Evaluation of Hospital Performance Using the Excess Days in Acute Care Measure in the Hospital Readmissions Reduction Program

Do Postsurgical Follow-Up Calls Reduce Unplanned 30-Day Readmissions in Neurosurgery Patients? A Quality Improvement Project in a University Hospital

BACKGROUND

Unplanned 30-day readmissions after surgery are a source of patient dissatisfaction, monitored by the Centers for Medicare and Medicaid Services, have financial penalties for hospitals, and are publicly reported. Neurosurgical operations have a higher 30-day unplanned readmission rate after the index discharge than other specialties. After a simple initiative for a 48-72-hour postdischarge telephone call, there was an observed significant decrease in readmission rates from 17% to 8% in 7 months at Thomas Jefferson University. To better understand the role of postoperative telephone calls in this reduction, a retrospective evaluation over a longer period was performed.

METHODS

A quality improvement initiative was assessed using patient records between August 2018 and May 2023. The primary observed subject is the 30-day unplanned readmission rate and secondarily a change in Physician Communication Score. Thirty-day unplanned readmission rate and Physician Communication Scores before and after the telephone call initiative were compared, checking for difference, variance, and correlation.

RESULTS

874 readmissions (average, 28/month; 95% confidence interval [CI], 25.3-29.3), 12.9% (95% CI, 11.9-13.9) were reported before the telephone call; of 673 readmissions (average, 26/month; 95% CI, 23-28.8), 12.9% (95% CI, 11.6-14.1) were reported after the telephone call. No significant difference, variance of scores or rates, or correlation of rate with communication score were noted before and after the initiative.

CONCLUSIONS

Telephone calls and peridischarge efficient communication are needed after neurologic surgery. This approach decreased unplanned readmissions in certain instances without having a significant impact on neurosurgical patients.

Hospital Performance Under Alternative Readmission Measures Incorporating Observation Stays

OBJECTIVE

To determine the extent to which counting observation stays changes hospital performance on 30-day readmission measures.

METHODS

This was a retrospective study of inpatient admissions and observation stays among fee-for-service Medicare enrollees in 2017. We generated 3 specifications of 30-day risk-standardized readmissions measures: the hospital-wide readmission (HWR) measure utilized by the Centers for Medicare and Medicaid Services, which captures inpatient readmissions within 30 days of inpatient discharge; an expanded HWR measure, which captures any unplanned hospitalization (inpatient admission or observation stay) within 30 days of inpatient discharge; an all-hospitalization readmission (AHR) measure, which captures any unplanned hospitalization following any hospital discharge (observation stays are included in both the numerator and denominator of the measure). Estimated excess readmissions for hospitals were compared across the 3 measures. High performers were defined as those with a lower-than-expected number of readmissions whereas low performers had higher-than-expected or excess readmissions. Multivariable logistic regression identified hospital characteristics associated with worse performance under the measures that included observation stays.

RESULTS

Our sample had 2586 hospitals with 5,749,779 hospitalizations. Observation stays ranged from 0% to 41.7% of total hospitalizations. Mean (SD) readmission rates were 16.6% (5.4) for the HWR, 18.5% (5.7) for the expanded HWR, and 17.9% (5.7) in the all-hospitalization readmission measure. Approximately 1 in 7 hospitals (14.9%) would switch from being classified as a high performer to a low performer or vice-versa if observation stays were fully included in the calculation of readmission rates. Safety-net hospitals and those with a higher propensity to use observation would perform significantly worse.

CONCLUSIONS

Fully incorporating observation stays in readmission measures would substantially change performance in value-based programs for safety-net hospitals and hospitals with high rates of observation stays.

Cardiovascular hospitalizations for Medicare advantage beneficiaries in the United States, 2009 to 2019

BACKGROUND

Federal programs measuring hospital quality of care for acute cardiovascular conditions are based solely on Medicare fee-for-service (FFS) beneficiaries, and exclude Medicare Advantage (MA) beneficiaries. In this study we characterize the proportion of Medicare beneficiaries enrolled in MA at the time of acute myocardial infarction (AMI), heart failure (HF), and ischemic stroke hospitalization.

METHODS

Retrospective cross-sectional study of short-term acute care hospitals using Medicare claims in 2009 and 2019.

