Risk-standardized Mortality Research Articles

ASO Visual Abstract: Comparison of Hospital Volume and Risk-Standardized Mortality Rate as a Proxy for Hospital Quality in Complex Oncologic Hepatopancreatobiliary Surgery.

ASO Visual Abstract: Comparison of Hospital Volume and Risk-Standardized Mortality Rate as a Proxy for Hospital Quality in Complex Oncologic Hepatopancreatobiliary Surgery.

Comparison of Hospital Volume and Risk-Standardized Mortality Rate as a Proxy for Hospital Quality in Complex Oncologic Hepatopancreatobiliary Surgery

BackgroundCentralization of hepatopancreatobiliary procedures to more experienced centers has been recommended but remains controversial. Hospital volume and risk-stratified mortality rates (RSMR) are metrics for interhospital comparison. We compared facility operative volume with facility RSMR as a proxy for hospital quality.Patients and MethodsPatients who underwent surgery for liver (LC), biliary tract (BTC), and pancreatic (PDAC) cancer were identified in the National Cancer Database (2004–2018). Hierarchical logistic regression was used to create facility-specific models for RSMR. Volume (high versus low) was determined by quintile. Performance (high versus low) was determined by RSMR tercile. Primary outcomes included median facility RSMR and RSMR distributions. Volume- and RSMR-based redistribution was simulated and compared for reductions in 90-day mortality.ResultsA total of 106,217 patients treated at 1282 facilities were included; 17,695 had LC, 23,075 had BTC, and 65,447 had PDAC. High-volume centers (HVC) had lower RSMR compared with medium-volume centers and low-volume centers for LC, BTC, and PDAC (all p < 0.001). High-performance centers (HPC) had lower RSMR compared with medium-performance centers and low-performance centers for LC, BTC, and PDAC (all p < 0.001). Volume-based redistribution required 16.0 patients for LC, 11.2 for BTC, and 14.9 for PDAC reassigned to 15, 22, and 20 centers, respectively, per life saved within each US census region. RSMR-based redistribution required 4.7 patients for LC, 4.2 for BTC, and 4.9 for PDAC reassigned to 316, 403, and 418 centers, respectively, per life saved within each US census region.ConclusionsHVC and HPC have the lowest overall and risk-standardized 90-day mortality after oncologic hepatopancreatobiliary procedures, but RSMR may outperform volume as a measure of hospital quality.

Pre-COVID-19 hospital quality and hospital response to COVID-19: examining associations between risk-adjusted mortality for patients hospitalised with COVID-19 and pre-COVID-19 hospital quality

ObjectivesThe extent to which care quality influenced outcomes for patients hospitalised with COVID-19 is unknown. Our objective was to determine if prepandemic hospital quality is associated with mortality among Medicare...

Hospital admissions and outcomes for systolic and diastolic heart failure in Spain between 2016 and 2019: A population-based study

Background and purposeIn Spain there is a lack of population data that specifically compare hospitalization for systolic and diastolic heart failure (HF). We assessed clinical characteristics, in-hospital mortality and 30-day cardiovascular readmission rates differentiating by HF type. MethodsWe conducted a retrospective observational study of patients discharged with the principal diagnosis of HF from The National Health System’ acute hospital during 2016–2019, distinguishing between systolic and diastolic HF. The source of the data was the Minimum Basic Data Set. The risk-standardized in-hospital mortality ratio and risk-standardized 30-day cardiovascular readmission ratio were calculated using multilevel risk adjustment models. Results190,200 episodes of HF were selected. Of these, 163,727 (86.1%) were classified as diastolic HF and were characterized by older age, higher proportion of women, diabetes mellitus, dementia and renal failure than those with systolic HF. In the multilevel risk adjustment models, diastolic HF was a protective factor for both in-hospital mortality (Odds ratio-OR-: 0.79; 95% confidence interval [CI], 0.75−0.83; p < 0.001) and 30-day cardiovascular readmission versus systolic HF (OR: 0.93; 95%CI: 0.88−0.97; p = 0.002). ConclusionsIn Spain, between 2016 and 2019, hospitalization episodes for HF were mostly due to diastolic HF. According to the multilevel risk adjustment models, diastolic HF compared to systolic HF was a protective factor for both in-hospital mortality and 30-day cardiovascular readmission.

