission risk. This study highlights the importance of expanding predictive models to include a broader set of clinical measures to create better-performing models of readmission risk for HF patients.

Post-Acute Care Outcomes of Cancer Patients <65 Reveal Disparities in Care Near the End of Life

Background: Post-acute care outcomes for patients with cancer <65 with multiple payers are largely unknown. Objective: Describe the population and outcomes of younger adults discharged to skilled nursing facility (SNF) and those discharged home or with home health care six months following hospitalization. Design: Descriptive cohort analysis. Setting/Subjects: Using a linkage between the Colorado All Payers Claims Database and the Colorado Central Cancer Registry, we studied patients <65 with stage III or IV advanced cancer between 2012 and 2017. Measurements: Receipt of cancer treatment, 30-day readmission, death, and hospice use. Groups of interest were compared by patient demographics and disease characteristics using chi-square tests. Logistic regression was used to describe unadjusted and adjusted outcome rates among discharge setting. Kaplan-Meier method was used to estimate survival by discharge destination. Results: Three percent of patients were discharged to SNF, 79.0% to home, and 18.0% to home health care. SNF discharges were less likely to receive cancer treatment. Among decedents, 39.0%, 51.0%, and 58.0% of SNF, home, and home health care discharges received hospice, respectively. Patients with Medicaid were more likely to be discharged to an SNF. Black/Hispanic patients were more likely to have Medicaid and received less radiation and hospice care, irrespective of discharge location. Those who were discharged to SNF were more likely to receive radiation compared to White patients. Conclusions: Younger patients with cancer discharged to SNF were unlikely to receive cancer treatment and hospice care before death. Racial disparities exist in cancer treatment receipt and hospice use warranting further investigation.

Personalized Postacute Hospitalization Recovery: A Novel Intervention to Improve Patient Experience and Reduce Cost

GOAL

Readmissions are a significant financial burden for payers. Cardiovascular-related discharges are particularly prone to readmission. Posthospital discharge support can impact patient recovery and probably reduce patient readmissions. This study aimed to address the underlying behavioral and psychosocial factors that can negatively affect patients after discharge.

METHODS

The study population was adult patients admitted to the hospital with a cardiovascular diagnosis who had a plan to discharge home. Those who consented to participate were randomized to intervention or control groups on a 1:1 basis. The intervention group received behavioral and emotional support, whereas the control group received usual care. Interventions included motivational interviewing, patient activation, empathetic communication, addressing mental health and substance use, and mindfulness.

PRINCIPAL FINDINGS

Observed total readmission costs were significantly lower in the intervention group than in the control group ($1.1 million vs. $2.0 million) as was the observed mean cost per readmitted patient ($44,052 vs. $91,278). The mean expected cost of readmission after adjustment for confounding variables was lower in the intervention group than in the control group ($8,094 vs. $9,882, p = .011).

PRACTICAL APPLICATIONS

Readmissions are a costly spend category. In this study, posthospital discharge support addressing the psychosocial factors contributing to patients' readmissions resulted in a lower total cost of care for those with a cardiovascular diagnosis. We describe an intervention that is reproducible and can be scaled broadly through technology to reduce readmission costs.

Disparities in 30-day readmission rates among Medicare enrollees with dementia

BACKGROUND

Readmissions contribute to excessive care costs and burden for people living with dementia. Assessments of racial disparities in readmissions among dementia populations are lacking, and the role of social and geographic risk factors such as individual-level exposure to greater neighborhood disadvantage is poorly understood. We examined the association between race and 30-day readmissions in a nationally representative sample of Black and non-Hispanic White individuals with dementia diagnoses.

METHODS

This retrospective cohort study used 100% Medicare fee-for-service claims from all 2014 hospitalizations nationwide among Medicare enrollees with dementia diagnosis linked to patient, stay, and hospital factors. The sample consisted of 1,523,142 hospital stays among 945,481 beneficiaries. The relationship between all cause 30-day readmissions and the explanatory variable of self-reported race (Black, non-Hispanic White) was examined via generalized estimating equations approach adjusting for patient, stay, and hospital-level characteristics to model 30-day readmission odds.

RESULTS

Black Medicare beneficiaries had 37% higher readmission odds compared to White beneficiaries (unadjusted OR 1.37, CI 1.35-1.39). This heightened readmission risk persisted after adjusting for geographic factors (OR 1.33, CI 1.31-1.34), social factors (OR 1.25, CI 1.23-1.27), hospital characteristics (OR 1.24, CI 1.23-1.26), stay-level factors (OR 1.22, CI 1.21-1.24), demographics (OR 1.21, CI 1.19-1.23), and comorbidities (OR 1.16, CI 1.14-1.17), suggesting racially-patterned disparities in care account for a portion of observed differences. Associations varied by individual-level exposure to neighborhood disadvantage such that the protective effect of living in a less disadvantaged neighborhood was associated with reduced readmissions for White but not Black beneficiaries. Conversely, among White beneficiaries, exposure to the most disadvantaged neighborhoods associated with greater readmission rates compared to White beneficiaries residing in less disadvantaged contexts.

CONCLUSIONS

There are significant racial and geographic disparities in 30-day readmission rates among Medicare beneficiaries with dementia diagnoses. Findings suggest distinct mechanisms underlying observed disparities differentially influence various subpopulations.

Independent Predictors and Causes of Thirty-Day Gastrointestinal Readmissions Following COVID-19-Related Hospitalizations: Analysis of the National Readmission Database

Background

The coronavirus disease 2019 (COVID-19) pandemic led to significant mortality and morbidity in the United States. The burden of COVID-19 was not limited to the respiratory tract alone but had significant extrapulmonary manifestations. We decided to examine the causes, predictors, and outcomes of gastrointestinal (GI)-related causes of 30-day readmission following index COVID-19 hospitalization.

Methods

We used the National Readmission Database (NRD) from 2020 to identify hospitalizations among adults with principal diagnosis of COVID-19. We identified GI-related hospitalizations within 30 days of index admission after excluding elective and traumatic admissions. We identified the top causes of GI-related readmission, and the outcomes of these hospitalizations. We used a multivariate Cox regression analysis to identify the independent predictors of readmission.

Results

Among 1,024,492 index hospitalizations with a primary diagnosis of COVID-19 in the 2020 NRD database, 644,903 were included in the 30-day readmission study. Of these 3,276 (0.5%) were readmitted in 30 days due to primary GI causes. The top five causes of readmissions we identified in this study were GI bleeding, intestinal obstruction, acute diverticulitis, acute pancreatitis, and acute cholecystitis. Multivariate Cox regression analysis done adjusting for confounders showed that renal failure, alcohol abuse, and peptic ulcer disease were associated with increased odds of 30-day readmission from GI-related causes.

Conclusions

GI manifestations of COVID-19 are not uncommon and remain an important cause of readmission. Targeted interventions addressing the modifiable predictors of readmission identified will be beneficial in reducing the burden on already limited healthcare resources.