RESULTS

There were 2,653 hospitals in 2009 and 2,732 hospitals in 2019. Across hospitals, the proportion of Medicare beneficiaries hospitalized for AMI who were enrolled in MA increased between 2009 (hospital-level median 14.4% [IQR 5.1%-26.0%]) and 2019 (33.3% [IQR 20.6%-45.2%]), with substantial variation across hospitals. Similar patterns were observed for HF (13.0% [IQR 5.3%-24.3%] to 31.0% [IQR 20.2%-42.3%]) and ischemic stroke (14.6% [IQR 5.3%-26.7%] to 33.3% [IQR 20.9%-46.0%]). Within each hospital referral region, hospital size (large 36.3% vs small 24.5%; adjusted difference 6.7%, 95% CI, 4.5%-8.8%), teaching status (teaching 34.5% vs nonteaching 28.2%; 2.8%, 1.4%-4.1%), and ownership status (private nonprofit 32.3% vs public 24.5%; 5.2%, 3.5%-6.9%) were each associated with a higher hospital MA proportion.

CONCLUSIONS

The proportion of Medicare beneficiaries hospitalized for AMI, HF, and ischemic stroke enrolled in MA doubled between 2009 and 2019, with substantial variation across hospitals. These findings have implications for federal efforts to measure and improve quality, which currently focus only on FFS beneficiaries.

Quality of Care and Clinical Outcomes for Patients With Heart Failure at Hospitals Caring for a High Proportion of Black Adults: Get With The Guidelines-Heart Failure Registry

Importance

Black adults with heart failure (HF) disproportionately experience higher population-level mortality than White adults with HF. Whether quality of care for HF differs at hospitals with high proportions of Black patients compared with other hospitals is unknown.

Objective

To compare quality and outcomes for patients with HF at hospitals with high proportions of Black patients vs other hospitals.

Design, Setting, and Participants

Patients hospitalized for HF at Get With The Guidelines (GWTG) HF sites from January 1, 2016, through December 1, 2019. These data were analyzed from May 2022 through November 2022.

Exposures

Hospitals caring for high proportions of Black patients.

Main Outcomes and Measures

Quality of HF care based on 14 evidence-based measures, overall defect-free HF care, and 30-day readmissions and mortality in Medicare patients.

Results

This study included 422 483 patients (224 270 male [53.1%] and 284 618 White [67.4%]) with a mean age of 73.0 years. Among 480 hospitals participating in GWTG-HF, 96 were classified as hospitals with high proportions of Black patients. Quality of care was similar between hospitals with high proportions of Black patients compared with other hospitals for 11 of 14 GWTG-HF measures, including use of angiotensin-converting enzyme inhibitors/angiotensin receptor blocker/angiotensin receptor neprilysin inhibitors for left ventricle systolic dysfunction (high-proportion Black hospitals: 92.7% vs other hospitals: 92.4%; adjusted odds ratio [OR], 0.91; 95% CI, 0.65-1.27), evidence-based β-blockers (94.7% vs 93.7%; OR, 1.02; 95% CI, 0.82-1.28), angiotensin receptor neprilysin inhibitors at discharge (14.3% vs 16.8%; OR, 0.74; 95% CI, 0.54-1.02), anticoagulation for atrial fibrillation/flutter (88.8% vs 87.5%; OR, 1.05; 95% CI, 0.76-1.45), and implantable cardioverter-defibrillator counseling/placement/prescription at discharge (70.9% vs 71.0%; OR, 0.75; 95% CI, 0.50-1.13). Patients at high-proportion Black hospitals were less likely to be discharged with a follow-up visit made within 7 days or less (70.4% vs 80.1%; OR, 0.68; 95% CI, 0.53-0.86), receive cardiac resynchronization device placement/prescription (50.6% vs 53.8%; OR, 0.63; 95% CI, 0.42-0.95), or an aldosterone antagonist (50.4% vs 53.5%; OR, 0.69; 95% CI, 0.50-0.97). Overall defect-free HF care was similar between both groups of hospitals (82.6% vs 83.4%; OR, 0.89; 95% CI, 0.67-1.19) and there were no significant within-hospital differences in quality for Black patients vs White patients. Among Medicare beneficiaries, the risk-adjusted hazard ratio (HR) for 30-day readmissions was higher at high-proportion Black vs other hospitals (HR, 1.14; 95% CI, 1.02-1.26), but similar for 30-day mortality (HR 0.92; 95% CI,0.84-1.02).