Sex-based analysis of NSTEMI processes of care and outcomes by hospital: a nationwide cohort study.

Contemporary studies demonstrate that non-ST-segment elevation myocardial infarction (NSTEMI) processes of care vary according to sex. Little is known regarding variation in practice between geographical areas and centers. We identified 305014 NSTEMI admissions in the United Kingdom (UK) Myocardial Infarction National Audit Project (MINAP), 2010-2017, including female sex (110209). Hierarchical, multivariate logistic regression models were fitted assessing for differences in primary outcomes according to sex. Risk standardized mortality rates (RSMR) were calculated for individual hospitals to illustrate correlation with variables of interest. 'Heat-maps' were plotted to show regional and sex-based variation in opportunity-based quality-indicator score (surrogate for optimal processes of care). Women presented older (77y vs. 69y, P<0.001) and were more often Caucasian (93%vs. 91%, P<0.001). Women were less frequently managed with an invasive coronary angiogram (ICA) (58%vs. 75%, P<0.001) or percutaneous coronary intervention (PCI) (35%vs. 49%, P<0.001)). In our hospital-clustered analysis, we show positive correlation between the RSMR and increasing proportion of women treated for NSTEMI (R2=0.17, P<0.001). There was clear negative correlation between proportion of women who had an optimum OBQI score during their admission and RSMR (R2=0.22, P<0.001), with weaker correlation in men (R2=0.08, P<0.001). Heat-maps according to clinical commissioning group (CCG) demonstrate significant regional variation in OBQI score, with women receiving poorer quality care throughout the UK. There was a significant in variation of the management of patients with NSTEMI according to sex, with widespread geographical variation. Structural changes are required to enable improved care for women.

Abstract 5: National Institutes of Health Stroke Scale Reporting in Administrative Claims Data: Incomplete and Biased Reporting in the First Three Years

Background: Since 2016, hospitals have been able to document International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes for National Institutes of Health Stroke Scale (NIHSS). As of 2023, Center for Medicare &amp; Medicaid Services uses NIHSS as a risk adjustment variable. We assessed associations between patient- and hospital-level variables and contemporary NIHSS reporting using Medicare datasets. Methods: Retrospective cross-sectional analysis of acute ischemic stroke (AIS) admissions from October 1, 2016-December 31, 2019 using de-identified, national 100% inpatient Medicare datasets. Index AIS admissions were identified using the ICD-10-CM code of I63.x. Demographic information, medical comorbidities, hospital characteristics, and NIHSS were abstracted. Medicare and Mount Sinai Health System registry data were linked using a matching algorithm. We calculated documentation of NIHSS at the patient and hospital level, predictors of NIHSS documentation, change over time, and concordance with local registry data. Results: There were 770104 index AIS admissions. NIHSS was documented in 40.1% of AIS admissions and by 62.5% of hospitals. Hospitals documenting ≥1 NIHSS were more commonly teaching hospitals, in metropolitan areas, stroke certified, higher-volume, and had ICU availability. Adjusted odds of documentation were lower for patients of black race compared to white and with inpatient mortality, increasing Charlson comorbidity score, discharge home, and treatment in non-metropolitan areas. NIHSS was documented for 52.9% of Medicare cases even though it was documented in 93.1% of registry cases, and 74.7% of Medicare NIHSS scores equaled registry admission NIHSS. Conclusions: Hospitals face financial implications for risk-standardized mortality rate adjustment, and administrative data play an increasingly important in stroke health services and outcomes research. Yet, missing ICD-10-CM NIHSS data remains widespread three years after introduction of the ICD-10-CM NIHSS code, and there are systematic differences in reporting at the patient and hospital levels.

A decade of firearm injuries: Have we improved?