Accounting for the Growth of Observation Stays in the Assessment of Medicare's Hospital Readmissions Reduction Program

IMPORTANCE

Decreases in 30-day readmissions following the implementation of the Medicare Hospital Readmissions Reduction Program (HRRP) have occurred against the backdrop of increasing hospital observation stay use, yet observation stays are not captured in readmission measures.

OBJECTIVE

To examine whether the HRRP was associated with decreases in 30-day readmissions after accounting for observation stays.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study included a 20% sample of inpatient admissions and observation stays among Medicare fee-for-service beneficiaries from January 1, 2009, to December 31, 2015. Data analysis was performed from November 2021 to June 2022. A differences-in-differences analysis assessed changes in 30-day readmissions after the announcement of the HRRP and implementation of penalties for target conditions (heart failure, acute myocardial infarction, and pneumonia) vs nontarget conditions under scenarios that excluded and included observation stays.

MAIN OUTCOMES AND MEASURES

Thirty-day inpatient admissions and observation stays.

RESULTS

The study included 8 944 295 hospitalizations (mean [SD] age, 78.7 [8.2] years; 58.6% were female; 1.3% Asian; 10.0% Black; 2.0% Hispanic; 0.5% North American Native; 85.0% White; and 1.2% other or unknown). Observation stays increased from 2.3% to 4.4% (91.3% relative increase) of index hospitalizations among target conditions and 14.1% to 21.3% (51.1% relative increase) of index hospitalizations for nontarget conditions. Readmission rates decreased significantly after the announcement of the HRRP and returned to baseline by the time penalties were implemented for both target and nontarget conditions regardless of whether observation stays were included. When only inpatient hospitalizations were counted, decreasing readmissions accrued into a -1.48 percentage point (95% CI, -1.65 to -1.31 percentage points) absolute reduction in readmission rates by the postpenalty period for target conditions and -1.13 percentage point (95% CI, -1.30 to -0.96 percentage points) absolute reduction in readmission rates by the postpenalty period for nontarget conditions. This reduction corresponded to a statistically significant differential change of -0.35 percentage points (95% CI, -0.59 to -0.11 percentage points). Accounting for observation stays more than halved the absolute decrease in readmission rates for target conditions (-0.66 percentage points; 95% CI, -0.83 to -0.49 percentage points). Nontarget conditions showed an overall greater decrease during the same period (-0.76 percentage points; 95% CI, -0.92 to -0.59 percentage points), corresponding to a differential change in readmission rates of 0.10 percentage points (95% CI, -0.14 to 0.33 percentage points) that was not statistically significant.

CONCLUSIONS AND RELEVANCE

The findings of this study suggest that the reduction of readmissions associated with the implementation of the HRRP was smaller than originally reported. More than half of the decrease in readmissions for target conditions appears to be attributable to the reclassification of inpatient admission to observation stays.

Predictors and Impact of Postoperative 30-Day Readmission in Glioblastoma

BACKGROUND

Postoperative 30-day readmissions have been shown to negatively affect survival and other important outcomes in patients with glioblastoma (GBM).

OBJECTIVE

To further investigate patient readmission risk factors of primary and recurrent patients with GBM.

METHODS

The authors retrospectively reviewed records of 418 adult patients undergoing 575 craniotomies for histologically confirmed GBM at an academic medical center. Patient demographics, comorbidities, and clinical characteristics were collected and compared by patient readmission status using chi-square and Mann-Whitney U testing. Multivariable logistic regression was performed to identify risk factors that predicted 30-day readmissions.

RESULTS

The cohort included 69 (12%) 30-day readmissions after 575 operations. Readmitted patients experienced significantly lower median overall survival (11.3 vs 16.4 months, P = .014), had a lower mean Karnofsky Performance Scale score (66.9 vs 74.2, P = .005), and had a longer initial length of stay (6.1 vs 5.3 days, P = .007) relative to their nonreadmitted counterparts. Readmitted patients experienced more postoperative deep vein thromboses or pulmonary embolisms (12% vs 4%, P = .006), new motor deficits (29% vs 14%, P = .002), and nonhome discharges (39% vs 22%, P = .005) relative to their nonreadmitted counterparts. Multivariable analysis demonstrated increased odds of 30-day readmission with each 10-point decrease in Karnofsky Performance Scale score (odds ratio [OR] 1.32, P = .002), each single-point increase in 5-factor modified frailty index (OR 1.51, P = .016), and initial presentation with cognitive deficits (OR 2.11, P = .013).

CONCLUSION

Preoperatively available clinical characteristics strongly predicted 30-day readmissions in patients undergoing surgery for GBM. Opportunities may exist to optimize preoperative and postoperative management of at-risk patients with GBM, with downstream improvements in clinical outcomes.

Local Supply Of Postdischarge Care Options Tied To Hospital Readmission Rates

The extent to which patients' risk for readmission after a hospitalization is influenced by local availability of postdischarge care options is not currently known. We used national, hospital-level data to assess whether the supply of postdischarge care options in hospitals' catchment areas was associated with readmission rates for Medicare patients after hospitalizations for acute myocardial infarction, heart failure, or pneumonia. Overall, readmission rates were negatively associated with per capita supply of primary care physicians (-0.16 percentage points per standard deviation) and licensed nursing home beds (-0.09 percentage points per standard deviation). In contrast, readmission rates were positively associated with per capita supply of nurse practitioners (0.09 percentage points per standard deviation). Our results suggest potential modifications to the Hospital Readmissions Reduction Program to account for local health system characteristics when assigning penalties to hospitals.

Access to post-acute care services reduces emergency department utilisation among individuals insured by Medicaid: An observational study

AIMS AND OBJECTIVES

We examined whether access to post-acute care services differed between individuals insured by Medicaid and commercial insurers and whether those differences explained emergency department utilisation 30 days post-hospitalisation.

BACKGROUND

Timely follow-up to community-based providers is a strategy to improve post-hospitalisation outcomes. However, little is known regarding the influence of post-acute care services on the likelihood of emergency department use post-hospitalisation for individuals insured by Medicaid.

DESIGN

We conducted a retrospective observational study of electronic health record data from an academic medical centre in a large northeastern urban setting. The STROBE checklist was used in reporting this observational study.

METHODS

Our analysis included adults insured by Medicaid or commercial insurers who were discharged from medical services between 1 August-31 October 2017 (n = 785). Logistic regression models were used to examine the effects of post-acute care services (primary care, home health, specialty care) on the odds of an emergency department visit.

RESULTS

Post-hospitalisation, 12% (n = 59) of individuals insured by Medicaid experienced an emergency department visit compared to 4.2% (n = 13) of individuals commercially insured. Having Medicaid insurance was associated with higher odds of emergency department visits post-hospitalisation (OR = 3.24). Having a home care visit or specialty care visit within 30 days post-discharge were significant predictors of lower odds of emergency department visits. Specific to specialty care visits, Medicaid was no longer a significant predictor of emergency department visits with specialty care being more influential (OR = 0.01).

CONCLUSIONS

Improving connections to appropriate post-acute care services, specifically specialty care, may improve outcomes among individuals insured by Medicaid.

