Home Health Care After Skilled Nursing Facility Discharge Following Heart Failure Hospitalization.

BACKGROUND/OBJECTIVE: Heart failure (HF) readmission rates have plateaued despite scrutiny of hospital discharge practices. Many HF patients are discharged to skilled nursing facility (SNF) after hospitalization before returning home. Home healthcare (HHC) services received during the additional transition from SNF to home may affect readmission risk. Here, we examined whether receipt of HHC affects readmission risk during the transition from SNF to home following HF hospitalization. DESIGN: Retrospective cohort study. SETTING: Fee-for-service Medicare data, 2012 to 2015. PARTICIPANTS: Beneficiaries, aged 65 years and older, hospitalized with HF who were subsequently discharged to SNF and then discharged home. MEASUREMENTS: The primary outcome was unplanned readmission within 30 days of discharge to home from SNF. We compared time to readmission between those with and without HHC services using a Cox model. RESULTS: Of 67 585 HF hospitalizations discharged to SNFs and subsequently discharged home, 13 257 (19.6%) were discharged with HHC, and 54 328 (80.4%) were discharged without HHC. Patients discharged home from SNFs with HHC had lower 30-day readmission rates than patients discharged without HHC (22.8% vs 24.5%; P < .0001) and a longer time to readmission. In an adjusted model, the hazard for readmission was 0.91 (0.86-0.95) with receipt of HHC. CONCLUSIONS: Recipients of HHC were less likely to be readmitted within 30 days vs those discharged home without HHC. This is unexpected, as patients discharged with HHC likely have more functional impairments. Since patients requiring a SNF stay after hospital discharge may have additional needs, they may particularly benefit from restorative therapy through HHC; however, only approximately 20% received such services. J Am Geriatr Soc 68:96-102, 2019.

Association Between Insurance Status and Access to Hospital Care in Emergency Department Disposition.

Importance: Studies of public hospitals have reported increasing incidence of emergency department (ED) transfers of uninsured patients for hospitalization, which is perceived to be associated with financial incentives. Objective: To examine the differences in risk-adjusted transfer and discharge rates by patient insurance status among hospitals capable of providing critical care. Design, Setting, and Participants: A cross-sectional analysis of the 2015 National Emergency Department Sample was conducted, including visits between January 2015 and December 2015. Adult ED visits throughout 2015 (n = 215 028) for the 3 common medical conditions of pneumonia, chronic obstructive pulmonary disease, and asthma, at hospitals with intensive care capabilities were included. Only hospitals with advanced critical care capabilities for pulmonary care were included. Main Outcomes and Measures: The primary outcomes were patient-level and hospital-level risk-adjusted ED discharges, ED transfers, and hospital admissions. Adjusted odds of discharge or transfer compared with admission among uninsured patients, Medicaid and Medicare beneficiaries, and privately insured patients are reported. Hospital ownership status was used for the secondary analysis. Results: Of the 30 542 691 ED visits to 953 hospitals included in the 2015 National Emergency Department Sample, 215 028 visits (0.7%) were for acute pulmonary diseases to 160 intensive care-capable hospitals. These visits were made by patients with a median (interquartile range [IQR]) age of 55 (40-71) years and who were predominantly female (124 931 [58.1%]). Substantial variation in unadjusted and risk-standardized ED discharge, ED transfer, and hospital admission rates was found across EDs. Compared with privately insured patients, uninsured patients were more likely to be discharged (odds ratio [OR], 1.66; 95% CI, 1.57-1.76) and transferred (adjusted OR [aOR], 2.41; 95% CI, 2.08-2.79). Medicaid beneficiaries had comparable odds of discharge (aOR, 1.00; 95% CI, 0.97-1.04) but higher odds of transfer (aOR, 1.19; 95% CI, 1.05-1.33). Conclusions and Relevance: After accounting for hospital critical care capability and patient case mix, the study found that uninsured patients and Medicaid beneficiaries with common medical conditions appeared to have higher odds of interhospital transfer.

Risk of Readmission After Discharge From Skilled Nursing Facilities Following Heart Failure Hospitalization: A Retrospective Cohort Study.