Firearm injuries are a growing public health issue, with marked increases coinciding with the coronavirus disease 2019 (COVID-19) pandemic. This study evaluates temporal trends over the past decade, hypothesizing that despite a growing number of injuries, mortality would be unaffected. In addition, the study characterizes the types of centers affected disproportionately by the reported firearm injury surge in 2020. Patients 18 years and older with firearm injuries from 2011 to 2020 were identified retrospectively using the National Trauma Data Bank (NTDB®). Trauma centers not operating for the entirety of the study period were excluded to allow for temporal comparisons. Joinpoint regression and risk-standardized mortality ratios (SMR) were used to evaluate injury counts and adjusted mortality over time. Subgroup analysis was performed to describe centers with the largest increases in firearm injuries in 2020. A total of 238,674 patients, treated at 420 unique trauma centers, met inclusion criteria. Firearm injuries increased by 31.1% in 2020, compared to an annual percent change of 2.4% from 2011 to 2019 ( p = 0.01). Subset analysis of centers with the largest changes in firearm injuries in 2020 found that they were more often Level I centers, with higher historic trauma volumes and percentages of firearm injuries ( p < 0.001). Unadjusted mortality decreased by 0.9% from 2011 to 2020, but after controlling for demographics, injury characteristics and physiology, there was no difference in adjusted mortality over the same time period. However, among patients with injury severity scores ≥25, adjusted mortality improved compared with 2011 (SMR of 0.950 in 2020; 95% confidence interval, 0.916-0.986). Firearm injuries pose an increasing burden to trauma systems, with Level I and high-volume centers seeing the largest growth in 2020. Despite increasing numbers of firearm injuries, mortality has remained unchanged over the past decade. Prognostic and Epidemiological; Level III.

Volume and region-based analysis using risk-standardized mortality rates of outcomes in HPB surgery

Volume and region-based analysis using risk-standardized mortality rates of outcomes in HPB surgery

Hospitalizaciones y eventos por insuficiencia cardiaca sistólica y diastólica en España entre 2016 y 2019. Un estudio de base poblacional

Background and purposeIn Spain there is a lack of population data that specifically compare hospitalization for systolic and diastolic heart failure (HF). We assessed clinical characteristics, in-hospital mortality and 30-day cardiovascular readmission rates differentiating by HF type. MethodsWe conducted a retrospective observational study of patients discharged with the principal diagnosis of HF from The National Health System’ acute hospital during 2016-2019, distinguishing between systolic and diastolic HF. The source of the data was the Minimum Basic Data Set. The risk-standardized in-hospital mortality ratio and risk-standardized 30-day cardiovascular readmission ratio were calculated using multilevel risk adjustment models. ResultsThe 190,200 episodes of HF were selected. Of these, 163,727 (86.1%) were classified as diastolic HF and were characterized by older age, higher proportion of women, diabetes mellitus, dementia and renal failure than those with systolic HF. In the multilevel risk adjustment models, diastolic HF was a protective factor for both in-hospital mortality (odds ratio [OR]: 0.79; 95% confidence interval [CI]: 0.75-0.83; P<.001) and 30-day cardiovascular readmission versus systolic HF (OR: 0.93; 95% CI: 0.88-0.97; P=.002). ConclusionsIn Spain, between 2016 and 2019, hospitalization episodes for HF were mostly due to diastolic HF. According to the multilevel risk adjustment models, diastolic HF compared to systolic HF was a protective factor for both in-hospital mortality and 30-day cardiovascular readmission.

Change in Hospital Risk-Standardized Stroke Mortality Performance With and Without the Passive Surveillance Stroke Severity Score

Background: Adjustment for baseline stroke severity is necessary for accurate assessment of hospital performance. We evaluated whether adjusting for the Passive Surveillance Stroke SeVerity (PaSSV) score, a measure of stroke severity derived using administrative data, changed hospital-specific estimated 30-day risk-standardized mortality rate (RSMR) after stroke. Methods: We used linked administrative data to identify adults who were hospitalized with ischemic stroke or intracerebral hemorrhage across 157 hospitals in Ontario, Canada between 2014 and 2019. We fitted a random effects logistic regression model using Markov Chain Monte Carlo methods to estimate hospital-specific 30-day RSMR and 95% credible intervals with adjustment for age, sex, Charlson comorbidity index, and stroke type. In a separate model, we additionally adjusted for stroke severity using PaSSV. Hospitals were defined as low-performing, average-performing, or high-performing depending on whether the RSMR and 95% credible interval were above, overlapping, or below the cohort’s crude mortality rate. Results: We identified 65,082 patients [48.0% were female, the median age (25th,75th percentiles) was 76 years (65,84), and 86.4% had an ischemic stroke]. The crude 30-day all-cause mortality rate was 14.1%. The inclusion of PaSSV in the model reclassified 18.5% (n=29) of the hospitals. Of the 143 hospitals initially classified as average-performing, after adjustment for PaSSV, 20 were reclassified as high-performing and 8 were reclassified as low-performing. Of the 4 hospitals initially classified as low-performing, 1 was reclassified as high-performing. All 10 hospitals initially classified as high-performing remained unchanged. Conclusion: PaSSV may be useful for risk-adjusting mortality when comparing hospital performance. External validation of our findings in other jurisdictions is needed.