RELEVANCE TO CLINICAL PRACTICE

Hospital-based nurses, including those in direct care, case management and discharge planning, play an important role in facilitating referrals and scheduling appointments prior to discharge. Individuals insured by Medicaid may require additional support in accessing these services and nurses are well-positioned to facilitate care continuity.

Why Do Patients Undergoing Extremity Prosthetic Reconstruction for Metastatic Disease Get Readmitted?

BACKGROUND

Orthopedic oncology patients are particularly susceptible to increased readmission rates and poor surgical outcomes, yet little is known about readmission rates. The goal of this study is to identify factors independently associated with 90-day readmission for patients undergoing oncologic resection and subsequent prosthetic reconstruction for metastatic disease of the hip and knee.

METHODS

This is a retrospective comparative cohort study of all patients treated from 2013 to 2019 at a single tertiary care referral institution who underwent endoprosthetic reconstruction by an orthopedic oncologist for metastatic disease of the extremities. The primary outcome measure was unplanned 90-day readmission.

RESULTS

We identified 112 patients undergoing 127 endoprosthetic reconstruction surgeries. Metastatic disease was most commonly from renal (26.8%), lung (23.6%), and breast (13.4%) cancer. The most common type of skeletal reconstruction performed was simple arthroplasty (54%). There were 43 readmissions overall (33.9%). When controlling for confounding factors, body mass index >40, insurance status, peripheral vascular disease, and longer hospital length of stay were independently associated with risk of readmission (P ≤ .05).

CONCLUSION

Readmission rates for endoprosthetic reconstructions for metastatic disease are high. Although predicting readmission remains challenging, risk stratification presents a viable option for helping minimize unplanned readmissions.

LEVEL OF EVIDENCE

III.

Adverse Discharge Outcomes Associated With the Medicare Hospital Readmissions Reduction Program Among Commercially Insured Adults

ABSTRACT

It is unknown if changes in the rate of discharges against medical advice (DAMA) are related to the implementation of the Medicare Hospital Readmissions Reduction Program (HRRP). We performed an interrupted time series analysis of monthly DAMA rates per 1,000 discharges of all enrolled individuals 18-64 years old with a hospitalization between January 1, 2006, and December 31, 2015, in a commercially insured population. We performed a segmented linear regression with two interruptions: (1) April 2010 to coincide with the passage of the HRRP and (2) October 2012 to coincide with the implementation of HRRP penalties. There were 1,087,812 discharges representing 668,823 individuals over 120 months. The downward trend in monthly DAMA rates was reversed significantly after April 2010 with a sustained 0.1 increase in the monthly rate that continued after the implementation of penalties in October 2012. Allowing for the two interruptions, there was a statistically significant positive trend (0.10; 0.06-0.13, p < .01) in April 2010. Relative to the first interruption, there was no statistically significant change in the slope in October 2012; the estimated slope was -0.04 (-0.08 to 0.002). Monthly DAMA rates increased in anticipation of and after HRRP implementation, suggesting a potential relationship between the HRRP and DAMA.

Predictors of Five-Year Readmission to an Inpatient Service among Patients with Alcohol Use Disorders: Report from a Low-Middle Income Country

BACKGROUND

Alcohol use disorder (AUD) is a relapsing-remitting disease that accounted for a sizable proportion of all-cause adult inpatient stays.

OBJECTIVES

To determine the predictors of any and multiple readmissions to inpatient care for AUD within 5 years of the index admission.

METHODS

This retrospective, register-based cohort study assessed consecutive patients with AUD admitted to a publicly-funded inpatient service between January 2007 and December 2014. Binary logistic regression was used to determine independent predictors for readmissions based on relevant demographic, clinical, and treatment variables that showed significant differences (p < 0.05) on univariate analysis.

RESULTS

Among 938 patients (age 35.9 ± 10.3 years; duration of alcohol use 159.6 ± 104.5 months; dual diagnosis 19%; comorbidity of substance use disorder 49.3%; medical disorder 34.8%, 299 (31.9%) and 115 (12.3%) had any and multiple readmissions, respectively. Comorbid "severe mental illness" (Odds ratio [OR] 1.99, 95% confidence interval [CI] 1.11-3.57) and urban residence (OR 1.58, 95% CI 1.13-2.18) increased the odds of any readmission; "Improved" status at discharge (OR 0.51, 95% CI 0.35-0.72) during index hospitalization reduced odds of readmission. Additionally, any medical or psychiatric comorbidities increased (OR 2.23, 95% CI 1.26-3.97), and comorbid substance use disorder decreased (OR 0.41, 95% CI 0.19-0.89) risk of multiple readmissions.

CONCLUSIONS

Clinicians could identify patients at-risk for any and multiple readmissions during the index hospitalization. A policy aimed at reducing the risk of rehospitalization, healthcare cost, and stigma should pay attention to the predictors of readmission. Such policy should further benefit resource-limited settings.

Racial Disparities in Stroke Readmissions Reduced in Hospitals With Better Nurse Staffing

BACKGROUND

Racial minorities are disproportionately affected by stroke, with Black patients experiencing worse poststroke outcomes than White patients. A modifiable aspect of acute stroke care delivery not yet examined is whether disparities in stroke outcomes are related to hospital nurse staffing levels.

OBJECTIVES

The aim of this study was to determine whether 7- and 30-day readmission disparities between Black and White patients were associated with nurse staffing levels.

METHODS

We conducted a secondary analysis of 542 hospitals in four states. Risk-adjusted, logistic regression models were used to determine the association of nurse staffing with 7- and 30-day all-cause readmissions for Black and White ischemic stroke patients.

RESULTS

Our sample included 98,150 ischemic stroke patients (87% White, 13% Black). Thirty-day readmission rates were 10.4% (12.7% for Black patients, 10.0% for White patients). In models accounting for hospital and patient characteristics, the odds of 30-day readmissions were higher for Black than White patients. A significant interaction was found between race and nurse staffing, with Black patients experiencing higher odds of 30- and 7-day readmissions for each additional patient cared for by a nurse. In the best-staffed hospitals (less than three patients per nurse), Black and White stroke patients' disparities were no longer significant.

DISCUSSION

Disparities in readmissions between Black and White stroke patients may be linked to the level of nurse staffing in the hospitals where they receive care. Tailoring nurse staffing levels to meet the needs of Black ischemic stroke patients represents a promising intervention to address systemic inequities linked to readmission disparities among minority stroke patients.

Emerging Implantable Device Technology for Patients at the Intersection of Electrophysiology and Heart Failure Interdisciplinary Care

Cardiac implantable electronic devices (CIEDs), including implantable cardioverter-defibrillators (ICDs) and cardiac resynchronization therapy (CRT), are part of guideline- indicated treatment for a subset of patients with heart failure with reduced ejection fraction (HFrEF). Current technological advancements in CIEDs have allowed the detection of specific patient physiologic parameters used for forecasting clinical decompensation through algorithmic, multiparameter remote monitoring. Other recent emerging technologies, including cardiac contractility modulation (CCM) and baroreflex activation therapy (BAT), may provide symptomatic or physiologic benefit in patients without an indication for CRT. Our goal in this state-of-the-art review is to describe the commercially available new technologies, purported mechanisms of action, evidence surrounding their clinical role, limitations, and future directions. Finally, we underline the need for standardized workflow and close interdisciplinary management of this population to ensure the delivery of high-quality care.

