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Public reporting of measures of hospital performance is an important component of quality improvement efforts in many countries. However, it can be challenging to provide an overall characterization of hospital performance because there are many measures of quality. In the United States, the Centers for Medicare and Medicaid Services reports over 100 measures that describe various domains of hospital quality, such as outcomes, the patient experience and whether established processes of care are followed. Although individual quality measures provide important insight, it is challenging to understand hospital performance as characterized by multiple quality measures. Accordingly, we developed a novel approach for characterizing hospital performance that highlights the similarities and differences between hospitals and identifies common patterns of hospital performance. Specifically, we built a semi-supervised machine learning algorithm and applied it to the publicly-available quality measures for 1,614 U.S. hospitals to graphically and quantitatively characterize hospital performance. In the resulting visualization, the varying density of hospitals demonstrates that there are key clusters of hospitals that share specific performance profiles, while there are other performance profiles that are rare. Several popular hospital rating systems aggregate some of the quality measures included in our study to produce a composite score; however, hospitals that were top-ranked by such systems were scattered across our visualization, indicating that these top-ranked hospitals actually excel in many different ways. Our application of a novel graph analytics method to data describing U.S. hospitals revealed nuanced differences in performance that are obscured in existing hospital rating systems.

Background— Women have an increased risk of rehospitalization in the immediate postdischarge period; however, few studies have determined how readmission risk dynamically changes on a day-to-day basis over the full year after hospitalization by sex and how these differences compare with the risk for mortality. Methods and Results— We identified >3 000 000 hospitalizations of patients with a principal discharge diagnosis of heart failure, acute myocardial infarction, or pneumonia and estimated sex differences in the daily risk of rehospitalization/death 1 year after discharge from a population of Medicare fee-for-service beneficiaries aged 65 years and older. We calculated the (1) time required for adjusted rehospitalization/mortality risks to decline 50% from maximum values after discharge, (2) time required for the adjusted readmission risk to approach plateau periods of minimal day-to-day change, and (3) extent to which adjusted risks are greater among recently hospitalized patients versus Medicare patients. We identified 1 392 289, 530 771, and 1 125 231 hospitalizations for heart failure, acute myocardial infarction, and pneumonia, respectively. The adjusted daily risk of rehospitalization varied by admitting condition (hazard rate ratio for women versus men, 1.10 for acute myocardial infarction; hazard rate ratio, 1.04 for heart failure; and hazard rate ratio, 0.98 for pneumonia). However, for all conditions, the adjusted daily risk of death was higher among men versus women (hazard rate ratio women versus with men, Conclusions— Although the association of sex with daily risk of rehospitalization varies across conditions, women are at highest risk after discharge for acute myocardial infarction. Future studies should focus on understanding the determinants of sex differences in rehospitalization risk among conditions.

Objectives To characterize the magnitude and duration of risk of rehospitalization according to age after hospitalization for heart failure (HF), acute myocardial infarction (AMI), or pneumonia. Design Retrospective cohort study. Setting U.S. hospitals (n = 4,767). Participants All Medicare fee-for-service beneficiaries aged 65 and older surviving hospitalization for HF, AMI, or pneumonia between October 2012 and December 2013. Measurements Daily risk of first rehospitalization for 1 year after hospital discharge was calculated according to age category (65–74, 75–84, ≥85) after adjustment for sex, race, comorbidities, and median ZIP code income. Time required for adjusted rehospitalization risk to decline 50% from maximum value after discharge, time required for adjusted risk to approach a plateau period of minimal day-to-day change, and degree to which adjusted risk was higher in recently hospitalized individuals than in the general elderly population were identified. Results There were 414,720 hospitalizations for HF, 177,752 for AMI, and 568,304 for pneumonia. The adjusted risk of rehospitalization declined with increasing age after HF hospitalization (P < .001), rose with increasing age after AMI hospitalization (P < .001), and was slightly lower with increasing age after pneumonia hospitalization (P = .002). Adjusted risks of rehospitalization were high beyond 30 days after hospitalization for all ages. Conclusion Although older age has heterogeneous relationships with rehospitalization risk, risk of readmission remains high for an extended time after discharge regardless of age or admitting condition. Condition-specific data on risk can be used to guide discussions on advanced care planning and strategies for longitudinal follow-up after hospitalization.

