Disability and Recovery After Hospitalization for Medical Illness Among Community-Living Older Persons: A Prospective Cohort Study.

OBJECTIVES: To determine for each basic, instrumental, and mobility activity after hospitalization for acute medical illness: (1) disability prevalence immediately before and monthly for 6 months after hospitalization; (2) disability incidence 1 month after hospitalization; and (3) recovery time from incident disability during months 2 to 6 after hospitalization. DESIGN: Prospective cohort study. SETTING: New Haven, Connecticut. PARTICIPANTS: A total of 515 community-living persons, mean age 82.7 years, hospitalized for acute noncritical medical illness and alive within 1 month of hospital discharge. MEASUREMENTS: Disability was defined monthly for each basic (bathing, dressing, walking, transferring), instrumental (shopping, housework, meal preparation, taking medications, managing finances), and mobility activity (walking a quarter mile, climbing flight of stairs, lifting/carrying 10 pounds, driving) if help was needed to perform the activity or if a car was not driven in the prior month. RESULTS: Disability was common 1 and 6 months after hospitalization for activities frequently involved in leaving the home to access care including walking a quarter mile (prevalence 65% and 53%, respectively) and driving (65% and 61%). Disability was also common for activities involved in self-managing chronic health conditions including meal preparation (53% and 41%) and taking medications (41% and 31%). New disability was common and often prolonged. For example, 43% had new disability walking a quarter mile, and 30% had new disability taking medications, with mean recovery time of 1.9 months and 1.7 months, respectively. Findings were similar for the subgroup of persons residing at home (ie, not in a nursing home) at the first monthly follow-up interview after hospitalization. CONCLUSION: Disability in specific functional activities important to leaving home to access care and self-managing health conditions is common, often new, and present for prolonged time periods after hospitalization for acute medical illness. Post-discharge care should support patients through extended periods of vulnerability beyond the immediate transitional period. J Am Geriatr Soc 68:486-495, 2020.

Modeling defibrillation benefit for survival among cardiac resynchronization therapy defibrillator recipients.

BACKGROUND: Patients with heart failure having a low expected probability of arrhythmic death may not benefit from implantable cardioverter defibrillators (ICDs). OBJECTIVE: The objective was to validate models to identify cardiac resynchronization therapy (CRT) candidates who may not require CRT devices with ICD functionality. METHODS: Heart failure (HF) patients with CRT-Ds and non-CRT ICDs from the National Cardiovascular Data Registry and others with no device from 3 separate registries and 3 heart failure trials were analyzed using multivariable Cox proportional hazards regression for survival with the Seattle Heart Failure Model (SHFM; estimates overall mortality) and the Seattle Proportional Risk Model (SPRM; estimates proportional risk of arrhythmic death). RESULTS: Among 60,185 patients (age 68.6 ±â€¯11.3 years, 31.9% female) meeting CRT-D criteria, 38,348 had CRT-Ds, 11,389 had non-CRT ICDs, and 10,448 had no device. CRT-D patients had a prominent adjusted survival benefit (HR 0.52, 95% CI 0.50-0.55, P < .0001 versus no device). CRT-D patients with SHFM-predicted 4-year survival ≥81% (median) and a low SPRM-predicted probability of an arrhythmic mode of death ≤42% (median) had an absolute adjusted risk reduction attributable to ICD functionality of just 0.95%/year with the majority of survival benefit (70%) attributable to CRT pacing. In contrast, CRT-D patients with SHFM-predicted survival median had substantially more ICD-attributable benefit (absolute risk reduction of 2.6%/year combined; P < .0001). CONCLUSIONS: The SPRM and SHFM identified a quarter of real-world, primary prevention CRT-D patients with minimal benefit from ICD functionality. Further studies to evaluate CRT pacemakers in these low-risk CRT candidates are indicated.

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.

Síndrome poshospitalización. ¿Causa daño el estrés por hospitalización? / Post hospital syndrome: is the stress of hospitalization causing harm?

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Thirty-Day Hospital Readmission After Acute Myocardial Infarction in China.