Follow up from the Lebanese Heart Failure Snapshot: Reflection of geopolitical instability

BACKGROUND

Heart failure has a great cost on the health care system. The readmission and mortality rates and their predictors are greatly affected by political and sociocultural unrests.

AIMS

To determine the readmission and mortality rates and their predictors in heart failure population in times of political and sociocultural unrests.

DESIGN

A cross-sectional follow-up with patients recruited for the Lebanese Heart Failure Snapshot was conducted over the month of June in 2019.

METHODS

Phone calls were conducted at 30-90 days, 6-12 months following hospital discharge for patient previously admitted to one of the study hospitals for heart failure exacerbation. Follow-up data was conducted from July 2019 till May 2020.

FINDINGS

The mean age of the 120 participants was 71 years with a mean ejection fraction of 41%. The 30-90 days, 6-12 months readmission rates were 20%, 56%, 75%, and 78%, respectively. Readmission predictors were non-sinus rhythm and low diastolic blood pressure at admission. Mortality rates at 30-90 days, 6-12 months were 7%, 11%, 17%, and 28%, respectively. Low diastolic blood pressure and longer length of hospital stay were associated with mortality.

CONCLUSION

The rapid changes in the country make it difficult to formulate an intervention plan. This was seen in the increased rates of readmission and the decreased rates of mortality. Rigorous research should be conducted at every phase of the sociocultural changes in developing countries that were hit by the COVID-19 pandemic and had their economy largely affected.

IMPACT

The occurrences of the countries can greatly influence the outcomes of patients with heart failure. This is true in developing countries that were affected by the COVID-19 pandemic socially, economically, and politically. Research should be done regularly to establish the effect of these changes on patients with heart failure. Nevertheless, nursing roles are the common denominator that should be adapted to all the changes and provided despite all challenges to assure improved outcomes. Such practices include discharge education tailored to the subjective needs of the patients and continuous, uninterrupted follow-up despite of all the occurrences. These practices are likely to decrease adverse outcomes in patients with heart failure.

Targeting zero preventable trauma readmissions

BACKGROUND

Nearly 1-in-10 trauma patients in the United States are readmitted within 30 days of discharge, with a median hospital cost of more than $8,000 per readmission. There are national efforts to reduce readmissions in trauma care, but we do not yet understand which are potentially preventable. Our study aims to quantify the potentially preventable readmissions (PPRs) in trauma care to serve as the anchor point for ongoing efforts to curb hospital readmissions and ultimately, bring preventable readmissions to zero.

METHODS

We identified inpatient hospitalizations after trauma and readmissions within 90 days in the 2017 National Readmissions Database (NRD). Potentially preventable readmissions were defined as the Agency for Healthcare Research and Quality-defined Ambulatory Care Sensitive Conditions, in addition to superficial surgical site infection, acute kidney injury/acute renal failure, and aspiration pneumonitis. Mean costs for these admissions were calculated using the NRD. A multivariable logistic regression model was used to characterize the relationship between patient characteristics and PPR.

RESULTS

A total of 1,320,083 patients were admitted for trauma care in the 2017 NRD, and 137,854 (10.4%) were readmitted within 90 days of discharge. Of these readmissions, 22.7% were potentially preventable. The mean cost was $10,001/PPR, resulting in $313,802,278 in cost to the US health care system. Of readmitted trauma patients younger than 65 years, Medicaid or Medicare patients had 2.7-fold increased odds of PPRs compared with privately insured patients. Patients of any age with congestive heart failure had 2.9 times increased odds of PPR, those with chronic obstructive pulmonary disease or complicated diabetes mellitus had 1.8 times increased odds, and those with chronic kidney disease had 1.7 times increased odds. Furthermore, as the days from discharge increased, the proportion of readmissions due to PPRs increased.

CONCLUSION

One-in-five trauma readmissions are potentially preventable, which account for more than $300 million annually in health care costs. Improved access to postdischarge ambulatory care may be key to minimizing PPRs, especially for those with certain comorbidities.

LEVEL OF EVIDENCE

Economic and value-based evaluations, level II.

Comparison of Back-Propagation Neural Network, LACE Index and HOSPITAL Score in Predicting All-Cause Risk of 30-Day Readmission

Background

The main purpose of this study is to predict the all-cause risk of 30-day readmission by employing the back-propagation neural network (BPNN) in comparison with traditional risk assessment tools of LACE index and HOSPITAL scores.

Methods

This was a retrospective cohort study from January 1st, 2018 to December 31st, 2019. A total of 55,688 hospitalizations from a medical center in Taiwan were examined. The LACE index (length of stay, acute admission, Charlson comorbidity index score, emergency department visits in previous 6 months) and HOSPITAL score (hemoglobin level at discharge, discharge from an Oncology service, sodium level at discharge, procedure during hospital stay, Index admission type, number of hospital admissions during the previous year, length of stay) are calculated. We employed variables from LACE index and HOSPITAL score as the input vector of BPNN for comparison purposes.

Results

The BPNN constructed in the current study has a considerably better ability with a C statistics achieved 0.74 (95% CI 0.73 to 0.75), which is statistically significant larger than that of the other two models using DeLong’s test. Also, it was possible to achieve higher sensitivity (70.32%) without penalizing the specificity (71.76%) and accuracy (71.68%) at its optimal threshold, which is at the 20% of patients with the highest predicted risk. Moreover, it is much more informative than the other two methods because of a considerably higher LR+ and a lower LR-.

Conclusion

Our findings suggest that more attention should be paid to methods based on non-linear classification systems, as they lead to substantial differences in risk-scores.

Reducing Readmissions for Chronic Obstructive Pulmonary Disease in Response to the Hospital Readmissions Reduction Program

