Unplanned Hospital Readmissions Research Articles

Using social risks to predict unplanned hospital readmission and emergency care among hospitalized Veterans.

(1) To estimate the association of social risk factors with unplanned readmission and emergency care after a hospital stay. (2) To create a social risk scoring index. We analyzed administrative data from the Department of Veterans Affairs (VA) Corporate Data Warehouse. Settings were VA medical centers that participated in a national social work staffing program. We grouped socially relevant diagnoses, screenings, assessments, and procedure codes into nine social risk domains. We used logistic regression to examine the extent to which domains predicted unplanned hospital readmission and emergency department (ED) use in 30 days after hospital discharge. Covariates were age, sex, and medical readmission risk score. We used model estimates to create a percentile score signaling Veterans' health-related social risk. We included 156,690 Veterans' admissions to a VA hospital with discharged to home from 1 October, 2016 to 30 September, 2022. The 30-day rate of unplanned readmission was 0.074 and of ED use was 0.240. After adjustment, the social risks with greatest probability of readmission were food insecurity (adjusted probability = 0.091 [95% confidence interval: 0.082, 0.101]), legal need (0.090 [0.079, 0.102]), and neighborhood deprivation (0.081 [0.081, 0.108]); versus no social risk (0.052). The greatest adjusted probabilities of ED use were among those who had experienced food insecurity (adjusted probability 0.28 [0.26, 0.30]), legal problems (0.28 [0.26, 0.30]), and violence (0.27 [0.25, 0.29]), versus no social risk (0.21). Veterans with social risk scores in the 95th percentile had greater rates of unplanned care than those with 95th percentile Care Assessment Needs score, a clinical prediction tool used in the VA. Veterans with social risks may need specialized interventions and targeted resources after a hospital stay. We propose a scoring method to rate social risk for use in clinical practice and future research.

A collaborative pharmacist-led intervention to prevent hospital readmissions among elderly patients discharged from the emergency department: a retrospective cohort study

Unplanned hospital readmission is a safety and quality healthcare measure, conferring significant costs to the healthcare system. Elderly individuals, particularly, are at high risk of readmissions, often due to issues related to medication management. Pharmacists play a pivotal role in addressing medication-related concerns, which can potentially reduce readmissions. This retrospective single-centre cohort study, conducted from November 2022 to February 2023 in an emergency department, aimed to determine if integrating emergency medicine pharmacists into Emergency Department care models reduces unplanned hospital readmissions within 28 days and to identify the interventions they employ. The inclusion criteria included patients aged ≥ 65, taking ≥ 3 medications, and presenting with falls, cognition changes, or reduced mobility and were planned for discharge to home from the emergency department. Collaborating with the Emergency Department Aged Care Service Emergency Team, a pharmacist provided comprehensive medication management consultations, discharge liaison services, and other pharmacy related interventions to eligible participants whenever the pharmacist was available. Patients who met the eligibility criteria but did not receive pharmacist interventions due to the pharmacist's unavailability served as the control group. This method was chosen to ensure that the control group consisted of comparable patients who only differed in terms of receiving the pharmacist intervention. The study included 210 participants, with 120 receiving pharmacist interventions and 90 acting as controls. The results revealed a significant reduction in unplanned hospital readmissions among participants who received pharmacist interventions (10.0%, n = 12) compared to controls (22.2%, n = 20), with a notable difference of 12.2% (95% confidence interval 2.4–23.4%, p = 0.01). A total of 107 interventions were documented, emphasising medication selection recommendations (28.0%) and identification of adverse drug reactions/drug-drug interactions (21.5%) as primary areas of focus. These findings suggest that integrating skilled pharmacists into Emergency Department Aged Care Service Emergency Team (ASET) lowered the rate of unplanned hospital readmission within 28 days resulting in improved hospital performance metric outcomes. This highlights the potential role of pharmacists in addressing medication-related issues and enhancing the quality and safety of healthcare delivery, particularly for elderly patients transitioning from the ED to home care settings.

Association between language discordance and unplanned hospital readmissions or emergency department revisits: a systematic review and meta-analysis

Background and objectiveStudies conflict about whether language discordance increases rates of hospital readmissions or emergency department (ED) revisits for adult and paediatric patients. The literature was systematically reviewed to investigate...