Multilevel Quality Indicators

Background: Quality indicators are frequently used to assess the performance of health care providers, in particular hospitals. Established approaches to the design of such indicators are subject to distortions due to indirect standardization and high variance of estimators. Indicators for geographical regions are rarely considered. Objectives: To develop and evaluate a methodology of multilevel quality indicators (MQIs) for both health care providers and geographical regions. Research Design: We formally derived MQIs from a statistical multilevel model, which may include characteristics of patients, providers, and regions. We used Monte Carlo simulation to assess the performance of MQIs relative to established approaches based on the standardized mortality/morbidity ratio (SMR) and the risk-standardized mortality rate (RSMR). Measures: Rank correlation between true provider/region effects and quality indicator estimates; shares of the 10% best and 10% worst providers identified by the quality indicators. Results: The proposed MQIs are (1) standardized hospital outcome rate (SHOR), (2) regional SHOR, and (3) regional standardized patient outcome rate. Monte Carlo simulations indicated that the SHOR provides substantially better estimates of provider performance than the SMR and risk-standardized mortality rate in almost all scenarios. The regional standardized patient outcome rate was slightly more stable than the regional SMR. We also found that modeling of regional characteristics generally improves the adequacy of provider-level estimates. Conclusions: MQIs methodology facilitates adequate and efficient estimation of quality indicators for both health care providers and geographical regions.

Sex-based analysis of NSTEMI processes of care and outcomes by hospital: a nationwide cohort study

Abstract Background Contemporary studies have demonstrated that in non-ST-segment elevation myocardial infarction (NSTEMI), processes of care vary significantly according to biological sex. Little is known regarding variation in practice between geographical areas and individual centers. Methods &amp; Results We identified 305,014 admissions with NSTEMI in the United Kingdom (UK) Myocardial Infarction National Audit Project (MINAP), 2010-2017, including female sex (n = 110,209). Females presented significantly older (77y vs. 69y, P&amp;lt;0.001), were more likely to be Caucasian (93% vs. 91%, P&amp;lt;0.001) and less likely to be current smokers (18% vs. 24%, P&amp;lt;0.001). Females were less frequently treated with GDMT after NSTEMI, less frequently managed with an invasive coronary angiogram (ICA) (58% vs. 75%, P&amp;lt;0.001) during index admission and less frequently underwent PCI (35% vs. 49%, P&amp;lt;0.001) or CABG surgery (5% vs. 9%, P&amp;lt;0.001) compared to males. Structural process of care differed between the sexes, with a lower proportion of females being treated on a dedicated cardiology ward (48% vs. 56%, P&amp;lt;0.001) or admitted under a attending cardiologist (44% vs. 52%, P&amp;lt;0.001). In our hospital-clustered analysis, we show a positive correlation between the risk-standardized mortality rates (RSMR) and increasing proportion of women treated for NSTEMI (R2=0.17, P&amp;lt;0.001). There was a clear negative correlation between the proportion of females who had an optimum opportunity-based quality indicator score (surrogate for optimum process of care) during their admission and RSMR (R2 =0.22, P&amp;lt;0.001), with a far weaker correlation in males (R2 =0.08, P&amp;lt;0.001). Conclusion There was a significant in variation of the management of patients with NSTEMI according to sex, with widespread geographical variation. Structural changes are likely required to enable successful change for female patients.

Premature mortality risk in individuals with convulsive epilepsy: Results from a longitudinal, prospective, population-based study