Conclusions and Relevance

Quality of care for HF was similar across 11 of 14 measures at hospitals caring for high proportions of Black patients compared with other hospitals, as was overall defect-free HF care. There were no significant within-hospital differences in quality for Black patients vs White patients.

Introducing value-based healthcare perspectives into hospital performance assessment: A scoping review

OBJECTIVE

Value-based healthcare (VBHC) puts patient outcomes at the center of the healthcare process while optimizing the use of hospital resources across multiple stakeholders. This scoping review was conducted to summarize how VBHC had been represented in theory and in practice, how it had been applied to assess hospital performance, and how well it had been ultimately implemented.

METHODS

For this review, we followed the PRISMA-ScR protocol and searched five major online databases for articles published between January 2006 and July 2022. We included original articles that used the concept of VBHC to conduct performance assessments of healthcare organizations. We extracted and analyzed key concepts and information on the dimensions of VBHC, specific strategies and methods for using VBHC in performance assessment, and the effectiveness of the assessment.

RESULTS

We identified 48 eligible studies from 7866 articles. Nineteen nonempirical studies focused on the development of a VBHC performance assessment indicator system, and 29 empirical studies reported on the ways and points of introducing VBHC into performance assessment and its effectiveness. Ultimately, we summarized the key dimensions, processes, and effects of performance assessment after introducing VBHC.

CONCLUSION

Current healthcare performance assessment has begun to focus on implementing VBHC as an integrated strategy, and future work should further clarify the reliability of metrics and their association with evaluation outcomes and consider the effective integration of clinical outcomes and patient-reported outcomes.

Why Did New York State Hospitals Rank So Poorly?

BACKGROUND

According to the Centers for Medicare and Medicaid Services star ratings, New York State (NYS) hospitals are relatively poor performers, with 33% achieving 1 star compared with 5% of hospitals across the United States.

OBJECTIVES

We compared NYS hospitals to all United States hospitals using Centers for Medicare and Medicaid Services Hospital Value-Based Purchasing (HVBP) and star ratings component measures. We perform risk adjustment for hospital and market characteristics associated poor performance.

RESEARCH DESIGN

This was a cross-sectional observational study.

SUBJECTS

All acute care hospitals in the United States which had HVBP scores for 2019 in April 21, 2021, Hospital Care Compare database.

MEASURES

Analysis of variance was used to compare NYS hospitals to all United States hospitals. Multivariable-based risk adjustment was applied to NYS hospitals with adjustment for hospital characteristics (eg, occupancy, size), hospital fiscal ratios (eg, operating margin), and market characteristics (eg, percent of hospital market that has a high school diploma).

RESULTS

NYS hospitals averaged lower patient satisfaction and higher readmissions. These domains were statistically significantly associated with lower socioeconomic status in the hospital market area. Risk adjustment reduced but did not eliminate these differences. NYS also performed poorly on pressure ulcers and deep vein thrombosis/pulmonary embolism prevention. NYS hospitals were similar to the United States in mortality and hospital-acquired infections.

CONCLUSIONS

Differences in the demographic makeup of hospital markets account for some of the poor performance of NYS hospitals. Some aspects, such as long length of stay, may be associated with wider regional trends.

Comparison of Machine Learning Algorithms for Predicting Hospital Readmissions and Worsening Heart Failure Events in Patients With Heart Failure With Reduced Ejection Fraction: Modeling Study

BACKGROUND

Heart failure (HF) is highly prevalent in the United States. Approximately one-third to one-half of HF cases are categorized as HF with reduced ejection fraction (HFrEF). Patients with HFrEF are at risk of worsening HF, have a high risk of adverse outcomes, and experience higher health care use and costs. Therefore, it is crucial to identify patients with HFrEF who are at high risk of subsequent events after HF hospitalization.

OBJECTIVE

Machine learning (ML) has been used to predict HF-related outcomes. The objective of this study was to compare different ML prediction models and feature construction methods to predict 30-, 90-, and 365-day hospital readmissions and worsening HF events (WHFEs).