Rationale: In August 2013, the Hospital Readmission Reduction Program announced financial penalties on hospitals with higher than expected risk-adjusted 30-day readmission rates for Medicare beneficiaries hospitalized for chronic obstructive pulmonary disease (COPD) exacerbation. In October 2014, penalties were imposed. We hypothesized that penalties would be associated with decreased readmissions after COPD hospitalizations. Objectives: To determine whether the announcement and enactment of financial penalties for COPD were associated with decreases in hospital readmissions for COPD. Methods: We used data from California's Office of Statewide Health Planning and Development to examine unplanned 30-day all-cause and COPD-related readmissions after COPD hospitalization. The preannouncement period was January 2010 to July 2013. The postannouncement period was August 2013 to September 2014. The postenactment period was October 2014 to December 2017. Using interrupted time series, we investigated the immediate change after the intervention (level change) and differences in the preintervention and postintervention trends (slope change). Results: We identified 333,429 index hospitalizations for COPD from 449 California hospitals. Overall, 69% of patients had Medicare insurance. For all-cause readmissions, the level change at announcement was 0.16% (95% confidence interval [CI], -1.07 to 1.38; P = 0.80); the change in slope between preannouncement and postannouncement periods was -0.01% (95% CI, -0.15 to 0.13; P = 0.92). The level change at enactment was 0.29% (95% CI, -1.11 to 1.69; P = 0.68); the change in slope between postannouncement and postenactment was 0.04% (95% CI, -0.10 to 0.18; P = 0.57). For patients with COPD-related readmissions, the level change at the time of the announcement was 0.09% (95% CI, -0.68 to 0.85; P = 0.83); the change in slope was 0.003% (95% CI, -0.08 to 0.09; P = 0.94). The level change at the time of the enactment was 0.22% (95% CI, -0.69 to 1.12; P = 0.64); the change in slope was -0.02% (95% CI, -0.10 to 0.07; P = 0.72). Conclusions: We did not detect decreases in either all-cause or COPD-related readmission rates at either time point. Although this would suggest that the Hospital Readmission Reduction Program penalty was ineffective for COPD, COPD readmissions had decreased at an earlier time point (October 2012) when penalties were announced for conditions other than COPD. Based on this, we believe early, broad interventions decreased readmissions, such that no difference was seen at this later time points despite institution of COPD-specific penalties.

Evaluation of an intervention targeted with predictive analytics to prevent readmissions in an integrated health system: observational study

OBJECTIVES

To determine the associations between a care coordination intervention (the Transitions Program) targeted to patients after hospital discharge and 30 day readmission and mortality in a large, integrated healthcare system.

DESIGN

Observational study.

SETTING

21 hospitals operated by Kaiser Permanente Northern California.

PARTICIPANTS

1 539 285 eligible index hospital admissions corresponding to 739 040 unique patients from June 2010 to December 2018. 411 507 patients were discharged post-implementation of the Transitions Program; 80 424 (19.5%) of these patients were at medium or high predicted risk and were assigned to receive the intervention after discharge.

INTERVENTION

Patients admitted to hospital were automatically assigned to be followed by the Transitions Program in the 30 days post-discharge if their predicted risk of 30 day readmission or mortality was greater than 25% on the basis of electronic health record data.

MAIN OUTCOME MEASURES

Non-elective hospital readmissions and all cause mortality in the 30 days after hospital discharge.

RESULTS

Difference-in-differences estimates indicated that the intervention was associated with significantly reduced odds of 30 day non-elective readmission (adjusted odds ratio 0.91, 95% confidence interval 0.89 to 0.93; absolute risk reduction 95% confidence interval -2.5%, -3.1% to -2.0%) but not with the odds of 30 day post-discharge mortality (1.00, 0.95 to 1.04). Based on the regression discontinuity estimate, the association with readmission was of similar magnitude (absolute risk reduction -2.7%, -3.2% to -2.2%) among patients at medium risk near the risk threshold used for enrollment. However, the regression discontinuity estimate of the association with post-discharge mortality (-0.7% -1.4% to -0.0%) was significant and suggested benefit in this subgroup of patients.

CONCLUSIONS

In an integrated health system, the implementation of a comprehensive readmissions prevention intervention was associated with a reduction in 30 day readmission rates. Moreover, there was no association with 30 day post-discharge mortality, except among medium risk patients, where some evidence for benefit was found. Altogether, the study provides evidence to suggest the effectiveness of readmission prevention interventions in community settings, but further research might be required to confirm the findings beyond this setting.

National Trends in Heart Failure Hospitalizations and Readmissions From 2010 to 2017

Importance

Previous studies have described the secular trends of overall heart failure (HF) hospitalizations, but the literature describing the national trends of unique index hospitalizations and readmission visits for the primary management of HF is lacking.

Objectives

To examine contemporary overall and sex-specific trends of unique primary HF (grouped by number of visits for the same patient in a given year) and 30-day readmission visits in a large national US administrative database from 2010 to 2017.

Design, Setting, and Participants

This cohort study used data from all adult hospitalizations in the Nationwide Readmission Database from January 1, 2010, to December 31, 2017, with a primary diagnosis of HF. Data analyses were conducted from March to November 2020.

Exposures

Admission for a primary diagnosis of HF at discharge.

Main Outcomes and Measures

Unique and overall hospitalizations with a primary diagnosis of HF and postdischarge readmissions. Unique primary HF hospitalizations were grouped by number of visits for the same patient in a given year.

Results

There were 8 273 270 primary HF hospitalizations with a single primary HF admission present in 5 092 626 unique patients, and 1 269 109 had 2 or more HF hospitalizations. The mean age was 72.1 (95% CI, 72.0-72.3) years, and 48.9% (95% CI, 48.7-49.0) were women. The primary HF hospitalization rates per 1000 US adults declined from 4.4 in 2010 to 4.1 in 2013 and then increased from 4.2 in 2014 to 4.9 in 2017. The rates per 1000 US adults for postdischarge HF readmissions (1.0 in 2010 to 0.9 in 2014 to 1.1 in 2017) and all-cause 30-day readmissions (0.8 in 2010 to 0.7 in 2014 to 0.9 in 2017) had similar trends.

Conclusions and Relevance

In this analysis of a nationally representative administrative data set, for primary HF admissions, crude rates of overall and unique patient hospitalizations declined from 2010 to 2014 followed by an increase from 2014 to 2017. Additionally, readmission visits after index HF hospitalizations followed a similar trend. Future studies are needed to verify these findings to improve policies for HF management.

Care Strategies for Reducing Hospital Readmissions Using Stochastic Programming

A hospital readmission occurs when a patient has an unplanned admission to a hospital within a specific time period of discharge from an earlier or initial hospital stay. Preventable readmissions have turned into a critical challenge for the healthcare system globally, and hospitals seek care strategies that reduce the readmission burden. Some countries have developed hospital readmission reduction policies, and in some cases, these policies impose financial penalties for hospitals with high readmission rates. Decision models are needed to help hospitals identify care strategies that avoid financial penalties, yet maintain balance among quality of care, the cost of care, and the hospital’s readmission reduction goals. We develop a multi-condition care strategy model to help hospitals prioritize treatment plans and allocate resources. The stochastic programming model has probabilistic constraints to control the expected readmission probability for a set of patients. The model determines which care strategies will be the most cost-effective and the extent to which resources should be allocated to those initiatives to reach the desired readmission reduction targets and maintain high quality of care. A sensitivity analysis was conducted to explore the value of the model for low- and high-performing hospitals and multiple health conditions. Model outputs are valuable to hospitals as they examine the expected cost of hitting its target and the expected improvement to its readmission rates.

Serious mental illness, other mental health disorders, and outpatient health care as predictors of 30-day readmissions following medical hospitalization

OBJECTIVE

Prior research has not addressed whether both serious mental illness (SMI) and other mental health (OMH) disorders affect the likelihood of 30-day readmissions after medical hospitalizations, or whether post-discharge use of outpatient medical, mental health, and pharmacy services is associated with readmission likelihood.