OBJECTIVE: Discharge to skilled nursing facilities (SNFs) is common in patients with heart failure (HF). It is unknown whether the transition from SNF to home is risky for these patients. Our objective was to study outcomes for the 30 days after discharge from SNF to home among Medicare patients hospitalized with HF who had subsequent SNF stays of 30 days or less. DESIGN: Retrospective cohort study. SETTING AND PARTICIPANTS: All Medicare fee-for-service beneficiaries 65 and older admitted during 2012-2015 with a HF diagnosis discharged to SNF then subsequently discharged home. MEASURES: Patients were followed for 30 days following SNF discharge. We categorized patients by SNF length of stay: 1 to 6 days, 7 to 13 days, and 14 to 30 days. For each group, we modeled time to a composite outcome of unplanned readmission or death after SNF discharge. Our model examined 0-2 days and 3-30 days post-SNF discharge. RESULTS: Our study included 67,585 HF hospitalizations discharged to SNF and subsequently discharged home. Overall, 16,333 (24.2%) SNF discharges to home were readmitted within 30 days of SNF discharge. The hazard rate of the composite outcome for each group was significantly increased on days 0 to 2 after SNF discharge compared to days 3 to 30, as reflected in their hazard rate ratios: for patients with SNF length of stay 1 to 6 days, 4.60 (4.23-5.00); SNF length of stay 7 to 13 days, 2.61 (2.45-2.78); SNF length of stay 14 to 30 days, 1.70 (1.62-1.78). CONCLUSIONS/IMPLICATIONS: The hazard rate of readmission after SNF discharge following HF hospitalization is highest during the first 2 days home. This risk attenuated with longer SNF length of stay. Interventions to improve postdischarge outcomes have primarily focused on hospital discharge. This evidence suggests that interventions to reduce readmissions may be more effective if they also incorporate the SNF-to-home transition.

Association of Income Disparities with Patient-Reported Healthcare Experience.

BACKGROUND: Disparities in health outcome exist among patients according to socioeconomic status. However, little is known regarding the differences in healthcare experiences across the various levels of income of patients. In a nationally representative US adult population, we evaluate the differences in healthcare experiences based on patient level of income. OBJECTIVES: To evaluate the differences in patient healthcare experiences based on level of income. PATIENTS AND METHODS: We identified 68,447 individuals (mean age, 48 ± 18 years; 55% female) representing 176.8 million US adults, who had an established healthcare provider in the 2010-2013 Medical Expenditure Panel Survey cohort. This retrospective study examined the differences in all five patient-reported healthcare experience measures (access to care, provider responsiveness, patient-provider communication, shared decision-making, and patient satisfaction) under the Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey. We examined the relationship between patient income and their healthcare experience. RESULTS: Overall, 32% of the study participants were high-income earners while 23% had very-low income. Lower income was consistently associated with poor patient report on healthcare experience. Compared with those with high income, very-low-income-earning participants had 1.63 times greater odds (OR 1.63, 95% CI 1.45-1.82) of experiencing difficulty accessing care, had 1.34 times higher odds (OR 1.34, 95% CI 1.25-1.45) of experiencing poor communication, had higher odds (OR 1.68, 95% CI 1.46-1.92) of experiencing delays in healthcare delivery, and were more likely to report poor provider satisfaction (OR 1.48, 95% CI 1.37-1.61). CONCLUSION: Lower income-earning patients have poorer healthcare experience in all aspects of access and quality of care. Targeted policies focusing on improving communication, engagement, and satisfaction are needed to enhance patient healthcare experience for this vulnerable population.

Assessment of Instruments for Measurement of Delirium Severity: A Systematic Review.

Importance: Measurement of delirium severity has been recognized as highly important for tracking prognosis, monitoring response to treatment, and estimating burden of care for patients both during and after hospitalization. Rather than simply rating delirium as present or absent, the ability to quantify its severity would enable development and monitoring of more effective treatment approaches for the condition. Objectives: To present a comprehensive review of delirium severity instruments, conduct a methodologic quality rating of the original validation study of the most commonly used instruments, and select a group of top-rated instruments. Evidence Review: This systematic review was conducted using literature from Embase, PsycINFO, PubMed, Web of Science, and Cumulative Index to Nursing and Allied Health Literature, from January 1, 1974, through March 31, 2017, with the key words delirium, severity, tests, measures, and intensity. Inclusion criteria were original articles assessing delirium severity and using a delirium-specific severity instrument. Final listings of articles were supplemented with hand searches of reference listings to ensure completeness. At least 2 reviewers independently completed each step of the review process: article selection, data extraction, and methodologic quality assessment of relevant articles using a validated rating scale. All discrepancies between raters were resolved by consensus. Findings: Of 9409 articles identified, 228 underwent full text review, and we identified 42 different instruments of delirium severity. Eleven of the 42 tools were multidomain, delirium-specific instruments providing a quantitative rating of delirium severity; these instruments underwent a methodologic quality review. Applying prespecified criteria related to frequency of use, methodologic quality, construct or predictive validity, and broad domain coverage, an expert panel used an iterative modified Delphi process to select 6 final high-quality instruments meeting these criteria: the Confusion Assessment Method-Severity Score, Confusional State Examination, Delirium-O-Meter, Delirium Observation Scale, Delirium Rating Scale, and Memorial Delirium Assessment Scale. Conclusions and Relevance: The 6 instruments identified may enable accurate measurement of delirium severity to improve clinical care for patients with this condition. This work may stimulate increased usage and head-to-head comparison of these instruments.

