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Medicare hospital core process measures have improved over time, but little is known about how the distribution of performance across hospitals has changed, particularly among the lowest performing hospitals.

Understanding both cost and quality across institutions is a critical first step to illuminating the value of care purchased by Medicare. Under contract with the Centers for Medicare and Medicaid Services, we developed a method for profiling hospitals by 30-day episode-of-care costs (payments for Medicare beneficiaries) for acute myocardial infarction (AMI).

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Recent studies show an association between neighborhood-level measures of socioeconomic status (SES) and outcomes for patients with heart failure. We do not know whether neighborhood SES has a primary effect or is a marker for individual SES.

Risk-standardized measures of hospital outcomes reported by the Centers for Medicare and Medicaid Services include Medicare fee-for-service (FFS) patients and exclude Medicare Advantage (MA) patients due to data availability. MA penetration varies greatly nationwide and seems to be associated with increased FFS population risk. Whether variation in MA penetration affects the performance on the Centers for Medicare and Medicaid Service measures is unknown.

Risk-standardized hospital readmission rates are used as publicly reported measures reflecting quality of care. Valid risk-standardized models adjust for differences in patient-level factors across hospitals. We conducted a systematic review of peer-reviewed literature to identify models that compare hospital-level poststroke readmission rates, evaluate patient-level risk scores predicting readmission, or describe patient and process-of-care predictors of readmission after stroke.

Patient outcomes provide a critical perspective on quality of care. The Centers for Medicare and Medicaid Services (CMS) is publicly reporting hospital 30-day risk-standardized mortality rates (RSMRs) and risk-standardized readmission rates (RSRRs) for patients hospitalized with acute myocardial infarction (AMI) and heart failure (HF). We provide a national perspective on hospital performance for the 2010 release of these measures.

Use of more than one health care system to obtain care is common among adults receiving care within the Veterans Affairs (VA) medical system. It is not known what effect using care from multiple sources has on the quality of care patients receive.

IMPORTANCE: Present-on-admission (POA) indicators in administrative claims data allow researchers to distinguish between preexisting conditions and those acquired during a hospital stay. The impact of adding POA information to claims-based measures of hospital quality has not yet been investigated to better understand patient underlying risk factors in the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision setting. OBJECTIVE: To assess POA indicator use on Medicare claims and to assess the hospital- and patient-level outcomes associated with incorporating POA indicators in identifying risk factors for publicly reported outcome measures used by the Centers for Medicare & Medicaid Services (CMS). DESIGN, SETTING, AND PARTICIPANTS: This comparative effectiveness study used national CMS claims data between July 1, 2015, and June 30, 2018. Six hospital quality measures assessing readmission and mortality outcomes were modified to include POA indicators in risk adjustment models. The models using POA were then compared with models using the existing complications-of-care algorithm to evaluate changes in risk model performance. Patient claims data were included for all Medicare fee-for-service and Veterans Administration beneficiaries aged 65 years or older with inpatient hospitalizations for acute myocardial infarction, heart failure, or pneumonia within the measurement period. Data were analyzed between September 2019 and March 2020. MAIN OUTCOMES AND MEASURES: Changes in patient-level (C statistics) and hospital-level (quintile shifts in risk-standardized outcome rates) model performance after including POA indicators in risk adjustment. RESULTS: Data from a total of 6?027?988 index admissions were included for analysis, ranging from 491?366 admissions (269?209 [54.8%] men; mean [SD] age, 78.2 [8.3] years) for the acute myocardial infarction mortality outcome measure to 1?395?870 admissions (677?158 [48.5%] men; mean [SD] age, 80.3 [8.7] years) for the pneumonia readmission measure. Use of POA indicators was associated with improvements in risk adjustment model performance, particularly for mortality measures (eg, the C statistic increased from 0.728 [95% CI, 0.726-0.730] to 0.774 [95% CI, 0.773-0.776] when incorporating POA indicators into the acute myocardial infarction mortality measure). CONCLUSIONS AND RELEVANCE: The findings of this quality improvement study suggest that leveraging POA indicators in the risk adjustment methodology for hospital quality outcome measures may help to more fully capture patients’ risk factors and improve overall model performance. Incorporating POA indicators does not require extra effort on the part of hospitals and would be easy to implement in publicly reported quality outcome measures.