METHODS

Using the Truven Health Analytics MarketScan® Medicaid Multi-State Database, we studied 43,817 Medicaid beneficiaries, age 18-64, following discharge from medical hospitalizations in 2011. Logistic regression models compared all-cause, 30-day readmissions among those with SMI, OMH, and no psychiatric diagnosis, and examined associations of 30-day outpatient service use with 30-day readmissions.

RESULTS

Thirty-day readmission rates were 15.9% (SMI), 13.8% (OMH), and 11.7% (no mental illness). In multivariable analysis, compared to patients without mental illness, odds of readmission were greater for those with SMI (aOR = 1.43, 95%CI:1.32-1.51) and OMH (aOR = 1.21, 95%CI:1.12-1.30), and lower among those using outpatient mental health services (aOR = 0.50, 95%CI: 0.44-0.56).

CONCLUSION

The adult Medicaid population disproportionately includes patients with SMI and OMH disorders, both of which were found to be associated with 30-day hospital readmissions. Receiving outpatient mental health services after hospital discharge may be protective against readmission following medical hospitalizations, suggesting the need for further research on these topics.

Examination of Post-discharge Follow-up Appointment Status and 30-Day Readmission

BACKGROUND

Post-hospital discharge follow-up appointments are intended to evaluate patients' recovery following a hospitalization, but it is unclear how appointment statuses are associated with readmissions.

OBJECTIVE

To examine the association between post-discharge ambulatory follow-up status, (1) having a scheduled appointment and (2) arriving to said appointment, and 30-day readmission.

DESIGN AND SETTING

A retrospective cohort study of patients hospitalized at 12 hospitals in an Integrated Delivery Network and their ambulatory appointments in that same network.

PATIENTS AND MAIN MEASURES

We included 50,772 patients who had an ambulatory appointment within 18 months of an inpatient admission in 2018. Primary outcome was readmission within 30 days post-discharge.

KEY RESULTS

There were 32,108 (63.2%) patients with scheduled follow-up appointments and 18,664 (36.8%) patients with no follow-up; 28,313 (88.2%) patients arrived, 3149 (9.8%) missed, and 646 (2.0%) were readmitted prior to their scheduled appointments. Overall 30-day readmission rate was 7.3%; 6.0% [5.75-6.31] for those who arrived, 8.8% [8.44-9.25] for those without follow-up, and 10.3% [9.28-11.40] for those who missed a scheduled appointment (p < 0.001). After adjusting for covariates, patients who arrived at their appointment in the first week following discharge were significantly less likely to be readmitted than those not having any follow-up scheduled (medical adjusted hazard ratio (aHR) 0.57 [0.47-0.69], p < 0.001; surgical aHR 0.58 [0.44-0.75], p < 0.001) There was an increased risk at weeks 3 and 4 for medical patients who arrived at a follow-up compared to those with no follow-up scheduled (week 3 aHR 1.29 [1.10-1.51], p = 0.001; week 4 aHR 1.46 [1.26-1.70], p < 0.001).

CONCLUSIONS

The benefit of patients arriving to their post-discharge appointments compared with patients who missed their follow-up visits or had no follow-up scheduled, is only significant during first week post-discharge, suggesting that coordination within 1 week of discharge is critical in reducing 30-day readmissions.

Readmissions and costs among younger and older adults for targeted conditions during the enactment of the hospital readmission reduction program

Background

The Hospital Readmissions Reduction Program (HRRP) was introduced to reduce readmission rates among Medicare beneficiaries, however little is known about readmissions and costs for HRRP-targeted conditions in younger populations. The primary objective of this study was to examine readmission trends and costs for targeted conditions during policy implementation among younger and older adults in the U.S.

Methods

We analyzed the Nationwide Readmission Database from January 2010 to September 2015 in younger (18–64 years) and older (≥65 years) patients with acute myocardial infarction (AMI), heart failure (HF), pneumonia, and acute exacerbations of chronic obstructive pulmonary disease (AECOPD). Pre- and post-HRRP periods were defined based on implementation of the policy for each condition. Readmission rates were evaluated using an interrupted time series with difference-in-difference analyses and hospital cost differences between early and late readmissions (≤30 vs. > 30 days) were evaluated using generalized linear models.

Results

Overall, this study included 16,884,612 hospitalizations with 3,337,266 readmissions among all age groups and 5,977,177 hospitalizations with 1,104,940 readmissions in those aged 18–64 years. Readmission rates decreased in all conditions. In the HRRP announcement period, readmissions declined significantly for those aged 40–64 years for AMI (p < 0.0001) and HF (p = 0.003). Readmissions decreased significantly in the post-HRRP period for those aged 40–64 years at a slower rate for AMI (p = 0.003) and HF (p = 0.05). Readmission rates among younger patients (18–64 years) varied within all four targeted conditions in HRRP announcement and post-HRRP periods. Adjusted models showed a significantly higher readmission cost in those readmitted within 30 days among younger and older populations for AMI (p < 0.0001), HF (p < 0.0001), pneumonia (p < 0.0001), and AECOPD (p < 0.0001).

Conclusion

Readmissions for targeted conditions decreased in the U.S. during the enactment of the HRRP policy and younger age groups (< 65 years) not targeted by the policy saw a mixed effect. Healthcare expenditures in younger and older populations were significantly higher for early readmissions with all targeted conditions. Further research is necessary evaluating total healthcare utilization including emergency department visits, observation units, and hospital readmissions in order to better understand the extent of the HRRP on U.S. healthcare.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-06399-z.

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.

Triple Aim and the Hospital Readmission Reduction Program

Objectives:

Despite substantial attention on hospital readmission rates, the impact of the Hospital Readmission Reduction Program (HRRP) on a comprehensive set of Triple Aim goals has not been studied: improve hospital quality, reduce cost, and improve patient experience.

Methods:

We analyze inpatient claims data from 2006 to 2015 from the Dallas Fort Worth Hospital Council Foundation with a panel of 27,397 patients with chronic obstructive pulmonary disease and congestive heart failure. We deploy a quasi-natural experiment using a difference-in-difference specification to estimate the effect of HRRP effect on readmission rates, length of stay (LOS), and hospital satisfaction.

Results:

We find that the likelihood of 30-day readmissions declined by 2.6%, average LOS decreased by 7.9%, and overall hospital rating increased by 2.1% among hospitals that fell under the scope of the HRRP, compared to non-HRRP hospitals. Our results provide evidence of a spillover effect of the HRRP in terms of its impact not only on Medicare patients, but across all insurance types, and other performance measures such as cost and patient experience.

Conclusion:

Our findings indicate that HRRP hospitals do not trade-off reductions in readmission rates with lower quality across other patient health outcomes. Rather, we find evidence that the HRRP has affected all 3 dimensions of the Triple Aim with respect to patient and hospital outcomes.

The impact of diabetology consultations on length of stay in hospitalized patients with diabetes

Introduction

Both hyperglycaemia and hypoglycaemia in hospitalized patients have been shown to be associated with a longer length of stay, higher readmission rates, and higher rates of morbidity and mortality. With 25%-30% of all hospitalized patients carrying a diagnosis of diabetes, it is important to optimize glycaemic control. Current guidelines for care of inpatients with diabetes now suggest consulting a specialized diabetes team for all patients when possible.

