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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.

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

Objectives (1) To determine the relationship of incident delirium during hospitalization with 90-day mortality; (2) to identify potential in-hospital mediators through which delirium increases 90-day mortality. Design Analysis of data from Project Recovery, a controlled clinical trial of a delirium prevention intervention from 1995 to 1998 with follow-up through 2000. Setting Large academic hospital. Participants Patients ≥70 years old without delirium at hospital admission who were at intermediate-to-high risk of developing delirium and received usual care only. Measurements (1) Incident delirium; (2) potential mediators of delirium on death including use of restraining devices (physical restraints, urinary catheters), development of hospital acquired conditions (HACs) (falls, pressure ulcers), and exposure to other noxious insults (sleep deprivation, acute malnutrition, dehydration, aspiration pneumonia); (3) death within 90 days of admission. Results Among 469 patients, 70 (15%) developed incident delirium. These patients were more likely to experience restraining devices (37% vs 16%, P < .001), HACs (37% vs 12%, P < .001), other noxious insults (63% vs 49%, P = .03), and 90-day mortality (24% vs 6%, P < .001). The inverse probability weighted hazard of death due to delirium was 4.2 (95% CI = 2.8–6.3) in bivariable analyses, increased in a graded manner with additional exposures to restraining devices, HACs, and other noxious insults, and declined by 10.9% after addition of these potential mediator categories, providing evidence of mediation. Conclusion Restraining devices, HACs, and additional noxious insults were more frequent among patients with delirium, increased mortality in a graded manner, and were responsible for a significant percentage of the association of delirium with death. Additional efforts to prevent potential downstream mediators through which delirium increases mortality may help to improve outcomes among hospitalized older adults.

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.

The immediate period after hospital discharge is dangerous. Patients’ health, often marginal at best, frequently deteriorates, sending them to the emergency department,1 back to the hospital in-patient service,2 or into a period of functional decline.3,4 Among older patients hospitalized with heart failure, for example, death is even more common in the month following discharge than during the initial hospital stay.5,6 Vulnerabilities in this period are many, and patients are susceptible to deterioration in health from a broad spectrum of conditions, not just the initial illness that triggered hospitalization.7 This period has been labeled post-hospital syndrome, as it appears that patients have an acquired, transient period of generalized risk to a wide range of medical problems.8 As recognition of these risks has increased, the goal of improved short-term outcomes after hospitalization has become a focus for providers, payers, and policymakers.9 In this issue of the Journal, McAlister and colleagues ask whether short-term vulnerability after hospitalization is related to weekend versus weekday discharge. After examining almost 8,000 patients discharged from the general medical wards of 7 teaching hospitals in Alberta, Canada, the authors found that only 1 in 7 were discharged on weekends, defined as Saturday or Sunday. Patients discharged on the weekend were younger, had fewer chronic health conditions, and shorter average lengths of stay. In analyses adjusted for patient demographics and a measure of short-term risk after hospitalization (LACE score), weekend discharge was not associated with higher rates of unplanned readmission or death at 30 days. Most strikingly, only the healthiest patients were discharged on weekends. These results are similar to findings from the authors’ previous work on patients hospitalized with heart failure.10 Yet the implications for discharge planning are much less clear, as the few analyses of discharge day from the authors10 and others11 do not account for the range of factors that may influence risk after hospitalization such as patients’ clinical characteristics, the quality of both hospital and transitional care, and the post-hospital environments to which patients are discharged. Not surprisingly, different methodologic approaches have shown weekend discharge to be associated with a range of outcomes including lower,11 identical,12 and higher10 rates of unplanned readmission and death. Moreover, the influence of discharge timing itself is likely to involve further complexities including patients’ readiness for discharge,13 the specific days of the week on which both admission and discharge occur,14 and the outpatient resources made available to patients by specific health insurance carriers.14 These studies illustrate a fundamental issue with our efforts to reduce short-term readmission, namely, that we do not understand which factors most influence risk.15 Prediction models have generally focused on traditional markers of risk including patients’ demographic characteristics, their physical examination findings, and laboratory test results. While models based on these variables are often excellent at discriminating between patients who are likely to die soon after hospitalization, their ability to identify specific patients who will be rehospitalized has been mediocre.16,17 This difficulty with prediction suggests that readmission has far more complex determinants than death in the short-term period after hospitalization. Unfortunately, we have yet to identify and model the factors that matter most. Where should we look to find these additional sources of vulnerability after hospitalization? Previous research has made clear that we are unlikely to find single markers of risk that adequately predict the future. Rather, we will need to develop more complete understandings of patients including their dynamics of recovery, the role of the hospital environment in prolonging or instigating further vulnerability, the manners by which organizational context and implementation strategies impact transitional care, and the ways in which social and environmental factors hasten or retard recovery. For each of these categories, there are multiple specific questions to address. The following are illustrative examples