Admission diagnoses among patients with heart failure: Variation by ACO performance on a measure of risk-standardized acute admission rates.

BACKGROUND: A key quality metric for Accountable Care Organizations (ACOs) is the rate of hospitalization among patients with heart failure (HF). Among this patient population, non-HF-related hospitalizations account for a substantial proportion of admissions. Understanding the types of admissions and the distribution of admission types across ACOs of varying performance may provide important insights for lowering admission rates. METHODS: We examined admission diagnoses among 220 Medicare Shared Savings Program ACOs in 2013. ACOs were stratified into quartiles by their performance on a measure of unplanned risk-standardized acute admission rates (RSAARs) among patients with HF. Using a previously validated algorithm, we categorized admissions by principal discharge diagnosis into: HF, cardiovascular/non-HF, and noncardiovascular. We compared the mean admission rates by admission type as well as the proportion of admission types across RSAAR quartiles (Q1-Q4). RESULTS: Among 220 ACOs caring for 227,356 patients with HF, the median (IQR) RSAARs per 100 person-years ranged from 64.5 (61.7-67.7) in Q1 (best performers) to 94.0 (90.1-99.9) in Q4 (worst performers). The mean admission rates by admission types for ACOs in Q1 compared with Q4 were as follows: HF admissions: 9.8 (2.2) vs 14.6 (2.8) per 100 person years (P < .0001); cardiovascular/non-HF admissions: 11.1 (1.6) vs 15.9 (2.6) per 100 person-years (P < .0001); and noncardiovascular admissions: 42.7 (5.4) vs 69.6 (11.3) per 100 person-years (P < .0001). The proportion of admission due to HF, cardiovascular/non-HF, and noncardiovascular conditions was 15.4%, 17.5%, and 67.1% in Q1 compared with 14.6%, 15.9%, and 69.4% in Q4 (P < .007). CONCLUSIONS: Although ACOs with the best performance on a measure of all-cause admission rates among people with HF tended to have fewer admissions for HF, cardiovascular/non-HF, and noncardiovascular conditions compared with ACOs with the worst performance (highest admission rates), the largest difference in admission rates were for noncardiovascular admission types. Across all ACOs, two-thirds of admissions of patients with HF were for noncardiovascular causes. These findings suggest that comprehensive approaches are needed to reduce the diverse admission types for which HF patients are at risk.

Trends in 30-Day Readmission Rates for Medicare and Non-Medicare Patients in the Era of the Affordable Care Act.

BACKGROUND: Temporal changes in the readmission rates for patient groups and conditions that were not directly under the purview of the Hospital Readmissions Reduction Program (HRRP) can help assess whether efforts to lower readmissions extended beyond targeted patients and conditions. METHODS: Using the Nationwide Readmissions Database (2010-2015), we assessed trends in all-cause readmission rates for 1 of the 3 HRRP conditions (acute myocardial infarction, heart failure, pneumonia) or conditions not targeted by the HRRP in age-insurance groups defined by age group (≥65 years or <65 years) and payer (Medicare, Medicaid, or private insurance). RESULTS: In the group aged ≥65 years, readmission rates for those covered by Medicare, Medicaid, and private insurance decreased annually for acute myocardial infarction (risk-adjusted odds ratio [OR; 95% confidence interval] among Medicare patients, 0.94 [0.94-0.95], among Medicaid patients, 0.93 [0.90-0.97], and among patients with private-insurance, 0.95 [0.93-0.97]); heart failure (ORs, 0.96 [0.96-0.97], 0.96 [0.94-0.98], and 0.97 [0.96-0.99], for the 3 payers, respectively), and pneumonia (ORs, 0.96 [0.96-0.97), 0.94 [0.92-0.96], and 0.96 [0.95-0.97], respectively). Readmission rates also decreased in the group aged <65 years for acute myocardial infarction (ORs: Medicare 0.97 [0.96-0.98], Medicaid 0.94 [0.92-0.95], and private insurance 0.93 [0.92-0.94]), heart failure (ORs, 0.98 [0.97-0.98]: 0.96 [0.96-0.97], and 0.97 [0.95-0.98], for the 3 payers, respectively), and pneumonia (ORs, 0.98 [0.97-0.99], 0.98 [0.97-0.99], and 0.98 [0.97-1.00], respectively). Further, readmission rates decreased significantly for non-target conditions. CONCLUSIONS: There appears to be a systematic improvement in readmission rates for patient groups beyond the population of fee-for-service, older, Medicare beneficiaries included in the HRRP.