Importance Payers and policy makers have advocated for transitioning toward value-based payment models. However, little is known about what is the extent of hospital variation in the value of care and whether there are any hospital characteristics associated with high-value care. Objectives To investigate the association between hospital-level 30-day risk-standardized mortality rates (RSMRs) and 30-day risk-standardized payments (RSPs) for acute myocardial infarction (AMI), heart failure (HF), and pneumonia (PNA); to characterize patterns of value in care; and to identify hospital characteristics associated with high-value care (defined by having lower than median RSMRs and RSPs). Design, Setting, and Participants This national cross-sectional study applied weighted linear correlation to investigate the association between hospital RSMRs and RSPs for AMI, HF, and PNA between July 1, 2011, and June 30, 2014, among all hospitals; examined correlations in subgroups of hospitals based on key characteristics; and assessed the proportion and characteristics of hospitals delivering high-value care. The data analysis was completed in October 2017. The setting was acute care hospitals. Participants were Medicare fee-for-service beneficiaries discharged with AMI, HF, or PNA. Main Outcomes and Measures Hospital-level 30-day RSMRs and RSPs for AMI, HF, and PNA. Results The AMI sample consisted of 4339 hospitals with 487 141 hospitalizations for mortality and 462 905 hospitalizations for payment. The HF sample included 4641 hospitals with 960 960 hospitalizations for mortality and 903 721 hospitalizations for payment. The PNA sample contained 4685 hospitals with 952 022 hospitalizations for mortality and 901 764 hospitalizations for payment. The median (interquartile range [IQR]) RSMRs and RSPs, respectively, was 14.3% (IQR, 13.8%-14.8%) and $21 620 (IQR, $20 966-$22 567) for AMI, 11.7% (IQR, 11.0%-12.5%) and $15 139 (IQR, $14 310-$16 118) for HF, and 11.5% (IQR, 10.6%-12.6%) and $14 220 (IQR, $13 342-$15 097) for PNA. There were statistically significant but weak inverse correlations between the RSMRs and RSPs of −0.08 (95% CI, −0.11 to −0.05) for AMI, −0.21 (95% CI, −0.24 to −0.18) for HF, and −0.07 (95% CI, −0.09 to −0.04) for PNA. The largest shared variance between the RSMRs and RSPs was only 4.4% (for HF). The correlations between the RSMRs and RSPs did not differ significantly across teaching status, safety-net status, urban/rural status, or the proportion of patients with low socioeconomic status. Approximately 1 in 4 hospitals (20.9% for AMI, 23.0% for HF, and 23.9% for PNA) had both lower than median RSMRs and RSPs. Conclusions and Relevance These findings suggest that there is significant potential for improvement in the value of AMI, HF, and PNA care and also suggest that high-value care for these conditions is attainable across most hospital types.

Background The risk of rehospitalization is elevated in the immediate post-discharge period and declines over time. It is not known if the extent and timing of risk vary across readmission diagnoses, suggesting that recovery and vulnerability after discharge differ by physiologic system. Objective We compared risk trajectories for major readmission diagnoses in the year after discharge among all Medicare fee-for-service beneficiaries hospitalized with heart failure (HF), acute myocardial infarction (AMI), or pneumonia from 2008–2010. Methods We estimated the daily risk of rehospitalization for 12 major readmission diagnostic categories after accounting for the competing risk of death after discharge. For each diagnostic category, we identified (1) the time required for readmission risk to peak and then decline 50% from maximum values after discharge; (2) the time required for readmission risk to approach plateau periods of minimal day-to-day change; and (3) the extent to which hospitalization risks are higher among patients recently discharged from the hospital compared with the general elderly population. Results Among >3,000,000 hospitalizations, the yearly rate of rehospitalization was 67.0%, 49.5%, and 55.3% after hospitalization for HF, AMI, and pneumonia, respectively. The extent and timing of risk varied by readmission diagnosis and initial admitting condition. Risk of readmission for gastrointestinal bleeding/anemia peaked particularly late after hospital discharge, occurring 10, 6, and 7 days after hospitalization for HF, AMI, and pneumonia, respectively. Risk of readmission for trauma/injury declined particularly slowly, requiring 38, 20, and 38 days to decline by 50% after hospitalization for HF, AMI, and pneumonia, respectively. Conclusions Patterns of vulnerability to different conditions that cause rehospitalization vary by time after hospital discharge. This finding suggests that recovery of various physiologic systems occurs at different rates and that post-discharge interventions to minimize vulnerability to specific conditions should be tailored to their underlying risks.