Randomized Trial to Evaluate Effects of Peer- and Clinician-Led Interventions for Caregivers of Individuals With Acquired Brain Injury

ObjectiveTo evaluate the effectiveness of 2 interventions for caregivers of patients with acquired brain injury (ABI) transitioning home after inpatient rehabilitation, to prepare them for the role of caregiving and reduce stress and depression. DesignControlled trial with participants randomly assigned to (1) usual care (UC), (2) clinician-delivered Problem-Solving Training (PST), or (3) peer-led Building Better Caregivers (BBC) training; both experimental interventions initiated during the inpatient rehabilitation stay, delivered virtually, of similar intensity (six 60-minute sessions), and focused on managing stress and building skills related to caregiving. SettingNonprofit rehabilitation hospital specializing in care of persons with acquired brain and spinal cord injuries. ParticipantsCaregivers (n=169) of patients with ABI (54 stroke; 115 other ABI) admitted for rehabilitation whose discharge location was home with care provided by family members (caregivers: 83% women, 62% White, age [mean ± SD]: 51±11.5 y). Participants were recruited from February 2021 to November 2022, when COVID-19 restrictions were in place. InterventionsNoted above. Main Outcome MeasuresCaregiver-reported stress, depressive symptoms, and caregiving self-efficacy; patient unplanned hospital readmissions and emergency department visits 30 days post discharge. ResultsOnly 61% of participants in the 2 intervention groups completed 3 or more of 6 intervention sessions and only 53% completed all data collection surveys. Statistically significant improvements between UC and PST groups were noted for caregiver stress (p=.039). Positive differences in caregiver self-efficacy found between UC and the BBC intervention groups approached significance at 30 days after discharge (p=.054). Patient unplanned hospital readmissions and days hospitalized were also higher, albeit not statistically significant, for UC participants than both intervention groups. ConclusionsAlthough positive findings were noted, results were negatively affected by study limitations including low enrollment and limited engagement (intervention completion and follow-up outcomes assessment). These limitations resulted, in part, from restrictions put into place during the COVID-19 pandemic, which limited contact with study participants and required alterations to the BBC intervention likely influencing its effectiveness. Despite limitations noted, the encouraging findings suggest the need for further research.

Current practices and challenges of outpatient parenteral antimicrobial therapy: a narrative review.

Extended hospitalization for infection management increases inpatient care costs and the risk of healthcare-associated adverse events, including infections. The growing global demand for healthcare, the diminishing availability of hospital beds and an increasing patient preference for care within their own home have been the primary drivers of the expansion of hospital-in-the-home programmes. Such programmes include the use of IV antimicrobials in outpatient settings, known as outpatient parenteral antimicrobial therapy (OPAT). However, OPAT practices vary globally. This review article aims to describe the current OPAT practices and challenges worldwide. OPAT practice begins with patient evaluation and selection using eligibility criteria, which requires collaboration between the interdisciplinary OPAT team, patients and caregivers. Depending on care requirements, eligible patients may be enrolled to various models of care, receiving medication by healthcare professionals at outpatient infusion centres, hospital clinics, home visits or through self-administration. OPAT can be used for the management of many infections where an effective oral treatment option is lacking. Various classes of parenteral antimicrobials, including β-lactams, aminoglycosides, glycopeptides, fluoroquinolones and antifungals such as echinocandins, are used globally in OPAT practice. Despite its benefits, OPAT has numerous challenges, including complications from medication administration devices, antimicrobial side effects, monitoring requirements, antimicrobial instability, patient non-adherence, patient OPAT rejection, and challenges related to OPAT team structure and administration, all of which impact its outcome. A negative outcome could include unplanned hospital readmission. Future research should focus on mitigating these challenges to enable optimization of the OPAT service and thereby maximize the documented benefits for the healthcare system, patients and healthcare providers.

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

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. 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. 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. 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.

Prediction of Readmission Following Sepsis Using Social Determinants of Health.