Risk Trajectories of Readmission and Death in the First Year after Hospitalization for Chronic Obstructive Pulmonary Disease.

RATIONALE: Characterization of the dynamic nature of posthospital risk in chronic obstructive pulmonary disease (COPD) is needed to provide counseling and plan clinical services. OBJECTIVES: To analyze risk of readmission and death after discharge for COPD among Medicare beneficiaries aged 65 years and older and to determine the association between ventilator support and risk trajectory. METHODS: We computed daily absolute risks of hospital readmission and death for 1 year after discharge for COPD, stratified by ventilator support. We determined the time required for risks to decline by 50% from maximum daily values after discharge and for daily risks to plateau. We compared risks with those found in the general elderly population. MEASUREMENTS AND MAIN RESULTS: Among 2,340,637 hospitalizations, the readmission rate at 1 year was 64.2%, including 63.5%, 66.0%, and 64.1% among those receiving invasive, noninvasive, and no ventilation, respectively. Among 1,283,069 hospitalizations, mortality at 1 year was 26.2%, including 45.7%, 41.8%, and 24.4% among those same respective groups. Daily risk of readmission declined by 50% within 28, 39, and 43 days and plateaued at 46, 54, and 61 days among those receiving invasive, noninvasive, and no ventilation, respectively. Risk of death declined by 50% by 3, 4, and 17 days and plateaued by 21, 18, and 24 days in the same respective groups. Risks of hospitalization and death were significantly higher after discharge for COPD than among the general Medicare population. CONCLUSIONS: Discharge from the hospital is associated with prolonged risks of readmission and death that vary with need for ventilator support. Interventions limited to the first month after discharge may be insufficient to improve longitudinal outcomes.

Association of the Hospital Readmissions Reduction Program With Mortality During and After Hospitalization for Acute Myocardial Infarction, Heart Failure, and Pneumonia.

Importance: The US Hospital Readmissions Reduction Program (HRRP) was associated with reduced readmissions among Medicare beneficiaries hospitalized for acute myocardial infarction (AMI), heart failure (HF), and pneumonia. It is important to assess whether there has been a signal for concomitant harm with an increase in mortality. Objective: To evaluate whether the announcement or the implementation of HRRP was associated with an increase in either in-hospital or 30-day postdischarge mortality following hospitalization for AMI, HF, or pneumonia. Design, Setting, and Participants: In this cohort study, using Medicare data, all hospitalizations for AMI, HF, and pneumonia were identified among fee-for-service Medicare beneficiaries aged 65 years and older from January 1, 2006, to December 31, 2014. These were assessed for changes in trends for risk-adjusted rates of in-hospital and 30-day postdischarge mortality after announcement and implementation of the HRRP using an interrupted time series framework. Analyses were done in November 2017 and December 2017. Exposures: Announcement of the HRRP in March 2010, and implementation of its penalties in October 2012. Main Outcomes and Measures: Monthly risk-adjusted rates of in-hospital and 30-day postdischarge mortality. Results: The sample included 1.7 million AMI, 4 million HF, and 3.5 million pneumonia hospitalizations. Between 2006 and 2014, in-hospital mortality decreased for the 3 conditions (AMI, from 10.4% to 9.7%; HF, from 4.3% to 3.5%; pneumonia, from 5.3% to 4.0%) while 30-day postdischarge mortality decreased from 7.4% to 7.0% for AMI (P for trend < .001), but increased from 7.4% to 9.2% for HF (P for trend < .001) and from 7.6% to 8.6% for pneumonia (P for trend < .001). Before the HRRP announcement, monthly postdischarge mortality was stable for AMI (slope for monthly change, 0.002%; 95% CI, -0.001% to 0.006% per month), and increased by 0.004% (95% CI, 0.000% to 0.007%) per month for HF and by 0.005% (95% CI, 0.002% to 0.008%) per month for pneumonia. There were no inflections in slope around HRRP announcement or implementation (P > .05 for all). In contrast, there were significant negative deflections in slopes for readmission rates at HRRP announcement for all conditions. Conclusions and Relevance: Among Medicare beneficiaries, there was no evidence for an increase in in-hospital or postdischarge mortality associated with HRRP announcement or implementation-a period with substantial reductions in readmissions. The improvement in readmission was therefore not associated with any increase in in-hospital or 30-day postdischarge mortality.