ObjectiveTo assess premature mortality and identify associated risk factors among individuals with convulsive epilepsy in resource-poor settings using a longitudinal, prospective, population-based approach. MethodThe study recruited people with convulsive epilepsy who underwent assessment and management of epilepsy at primary healthcare centers in rural Northwest China, including newly diagnosed individuals and previously identified prevalent cases. All participants were confirmed to have epilepsy by neurologists according to strict criteria and were followed up monthly by primary care physicians. Demographic data and cause of death (COD) were obtained from death certificates or verbal autopsies conducted by neurologists, following the International Classification of Diseases, 10th Edition. The standardized mortality ratio (SMR) and proportionate mortality ratio (PMR) for each cause of death were estimated using the Cause-Of-Death Surveillance Dataset of China (2020). Survival analysis was used to identify risk factors associated with all-cause mortality and death directly due to epilepsy. ResultsDuring 5.9 years of follow-up with 40,947 person-years, there were 781 (11.2%) deaths among 6967 participants. The risk of premature death in people with convulsive epilepsy was 2.7-fold higher than that in the general population. Young participants had a significantly higher risk (standardized mortality ratio 26.5–52.5) of premature death. The proportionate mortality ratio was higher for cerebrovascular disease (15%), sudden unexpected death in epilepsy (SUDEP) (13.4%), cardiovascular disease (11.7%), status epilepsy (SE) (11.3%), and epilepsy-related accidents (14.0%) than other premature mortality cause of deaths. Additionally, the highest standardized proportional mortality ratio (SPMR) was observed from drowning in all cause of death (10.4, 95% confidence interval [CI]: 7.6–13.8), followed by burning (9.0, 95% CI: 3.7–18.9). Factors that increased the risk of all-cause mortality included male sex, late age of onset, short disease duration, high body mass index, monotherapy, and the frequency of generalized tonic-clonic seizures (GTCS). High frequency of generalized tonic-clonic seizures (> 3 attacks in the last year) was an independent risk factor for premature death directly due to epilepsy (including sudden unexpected death in epilepsy, status epilepsy, and epilepsy-related accidents), while early age of onset (≤ 14 years) and long duration of epilepsy (> 20 years) were independent risk factors for sudden unexpected death in epilepsy. In addition, short duration of epilepsy (≤ 20 years) was an independent risk factor for status epilepsy. ConclusionsThis study demonstrated that individuals with poorly controlled seizures are more likely to experience premature death, with most deaths being epilepsy-related and preventable. These findings underline the importance of effective seizure treatment and the potential impact on reducing premature mortality among people with convulsive epilepsy.

Association Between Emergency Medical Service Agency Volume and Mortality in Trauma Patients.

The aim of this study was to evaluate the association of annual trauma patient volume on outcomes for emergency medical services (EMS) agencies. Regionalization of trauma care saves lives. The underlying concept driving this is a volume-outcome relationship. EMS are the entry point to the trauma system, yet it is unknown if a volume-outcome relationship exists for EMS. A retrospective analysis of prospective cohort including 8 trauma centers and 20 EMS air medical and metropolitan ground transport agencies. Patients 18 to 90 years old with injury severity scores ≥9 transported from the scene were included. Patient and agency-level risk-adjusted regression determined the association between EMS agency trauma patient volume and early mortality. A total of 33,511 were included with a median EMS agency volume of 374 patients annually (interquartile range: 90-580). Each 50-patient increase in EMS agency volume was associated with 5% decreased odds of 6-hour mortality (adjusted odds ratio=0.95; 95% CI: 0.92-0.99, P =0.03) and 3% decreased odds of 24-hour mortality (adjusted odds ratio=0.97; 95% CI: 0.95-0.99, P =0.04). Prespecified subgroup analysis showed EMS agency volume was associated with reduced odds of mortality for patients with prehospital shock, requiring prehospital airway placement, undergoing air medical transport, and those with traumatic brain injury. Agency-level analysis demonstrated that high-volume (>374 patients/year) EMS agencies had a significantly lower risk-standardized 6-hour mortality rate than low-volume (<374 patients/year) EMS agencies (1.9% vs 4.8%, P <0.01). A higher volume of trauma patients transported at the EMS agency level is associated with improved early mortality. Further investigation of this volume-outcome relationship is necessary to leverage quality improvement, benchmarking, and educational initiatives.

Association of short-term hospital-level outcome metrics with 1-year mortality and recurrence for US Medicare beneficiaries with ischemic stroke.