Aim

This study was a retrospective cohort study to evaluate the impact of an inpatient diabetology consult within 48 hours of admission on patients' length of stay.

Methods

All patients admitted to the general medicine service between 2013 and 2018 with a diagnosis of diabetes in their medical record were included, which consisted of 11 477 inpatient stays. We looked at the effect of an inpatient diabetology consultation within the first 48 hours on length of stay, complications and 30-day readmission rates.

Results

We found that patients whose care included a diabetology consult within 48 hours of admission had a statistically significant shorter length of stay by 1.56 days compared to the remainder of the group. There was no difference in complications or 30-day readmission rates between the groups.

Conclusion

Among general medicine patients with a diagnosis of diabetes, timely diabetology consultations reduced patients' length of stay and have the potential to improve their care and lessen the economic impact.

Readmission Rates for Chronic Obstructive Pulmonary Disease Under the Hospital Readmissions Reduction Program: an Interrupted Time Series Analysis

BACKGROUND

Hospital readmission rates decreased for myocardial infarction (AMI), heart failure (CHF), and pneumonia with implementation of the first phase of the Hospital Readmissions Reduction Program (HRRP). It is not established whether readmissions fell for chronic obstructive pulmonary disease (COPD), an HRRP condition added in 2014.

OBJECTIVE

We sought to determine whether HRRP penalties influenced COPD readmissions among Medicare, Medicaid, or privately insured patients.

DESIGN

We analyzed a retrospective cohort, evaluating readmissions across implementation periods for HRRP penalties ("pre-HRRP" January 2010-April 2011, "implementation" May 2011-September 2012, "partial penalty" October 2012-September 2014, and "full penalty" October 2014-December 2016).

PATIENTS

We assessed discharged patients ≥ 40 years old with COPD versus those with HRRP Phase 1 conditions (AMI, CHF, and pneumonia) or non-HRRP residual diagnoses in the Nationwide Readmissions Database.

INTERVENTIONS

HRRP was announced and implemented during this period, forming a natural experiment.

MEASUREMENTS

We calculated differences-in-differences (DID) for 30-day COPD versus HRRP Phase 1 and non-HRRP readmissions.

KEY RESULTS

COPD discharges for 1.2 million Medicare enrollees were compared with 22 million non-HRRP and 3.4 million HRRP Phase 1 discharges. COPD readmissions decreased from 19 to 17% over the study. This reduction was significantly greater than non-HRRP conditions (DID - 0.41%), but not HRRP Phase 1 (DID + 0.02%). A parallel trend was observed in the privately insured, with significant reduction compared with non-HRRP (DID - 0.83%), but not HRRP Phase 1 conditions (DID - 0.45%). Non-significant reductions occurred in Medicaid (DID - 0.52% vs. non-HRRP and - 0.21% vs. Phase 1 conditions).

CONCLUSIONS

In Medicare, HRRP implementation was associated with reductions in COPD readmissions compared with non-HRRP controls but not versus other HRRP conditions. Parallel findings were observed in commercial insurance, but not in Medicaid. Condition-specific penalties may not reduce readmissions further than existing HRRP trends.

The Early Impact of the Centers for Medicare & Medicaid Services State Innovation Models Initiative on 30-Day Hospital Readmissions Among Adults With Diabetes

BACKGROUND

The Centers for Medicare & Medicaid Services (CMS) State Innovation Models (SIM) Initiative funds states to accelerate delivery system and payment reforms. All SIM states focus on improving diabetes care, but SIM's effect on 30-day readmissions among adults with diabetes remains unclear.

METHODS

A quasi-experimental research design estimated the impact of SIM on 30-day hospital readmissions among adults with diabetes in 3 round 1 SIM states (N=671,996) and 3 comparison states (N=2,719,603) from 2010 to 2015. Difference-in-differences multivariable logistic regression models that incorporated 4-group propensity score weighting were estimated. Heterogeneity of SIM effects by grantee state and for CMS populations were assessed.

RESULTS

In adjusted difference-in-difference analyses, SIM was associated with an increase in odds of 30-day hospital readmission among patients in SIM states in the post-SIM versus pre-SIM period relative to the ratio in odds of readmission among patients in the comparison states post-SIM versus pre-SIM (ratio of adjusted odds ratio=1.057, P=0.01). Restricting the analyses to CMS populations (Medicare and Medicaid beneficiaries), resulted in consistent findings (ratio of adjusted odds ratio=1.057, P=0.034). SIM did not have different effects on 30-day readmissions by state.

CONCLUSIONS

We found no evidence that SIM reduced 30-day readmission rates among adults with diabetes during the first 2 years of round 1 implementation, even among CMS beneficiaries. It may be difficult to reduce readmissions statewide without greater investment in health information exchange and more intensive use of payment models that promote interorganizational coordination.

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

BACKGROUND

Children insured by Medicaid have higher readmission rates than privately insured children. However, little is known about whether this disparity has changed over time.

METHODS

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.

RESULTS

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).

CONCLUSIONS

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.

Rate and Modifiable Predictors of 30-Day Readmission in Patients with Acute Respiratory Distress Syndrome in the United States

Background

The 30-day readmission rates are being used as a quality measure by Centers for Medicare and Medicaid Services (CMS) for specific medical and surgical conditions. Acute respiratory distress syndrome (ARDS) is one of the important causes of morbidity and mortality in the United States (US). The characteristics and predictors of 30-day readmission in ARDS patients in the US are not widely known, which we have depicted in our study.

Objective

The aim of this study is to identify 30-day readmission rates, characteristics, and predictors of ARDS patients using the largest publicly available nationwide database.

Methods

We used the National Readmission Database from the year 2013 to extract the patients with ARDS by primary discharge diagnosis with ICD9-CM codes. All-cause unplanned 30-day readmission rates were calculated for patients admitted between January and November 2013. The independent predictors for unplanned 30-day readmission were identified by survey logistic regression.

Results

After excluding elective readmission, the all-cause unplanned 30-day readmission rate for ARDS patients was 18%. Index admissions readmitted within 30-day had a significantly higher baseline burden of comorbidities with a Charlson Comorbidity Index (CCI) ≥1 as compared to those who were not readmitted within 30 days. In multivariate regression analysis, several predictors associated with 30-day readmission were self-pay/no charge/other (OR 1.19, 95%CI: 1.02-1.38; p = 0.02), higher-income class (OR 0.86, 95%CI:0.79-0.99; p = 0.03), private insurance (OR 0.81, 95%CI:0.67-0.94; p = 0.01), and teaching metropolitan hospital (OR 0.72, 95%CI:0.61-0.94; p = 0.01).

Conclusion

The unplanned 30-day readmission rates are higher in ARDS patients in the US. Several modifiable factors such as insurance, socioeconomic status, and hospital type are associated with 30-day readmission among ARDS patients.