METHODS

We used the Veradigm PINNACLE outpatient registry linked to Symphony Health's Integrated Dataverse data from July 1, 2013, to September 30, 2017. Adults with a confirmed diagnosis of HFrEF and HF-related hospitalization were included. WHFEs were defined as HF-related hospitalizations or outpatient intravenous diuretic use within 1 year of the first HF hospitalization. We used different approaches to construct ML features from clinical codes, including frequencies of clinical classification software (CCS) categories, Bidirectional Encoder Representations From Transformers (BERT) trained with CCS sequences (BERT + CCS), BERT trained on raw clinical codes (BERT + raw), and prespecified features based on clinical knowledge. A multilayer perceptron neural network, extreme gradient boosting (XGBoost), random forest, and logistic regression prediction models were applied and compared.

RESULTS

A total of 30,687 adult patients with HFrEF were included in the analysis; 11.41% (3184/27,917) of adults experienced a hospital readmission within 30 days of their first HF hospitalization, and nearly half (9231/21,562, 42.81%) of the patients experienced at least 1 WHFE within 1 year after HF hospitalization. The prediction models and feature combinations with the best area under the receiver operating characteristic curve (AUC) for each outcome were XGBoost with CCS frequency (AUC=0.595) for 30-day readmission, random forest with CCS frequency (AUC=0.630) for 90-day readmission, XGBoost with CCS frequency (AUC=0.649) for 365-day readmission, and XGBoost with CCS frequency (AUC=0.640) for WHFEs. Our ML models could discriminate between readmission and WHFE among patients with HFrEF. Our model performance was mediocre, especially for the 30-day readmission events, most likely owing to limitations of the data, including an imbalance between positive and negative cases and high missing rates of many clinical variables and outcome definitions.

CONCLUSIONS

We predicted readmissions and WHFEs after HF hospitalizations in patients with HFrEF. Features identified by data-driven approaches may be comparable with those identified by clinical domain knowledge. Future work may be warranted to validate and improve the models using more longitudinal electronic health records that are complete, are comprehensive, and have a longer follow-up time.

Achieving Equity in Hospital Performance Assessments Using Composite Race-Specific Measures of Risk-Standardized Readmission and Mortality Rates for Heart Failure

BACKGROUND

The contemporary measures of hospital performance for heart failure hospitalization and 30-day risk-standardized readmission rate (RSRR) and risk-standardized mortality rate (RSMR) are estimated using the same risk adjustment model and overall event rate for all patients. Thus, these measures are mainly driven by the care quality and outcomes for the majority racial and ethnic group, and may not adequately represent the hospital performance for patients of Black and other races.

METHODS

Fee-for-service Medicare beneficiaries from January 2014 to December 2019 hospitalized with heart failure were identified. Hospital-level 30-day RSRR and RSMR were estimated using the traditional race-agnostic models and the race-specific approach. The composite race-specific performance metric was calculated as the average of the RSRR/RMSR measures derived separately for each race and ethnicity group. Correlation and concordance in hospital performance for all patients and patients of Black and other races were assessed using the composite race-specific and race-agnostic metrics.

RESULTS

The study included 1 903 232 patients (75.7% White [n=1 439 958]; 14.5% Black [n=276 684]; and 9.8% other races [n=186 590]) with heart failure from 1860 hospitals. There was a modest correlation between hospital-level 30-day performance metrics for patients of White versus Black race (Pearson correlation coefficient: RSRR=0.42; RSMR=0.26). Compared with the race-agnostic RSRR and RSMR, composite race-specific metrics for all patients demonstrated stronger correlation with RSRR (correlation coefficient: 0.60 versus 0.74) and RSMR (correlation coefficient: 0.44 versus 0.51) for Black patients. Concordance in hospital performance for all patients and patients of Black race was also higher with race-specific (versus race-agnostic) metrics (RSRR=64% versus 53% concordantly high-performing; 61% versus 51% concordantly low-performing). Race-specific RSRR and RSMR metrics (versus race-agnostic) led to reclassification in performance ranking of 35.8% and 39.2% of hospitals, respectively, with better 30-day and 1-year outcomes for patients of all race groups at hospitals reclassified as high-performing.