Whether stroke patients treated at hospitals with better short-term outcome metrics have better long-term outcomes is unknown. We investigated whether treatment at US hospitals with better 30-day hospital-level stroke outcome metrics was associated with better 1-year outcomes, including reduced mortality and recurrent stroke, for patients after ischemic stroke. This cohort study included Medicare fee-for-service beneficiaries aged ≥65 years discharged alive from US hospitals with a principal diagnosis of ischemic stroke from 07/01/2015 to 12/31/2018. We categorized patients by the treating hospital's performance on the CMS hospital-specific 30-day risk-standardized all-cause mortality and readmission measures for ischemic stroke from 07/01/2012 to 06/30/2015: Low-Low (both CMS mortality and readmission rates for the hospital were <25th percentile of national rates), High-High (both >75th percentile), and Intermediate (all other hospitals). We balanced characteristics between hospital performance categories using stabilized inverse probability weights (IPW) based on patient demographic and clinical factors. We fit Cox models assessing patient risks of 1-year all-cause mortality and ischemic stroke recurrence across hospital performance categories, weighted by the IPW and accounting for competing risks. There were 595,929 stroke patients (mean age 78.9±8.8 years, 54.4% women) discharged from 2,563 hospitals (134 Low-Low, 2288 Intermediate, 141 High-High). For Low-Low, Intermediate, and High-High hospitals, respectively, 1-year mortality rates were 23.8% (95% confidence interval [CI] 23.3%-24.3%), 25.2% (25.1%-25.3%), and 26.5% (26.1%-26.9%), and recurrence rates were 8.0% (7.6%-8.3%), 7.9% (7.8%-8.0%), and 8.0% (7.7%-8.3%). Compared with patients treated at High-High hospitals, those treated at Low-Low and Intermediate hospitals, respectively, had 15% (hazard ratio 0.85; 95% CI 0.82-0.87) and 9% (0.91; 0.89-0.93) lower risks of 1-year mortality but no difference in recurrence. Ischemic stroke patients treated at hospitals with better CMS short-term outcome metrics had lower risks of post-discharge 1-year mortality, but similar recurrent stroke rates, compared with patients treated at other hospitals.

Primary Percutaneous Coronary Intervention in Patients With Spontaneous Coronary Artery Dissection vs Coronary Artery Disease

BackgroundSpontaneous coronary artery dissection (SCAD) is a rare cause of acute myocardial infarction. Revascularization in SCAD remains very challenging and therefore is not recommended as the initial management strategy in stable SCAD without high-risk features. ObjectivesThe aim of this study was to compare in-hospital mortality and 30-day readmission rates between patients with SCAD with ST-segment elevation myocardial infarction (STEMI) treated with primary percutaneous coronary intervention (PPCI) and patients with STEMI without SCAD undergoing PPCI. MethodsThis study was conducted using the administrative minimum dataset of the Spanish National Health System (2016-2020). Risk-standardized in-hospital mortality ratios and readmission ratios were calculated, and results were adjusted using propensity score (PS) analyses. ResultsA total of 65,957 episodes of PPCI were identified after exclusions. The crude in-hospital mortality rate was 4.8%. Of these, 315 (0.5%) were SCAD PPCI and 65,642 were non-SCAD PPCI. SCAD PPCI patients were younger and more frequently women than non-SCAD PPCI patients. Crude mortality (5.7% vs 4.8%), risk-standardized in-hospital mortality ratio (5.3% vs 5.3%), and PS-adjusted (315 pairs) mortality (5.7% vs 5.7%) were similar in SCAD PPCI and non-SCAD PPCI patients. In addition, crude (3% vs 3.3%) and PS-adjusted (297 pairs) 30-day readmission rates (3% vs 4%) were also similar in both groups. ConclusionsPPCI, when indicated in patients with STEMI and SCAD, has similar in-hospital mortality and 30-day readmission rates compared with PPCI for atherothrombotic STEMI. These findings support the value of PPCI in selected patients with SCAD.

Relationship Between In-Hospital Adverse Events and Hospital Performance on 30-Day All-cause Mortality and Readmission for Patients With Heart Failure.

