Assessing the quality of public services: For-profits, chains, and concentration in the hospital market.

We examine variation in US hospital quality across ownership, chain membership, and market concentration. We propose a new measure of quality derived from penalties imposed on hospitals under the flagship Hospital Readmissions Reduction Program, and use regression models to risk-adjust for hospital characteristics and county demographics. While the overall association between for-profit ownership and quality is negative, there is evidence of substantial heterogeneity. The quality of for-profit relative to non-profit hospitals declines with increasing market concentration. Moreover, the quality gap is primarily driven by for-profit chains. While the competition result mirrors earlier findings in the literature, the chain result appears to be new: it suggests that any potential quality gains afforded by chains are mostly realized by not-for-profit hospitals.

Examining emergency department utilization following bariatric surgery.

BACKGROUND: Emergency department (ED) utilization following surgery is poorly understood and places immense strain on the healthcare system, being responsible for up to $38 billion in wasteful spending annually. The aim of this study was to quantify ED utilization following bariatric procedures to identify causes and areas of improvement. MATERIALS AND METHODS: A retrospective review of a prospectively maintained database was conducted for all patients who underwent metabolic bariatric surgery (MBS) between November 2006 and June 2019. The study includes 4703 patients across 8 hospitals in a single health system. Patients who returned to the ED within 30 and 90 days were analyzed for relation to surgery and preventability. RESULTS: Of the 4703 patients that underwent MBS, 907 (19.3%) visited the ED at least once within 90 days and 350 (7.4%) required hospital readmission. The most common bariatric procedure performed was the Roux-en-Y Gastric Bypass (RYGB) (3716/4703) with an average BMI of 43.8. The median length between discharge and ED visit was 19 days. Under 50% of patients called prior to ED presentation and 61% of these ED visits resulted in discharge. CONCLUSION: While hospital readmissions following MBS have been scrutinized in literature, investigation of ED utilization remains scarce. Our study is one of few to investigate postoperative ED utilization up to 90 days following bariatric intervention. A clear opportunity exists to improve discharge education and early post-discharge communication. This would additionally alleviate burden to allow focus on the acutely ill.

Unplanned hospital readmissions following HeartMate 3 implantation: Readmission rates, causes, and impact on survival.

BACKGROUND: Hospital readmissions following left ventricular assist device (LVAD) remain a frequent comorbidity, associated with decreased quality of life and increased resources utilization. This study sought to determine causes, predictors, and impact on survival of hospitalizations during HeartMate 3 (HM3) support. METHODS: All patients implanted with HM3 between November 2014 to December 2019 at Columbia University Irving Medical Center were consecutively enrolled in the study. Demographics and clinical characteristics from the index admission and the first outpatient visit were collected and used to estimate 1-year and 900-day readmission-free survival and overall survival. Multivariable analysis was performed for subsequent readmissions. RESULTS: Of 182 patients who received a HM3 LVAD, 167 (92%) were discharged after index admission and experienced 407 unplanned readmissions over the median follow up of 727 (interquartile range (IQR): 410.5, 1124.5) days. One-year and 900-day mean cumulative number of all-cause unplanned readmissions was 0.43 (95%CI, 0.36, 0.51) and 1.13 (95%CI, 0.99, 1.29). The most frequent causes of rehospitalizations included major infections (29.3%), bleeding (13.2%), device-related (12.5%), volume overload (7.1%), and other (28%). One-year and 900-day survival free from all-cause readmission was 38% (95%CI, 31-46%) and 16.6% (95%CI, 10.3-24.4%). One-year and 900-day freedom from 2, 3, and ≥4 readmissions were 60.7%, 74%, 74.5% and 26.2%, 33.3%, 41.3%. One-year and 900-day survival were unaffected by the number of readmissions and remained >90%. Male sex, ischemic etiology, diabetes, lower serum creatinine, longer duration of index hospitalization, and a history of readmission between discharge and the first outpatient visit were associated with subsequent readmissions. CONCLUSIONS: Unplanned hospital readmissions after HM3 are common, with infections and bleeding accounting for the majority of readmissions. Irrespective of the number of readmissions, one-year survival remained unaffected.

Determinants of hospital readmissions in older people with dementia: a narrative review.