To determine the predictive value of social determinants of health (SDoH) variables on 30-day readmission following a sepsis hospitalization as compared with traditional clinical variables. Multicenter retrospective cohort study using patient-level data, including demographic, clinical, and survey data. Thirty-five hospitals across the United States from 2017 to 2021. Two hundred seventy-one thousand four hundred twenty-eight individuals in the AllofUs initiative, of which 8909 had an index sepsis hospitalization. None. Unplanned 30-day readmission to the hospital. Multinomial logistic regression models were constructed to account for survival in determination of variables associate with 30-day readmission and are presented as adjusted odds rations (aORs). Of the 8909 sepsis patients in our cohort, 21% had an unplanned hospital readmission within 30 days. Median age (interquartile range) was 54 years (41-65 yr), 4762 (53.4%) were female, and there were self-reported 1612 (18.09%) Black, 2271 (25.49%) Hispanic, and 4642 (52.1%) White individuals. In multinomial logistic regression models accounting for survival, we identified that change to nonphysician provider type due to economic reasons (aOR, 2.55 [2.35-2.74]), delay of receiving medical care due to lack of transportation (aOR, 1.68 [1.62-1.74]), and inability to afford flow-up care (aOR, 1.59 [1.52-1.66]) were strongly and independently associated with a 30-day readmission when adjusting for survival. Patients who lived in a ZIP code with a high percentage of patients in poverty and without health insurance were also more likely to be readmitted within 30 days (aOR, 1.26 [1.22-1.29] and aOR, 1.28 [1.26-1.29], respectively). Finally, we found that having a primary care provider and health insurance were associated with low odds of an unplanned 30-day readmission. In this multicenter retrospective cohort, several SDoH variables were strongly associated with unplanned 30-day readmission. Models predicting readmission following sepsis hospitalization may benefit from the addition of SDoH factors to traditional clinical variables.

Advanced practice nurse-coordinated same-day-discharge after atrial fibrillation ablation

Abstract Background Catheter ablation is an effective atrial fibrillation (AF) therapy, but a complex, resource-intensive procedure. Same-day discharge (SDD) reduces utilization of health care resources including personell and hospital beds, and may help to accommodate the increasing demand for AF ablation. However, besides structural adaptations, SDD requires more efficient logistics and coordination. Purpose Against this background, we established and validated a streamlined SDD program fully coordinated by an advanced practice nurse. Methods As dedicated SDD coordinator the advanced practice nurse was in charge of the full SDD protocol, including patient eligibility, patient flow, in-hospital logistics, patient education, discharge and short-term follow-up. For inclusion, basic home support and accessibility of the hospital within 60 minutes had to be warranted. Patients with LVEF <35% were excluded. Ablation was performed at the operator’s discretion. Ultrasound-guided femoral puncture was at the operator’s discretion for the first 150 SDD patients but became mandatory per protocol for all subsequent patients. Discharge by the SDD coordinator followed a standardized protocol including supervised ambulation, patient education, femoral inspection and echo. On post-ablation days 1 and 3, patients were called by the SDD coordinator to ensure well-being and good aspect of the femoral access site (smartphone foto control). In addition, patients could consult the SDD coordinator via mobile phone any time during working hours. In-person follow-up visits were scheduled at 2 weeks and 3, 6 and 12 months post-ablation. Results 420 consecutive patients were evaluated by the SDD coordinator of whom 331 were eligible for SDD. Reasons for exclusion were lack of home support (4.5%), living remotely (6.9%), or LVEF <35% (4.0%). 300 of the eligible patients (91%) were successfully discharged the same day (Fig. 1). Rates of unplanned medical attention (4.0%) and 30d-readmission (1.6%) were extremely low. Importantly, there was no major post-SDD complication. Unplanned medical attention and hospital readmissions were largely driven by minor femoral access site complications. Of note, those were significantly reduced upon introduction of mandatory ultrasound-guided puncture after the first 150 SDD patients (p=0.0145, Fig. 2). SDD coordination by the advanced practice nurse streamlined patient flow and in-hospital logistics and significantly reduced the total workload of nursing and medical staff. This resulted in great acceptance of the SDD program and satisfaction both among staff and patients. Conclusions Advanced practice nurse-coordinated SDD after AF ablation is safe and efficient. In fact, the position of a dedicated coordinator may be a key in the forthcoming transition of hospitals to SDD. Importantly, ultrasound-guided femoral puncture virtually eliminated relevant femoral access site complications and should be a prerequisite for SDD.Figure 1Figure 2