Objective To characterize the absolute risks for older patients of readmission to hospital and death in the year after hospitalization for heart failure, acute myocardial infarction, or pneumonia. Design Retrospective cohort study. Setting 4767 hospitals caring for Medicare fee for service beneficiaries in the United States, 2008-10. Participants More than 3 million Medicare fee for service beneficiaries, aged 65 years or more, surviving hospitalization for heart failure, acute myocardial infarction, or pneumonia. Main outcome measures Daily absolute risks of first readmission to hospital and death for one year after discharge. To illustrate risk trajectories, we identified the time required for risks of readmission to hospital and death to decline 50% from maximum values after discharge; the time required for risks to approach plateau periods of minimal day to day change, defined as 95% reductions in daily changes in risk from maximum daily declines after discharge; and the extent to which risks are higher among patients recently discharged from hospital compared with the general elderly population. Results Within one year of hospital discharge, readmission to hospital and death, respectively, occurred following 67.4% and 35.8% of hospitalizations for heart failure, 49.9% and 25.1% for acute myocardial infarction, and 55.6% and 31.1% for pneumonia. Risk of first readmission had declined 50% by day 38 after hospitalization for heart failure, day 13 after hospitalization for acute myocardial infarction, and day 25 after hospitalization for pneumonia; risk of death declined 50% by day 11, 6, and 10, respectively. Daily change in risk of first readmission to hospital declined 95% by day 45, 38, and 45; daily change in risk of death declined 95% by day 21, 19, and 21. After hospitalization for heart failure, acute myocardial infarction, or pneumonia, the magnitude of the relative risk for hospital admission over the first 90 days was 8, 6, and 6 times greater than that of the general older population; the relative risk of death was 11, 8, and 10 times greater. Conclusions Risk declines slowly for older patients after hospitalization for heart failure, acute myocardial infarction, or pneumonia and is increased for months. Specific risk trajectories vary by discharge diagnosis and outcome. Patients should remain vigilant for deterioration in health for an extended time after discharge. Health providers can use knowledge of absolute risks and their changes over time to better align interventions designed to reduce adverse outcomes after discharge with the highest risk periods for patients.

Background— Young women ( Methods and Results— We included patients aged 18 to 64 years with a principal diagnosis of acute myocardial infarction. Data were used from the Healthcare Cost and Utilization Project-State Inpatient Database for California (07–09). Readmission diagnoses were categorized by using an aggregated version of the Centers for Medicare and Medicaid Services’ Condition Categories, and readmission timing was determined from the day after discharge. Of 42 518 younger patients with acute myocardial infarction (26.4% female), 4775 (11.2%) had at least 1 readmission. The 30-day all-cause readmission rate was higher for women (15.5% versus 9.7%, P P =0.01). Female sex was associated with a higher rate of 30-day readmission, which persisted after adjustment (hazard ratio, 1.22; 95% confidence interval, 1.15–1.30). There was no significant interaction between age and sex on readmission. Conclusions— In comparison with men, younger women have a higher risk for readmission, even after the adjustment for confounders. The timing of 30-day readmission was similar in women and men, and both sexes were susceptible to a wide range of causes for readmission.