INTRODUCTION: Over 50% of hospitalised older people with dementia have multimorbidity, and are at an increased risk of hospital readmissions within 30 days of their discharge. Between 20-40% of these readmissions may be preventable. Current research focuses on the physical causes of hospital readmissions. However, older people with dementia have additional psychosocial factors that are likely to increase their risk of readmissions. This narrative review aimed to identify psychosocial determinants of hospital readmissions, within the context of known physical factors. METHODS: Electronic databases MEDLINE, EMBASE, CINAHL and PsychInfo were searched from inception until July 2022 and followed up in February 2024. Quantitative and qualitative studies in English including adults aged 65 years and over with dementia, their care workers and informal carers were considered if they investigated hospital readmissions. An inductive approach was adopted to map the determinants of readmissions. Identified themes were described as narrative categories. RESULTS: Seventeen studies including 7,194,878 participants met our inclusion criteria from a total of 6369 articles. Sixteen quantitative studies included observational cohort and randomised controlled trial designs, and one study was qualitative. Ten studies were based in the USA, and one study each from Taiwan, Australia, Canada, Sweden, Japan, Denmark, and The Netherlands. Large hospital and insurance records provided data on over 2 million patients in one American study. Physical determinants included reduced mobility and accumulation of long-term conditions. Psychosocial determinants included inadequate hospital discharge planning, limited interdisciplinary collaboration, socioeconomic inequalities among ethnic minorities, and behavioural and psychological symptoms. Other important psychosocial factors such as loneliness, poverty and mental well-being, were not included in the studies. CONCLUSION: Poorly defined roles and responsibilities of health and social care professionals and poor communication during care transitions, increase the risk of readmission in older people with dementia. These identified psychosocial determinants are likely to significantly contribute to readmissions. However, future research should focus on the understanding of the interaction between a host of psychosocial and physical determinants, and multidisciplinary interventions across care settings to reduce hospital readmissions.

Disentangling organizational levers and economic benefits in transitional care programs: a systematic review and configurational analysis.

BACKGROUND: Promoting safe and efficient transitions of care is critical to reducing readmission rates and associated costs and improving the quality of patient care. A growing body of literature suggests that transitional care (TC) programs are effective in improving quality of life and reducing unplanned readmissions for several patient groups. TC programs are highly complex and multidimensional, requiring evidence on how specific practices and system characteristics influence their effectiveness in patient care, readmission reduction and costs. METHODS: Using a systematic review and a configurational approach, the study examines the role played by system characteristics (size, ownership, professional skills, technology used), the organizational components implemented, analyzing their combinations, and the potential economic impact of TC programs. RESULTS: The more organizational components are implemented, the greater the likelihood that a TC program will be successful in reducing readmission rates. Not all components have the same effect. The results show that certain components, 'post-discharge symptom monitoring and management' and 'discharge planning', are necessary but not sufficient to achieve the outcome. The results indicate the existence of two different combinations of components that can be considered sufficient for the reduction of readmissions. Furthermore, while system characteristics are underexplored, the study shows different ways of incorporating the skill mix of professionals and their mode of coordination in TC programs. Four organizational models emerge: the health-based monocentric, the social-based monocentric, the multidisciplinary team and the mono-specialist team. The economic impact of the programs is generally positive. Despite an increase in patient management costs, there is an overall reduction in all post-intervention costs, particularly those related to readmissions. CONCLUSIONS: The results underline the importance of examining in depth the role of system characteristics and organizational factors in facilitating the creation of a successful TC program. The work gives preliminary insights into how to systematize organizational practices and different coordination modes for facilitating decision-makers' choices in TC implementation. While there is evidence that TC programs also have economic benefits, the quality of economic evaluations is relatively low and needs further study.

Predictors of hospital readmission rate in geriatric patients.