Association of Changing Hospital Readmission Rates With Mortality Rates After Hospital Discharge.

IMPORTANCE: The Affordable Care Act has led to US national reductions in hospital 30-day readmission rates for heart failure (HF), acute myocardial infarction (AMI), and pneumonia. Whether readmission reductions have had the unintended consequence of increasing mortality after hospitalization is unknown. OBJECTIVE: To examine the correlation of paired trends in hospital 30-day readmission rates and hospital 30-day mortality rates after discharge. DESIGN, SETTING, AND PARTICIPANTS: Retrospective study of Medicare fee-for-service beneficiaries aged 65 years or older hospitalized with HF, AMI, or pneumonia from January 1, 2008, through December 31, 2014. EXPOSURE: Thirty-day risk-adjusted readmission rate (RARR). MAIN OUTCOMES AND MEASURES: Thirty-day RARRs and 30-day risk-adjusted mortality rates (RAMRs) after discharge were calculated for each condition in each month at each hospital in 2008 through 2014. Monthly trends in each hospital's 30-day RARRs and 30-day RAMRs after discharge were examined for each condition. The weighted Pearson correlation coefficient was calculated for hospitals' paired monthly trends in 30-day RARRs and 30-day RAMRs after discharge for each condition. RESULTS: In 2008 through 2014, 2 962 554 hospitalizations for HF, 1 229 939 for AMI, and 2 544 530 for pneumonia were identified at 5016, 4772, and 5057 hospitals, respectively. In January 2008, mean hospital 30-day RARRs and 30-day RAMRs after discharge were 24.6% and 8.4% for HF, 19.3% and 7.6% for AMI, and 18.3% and 8.5% for pneumonia. Hospital 30-day RARRs declined in the aggregate across hospitals from 2008 through 2014; monthly changes in RARRs were -0.053% (95% CI, -0.055% to -0.051%) for HF, -0.044% (95% CI, -0.047% to -0.041%) for AMI, and -0.033% (95% CI, -0.035% to -0.031%) for pneumonia. In contrast, monthly aggregate changes across hospitals in hospital 30-day RAMRs after discharge varied by condition: HF, 0.008% (95% CI, 0.007% to 0.010%); AMI, -0.003% (95% CI, -0.005% to -0.001%); and pneumonia, 0.001% (95% CI, -0.001% to 0.003%). However, correlation coefficients in hospitals' paired monthly changes in 30-day RARRs and 30-day RAMRs after discharge were weakly positive: HF, 0.066 (95% CI, 0.036 to 0.096); AMI, 0.067 (95% CI, 0.027 to 0.106); and pneumonia, 0.108 (95% CI, 0.079 to 0.137). Findings were similar in secondary analyses, including with alternate definitions of hospital mortality. CONCLUSIONS AND RELEVANCE: Among Medicare fee-for-service beneficiaries hospitalized for heart failure, acute myocardial infarction, or pneumonia, reductions in hospital 30-day readmission rates were weakly but significantly correlated with reductions in hospital 30-day mortality rates after discharge. These findings do not support increasing postdischarge mortality related to reducing hospital readmissions.

Reductions in Readmission Rates Are Associated With Modest Improvements in Patient-reported Health Gains Following Hip and Knee Replacement in England.

BACKGROUND: Although many hospital readmission reduction initiatives have been introduced globally, health care systems ultimately aim to improve patients' health and well-being. We examined whether the hospitals that report greater success in reducing readmissions also see greater improvements in patient-reported outcomes. RESEARCH DESIGN: We examined hospital groups (Trusts) that provided hip replacement or knee replacement surgery in England between April 2010 and February 2013. For each Trust, we calculated risk-adjusted 30-day readmission rates from administrative datasets. We also obtained changes in patient-reported health between presurgical assessment and 6-month follow-up, using general health EuroQuol five dimensions questionaire (EQ-5D) and EuroQuol visual analogue scales (EQ-VAS) and procedure-specific (Oxford Hip and Knee Scores) measures. Panel models were used to assess whether changes over time in risk-adjusted readmission rates were associated with changes over time in risk-adjusted health gains. RESULTS: Each percentage point reduction in the risk-adjusted readmission rate for hip replacement was associated with an additional health gain of 0.004 for EQ-5D [95% confidence interval (CI), 0.002-0.006], 0.39 for EQ-VAS (95% CI, 0.26-0.52), and 0.32 for Oxford Hip Score (95% CI, 0.15-0.27). Corresponding figures for knee replacement were 0.003 for EQ-5D (95% CI, 0.001-0.004), 0.21 for EQ-VAS (95% CI, 0.12-0.30), and 0.14 in the Oxford Knee Score (95% CI, 0.09-0.20). CONCLUSIONS: Reductions in readmission rates were associated with modest improvements in patients' sense of their health and well-being at the hospital group level. In particular, fears that efforts to reduce readmission rates have had unintended consequences for patients appear to be unfounded.