CONCLUSIONS

Among patients hospitalized with heart failure, race-specific 30-day RSMR and RSRR are more equitable in representing hospital performance for patients of Black and other races.

Effect of Medicare Advantage on Hospital Readmission and Mortality Rankings

BACKGROUND

Medicare links hospital performance on readmissions and mortality to payment solely on the basis of outcomes among fee-for-service (FFS) beneficiaries. Whether including Medicare Advantage (MA) beneficiaries, who account for nearly half of all Medicare beneficiaries, in the evaluation of hospital performance affects rankings is unknown.

OBJECTIVE

To determine if the inclusion of MA beneficiaries in readmission and mortality measures reclassifies hospital performance rankings compared with current measures.

DESIGN

Cross-sectional.

SETTING

Population-based.

PARTICIPANTS

Hospitals participating in the Hospital Readmissions Reduction Program or Hospital Value-Based Purchasing Program.

MEASUREMENTS

Using the 100% Medicare files for FFS and MA claims, the authors calculated 30-day risk-adjusted readmissions and mortality for acute myocardial infarction, heart failure, chronic obstructive pulmonary disease, and pneumonia on the basis of only FFS beneficiaries and then both FFS and MA beneficiaries. Hospitals were divided into quintiles of performance based on FFS beneficiaries only, and the proportion of hospitals that were reclassified to a different performance group with the inclusion of MA beneficiaries was calculated.

RESULTS

Of the hospitals in the top-performing quintile for readmissions and mortality based on FFS beneficiaries, between 21.6% and 30.2% were reclassified to a lower-performing quintile with the inclusion of MA beneficiaries. Similar proportions of hospitals were reclassified from the bottom performance quintile to a higher one across all measures and conditions. Hospitals with a higher proportion of MA beneficiaries were more likely to improve in performance rankings.

LIMITATION

Hospital performance measurement and risk adjustment differed slightly from those used by Medicare.

CONCLUSION

Approximately 1 in 4 top-performing hospitals is reclassified to a lower performance group when MA beneficiaries are included in the evaluation of hospital readmissions and mortality. These findings suggest that Medicare's current value-based programs provide an incomplete picture of hospital performance.

PRIMARY FUNDING SOURCE

Laura and John Arnold Foundation.

Medicare's hospital readmissions reduction program and the rise in observation stays

OBJECTIVE

To evaluate whether Medicare's Hospital Readmissions Reduction Program (HRRP) is associated with increased observation stay use.

DATA SOURCES AND STUDY SETTING

A nationally representative sample of fee-for-service Medicare claims, January 2009-September 2016.

STUDY DESIGN

Using a difference-in-difference (DID) design, we modeled changes in observation stays as a proportion of total hospitalizations, separately comparing the initial (acute myocardial infarction, pneumonia, heart failure) and subsequent (chronic obstructive pulmonary disease) target conditions with a control group of nontarget conditions. Each model used 3 time periods: baseline (15 months before program announcement), an intervening period between announcement and implementation, and a 2-year post-implementation period, with specific dates defined by HRRP policies.

DATA COLLECTION/EXTRACTION METHODS

We derived a 20% random sample of all hospitalizations for beneficiaries continuously enrolled for 12 months before hospitalization (N = 7,162,189).

PRINCIPAL FINDINGS

Observation stays increased similarly for the initial HRRP target and nontarget conditions in the intervening period (0.01% points per month [95% CI -0.01, 0.3]). Post-implementation, observation stays increased significantly more for target versus nontarget conditions, but the difference is quite small (0.02% points per month [95% CI 0.002, 0.04]). Results for the COPD analysis were statistically insignificant in both policy periods.

CONCLUSIONS

The increase in observation stays is likely due to other factors, including audit activity and clinical advances.

Emergency Department Visits Versus Hospital Readmissions Among Patients Hospitalized for Heart Failure

BACKGROUND

Worsening heart failure (HF) often requires hospitalization but in some cases may be managed in the outpatient or emergency department (ED) settings. The predictors and clinical significance of ED visits without admission vs hospitalization are unclear.