The Association Between Structural, Performance, and Community Factors and the Likelihood of Receiving a Penalty Under the Hospital Readmissions Reduction Program (Fiscal Year 2013-2019)

Purpose: Little is known about the role of structural, performance, and community factors that impact the likelihood of receiving a penalty under the Hospital Readmission Reduction Program. This study examined the association between structural, performance, and community factors and the likelihood of receiving a penalty as well as investigated the likelihood of hospitals serving vulnerable populations of receiving a penalty.

Methods: Centers for Medicare and Medicaid Services and United States Census Bureau data were used in this analysis. Ordered logistic regressions in a cross-sectional analysis were employed to estimate the probability of receiving a high or low penalty in the fiscal year 2013 through 2019.

Results: On average, medium-sized, major teaching, and safety-net hospitals had the highest proportion of hospitals with a high penalty. After controlling for performance and community factors, structural factor variables such as safety-net status, rural status, and teaching status either were no longer significant or the likelihood magnitude changed. However, after controlling for performance and community factors, the statistical significance of hospital size variables and geographic location persisted across the years. Length of stay and occupancy rate variables were also statistically significant across the 7 years under review.

Conclusion: Taken together, structural, performance, and community factors are important in explaining variation in the likelihood of receiving a penalty. There is no evidence that safety-net, rural, and public hospitals are more likely to receive a penalty. The results also suggest that there is room for providers to reduce avoidable readmissions and policymakers to mitigate unintended consequences.

Hospital Transfer Rates Among US Nursing Home Residents With Advanced Illness Before and After Initiatives to Reduce Hospitalizations

IMPORTANCE

Hospital transfers among nursing home residents in the United States who have been diagnosed with advanced illnesses and have limited life expectancy are often burdensome, costly, and of little clinical benefit. National initiatives, introduced since 2012, have focused on reducing such hospitalizations, but little is known about the consequences of these initiatives in this population.

OBJECTIVE

To investigate the change in hospital transfer rates among nursing home residents with advanced illnesses, such as dementia, congestive heart failure (CHF), and chronic obstructive pulmonary disease (COPD), from 2011 to 2017-before and after the introduction of national initiatives to reduce hospitalizations.

DESIGN, SETTING, AND PARTICIPANTS

In this cross-sectional study, nationwide Minimum Data Set (MDS) assessments from January 1, 2011, to December 31, 2016 (with the follow-up for transfer rates until December 31, 2017), were used to identify annual inception cohorts of long-stay (>100 days) nursing home residents who had recently progressed to the advanced stages of dementia, CHF, or COPD. The data were analyzed from October 24, 2018, to October 3, 2019.

MAIN OUTCOMES AND MEASURES

The number of hospital transfers (hospitalizations, observation stays, and emergency department visits) per person-year alive was calculated from the MDS assessment from the date when residents first met the criteria for advanced illness up to 12 months afterward using Medicare claims from 2011 to 2017. Transfer rates for all causes, potentially avoidable conditions (sepsis, pneumonia, dehydration, urinary tract infections, CHF, and COPD), and serious bone fractures (pelvis, hip, wrist, ankle, and long bones of arms or legs) were investigated. Hospice enrollment and mortality were also ascertained.

RESULTS

The proportions of residents in the 2011 and 2016 cohorts who underwent any hospital transfer were 56.1% and 45.4% of those with advanced dementia, 77.6% and 69.5% of those with CHF, and 76.2% and 67.2% of those with COPD. The mean (SD) number of transfers per person-year alive for potentially avoidable conditions was higher in the 2011 cohort vs 2016 cohort: advanced dementia, 2.4 (14.0) vs 1.6 (11.2) (adjusted risk ratio [aRR], 0.73; 95% CI, 0.65-0.81); CHF, 8.5 (32.0) vs 6.7 (26.8) (aRR, 0.72; 95% CI, 0.65-0.81); and COPD, 7.8 (30.9) vs 5.5 (24.8) (aRR, 0.64; 95% CI, 0.57-0.72). Transfers for bone fractures remained unchanged, and mortality did not increase. Hospice enrollment was low across all illness groups and years (range, 23%-30%).

CONCLUSIONS AND RELEVANCE

The findings of this study suggest that concurrent with new initiatives aimed at reducing hospitalizations, hospital transfers declined between 2011 and 2017 among nursing home residents with advanced illnesses without increased mortality rates. Opportunities remain to further reduce unnecessary hospital transfers in this population and improve goal-directed care for those residents who opt to forgo hospitalization.

Suitability of elderly adult hospital readmission rates for profiling readmissions in younger adult and pediatric populations

OBJECTIVE

To determine the correlation between hospital 30-day risk-standardized readmission rates (RSRRs) in elderly adults and those in nonelderly adults and children.

DATA SOURCES/STUDY SETTING

US hospitals (n = 1760 hospitals admitting adult patients and 235 hospitals admitting both adult and pediatric patients) in the 2013-2014 Nationwide Readmissions Database.

STUDY DESIGN

Cross-sectional analysis comparing 30-day RSRRs for elderly adult (≥65 years), middle-aged adult (40-64 years), young adult (18-39 years), and pediatric (1-17 years) patients.

PRINCIPAL FINDINGS

Hospital elderly adult RSRRs were strongly correlated with middle-aged adult RSRRs (Pearson R² .69 [95% confidence interval (CI) 0.66-0.71]), moderately correlated with young adult RSRRs (Pearson R² .44 [95% CI 0.40-0.47]), and weakly correlated with pediatric RSRRs (Pearson R² .28 [95% CI 0.17-0.38]). Nearly identical findings were observed with measures of interquartile agreement and Kappa statistics. This stepwise relationship between age and strength of correlation was consistent across every hospital characteristic.

CONCLUSIONS

Hospital readmission rates in elderly adults, which are currently used for public reporting and hospital comparisons, may reflect broader hospital readmission performance in middle-aged and young adult populations; however, they are not reflective of hospital performance in pediatric populations.

How Have Hospitals in the Mississippi Delta Fared Under the 2019 Revised Hospital Readmissions Reduction Program?

In 2013, the Centers for Medicare and Medicaid Services (CMS) implemented the Hospital Readmissions Reduction Program (2013 HRRP), which financially penalized hospitals if their 30-day readmissions were higher than the national average. Without adjusting for socioeconomic status of patients, the 2013 HRRP overly penalized hospitals caring for the poor, especially hospitals in the Mississippi Delta region, one of the poorest regions in the U.S. In 2019, CMS revised the HRRP (2019 Revised HRRP) to stratify hospitals into quintiles based on the proportion of patients that are dual-eligible Medicare and Medicaid beneficiaries. This study aimed to examine the effect of the 2019 Revised HRRP on financial penalties for Delta hospitals using a difference-in-difference (DID) approach with data from the 2018 and 2019 HRRP Supplemental Files. The DID analysis found that relative to non-Delta hospitals, penalties in Delta hospitals were reduced by 0.08 percentage points from 2018 to 2019 (95% CI for the coefficient: -0.15, -0.01; P = .02), and the probability of a penalty was reduced by 6.64 percentage points (95% CI for the coefficient: -9.54, -3.75; P < .001). The stratification under the 2019 Revised HRRP is an important first step in reducing unfair penalties to hospitals that serve poor populations.