ObjectivesTo determine whether patients discharged after hospital admissions for conditions covered by national readmission programs who received care in emergency departments or observation units but were not readmitted within 30 days had an increased risk of death and to evaluate temporal trends in post-discharge acute care utilization in inpatient units, emergency departments, and observation units for these patients.DesignRetrospective cohort study.SettingMedicare claims data for 2008-16 in the United States.ParticipantsPatients aged 65 or older admitted to hospital with heart failure, acute myocardial infarction, or pneumonia—conditions included in the US Hospital Readmissions Reduction Program.Main outcome measuresPost-discharge 30 day mortality according to patients’ 30 day acute care utilization; acute care utilization in inpatient and observation units and the emergency department during the 30 day and 31-90 day post-discharge period.Results3 772 924 hospital admissions for heart failure, 1 570 113 for acute myocardial infarction, and 3 131 162 for pneumonia occurred. The overall post-discharge 30 day mortality was 8.7% for heart failure, 7.3% for acute myocardial infarction, and 8.4% for pneumonia. Risk adjusted mortality increased annually by 0.05% (95% confidence interval 0.02% to 0.08%) for heart failure, decreased by 0.06% (−0.09% to −0.04%) for acute myocardial infarction, and did not significantly change for pneumonia. Specifically, mortality increased for patients with heart failure who did not utilize any post-discharge acute care, increasing at a rate of 0.08% (0.05% to 0.12%) per year, exceeding the overall absolute annual increase in post-discharge mortality in heart failure, without an increase in mortality in observation units or the emergency department. Concurrent with a reduction in 30 day readmission rates, stays for observation and visits to the emergency department increased across all three conditions during and beyond the 30 day post-discharge period. Overall 30 day post-acute care utilization did not change significantly.ConclusionsThe only condition with increasing mortality through the study period was heart failure; the increase preceded the policy and was not present among patients who received emergency department or observation unit care without admission to hospital. During this period, the overall acute care utilization in the 30 days after discharge significantly decreased for heart failure and pneumonia, but not for acute myocardial infarction.

Objective:One approach to reduce health care spending and improve coordination of care is to pay for an episode of care rather than individual services. Anchoring these episodes around an index hospitalization is sensible because hospitalizations are a leading contributor to rising healthcare costs and an index admission provides a clear time to begin the episode. Understanding which care settings are responsible for a greater proportion of expenditures can inform efforts to improve efficiencies in the care provided. Our objectives were to: 1) characterize total episode payments for two conditions and 2) examine the care settings accounting for the highest proportions of the 30-day episode of care payment.

ObjectivesTo determine whether high performing hospitals with low 30 day risk standardized readmission rates have a lower proportion of readmissions from specific diagnoses and time periods after admission or instead have a similar distribution of readmission diagnoses and timing to lower performing institutions.Design Retrospective cohort study.SettingMedicare beneficiaries in the United States.ParticipantsPatients aged 65 and older who were readmitted within 30 days after hospital admission for heart failure, acute myocardial infarction, or pneumonia in 2007-09. Main outcome measuresReadmission diagnoses were classified with a modified version of the Centers for Medicare and Medicaid Services’ condition categories, and readmission timing was classified by day (0-30) after hospital discharge. Hospital 30 day risk standardized readmission rates over the three years of study were calculated with public reporting methods of the US federal government, and hospitals were categorized with bootstrap analysis as having high, average, or low readmission performance for each index condition. High and low performing hospitals had ≥95% probability of having an interval estimate respectively less than or greater than the national 30 day readmission rate over the three year period of study. All remaining hospitals were considered average performers.ResultsFor readmissions in the 30 days after the index admission, there were 320 003 after 1 291 211 admissions for heart failure (4041 hospitals), 102 536 after 517 827 admissions for acute myocardial infarction (2378 hospitals), and 208 438 after 1 135 932 admissions for pneumonia (4283 hospitals). The distribution of readmissions by diagnosis was similar across categories of hospital performance for all three conditions. High performing hospitals had fewer readmissions for all common diagnoses. Median time to readmission was similar by hospital performance for heart failure and acute myocardial infarction, though was 1.4 days longer among high versus low performing hospitals for pneumonia (P<0.001). Findings were unchanged after adjustment for other hospital characteristics potentially associated with readmission patterns.ConclusionsHigh performing hospitals have proportionately fewer 30 day readmissions without differences in readmission diagnoses and timing, suggesting the possible benefit of strategies that lower risk of readmission globally rather than for specific diagnoses or time periods after hospital stay.

Background:After hospitalization for heart failure (HF) and acute myocardial infarction (AMI), patients experience increased risk of death and hospital readmission. Defining the trajectory and timing of this period of risk may help guide interventions to improve post-discharge outcomes.

Objective:We examined how payments for a 30-day episode-of-care following AMI differ for hospitals with higher and lower proportions of dual-eligible AMI patients.

Objectives:Risk-standardized mortality is increasingly recognized as an important measure of hospital quality. We conducted a systematic review to identify models of morality after stroke developed to profile hospitals or predict patient mortality within 1 year of stroke hospitalization.

Objective:Hospital readmission has been used to risk-stratify patients and profile hospitals by public reporting of performance measures. We conducted a systematic review to identify models developed to compare hospital rates of readmission or predict patients' risk of readmission after stroke, and identify characteristics independently associated with readmission in these models.