METHODS

The ASCEND-HF trial included 2661 US patients hospitalized for HF with reduced or preserved ejection fraction. Clinical characteristics were compared between patients with a subsequent all-cause ED visit (with ED discharge) within 30 days vs all-cause readmission within 30 days. Factors associated with each type of care were assessed in multivariable models. Multivariable models landmarked at 30 days evaluated associations between each type of care and subsequent 150-day mortality.

RESULTS

Through 30-day follow-up, 193 patients (7%) had ED discharge, 459 (17%) had readmission, and 2009 (76%) had neither urgent visit. Patients with ED discharge vs readmission were similar with respect to age, sex, systolic blood pressure, ejection fraction, and coronary artery disease, whereas ED discharge patients had a modestly lower creatinine (P < .01). Among patients with either event within 30 days, a higher creatinine and prior HF hospitalization were associated with a higher likelihood of readmission, as compared with ED discharge (P < .02). Landmarked at 30 days, rates of death during the subsequent 150 days were 21.0% for patients who were readmitted and 11.4% for patients discharged from the ED. Compared with patients who were readmitted, ED discharge was independently associated with lower 150-day mortality (adjusted hazard ratio 0.58, 95% confidence interval 0.36-0.92, P = .02).

CONCLUSIONS

In this cohort of US patients hospitalized for HF, worse renal function and prior HF hospitalization were associated with a higher likelihood of early postdischarge readmission, as compared with ED discharge. Although subsequent mortality was high after discharge from the ED, this risk of mortality was significantly lower than patients who were readmitted to the hospital.

Assessing the concurrent validity of days alive and at home metric

BACKGROUND

Most patients living with serious illness value spending time at home. Emerging data suggest that days alive and at home (DAH) may be a useful metric, however more research is needed. We aimed to assess the concurrent validity of DAH with respect to clinically significant changes in patient- and caregiver-reported outcomes (PROs).

METHODS

We drew data from a study that compared two models of home-based palliative care among seriously ill patients and their caregivers in two Kaiser Permanente regions (Southern California and Northwest). We included participants aged 18 years or older (n = 3533) and corresponding caregivers (n = 463). We categorized patients and caregivers into three groups based on whether symptom burden (Edmonton Symptom Assessment System, ESAS) or caregiving preparedness (Preparedness for Caregiving Scale, CPS) showed improvements, deterioration, or no change from baseline to 1 month later. We measured DAH across four time windows: 30, 60, 90, and 180 days, after admission to home palliative care. We used two-way ANOVA to compare DAH across the PRO groups.

RESULTS

Adjusted pairwise comparisons showed that DAH was highest for patients whose ESAS scores improved or did not change compared with those with worsening symptoms. Although the mean differences ranged from less than a day to about 3 weeks, none exceeded 0.3 standard deviations. ESAS change scores had weak negative correlations (r = -0.11 to -0.21) with DAH measures. CPS change scores also showed weak, positive correlations (r = 0.23-0.24) with DAH measures.

CONCLUSION

DAH measures are associated, albeit weakly, with clinically important improvement or maintenance of patient symptom burden in a diverse, seriously ill population.

Clinical characteristics and risk factors of preventable hospital readmissions within 30 days

Knowledge regarding preventable hospital readmissions is scarce. Our aim was to compare the clinical characteristics of potentially preventable readmissions (PPRs) with non-PPRs. Additionally, we aimed to identify risk factors for PPRs. Our study included readmissions within 30 days after discharge from 1 of 7 hospital departments. Preventability was assessed by multidisciplinary meetings. Characteristics of the readmissions were collected and 23 risk factors were analyzed. Of the 1120 readmissions, 125 (11%) were PPRs. PPRs occurred equally among different departments (p = 0.21). 29.6% of PPRs were readmitted by a practitioner of a different medical specialty than the initial admission (IA) specialist. The PPR group had more readmissions within 7 days (PPR 54% vs. non-PPR 44%, p = 0.03). The median LOS was 1 day longer for PPRs (p = 0.16). Factors associated with PPR were higher age (p = 0.004), higher socio-economic status (p = 0.049), fewer prior hospital admissions (p = 0.004), and no outpatient visit prior to readmission (p = 0.025). This study found that PPRs can occur at any department in the hospital. There is not a single type of patient that can easily be pinpointed to be at risk of a PPR, probably due to the multifactorial nature of PPRs.