Outcomes after observation stays among older adult Medicare beneficiaries in the USA: retrospective cohort study.

Objective To characterize rates and trends over time of emergency department treatment-and-discharge stays, repeat observation stays, inpatient stays, any hospital revisit, and death within 30 days of discharge from observation stays.Design Retrospective cohort study.Setting 4750 hospitals in the USA.Participants Nationally representative sample of Medicare fee for service beneficiaries aged 65 or over discharged after 363 037 index observation stays, 2 540 000 index emergency department treatment-and-discharge stays, and 2 667 525 index inpatient stays from 2006-11.Main outcome measures Rates of emergency department treatment-and-discharge stays, observation stays, inpatient stays, any hospital revisit, and death within 30 days of discharge from index observation stays. Rates were compared with corresponding outcomes within 30 days of discharge from both index emergency department treatment-and-discharge stays and index inpatient stays.Results Among 363 037 index observation stays resulting in discharge from 2006-11, 30 day rates of emergency department treatment-and-discharge stays were 8.4%, repeat observation stays were 2.9%, inpatient stays were 11.2%, any hospital revisit was 20.1%, and death was 1.8%. Of all revisits, 49.7% were for inpatient stays. Revisit rates for emergency department treatment-and-discharge stays, repeat observation stays, and any hospital revisit increased from 2006-11 (P<0.001 for trend), while 30 day rates of inpatient stays (P=0.054 for trend) and 30 day mortality (P=0.091 for trend) were both unchanged. Averaged over the study period, 30 day rates of any hospital revisit were similar after discharge from index emergency department treatment-and-discharge stays (19.9%) and index observation stays (20.1%), as was 30 day mortality (1.8% for both). Rates of any hospital revisit (21.8%) and death (5.2%) were highest after discharge from index inpatient stays.Conclusions Hospital revisits are common after discharge from observation stays, frequently result in inpatient hospitalizations, and have increased over time among Medicare beneficiaries. As revisit rates are similar after emergency department and observation stays, strategies shown to enhance emergency department transitional care may be reasonable starting points to improve post-observation outcomes.

Sex Differences in Trajectories of Risk After Rehospitalization for Heart Failure, Acute Myocardial Infarction, or Pneumonia.

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, <1). For both sexes, there was a similar timing of peak daily risk, half daily risk, and reaching plateau. 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.

Patient-Provider Communication and Health Outcomes Among Individuals With Atherosclerotic Cardiovascular Disease in the United States: Medical Expenditure Panel Survey 2010 to 2013.

BACKGROUND: Consumer-reported patient-provider communication (PPC) assessed by Consumer Assessment of Health Plans Survey in ambulatory settings is incorporated as a complementary value metric for patient-centered care of chronic conditions in pay-for-performance programs. In this study, we examine the relationship of PPC with select indicators of patient-centered care in a nationally representative US adult population with established atherosclerotic cardiovascular disease. METHODS AND RESULTS: The study population consisted of a nationally representative sample of 6810 individuals (aged ≥18 years), representing 18.3 million adults with established atherosclerotic cardiovascular disease (self-reported or International Classification of Diseases, Ninth Edition diagnosis) reporting a usual source of care in the 2010 to 2013 pooled Medical Expenditure Panel Survey cohort. Participants responded to questions from Consumer Assessment of Health Plans Survey that assessed PPC, and we developed a weighted PPC composite score using their responses, categorized as 1 (poor), 2 (average), and 3 (optimal). Outcomes of interest were (1) patient-reported outcomes: 12-item Short Form physical/mental health status, (2) quality of care measures: statin and ASA use, (3) healthcare resource utilization: emergency room visits and hospital stays, and (4) total annual and out-of-pocket healthcare expenditures. Atherosclerotic cardiovascular disease patients reporting poor versus optimal were over 2-fold more likely to report poor outcomes; 52% and 26% more likely to report that they are not on statin and aspirin, respectively, had a significantly greater utilization of health resources (odds ratio≥2 emergency room visit, 1.41 [95% confidence interval, 1.09-1.81]; odds ratio≥2 hospitalization, 1.36 [95% confidence interval, 1.04-1.79]), as well as an estimated $1243 ($127-$2359) higher annual healthcare expenditure. CONCLUSIONS: This study reveals a strong relationship between PPC and patient-reported outcomes, utilization of evidence-based therapies, healthcare resource utilization, and expenditures among those with established atherosclerotic cardiovascular disease.