Predictive Modeling of Medical- and Orthopaedic-Related 90-Day Readmissions Following Primary Total Hip Arthroplasty

BackgroundThe rate of unplanned hospital readmissions following total hip arthroplasty (THA) varies from 3 to 10%, representing a major economic burden. However, it is unknown if specific factors are associated with different types of complications (ie, medical or orthopaedic-related) that lead to readmissions. Therefore, this study aimed to: (1) determine the overall, medical-related, and orthopaedic-related 90-day readmission rate; and (2) develop a predictive model for risk factors affecting overall, medical-related, and orthopaedic-related 90-day readmissions following THA. MethodsA prospective cohort of primary unilateral THAs performed at a large tertiary academic center in the United States from 2016 to 2020 was included (n = 8,893 patients) using a validated institutional data collection system. Orthopaedic-related readmissions were specific complications affecting the prosthesis, joint, and surgical wound. Medical readmissions were due to any other cause requiring medical management. Multivariable logistic regression models were used to investigate associations between prespecified risk factors and 90-day readmissions, as well as medical and orthopaedic-related readmissions independently. ResultsOverall, the rate of 90-day readmissions was 5.6%. Medical readmissions (4.2%) were found to be more prevalent than orthopaedic-related readmissions (1.4%). The area under the curve for the 90-day readmission model was 0.71 (95% confidence interval: 0.69 to 0.74). Factors significantly associated with medical-related readmissions were advanced age, Black race, education, Charlson Comorbidity Index, surgical approach, opioid overdose risk score, and nonhome discharge. In contrast, risk factors linked to orthopaedic-related readmissions encompassed body mass index, patient-reported outcome measure phenotype, nonosteoarthritis indication, opioid overdose risk, and nonhome discharge. ConclusionsOf the overall 90-day readmissions following primary THA, 75% were due to medical-related complications. Our successful predictive model for complication-specific 90-day readmissions highlights how different risk factors may disproportionately influence medical versus orthopaedic-related readmissions, suggesting that patient-specific, tailored preventive measures could reduce postoperative readmissions in the current value-based health care setting.

Symptom clusters and unplanned hospital readmission in Chinese patients with acute myocardial infarction on admission.

Acute myocardial infarction (AMI) has a high morbidity rate, high mortality rate, high readmission rate, high health care costs, and a high symptomatic, psychological, and economic burden on patients. Patients with AMI usually present with multiple symptoms simultaneously, which are manifested as symptom clusters. Symptom clusters have a profound impact on the quality of survival and clinical outcomes of AMI patients. The purpose of this study was to analyze unplanned hospital readmissions among cluster groups within a 1-year follow-up period, as well as to identify clusters of acute symptoms and the characteristics associated with them that appeared in patients with AMI. Between October 2021 and October 2022, 261 AMI patients in China were individually questioned for symptoms using a structured questionnaire. Mplus 8.3 software was used to conduct latent class analysis in order to find symptom clusters. Univariate analysis is used to examine characteristics associated with each cluster, and multinomial logistic regression is used to analyze a cluster membership as an independent predictor of hospital readmission after 1-year. Three unique clusters were found among the 11 acute symptoms: the typical chest symptom cluster (64.4%), the multiple symptom cluster (29.5%), and the atypical symptom cluster (6.1%). The cluster of atypical symptoms was more likely to have anemia and the worse values of Killip class compared with other clusters. The results of multiple logistic regression indicated that, in comparison to the typical chest cluster, the atypical symptom cluster substantially predicted a greater probability of 1-year hospital readmission (odd ratio 8.303, 95% confidence interval 2.550-27.031, P < 0.001). Out of the 11 acute symptoms, we have found three clusters: the typical chest symptom, multiple symptom, and atypical symptom clusters. Compared to patients in the other two clusters, those in the atypical symptom cluster-which included anemia and a large percentage of Killip class patients-had worse clinical indicators at hospital readmission during the duration of the 1-year follow-up. Both anemia and high Killip classification suggest that the patient's clinical presentation is poor and therefore the prognosis is worse. Intensive treatment should be considered for anemia and high level of Killip class patients with atypical presentation. Clinicians should focus on patients with atypical symptom clusters, enhance early recognition of symptoms, and develop targeted symptom management strategies to alleviate their discomfort in order to improve symptomatic outcomes.