BACKGROUND: Hospital readmissions among older adults are associated with progressive functional worsening, increased institutionalization and mortality. AIM: Identify the main predictors of readmission in older adults. METHODS: We examined readmission predictors in 777 hospitalized subjects (mean age 84.40 ± 6.77 years) assessed with Comprehensive Geriatric Assessment (CGA), clinical, anthropometric and biochemical evaluations. Comorbidity burden was estimated by Charlson Comorbidity Index (CCI). Median follow-up was 365 days. RESULTS: 358 patients (46.1%) had a second admission within 365 days of discharge. Estimated probability of having a second admission was 0.119 (95%C.I. 0.095-0.141), 0.158 (95%C.I. 0.131-0.183), and 0.496 (95%C.I. 0.458-0.532) at 21, 30 and 356 days, respectively. Main predictors of readmission at 1 year were length of stay (LOS) > 14 days (p < 0.001), albumin level < 30 g/l (p 0.018), values of glomerular filtration rate (eGFR) < 40 ml/min (p < 0.001), systolic blood pressure < 115 mmHg (p < 0.001), CCI ≥ 6 (p < 0.001), and cardiovascular diagnoses. When the joint effects of selected prognostic variables were accounted for, LOS > 14 days, worse renal function, systolic blood pressure < 115 mmHg, higher comorbidity burden remained independently associated with higher readmission risk. DISCUSSION: Selected predictors are associated with higher readmission risk, and the relationship evolves with time. CONCLUSIONS: This study highlights the importance of performing an accurate CGA, since defined domains and variables contained in the CGA (i.e., LOS, lower albumin and systolic blood pressure, poor renal function, and greater comorbidity burden), when combined altogether, may offer a valid tool to identify the most fragile patients with clinical and functional impairment enhancing their risk of unplanned early and late readmission.

Calculating surgical readmission rates in gynecologic oncology: The impact of patient factors.

OBJECTIVE: To determine the 30-day surgical readmission rate after major gynecologic oncology surgeries at a high-volume academic institution and correlated risk factors. METHODS: Retrospective cohort study was conducted of surgical admissions from January 2016 - December 2019 at a single institution. Data were extracted from patient charts, including reason for readmission and length of stay. A readmission rate was calculated. Nested case control design was used to identify correlations between readmission and patient specific risk-factors. Multivariable logistic regression models were used to determine risk factors with readmission. RESULTS: A total of 2152 patients were included. The readmission rate was 3.5%, most commonly due to GI disturbance and surgical site infection. Average readmission length was 5 days. Prior to adjusting for covariates, insurance status, primary diagnosis, index admission length, and disposition at discharge differed between patients who were and were not readmitted. After adjusting for co-variates, younger patients, index admission >2 days, and higher Charlson co-morbidity index were associated with readmission. CONCLUSIONS: Our surgical readmission rate was lower than previously reported rates in gynecologic oncology patients. Patient factors associated with readmission included younger age, longer index hospital admission, and higher medical co-morbidity index scores. Provider factors and institutional practice patterns could contribute to the decreased readmission rate. These findings underscore the importance of standardizing how we calculate readmission rate and interpret these data. Varying readmission rates and institutional practice patterns deserve closer scrutiny to inform best practice and future policies.

An analysis of the outcomes of Clostridioides difficile occurring in intestinal transplant recipients requiring hospitalization.

BACKGROUND: Organ transplantation is a known risk factor for Clostridioides difficile infection (CDI). There is limited published data on the impact of CDI in the intestinal transplant population. METHODS: We utilized the National Readmission Database (2010-2017) to study the outcomes of CDI in patients having a history of intestinal transplantation. Association of CDI with readmission and hospital resource utilization was computed in multivariable models adjusted for demographics and comorbidities. RESULTS: During 2010-2017, 8442 hospitalizations with the history of intestinal transplantation had indexed hospital admissions. Of these, 320 (3.8%) had CDI. CDI hospitalization in intestine transplant patients was associated with higher median cost $54 430 (IQR: 27 231, 109 980) as compared to patients who did not have CDI $48 888 (IQR: 22 578, 112 777), (ß: 71 814 95% confidence intervals [CI]: 676-142 953, p = .048). The median length of stay was also longer for patients with CDI 7 (IQR: 4, 13) days as compared to 5 (IQR: 3, 11) days in non-CDI (ß: 5.51 95% CI: 0.73-10.29, p = .02). The mortality rate, intestinal transplant complications, presence of malnutrition, acute kidney injury, ICU admissions, and sepsis were similar in both groups. CDI was the top cause of 30-day readmission in the intestinal transplant recipients with CDI during the index admission; the number of 30-day readmissions also increased from 2010 to 2017. CONCLUSION: CDI hospitalization in post-intestine transplant patients occurs commonly and is associated with a longer length of stay and higher costs during hospitalization. The CDI was the most common cause of readmission after the index admission of CDI in these patients.