Length of Stay From the Hospital Perspective: Practice of Early Discharge Is Not Associated With Increased Readmission Risk After Lung Cancer Surgery.

OBJECTIVE: To determine if hospitals that routinely discharge patients early after lobectomy have increased readmissions. BACKGROUND: Hospitals are increasingly motivated to reduce length of stay (LOS) after lung cancer surgery, yet it is unclear if a routine of early discharge is associated with increased readmissions. The relationship between hospital discharge practices and readmission rates is therefore of tremendous clinical and financial importance. METHODS: The National Cancer Database was queried for patients undergoing lobectomy for lung cancer from 2004 to 2013 at Commission on Cancer-accredited hospitals, which performed at least 25 lobectomies in a 2-year period. Facility discharge practices were characterized by a facility's median LOS relative to the median LOS for all patients in that same time period. RESULTS: In all, 59,734 patients met inclusion criteria; 2687 (4.5%) experienced an unplanned readmission. In a hierarchical logistic regression model, a routine of early discharge (defined as a facility's tendency to discharge patients faster than the population median in the same time period) was not associated with increased risk of readmission (odds ratio 1.12, 95% confidence interval 0.97-1.28, P = 0.12). In a risk-adjusted hospital readmission rate analysis, hospitals that discharged patients early did not experience more readmissions (P = 0.39). The lack of effect of early discharge practices on readmission rates was observed for both minimally invasive and thoracotomy approaches. CONCLUSIONS: It is possible for hospitals to develop early discharge practices without increasing readmissions. Further study is needed to identify the critical practice elements that have enabled hospitals to aggressively discharge patients without increasing readmission risk.

Association Between Hospital Penalty Status Under the Hospital Readmission Reduction Program and Readmission Rates for Target and Nontarget Conditions.

Importance: Readmission rates declined after announcement of the Hospital Readmission Reduction Program (HRRP), which penalizes hospitals for excess readmissions for acute myocardial infarction (AMI), heart failure (HF), and pneumonia. Objective: To compare trends in readmission rates for target and nontarget conditions, stratified by hospital penalty status. Design, Setting, and Participants: Retrospective cohort study of Medicare fee-for-service beneficiaries older than 64 years discharged between January 1, 2008, and June 30, 2015, from 2214 penalty hospitals and 1283 nonpenalty hospitals. Difference-interrupted time-series models were used to compare trends in readmission rates by condition and penalty status. Exposure: Hospital penalty status or target condition under the HRRP. Main Outcomes and Measures: Thirty-day risk adjusted, all-cause unplanned readmission rates for target and nontarget conditions. Results: The study included 48 137 102 hospitalizations of 20 351 161 Medicare beneficiaries. In January 2008, the mean readmission rates for AMI, HF, pneumonia, and nontarget conditions were 21.9%, 27.5%, 20.1%, and 18.4%, respectively, at hospitals later subject to financial penalties and 18.7%, 24.2%, 17.4%, and 15.7% at hospitals not subject to penalties. Between January 2008 and March 2010, prior to HRRP announcement, readmission rates were stable across hospitals (except AMI at nonpenalty hospitals). Following announcement of HRRP (March 2010), readmission rates for both target and nontarget conditions declined significantly faster for patients at hospitals later subject to financial penalties compared with those at nonpenalized hospitals (for AMI, additional decrease of -1.24 [95% CI, -1.84 to -0.65] percentage points per year relative to nonpenalty discharges; for HF, -1.25 [95% CI, -1.64 to -0.86]; for pneumonia, -1.37 [95% CI, -1.80 to -0.95]; and for nontarget conditions, -0.27 [95% CI, -0.38 to -0.17]; P < .001 for all). For penalty hospitals, readmission rates for target conditions declined significantly faster compared with nontarget conditions (for AMI, additional decline of -0.49 [95% CI, -0.81 to -0.16] percentage points per year relative to nontarget conditions [P = .004]; for HF, -0.90 [95% CI, -1.18 to -0.62; P < .001]; and for pneumonia, -0.57 [95% CI, -0.92 to -0.23; P < .001]). In contrast, among nonpenalty hospitals, readmissions for target conditions declined similarly or more slowly compared with nontarget conditions (for AMI, additional increase of 0.48 [95% CI, 0.01-0.95] percentage points per year [P = .05]; for HF, 0.08 [95% CI, -0.30 to 0.46; P = .67]; for pneumonia, 0.53 [95% CI, 0.13-0.93; P = .01]). After HRRP implementation in October 2012, the rate of change for readmission rates plateaued (P < .05 for all except pneumonia at nonpenalty hospitals), with the greatest relative change observed among hospitals subject to financial penalty. Conclusions and Relevance: Medicare fee-for-service patients at hospitals subject to penalties under the HRRP had greater reductions in readmission rates compared with those at nonpenalized hospitals. Changes were greater for target vs nontarget conditions for patients at the penalized hospitals but not at the other hospitals.