Patient-Physician Sex Discordance and "Before Medically Advised" Discharge from Hospital: A Population-Based Retrospective Cohort Study.

Patient-physician sex discordance (when patient sex does not match physician sex) has been associated with reduced clinical rapport and adverse outcomes including post-operative mortality and unplanned hospital readmission. It remains unknown whether patient-physician sex discordance is associated with "before medically advised" hospital discharge (BMA discharge; commonly known as discharge "against medical advice"). To evaluate whether patient-physician sex discordance is associated with BMA discharge. Retrospective cohort study using 15years (2002-2017) of linked population-based administrative health data for all non-elective, non-obstetrical acute care hospitalizations from British Columbia, Canada. All individuals with eligible hospitalizations during study interval. Exposure: patient-physician sex discordance. BMA discharge (primary), 30-day hospital readmission or death (secondary). We identified 1,926,118 eligible index hospitalizations, 2.6% of which ended in BMA discharge. Among male patients, sex discordance was associated with BMA discharge (crude rate, 4.0% vs 2.9%; adjusted odds ratio [aOR] 1.08; 95%CI 1.03-1.14; p = 0.003). Among female patients, sex discordance was not associated with BMA discharge (crude rate, 2.0% vs 2.3%; aOR 1.02; 95%CI 0.96-1.08; p = 0.557). Compared to patient-physician sex discordance, younger patient age, prior substance use, and prior BMA discharge all had stronger associations with BMA discharge. Patient-physician sex discordance was associated with a small increase in BMA discharge among male patients. This finding may reflect communication gaps, differences in the care provided by male and female physicians, discriminatory attitudes among male patients, or residual confounding. Improved communication and better treatment of pain and opioid withdrawal may reduce BMA discharge.

Physician Financial Incentives to Reduce Unplanned Hospital Readmissions: A Propensity Score Weighted Cohort Study

BackgroundUnplanned hospital readmissions are associated with adverse patient outcomes and substantial healthcare costs. It remains unknown whether physician financial incentives for enhanced discharge planning can reduce readmission risk. MethodsIn 2012, policymakers in British Columbia, Canada, introduced a $75 fee-for-service physician payment to incentivize enhanced discharge planning (the “G78717” fee code). We used population-based administrative health data to compare outcomes among G78717-exposed and G78717-unexposed patients. We identified all nonelective hospitalizations potentially eligible for the incentive over a 5-year study interval. We examined the composite risk of unplanned readmission or death and total direct healthcare costs accrued within 30 days of discharge. Propensity score overlap weights and adjustment were used to account for differences between exposed and unexposed patients. ResultsA total of 5262 of 24,787 G78717-exposed and 28,096 of 136,541 unexposed patients experienced subsequent unplanned readmission or death, suggesting exposure to the G78717 incentive did not reduce the risk of adverse outcomes after discharge (crude percent, 21.1% vs 20.6%; adjusted odds ratio, 0.97; 95% CI, 0.93-1.01; P = .23). Mean direct healthcare costs within 30 days of discharge were $3082 and $2993, respectively (adjusted cost ratio, 1.00; 95% CI, 0.95-1.05; P = .93). ConclusionsA physician financial incentive that encouraged enhanced hospital discharge planning did not reduced the risk of readmission or death, and did not significantly decrease direct healthcare costs. Policymakers should consider the baseline prevalence and effectiveness of enhanced discharge planning, the magnitude and design of financial incentives, and whether auditing of incentivized activities is required when implementing similar incentives elsewhere. Trial RegistrationClinicalTrials.gov ID, NCT03256734

The effect of family-centered care on unplanned emergency room visits, hospital readmissions and intensive care admissions after surgery: a root cause analysis from a prospective multicenter study in the Netherlands