Associations between source-apportioned PM2.5 and 30-day readmissions in heart failure patients.

BACKGROUND: Air pollution exposure is a significant risk factor for morbidity and mortality, especially for those with pre-existing chronic disease. Previous studies highlighted the risks that long-term particulate matter exposure has for readmissions. However, few studies have evaluated source and component specific associations particularly among vulnerable patient populations. OBJECTIVES: Use electronic health records from 5556 heart failure (HF) patients diagnosed between July 5, 2004 and December 31, 2010 that were part of the EPA CARES resource in conjunction with modeled source-specific fine particulate matter (PM2.5) to estimate the association between exposure to source and component apportioned PM2.5 at the time of HF diagnosis and 30-day readmissions. METHODS: We used zero-inflated mixed effects Poisson models with a random intercept for zip code to model associations while adjusting for age at diagnosis, year of diagnosis, race, sex, smoking status, and neighborhood socioeconomic status. We undertook several sensitivity analyses to explore the impact of geocoding precision and other factors on associations and expressed associations per interquartile range increase in exposures. RESULTS: We observed associations between 30-day readmissions and an interquartile range increase in gasoline- (16.9% increase; 95% confidence interval = 4.8%, 30.4%) and diesel-derived PM2.5 (9.9% increase; 95% confidence interval = 1.7%, 18.7%), and the secondary organic carbon component of PM2.5 (SOC; 20.4% increase; 95% confidence interval = 8.3%, 33.9%). Associations were stable in sensitivity analyses, and most consistently observed among Black study participants, those in lower income areas, and those diagnosed with HF at an earlier age. Concentration-response curves indicated a linear association for diesel and SOC. While there was some non-linearity in the gasoline concentration-response curve, only the linear component was associated with 30-day readmissions. DISCUSSION: There appear to be source specific associations between PM2.5 and 30-day readmissions particularly for traffic-related sources, potentially indicating unique toxicity of some sources for readmission risks that should be further explored.

Preventing Heart Failure Readmission in Patients with Low Socioeconomic Position.

PURPOSE OF REVIEW: This review aims to summarize the current burden of heart failure (HF) in the United States, specifically in patients with low socioeconomic position (SEP), and synthesize recommendations to prevent HF-related hospital readmissions in this vulnerable population. RECENT FINDINGS: As treatments have improved, HF-related mortality has declined over time, resulting in more patients living with HF. This has led to an increase in hospitalizations, however, putting excess strain on our healthcare system. HF patients with low SEP are a particularly vulnerable group, as they experience higher rates of hospitalization and readmission compared to their high SEP counterparts. The Hospital Readmission Reduction Program (HRRP) was created to motivate interventions that reduce hospital readmissions across diseases, with HF being a primary target. Numerous readmission prevention efforts have been suggested to target the pre-hospitalization, hospitalization, and post-hospitalization phases, including addressing social determinants of health (SDoH), improving coordination of care, optimizing discharge plans, and improving adherence to follow-up care and medication regimens. Many of these proposed interventions show promise in reducing HF-related readmissions and issues surrounding adequate caregiver support may be particularly important to reduce readmissions among persons in low SEP. Reducing HF-related hospital readmissions is possible, even in vulnerable populations like those with low SEP, but this will require coordinated efforts across the healthcare system and throughout the life course of these patients. Caregiver support is a necessary part of optimized care for low SEP HF patients and future efforts should consider interventions that support these caregivers.

Prevention of Unplanned Hospital Admissions in Multimorbid Patients Using Computational Modeling: Observational Retrospective Cohort Study.