Trajectories of Risk for Specific Readmission Diagnoses after Hospitalization for Heart Failure, Acute Myocardial Infarction, or Pneumonia.

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.

Hospital variation in admission to intensive care units for patients with acute myocardial infarction.

BACKGROUND: The treatment for patients with acute myocardial infarction (AMI) was transformed by the introduction of intensive care units (ICUs), yet we know little about how contemporary hospitals use this resource-intensive setting and whether higher use is associated with better outcomes. METHODS: We identified 114,136 adult hospitalizations for AMI from 307 hospitals in the 2009 to 2010 Premier database using codes from the International Classification of Diseases, Ninth Revision, Clinical Modification. Hospitals were stratified into quartiles by rates of ICU admission for AMI patients. Across quartiles, we examined in-hospital risk-standardized mortality rates and usage rates of critical care therapies for these patients. RESULTS: Rates of ICU admission for AMI patients varied markedly among hospitals (median 48%, Q1-Q4 20%-71%, range 0%-98%), and there was no association with in-hospital risk-standardized mortality rates (6% all quartiles, P = .7). However, hospitals admitting more AMI patients to the ICU were more likely to use critical care therapies overall (mechanical ventilation [from Q1 with lowest rate of ICU use to Q4 with highest rate 13%-16%], vasopressors/inotropes [17%-21%], intra-aortic balloon pumps [4%-7%], and pulmonary artery catheters [4%-5%]; P for trend < .05 in all comparisons). CONCLUSIONS: Rates of ICU admission for patients with AMI vary substantially across hospitals and were not associated with differences in mortality, but were associated with greater use of critical care therapies. These findings suggest uncertainty about the appropriate use of this resource-intensive setting and a need to optimize ICU triage for patients who will truly benefit.

National Trends in Hospital Readmission Rates among Medicare Fee-for-Service Survivors of Mitral Valve Surgery, 1999-2010.

BACKGROUND: Older patients who undergo mitral valve surgery (MVS) have high 1-year survival rates, but little is known about the experience of survivors. Our objective was to determine trends in 1-year hospital readmission rates and length of stay (LOS) in these individuals. METHODS: We included 100% of Medicare Fee-for-Service patients ≥65 years of age who underwent MVS between 1999-2010 and survived to 1 year (N = 146,877). We used proportional hazards regression to analyze the post-MVS 1-year readmission rate in each year, mean hospital LOS (after index admission), and readmission rates by subgroups (age, sex, race). RESULTS: The 1-year survival rate among patients undergoing MVS was 81.3%. Among survivors, 49.1% experienced a hospital readmission within 1 year. The post-MVS 1-year readmission rate declined from 1999-2010 (49.5% to 46.9%, P<0.01), and mean hospital LOS decreased from 6.2 to 5.3 (P<0.01). Readmission rates were highest in oldest patients, but declined in all age subgroups (65-74: 47.4% to 44.4%; 75-84: 51.4% to 49.2%, ≥85: 56.4% to 50.0%, all P<0.01). There were declines in women and men (women: 51.7% to 50.8%, P<0.01; men: 46.9% to 43.0%, P<0.01), and in whites and patients of other race, but not in blacks (whites: 49.0% to 46.2%, P<0.01; other: 55.0% to 48.9%, P<0.01; blacks: 58.1% to 59.0%, P = 0.18). CONCLUSIONS: Among older adults surviving MVS to 1 year, slightly fewer than half experience a hospital readmission. There has been a modest decline in both the readmission rate and LOS over time, with worse outcomes in women and blacks.