BackgroundOptimizing transitional care by practicing family-centered care might reduce unplanned events for patients who undergo major abdominal cancer surgery. However, it remains unknown whether involving family caregivers in patients’ healthcare also has negative consequences for patient safety. This study assessed the safety of family involvement in patients’ healthcare by examining the cause of unplanned events in patients who participated in a family involvement program (FIP) after major abdominal cancer surgery.MethodsThis is a secondary analysis focusing on the intervention group of a prospective cohort study conducted in the Netherlands. Data were collected from April 2019 to May 2022. Participants in the intervention group were patients who engaged in a FIP. Unplanned events were analyzed, and root causes were identified using the medical version of a prevention- and recovery-information system for monitoring and analysis (PRISMA) that analyses unintended events in healthcare. Unplanned events were compared between patients who received care from family caregivers and patients who received professional at-home care after discharge. A Mann-Whitney U test was used to analyze data.ResultsOf the 152 FIP participants, 68 experienced an unplanned event and were included. 112 unplanned events occurred with 145 root causes since some unplanned events had several root causes. Most root causes of unplanned events were patient-related factors (n = 109, 75%), such as patient characteristics and disease-related factors. No root causes due to inadequate healthcare from the family caregiver were identified. Unplanned events did not differ statistically (interquartile range 1–2) (p = 0.35) between patients who received care from trained family caregivers and those who received professional at-home care after discharge.ConclusionBased on the insights from the root-cause analysis in this prospective multicenter study, it appears that unplanned emergency room visits and hospital readmissions are not related to the active involvement of family caregivers in surgical follow-up care. Moreover, surgical follow-up care by trained family caregivers during hospitalization was not associated with increased rates of unplanned adverse events. Hence, the concept of active family involvement by proficiently trained family caregivers in postoperative care appears safe and feasible for patients undergoing major abdominal surgery.

Artificial intelligence informing clinical decision making on the risk of hospital readmissions in multi-morbid patients: a systematic review

Abstract Introduction Multi-morbid patients have complex care needs and are more likely to utilise healthcare services, which represents a financial burden on healthcare organisations. 30-day readmission of patients is a method of measuring the quality of the services provided within healthcare.[1] Artificial intelligence (AI) models can flag multi-morbidity patients at increased risk of readmission.[2] However, it is unclear which common predictors have been used to develop these models. Aim To systematically review the medical literature to identify predictors that have been used to develop AI models that predicted unplanned 30-day hospital readmissions of multi-morbid patients, and whether these predictors were modifiable or non-modifiable. Methods Four large databases: Medline, Embase, Web of Science and Cumulative Index to Nursing and Allied Health Literature (CINAHL) were searched on 15th November 2022. Only publications that developed a machine learning algorithm to predict unplanned 30-day hospital readmission for patients with multi-morbidity were included. Articles published in English language were eligible for inclusion. A narrative synthesis of all eligible studies was undertaken. Key findings were identified through inductive strategy, which includes simplifying raw data in the included articles into a comprehensive format. This systematic review was registered with the PROSPRO database (CRD42022373937) and followed PRISMA guidelines. Results There were 1,906 articles extracted from all databases, 18 of which met our inclusion criteria. A total of 669 predictors of hospital readmission were found, and were divided into 103 modifiable (i.e., action could be taken to change the outcome) and 566 non-modifiable (i.e. age, gender, number of previous emergency admissions. The average number of modifiable predictors per prediction model was six, with the most common being length of hospital stay, multi-morbidity, obesity, hypertension, diabetes, depression, and anaemia. The most commonly used AI algorithm was the gradient boosting algorithm. This algorithm generally showed a better performance than other models reported. The performance of all models in the included studies was compared; 13 studies showed an average sensitivity of 72%. The average specificity was calculated at 73% from 11 studies. The highest AUC reported was above 0.9, which demonstrates an excellent performing model, while five models did not report a value for the AUC. Conclusion We identified modifiable and non-modifiable predictors used in previously developed AI algorithms that predict 30-day hospital readmissions of multi-morbid patients. Modifiable predictors in particular can help guide clinical decision-making by allowing early actions to be taken in primary care to potentially reduce the risk of readmission. However, one limitation of this review is that some included studies used balanced (i.e. synthetic) data which could have introduced a level of bias.