BACKGROUND: Enhanced management of multimorbidity constitutes a major clinical challenge. Multimorbidity shows well-established causal relationships with the high use of health care resources and, specifically, with unplanned hospital admissions. Enhanced patient stratification is vital for achieving effectiveness through personalized postdischarge service selection. OBJECTIVE: The study has a 2-fold aim: (1) generation and assessment of predictive models of mortality and readmission at 90 days after discharge; and (2) characterization of patients' profiles for personalized service selection purposes. METHODS: Gradient boosting techniques were used to generate predictive models based on multisource data (registries, clinical/functional and social support) from 761 nonsurgical patients admitted in a tertiary hospital over 12 months (October 2017 to November 2018). K-means clustering was used to characterize patient profiles. RESULTS: Performance (area under the receiver operating characteristic curve, sensitivity, and specificity) of the predictive models was 0.82, 0.78, and 0.70 and 0.72, 0.70, and 0.63 for mortality and readmissions, respectively. A total of 4 patients' profiles were identified. In brief, the reference patients (cluster 1; 281/761, 36.9%), 53.7% (151/281) men and mean age of 71 (SD 16) years, showed 3.6% (10/281) mortality and 15.7% (44/281) readmissions at 90 days following discharge. The unhealthy lifestyle habit profile (cluster 2; 179/761, 23.5%) predominantly comprised males (137/179, 76.5%) with similar age, mean 70 (SD 13) years, but showed slightly higher mortality (10/179, 5.6%) and markedly higher readmission rate (49/179, 27.4%). Patients in the frailty profile (cluster 3; 152/761, 19.9%) were older (mean 81 years, SD 13 years) and predominantly female (63/152, 41.4%, males). They showed medical complexity with a high level of social vulnerability and the highest mortality rate (23/152, 15.1%), but with a similar hospitalization rate (39/152, 25.7%) compared with cluster 2. Finally, the medical complexity profile (cluster 4; 149/761, 19.6%), mean age 83 (SD 9) years, 55.7% (83/149) males, showed the highest clinical complexity resulting in 12.8% (19/149) mortality and the highest readmission rate (56/149, 37.6%). CONCLUSIONS: The results indicated the potential to predict mortality and morbidity-related adverse events leading to unplanned hospital readmissions. The resulting patient profiles fostered recommendations for personalized service selection with the capacity for value generation.

Why reducing avoidable hospital readmissions is a 'wicked' problem for leaders: A qualitative exploration of nursing and allied health perceptions.

AIMS: To investigate nursing and allied health professional perceptions of the interrelationship between avoidable hospital readmissions and fundamental care delivery. DESIGN: A qualitative, exploratory study using a critical realist approach. METHOD: One-to-one semi-structured interviews with 14 nursing and allied health professionals conducted between May and September 2019. RESULTS: Several tensions and contradictions were identified in the data, which demonstrated clinicians' perceptions about the priority of both fundamental care and two avoidable readmission conditions (aspiration pneumonia and constipation). These tensions are illustrated in two major themes: Avoidable versus inevitable; and everyone versus no one. The first theme demonstrates clinicians' perceptions that readmissions for aspiration pneumonia and constipation are not common, despite acknowledging that they generally lacked knowledge on readmission rates; and that these conditions may not be preventable in acute settings. The second theme demonstrates clinicians' perception that preventing readmissions is everyone's responsibility, however, this was coupled with a lack of articulation around how this multidisciplinary approach could be achieved, leading to a distinct lack of agency for care delivery. CONCLUSION: Articulating the tensions described in the results provides vital knowledge for understanding how clinicians may respond to initiatives designed to reduce avoidable readmissions. Avoidable hospital readmissions may be usefully understood as a wicked problem: one that is complex and requires adaptive, not linear, solutions. Wicked problems pose a challenge for leaders and managers in healthcare because top-down, hierarchical strategies are unlikely to be successful. Effective prevention of avoidable readmissions requires leaders to enable facilitator-led change through relational leadership strategies. IMPACT: Avoidable hospital readmissions are a global problem increasingly addressed via funding changes and the introduction of penalties to hospitals. This study provides insights on clinicians' perspectives of avoidable hospital readmissions and their prevention, demonstrating the complexity of this challenge and the need for healthcare leaders to enable individual and organizational readiness for change.

Multimorbidity and prior falls correlate with risk of 30-day hospital readmission in aged 80+: A prospective cohort study.