Isuru Ranasinghe and colleagues compare readmissions after hospitalization for heart failure, acute myocardial infarction, or pneumonia in adults aged 18 to 64 years with readmissions in those aged 65 and older. Please see later in the article for the Editors' Summary, Background Patients aged ≥65 years are vulnerable to readmissions due to a transient period of generalized risk after hospitalization. However, whether young and middle-aged adults share a similar risk pattern is uncertain. We compared the rate, timing, and readmission diagnoses following hospitalization for heart failure (HF), acute myocardial infarction (AMI), and pneumonia among patients aged 18–64 years with patients aged ≥65 years. Methods and Findings We used an all-payer administrative dataset from California consisting of all hospitalizations for HF (n = 206,141), AMI (n = 107,256), and pneumonia (n = 199,620) from 2007–2009. The primary outcomes were unplanned 30-day readmission rate, timing of readmission, and readmission diagnoses. Our findings show that the readmission rate among patients aged 18–64 years exceeded the readmission rate in patients aged ≥65 years in the HF cohort (23.4% vs. 22.0%, p, Editors' Summary Background Many elderly people who are admitted to hospital, successfully treated, and discharged are readmitted soon after, often for an unrelated illness. In the US, for example, nearly a fifth of Medicare beneficiaries are readmitted to hospital within 30 days of discharge (Medicare is a national insurance program that primarily pays for health care services for Americans aged 65 and older). Experts have recently coined the term “post-hospital syndrome” for the transient period of increased susceptibility to a range of adverse health events that elderly patients seem to experience and have suggested that exposure to stress during hospital stays may underlie the syndrome. For example, hospital patients frequently have their sleep disrupted because of hospital routines, they are often in pain, they may have insufficient food intake (sometimes because they are waiting for an operation), and they may lose physical conditioning because they are confined to bed. These and other stressors can reduce individuals' natural reserves and increase their vulnerability to a range of illnesses and conditions. Why Was This Study Done? Although stress is one possible determinant of the post-hospital syndrome, the underlying causes and patterns of hospital readmission are generally poorly understood. In particular, it is not known whether the post-hospital syndrome affects young and middle-aged patients as well as elderly patients. Importantly, a better understanding of the post-hospital syndrome is needed before effective strategies to reduce hospital readmissions can be developed. In this retrospective observational cohort study, the researchers compare readmission rates, timing, and diagnoses after hospitalization for heart failure (HF), acute myocardial infarction (AMI; heart attack), and pneumonia among patients aged 18–64 years living in California with readmission rates, timing, and diagnoses among patients aged 65 years or older hospitalized for the same conditions. A retrospective observational cohort study analyzes data that has been already been collected for a group (cohort) of people. Readmission is common among people of all ages who are admitted to hospital for HF, AMI, and pneumonia, and readmissions after hospitalization for these conditions among elderly Medicare patients are used in the US as a measure of hospital quality; hospitals with high readmission rates are subject to a Medicare reimbursement penalty. What Did the Researchers Do and Find? The researchers used the Healthcare Cost and Utilization Project inpatient dataset for California to identify all the hospitalizations for HF, AMI, and pneumonia in California in 2007–2009 and to obtain data on the 30-day unplanned rehospitalization rate, timing of readmission, and readmission diagnoses for the identified patients (more than half a million patients). Nearly 30% of all hospital readmissions after hospitalization for HF, AMI, and pneumonia in California occurred among patients aged 18–64. After hospitalization for AMI, pneumonia, and HF, 11.2%, 14.4%, and 23.4%, respectively, of young and middle-aged patients were readmitted. Notably, the 30-day readmission rate among patients aged 18–64 admitted for HF exceeded the readmission rate among elderly patients admitted for the same condition. After allowing for other factors likely to affect the risk of readmission such as other illnesses, the 30-day readmission risk in patients aged 18–64 was similar to that in patients aged 65 years or older admitted for HF and pneumonia and only marginally lower among patients admitted for AMI. Finally, the timing of readmission was similar in both age groups and diagnoses other than the index admission diagnosis accounted for a substantial proportion of readmissions in both age groups. What Do These Findings Mean? This study shows that after adjusting for differences in patient characteristics, the 30-day hospital readmission rates among young and middle-aged patients after hospitalization for HF, AMI, and pneumonia were similar to those among elderly patients. Moreover, the timing of readmission and the reasons for readmission among young and middle-aged patients were similar to those among elderly patients. These findings may not apply to other US states or to other countries and may not reflect the pattern of hospital readmissions following conditions other than HF, AMI, and pneumonia. Nevertheless, these findings suggest that the post-hospital syndrome affects young and middle-aged as well as elderly patients. Hospital readmission should therefore be considered as a potential problem for people of all ages and broad-based, multidisciplinary strategies that target patients of all ages should be developed to mitigate the risk of hospital readmissions. Additional Information Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001737. The Institute for Healthcare Improvement provides information about reducing avoidable hospital readmissions Information about the US Centers for Medicare & Medicaid Services readmissions reduction program is available An article written by one of the study authors about the post-hospital syndrome is available