Hospitals with high mortality and readmission rates for patients with heart failure (HF) might also perform poorly in other quality concepts. We sought to evaluate the association between hospital performance on mortality and readmission with hospital performance rates of safety adverse events. This cross-sectional study linked the 2009 to 2019 patient-level adverse events data from the Medicare Patient Safety Monitoring System, a randomly selected medical records-abstracted patient safety database, to the 2005 to 2016 hospital-level HF-specific 30-day all-cause mortality and readmissions data from the United States Centers for Medicare & Medicaid Services. Hospitals were classified to one of 3 performance categories based on their risk-standardized 30-day all-cause mortality and readmission rates: better (both in <25th percentile), worse (both >75th percentile), and average (otherwise). Our main outcome was the occurrence (yes/no) of one or more adverse events during hospitalization. A mixed-effect model was fit to assess the relationship between a patient's risk of having adverse events and hospital performance categories, adjusted for patient and hospital characteristics. The study included 39 597 patients with HF from 3108 hospitals, of which 252 hospitals (8.1%) and 215 (6.9%) were in the better and worse categories, respectively. The rate of patients with one or more adverse events during a hospitalization was 12.5% (95% CI, 12.1-12.8). Compared with patients admitted to better hospitals, patients admitted to worse hospitals had a higher risk of one or more hospital-acquired adverse events (adjusted risk ratio, 1.24 [95% CI, 1.06-1.44]). Patients admitted with HF to hospitals with high 30-day all-cause mortality and readmission rates had a higher risk of in-hospital adverse events. There may be common quality issues among these 3 measure concepts in these hospitals that produce poor performance for patients with HF.

Clinical Use of CathPCI Registry Risk Score and Its Validation to Predict Long-Term Mortality

Risk models to estimate percutaneous coronary intervention (PCI) mortality have limited value in complex high-risk patients. However, it was improved by a recently developed bedside model to predict in-hospital mortality using data from the American College of Cardiology CathPCI Registry that included 706,263 patients. The median risk-standardized in-hospital mortality rate was 1.9%. In an attempt to validate this model in patients admitted because of acute coronary ischemia to predict in-hospital, 30-day, and 1-year mortality, we applied the proposed risk score to the study population of the Acute Coronary Syndrome Israeli Survey (ACSIS). This study was conducted for 2 months in 2018 and included all patients admitted to 25 coronary care units and cardiology departments in Israel. The ACSIS included 1,155 patients admitted because of acute myocardial infarction and who underwent PCI. In-hospital, 30-day, and 1-year mortality were 2.3%, 3.1%, and 6.2%, respectively. The CathPCI risk score yielded an area under the receiver operating characteristic curve of 0.96 (95% confidence interval [CI] 0.94 to 0.99) for in-hospital mortality; 0.96 (95% CI 0.94 to 0.98) for the 30-day mortality, and 0.88 (95% CI 0.83 to 0.93) for the 1-year mortality. The current model also included frail patients, and those with aortic stenosis, refractory shock, and after cardiac arrest. In conclusion, the CathPCI Registry risk score was validated using data from the ACSIS. Because the ACSIS population comprised patients with acute ischemia including those with high-risk features this model demonstrates a wider scope of application compared with previous ones. In addition, the model seems to be suitable to predict also the 30-day and 1-year mortality.

Trends in Short-, Intermediate-, and Long-Term Mortality Following Hospitalization for Myocardial Infarction Among Medicare Beneficiaries, 2008 to 2018.

Background Advances in technology and care quality have transformed the care of acute myocardial infarction (AMI), but little is known about trends in mortality rates across separate time periods after hospitalization. Methods and Results We identified all Medicare fee-for-service beneficiaries hospitalized with incident AMI from 2008 to 2018. We calculated unadjusted mortality rates by dividing the number of all-cause deaths by the number of patients with incident AMI for the following time periods: acute (in hospital), post acute (0-30 days after hospital discharge), short term (31 days to 1 year after discharge), intermediate term (1-2 years after discharge), and long term (2-3 years after discharge). Each period was considered separately (ie, patients who died during one period were not counted in subsequent periods). Using logistic regression to account for differences in patient characteristics, we calculated annual risk standardized mortality ratios defined as observed over expected mortality based on 2008 rates. Among 768 084 patients with incident AMI (mean age 81 years, 48% male, 87% White), declines in observed-to-expected mortality ratios were observed for each time period: acute (0.68 [95% CI, 0.66-0.71]), postacute (0.72 [95% CI, 0.71-0.75]), short term (0.77 [95% CI, 0.75-0.78]), intermediate term (0.79 [95% CI, 0.77-0.81]), and long term (0.77 [95% CI, 0.75-0.79]). Declines were observed both for patients with and without ST-segment-elevation AMI. Conclusions For patients with incident AMI, there have been improvements in mortality rates across periods spanning the hospital stay through 3 years after discharge, reflecting advances in AMI care from hospitalization through long-term outpatient follow-up.

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

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. 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. 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. 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.