BACKGROUND/PURPOSE: Thirty-day hospital readmission rate significantly raised with advanced age. The performance of existing predictive models for readmission risk remained uncertain in the oldest population. We aimed to examine the effect of geriatric conditions and multimorbidity on readmission risk among older adults aged 80 and over. METHODS: This prospective cohort study enrolled patients aged 80 and older discharged from a geriatric ward at a tertiary hospital, with phone follow-up for 12 months. Demographics, multimorbidity, and geriatric conditions were assessed before hospital discharge. Logistic regression models were conducted to analyse risk factors for 30-day readmission. RESULTS: Patients readmitted had higher Charlson comorbidity index scores, and were more likely to have falls, frailty, and longer hospital stay, compared to those without 30-day readmission. Multivariate analysis revealed that higher Charlson comorbidity index score was associated with readmission risk. Older patients with a fall history within 12 months had a near 4-fold increase in readmission risk. Severe frailty status before index admission was associated with a higher 30-day readmission risk. Functional status at discharge was not associated with readmission risk. CONCLUSION: In addition to multimorbidity, history of falls and frailty were associated with higher hospital readmission risk in the oldest.

One-year trajectories of self-care behaviours and unplanned hospital readmissions among patients with heart failure: A prospective longitudinal study.

AIM AND OBJECTIVES: This study aimed to identify the associations between longitudinal trajectories of self-care behaviours and unplanned hospital readmissions in patients with heart failure. BACKGROUND: Adherence to self-care behaviours is crucial to prevent hospital readmissions; however, self-care behaviours remain unsatisfactory among patients with heart failure. Studies of long-term trajectories of self-care behaviours and their influence on hospital readmissions are limited in this population. DESIGN: A prospective, longitudinal observational study. METHODS: Among 137 participants with heart failure (mean age 67.36 years, 62% men), we analysed the 1-year follow-up data to determine the association between 1-year trajectories of self-care behaviours and hospital readmissions using Kaplan-Meier analysis and multivariable Cox regression, adjusted for confounding variables. RESULTS: Self-care behaviour trajectories of heart failure patients were classified as 'high-stable' (58.4%) or 'low-sustained' (41.6%). The cumulative rate of readmissions for the low-sustained class was higher than that of the high-stable class for all periods. Factors influencing readmissions included anaemia, cognitive function, frailty and self-care behaviours trajectories. The low-sustained class had a 2.77 times higher risk of readmissions within 1 year than that in the high-stable class. CONCLUSIONS: Longitudinal self-care behaviours pattern trajectories of heart failure patients were stratified as high-stable and low-sustained. Routine follow-up assessment of patients' self-care behavioural patterns, including anaemia and frailty, and cognitive function can minimise unplanned hospital readmissions. RELEVANCE TO CLINICAL PRACTICE: Identification of trajectory patterns of self-care behaviours over time and provision of timely and individualised care can reduce readmissions for heart failure patients. Healthcare professionals should recognise the significance of developing tailored strategies incorporating longitudinal self-care behavioural patterns in heart failure patients. REPORTING METHOD: The study has been reported in accordance with the STROBE checklist (Appendix S1). PATIENT OR PUBLIC CONTRIBUTION: Patients have completed a self-reported questionnaire after providing informed consent.

Disparities in transitions of acute stroke care: The transitions of care stroke disparities study methodological report.

OBJECTIVE: The Transitions of Stroke Care Disparities Study (TCSD-S) is an observational study designed to determine race-ethnic and sex disparities in post-hospital discharge transitions of stroke care and stroke outcomes and to develop hospital-level initiatives to reduce these disparities to improve stroke outcomes. MATERIALS AND METHODS: Here, we present the study rationale, describe the methodology, report preliminary outcomes, and discuss a critical need for the development, implementation, and dissemination of interventions for successful post-hospital transition of stroke care. The preliminary outcomes describe the demographic, stroke risk factor, socioeconomic, and acute care characteristics of eligible participants by race-ethnicity and sex. We also report on all-cause and vascular-related death, readmissions, and hospital/emergency room representations at 30- and 90-days after hospital discharge. RESULTS: The preliminary sample included data from 1048 ischemic stroke and intracerebral hemorrhage discharged from 10 comprehensive stroke centers across the state of Florida. The overall sample was 45% female, 22% Non-Hispanic Black and 21% Hispanic participants, with an average age of 64 ± 14 years. All cause death, readmissions, or hospital/emergency room representations are 10% and 19% at 30 and 90 days, respectively. One in 5 outcomes was vascular-related. CONCLUSIONS: This study highlights the transition from stroke hospitalization as an area in need for considerable improvement in systems of care for stroke patients discharged from hospital. Results from our preliminary analysis highlight the importance of investigating race-ethnic and sex differences in post-stroke outcomes.