Background Readmission after acute myocardial infarction in low- and middle-income countries like China is not well characterized. Methods and Results We approached consecutive patients with acute myocardial infarction hospitalized within 24 hours of symptom onset and discharged alive from 53 geographically diverse hospitals in China. We described rates of unplanned 30-day readmission, their timing and admitting diagnoses, and fit Cox proportional hazards models to identify factors associated with readmission. Among 3387 patients, median (interquartile range) age was 61 (52-69) years, and 76.9% were men. The index median length of stay was 11 (8-14) days. Unplanned 30-day readmission occurred in 6.3% of the cohort; most readmissions (77.7%) were for cardiovascular diagnoses. Nearly half (41.9% of all-cause readmissions; 44.3% of cardiovascular readmissions) occurred within 5 days of discharge. Mini-Global Registry of Acute Coronary Events scores at admission (hazard ratio [HR], 1.15 for every 10-point increase; 95% CI, 1.05-1.25), longer length of stay (HR, 1.03; 95% CI, 1.00-1.06 for each extra day), and in-hospital recurrent angina (HR, 1.40; 95% CI, 1.04-1.89) were associated with higher unplanned all-cause readmission. Revascularization during the index hospitalization (70.2% of the cohort) was associated with lower risks of all-cause readmission (HR, 0.27; 95% CI, 0.18-0.42). In addition, left ventricular ejection fraction <0.4 (HR, 1.79; 95% CI, 1.05-3.07) and in-hospital complication (HR, 1.20; 95% CI, 1.03-1.39) were associated with higher risk of unplanned cardiovascular readmission, and ST-segment-elevation myocardial infarction (HR, 0.60; 95% CI, 0.36-0.98) was associated with lower risk of unplanned cardiovascular readmission. Sex, family income, depression, stress level, lower social support, disease-specific health status, and medications were not associated with readmission. Conclusions In China, most readmissions are for cardiovascular events, and almost half occur within 5 days of discharge. Clinical factors identify patients at higher and lower unplanned readmissions. Clinical Trial Registration URL: https://www.clinicaltrials.gov . Unique identifier: NCT01624909.

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.

Trends in Performance and Opportunities for Improvement on a Composite Measure of Acute Myocardial Infarction Care.

Background Despite improvements on individual process of care measures for acute myocardial infarction (AMI), little is known about performance on a composite measure of AMI care that assesses the delivery of many components of high-quality AMI care. We sought to examine trends in patient- and hospital-level performance on a composite defect-free care measure, identify disparities in the performance across sociodemographic groups, and identify opportunities to further improve quality and outcomes. Methods and Results We calculated the proportion of patients in the National Cardiovascular Data Registry-Acute Coronary Treatment and Intervention Outcomes Network Registry-Get With The Guidelines (now known as the Chest Pain - Myocardial Infarction Registry) between January 1, 2010, and December 31, 2017, receiving defect-free AMI care including guideline-recommended pharmacotherapy, timely provision of medical and reperfusion therapy, assessment of ventricular function, referral to cardiac rehabilitation, and smoking cessation counseling for patients with AMI. A total of 522 800 patients at 222 hospitals were included. Overall, the proportion of patients receiving defect-free care significantly increased from 66.0% in 2010 to 77.1% in 2017 ( P<0.001). Improvements in performance were observed across all sociodemographic subgroups, with the greatest absolute improvement observed for black and Hispanic patients ( P<0.001). However, absolute performance was consistently lower among older patients, women, black and Hispanic patients, and those with government insurance in 2017 ( P<0.001 for all). Improvements in care and reduced variation in performance were observed at the hospital level overall (2010, median [IQR] 67.2% [40.7%-76.3%]; 2017, median [IQR] 80.7% [73.1%-88.1%]; P<0.001) as well as across region, safety net status, teaching status, and proportion of patients who are nonwhite and have Medicaid insurance coverage ( P<0.001 for all). Conclusions Despite improvements in the proportion of patients with AMI receiving defect-free care overall and across sociodemographic groups, nearly 1 in 4 patients in 2017 still did not receive optimal care and absolute performance was consistently lower among older patients, women, black, and Hispanic patients. Composite measures of cardiovascular care, which assess the delivery of several evidence-based processes of care, can illuminate opportunities to improve the quality of care beyond that provided by conventional process measures.

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.

Is Posthospital Syndrome a Result of Hospitalization-Induced Allostatic Overload?

After discharge from the hospital, patients face a transient period of generalized susceptibility to disease as well as an elevated risk for adverse events, including hospital readmission and death. The term posthospital syndrome (PHS) has been used to describe this time of enhanced vulnerability. Based on data from bench to bedside, this narrative review examines the hypothesis that hospitalrelated allostatic overload is a plausible etiology of PHS. Resulting from extended exposure to stress, allostatic overload is a maladaptive state driven by overuse and dysregulation of the hypothalamic-pituitary-adrenal axis and the autonomic nervous system that ultimately generates pathophysiologic consequences to multiple organ systems. Markers of allostatic overload, including elevated levels of cortisol, catecholamines, and inflammatory markers, have been associated with adverse outcomes after hospital discharge. Based on the evidence, we suggest a possible mechanism for postdischarge vulnerability, encourage critical contemplation of traditional hospital environments, and suggest interventions that might improve outcomes.

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.

Predicting death after acute myocardial infarction.

Recognizing and understanding the risk factors for mortality after acute myocardial infarction (AMI) provide clinicians and patients important information to determine prognosis and guide treatment. Most risk stratification models use demographic and clinical information that exists prior to hospitalization plus clinical presentation characteristics to estimate a patient's risk of mortality. In this review, we summarize the most important risk factors and discuss current models to predict mortality.