Young women (≤55 years) experience a 2-3 fold greater mortality following acute myocardial infarction (AMI), yet it is unknown if they have an increased risk of 30-day all cause readmission, compared with similarly aged men. We sought to (a) examine sex differences in patient characteristics (i.e

Importance To better guide strategies intended to reduce high rates of 30-day readmission after hospitalization for heart failure (HF), acute myocardial infarction (MI), or pneumonia, further information is needed about readmission diagnoses, readmission timing, and the relationship of both to patient age, sex, and race. Objective To examine readmission diagnoses and timing among Medicare beneficiaries readmitted within 30 days after hospitalization for HF, acute MI, or pneumonia. Design, Setting, and Patients We analyzed 2007-2009 Medicare fee-for-service claims data to identify patterns of 30-day readmission by patient demographic characteristics and time after hospitalization for HF, acute MI, or pneumonia. Readmission diagnoses were categorized using an aggregated version of the Centers for Medicare & Medicaid Services' Condition Categories. Readmission timing was determined by day after discharge. Main Outcome Measures We examined the percentage of 30-day readmissions occurring on each day (0-30) after discharge; the most common readmission diagnoses occurring during cumulative periods (days 0-3, 0-7, 0-15, and 0-30) and consecutive periods (days 0-3, 4-7, 8-15, and 16-30) after hospitalization; median time to readmission for common readmission diagnoses; and the relationship between patient demographic characteristics and readmission diagnoses and timing. Results From 2007 through 2009, we identified 329 308 30-day readmissions after 1 330 157 HF hospitalizations (24.8% readmitted), 108 992 30-day readmissions after 548 834 acute MI hospitalizations (19.9% readmitted), and 214 239 30-day readmissions after 1 168 624 pneumonia hospitalizations (18.3% readmitted). The proportion of patients readmitted for the same condition was 35.2% after the index HF hospitalization, 10.0% after the index acute MI hospitalization, and 22.4% after the index pneumonia hospitalization. Of all readmissions within 30 days of hospitalization, the majority occurred within 15 days of hospitalization: 61.0%, HF cohort; 67.6%, acute MI cohort; and 62.6%, pneumonia cohort. The diverse spectrum of readmission diagnoses was largely similar in both cumulative and consecutive periods after discharge. Median time to 30-day readmission was 12 days for patients initially hospitalized for HF, 10 days for patients initially hospitalized for acute MI, and 12 days for patients initially hospitalized for pneumonia and was comparable across common readmission diagnoses. Neither readmission diagnoses nor timing substantively varied by age, sex, or race. Conclusion and Relevance Among Medicare fee-for-service beneficiaries hospitalized for HF, acute MI, or pneumonia, 30-day readmissions were frequent throughout the month after hospitalization and resulted from a similar spectrum of readmission diagnoses regardless of age, sex, race, or time after discharge.

Objectives To 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. Setting Medicare beneficiaries in the United States. Participants Patients 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 measures Readmission 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. Results For 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