Demystifying hospital charges for hospital readmissions in 2017 in the United States for psychosis (DRG = 885).

Existing research on hospital charges is primarily focused on hospital admissions, but not on hospital readmissions. Our research fills this gap. We utilize the 2017 Hospital Readmissions database from the Agency for Healthcare Research and Quality (AHRQ) to empirically study factors that impact hospital charges for hospital readmissions. We focus on psychosis (DRG = 885) which has 609,360 records in 2017 in the AHRQ database. We employ regression analyses using patient demographics, inpatient care variables, and hospital characteristics to explain variance in hospital charges. Results show that inpatient care (diagnoses, procedures, length of stay), hospital ownership, and younger patients result in higher hospital charges.

Emergency Department Visits Versus Hospital Readmissions Among Patients Hospitalized for Heart Failure.

BACKGROUND: Worsening heart failure (HF) often requires hospitalization but in some cases may be managed in the outpatient or emergency department (ED) settings. The predictors and clinical significance of ED visits without admission vs hospitalization are unclear. METHODS: The ASCEND-HF trial included 2661 US patients hospitalized for HF with reduced or preserved ejection fraction. Clinical characteristics were compared between patients with a subsequent all-cause ED visit (with ED discharge) within 30 days vs all-cause readmission within 30 days. Factors associated with each type of care were assessed in multivariable models. Multivariable models landmarked at 30 days evaluated associations between each type of care and subsequent 150-day mortality. RESULTS: Through 30-day follow-up, 193 patients (7%) had ED discharge, 459 (17%) had readmission, and 2009 (76%) had neither urgent visit. Patients with ED discharge vs readmission were similar with respect to age, sex, systolic blood pressure, ejection fraction, and coronary artery disease, whereas ED discharge patients had a modestly lower creatinine (P < .01). Among patients with either event within 30 days, a higher creatinine and prior HF hospitalization were associated with a higher likelihood of readmission, as compared with ED discharge (P < .02). Landmarked at 30 days, rates of death during the subsequent 150 days were 21.0% for patients who were readmitted and 11.4% for patients discharged from the ED. Compared with patients who were readmitted, ED discharge was independently associated with lower 150-day mortality (adjusted hazard ratio 0.58, 95% confidence interval 0.36-0.92, P = .02). CONCLUSIONS: In this cohort of US patients hospitalized for HF, worse renal function and prior HF hospitalization were associated with a higher likelihood of early postdischarge readmission, as compared with ED discharge. Although subsequent mortality was high after discharge from the ED, this risk of mortality was significantly lower than patients who were readmitted to the hospital.

Understanding repeat hospitalizations in intermediate-to-high risk aortic stenosis patients following transcatheter aortic valve replacement.

OBJECTIVES: We describe the causes, timing and predictors of readmissions and analyze its impact on clinical outcomes in intermediate-to-high-risk patients with severe symptomatic aortic stenosis (AS) who underwent transcatheter aortic valve replacement (TAVR). BACKGROUND: Intermediate-high risk TAVR patients with severe AS have an increased risk for hospital readmissions due to the high burden of comorbidities. METHODS: Patients who underwent TAVR from 2012 to 2018 at a single tertiary cardiac center were included and followed for 1 year. Readmissions were categorized as noncardiovascular (non-CV) and CV. RESULTS: A total of 611 patients (410 with no readmissions, 201 with ≥1 readmissions) were included. There was a total of 317 readmissions (mean: 1.58 ± 1.09 per readmitted patient) with 65 patients having ≥2 readmissions. 64.0% were non-CV and 36.0% were CV. The top three CV causes were pacemaker/implantable cardioverter-defibrillator placement, bleeding, and stroke. About 23% occurred at 1 m, the majority were CV; 45% occurred between 7 and 12 m, the majority were non-CV. Those with ≥1 readmissions had a higher burden of comorbidities including peripheral arterial disease, diabetes, immunosuppression, prior percutaneous coronary interventions, and dialysis. Readmissions were associated with higher 1-year mortality (adjusted hazard ratio: 2.53, 95% confidence interval: 1.40-4.59; p = 0.002). High-risk patients had higher non-CV readmissions (0.37 ± 0.79 vs. 0.25 ± 0.62; p = 0.044) compared to intermediate-risk patients but similar CV readmissions (p = 0.645). CONCLUSIONS: Understanding readmissions post-TAVR will promote the early identification of at-risk groups and the implementation of preventative measures to improve outcomes and reduce the burden and costs of readmissions.

Pediatric asthma hospitalization: individual and environmental characteristics of high utilizers in South Texas.

Objective: Few studies have examined factors affecting the high frequency of hospitalization for pediatric asthma. This study identifies individual and environmental characteristics of children with asthma from a low-income community with a high number of hospitalizations.Methods: The study population included 902 children admitted at least once to a children's hospital in South Texas because of asthma from 2010 to 2016. The population was divided into three groups by utilization frequency (high: ≥4 times, medium: 2-3 times, or low: 1 time). Individual-level factors at index admission and environmental factors were included for the analysis. Unadjusted and adjusted multivariate ordered logistic regression models were applied to identify significant characteristics of high hospital utilizers.Results: The high utilization group comprised 2.4% of total patients and accounted for substantial hospital resource utilization: 10.8% of all admissions and 13.5% of days stayed in the hospital. Patients in the high utilization group showed longer length of stay (LOS) and shorter time between admissions on average than the other two groups. The multivariate ordered logistic regression models revealed that age of 5-11 years (OR = 0.57, 95%CI = 0.35-0.93), longer LOS (2 days: OR = 1.80, 95%CI = 1.15-2.84; ≥3 days: OR = 3.38, 95%CI = 2.10-5.46), warm season at index admission (OR = 1.49, 95%CI = 1.01-2.20), and higher average ozone level in children's residential neighborhoods (OR = 1.78, 95%CI = 1.01-3.14) were significantly associated with a higher number of asthma hospitalizations.Conclusions: The findings suggest the importance of monitoring high hospital utilizers and establishing strategies for such patients based on their characteristics to reduce repeated hospitalizations and to increase optimal use of hospital resources.

Improving the safety of outpatient parenteral antimicrobial therapy for patients with solid tumors.

BACKGROUND AND OBJECTIVES: Outpatient parenteral antimicrobial therapy (OPAT) for infections has been in use for nearly 40 years, and although it has been found safe and efficacious, its use has been studied primarily among otherwise healthy patients. We aimed to develop and evaluate an OPAT program for patients with cancer, particularly solid tumors. METHODS: We implemented multiple quality improvement interventions between June 2018 and January 2020. We retrospectively and prospectively collected data on demographics, the completeness of infectious diseases (ID) physician consultation notes, rates of laboratory test result monitoring, ID clinic follow-up, and 30-day outcomes, including unplanned OPAT-related readmissions, OPAT-related emergency center visits, and deaths. RESULTS: Completeness of ID provider notes improved from a baseline of 77 to 100% (p < .0001) for antimicrobial recommendations, 75 to 97% (p < .0001) for follow-up recommendations, and 19 to 98% (p < .0001) for laboratory test result monitoring recommendations. Completion of laboratory tests increased from a baseline rate of 24 to 56% (p = .027). Thirty-day unplanned OPAT-related readmission, ID clinic follow-up, 30-day emergency center visit, and death rates improved without reaching statistical significance. CONCLUSIONS: Sustained efforts, multiple interventions, and multidisciplinary engagement can improve laboratory test result monitoring among solid tumor patients discharged with OPAT. Although demonstrating a decrease in unplanned readmissions through institution of a formal OPAT program among patients with solid malignancies may be more difficult compared with the general population, the program may still result in improved safety.