Hospitalized Patients with Delirium and 28-Day Unplanned Hospital Readmissions: A Longitudinal Retrospective Cohort Study

ObjectiveTo establish the predictors of 28-day unplanned hospital readmissions (28D-UHR) in older adults (aged >65 years) with delirium during index hospital admission. DesignRetrospective longitudinal cohort study. Setting and Participants1634 patients (aged >65 years) admitted to a Melbourne quaternary hospital with delirium during index admission. MethodsDelirium during hospital admission was defined by the inclusion of one of the following International Classification of Diseases, Tenth Revision, codes F05.0, F05.1, F05.8, or F05.9 in the hospital medical discharge summary. Descriptive statistics were obtained for baseline characteristics. Multivariate logistic regression model was developed to assess predictors of 28D-UHR. ResultsA total of 1634 patients with delirium during their inpatient admission were included, with 9.8% (160 patients) incidence of 28D-UHR. For patients who were readmitted, a shorter length of stay [odds ratio (OR) 0.98, 95% CI 0.96-0.99], higher number of medications on discharge from index admission (OR 1.10, 95% CI 1.06-1.14), and residing in a nursing home preadmission (OR 1.35, 95% CI 1.04-1.75) were associated with 28D-UHR. Conclusions and ImplicationsThis study found that nursing home residence pre index admission, shorter length of stay (LOS), and polypharmacy were predictors of 28D-UHR. Further research into strategies to minimize 28D-UHR is required. Exploration of predischarge pharmacy-driven deprescribing programs and hospital-based postdischarge support for nursing home staff are important areas for future intervention.

Multi-trajectories of symptoms and their associations with unplanned 30-day hospital readmission among patients with heart failure: a longitudinal study.

This study aimed to uncover hidden patterns and predictors of symptom multi-trajectories within 30 days after discharge in patients with heart failure and assess the risk of unplanned 30-day hospital readmission in different patterns. The study was conducted from September 2022 to September 2023 in four third-class hospitals in Tianjin, China. A total of 301 patients with heart failure were enrolled in the cohort, and 248 patients completed a 30-day follow-up after discharge. Three multi-trajectory groups were identified: mild symptom status (24.19%), moderate symptom status (57.26%), and severe symptom status (18.55%). With the mild symptom status group as a reference, physical frailty, psychological frailty, and comorbid renal dysfunction were predictors of the moderate symptom status group. Physical frailty, psychological frailty, resilience, taking diuretics, and comorbid renal dysfunction were predictors of the severe symptom status group. Compared with the mild symptom status group, the severe symptom status group was significantly associated with high unplanned 30-day hospital readmission risks. This study identified three distinct multi-trajectory groups among patients with heart failure within 30 days after discharge. The severe symptom status group was associated with a significantly increased risk of unplanned 30-day hospital readmission. Common and different factors predicted different symptom multi-trajectories. Healthcare providers should assess the physical and psychological frailty and renal dysfunction of patients with heart failure before discharge. Inpatient care aimed at alleviating physical and psychological frailty and enhancing resilience may be important to improve patients' symptom development post-discharge.

Enteral nutrition on discharge from intensive care and 30-day unplanned readmission: An exploratory, retrospective study of association

Individuals who survive critical illness are often malnourished with inadequate oral nutrient intake after leaving the intensive care unit (ICU). Enteral nutrition (EN) improves nutrient intake but there is limited evidence on the impact of maintaining EN after discharge from the ICU. The objective of this exploratory study was to understand the association between EN maintenance after ICU and 30-day unplanned hospital re-admission, to inform on future prospective research into the effects of post-ICU nutrition. This was a single-centre, retrospective study of ICU patients, requiring ventilation, who received EN for at least 3 days in ICU and were discharged to the ward. 102 patients met the inclusion criteria; 45 (44.1%) maintained EN and 57 (55.9%) discontinued EN after ICU discharge; there were no significant differences in demographics or clinical measures at ICU admission. Reason for EN discontinuation was documented in 38 (66.7%) patients, with 27 (71%) discontinuing EN due to a routine ward practice of feeding tube removal. Unplanned 30-day hospital re-admission occurred in 17 (16.7%) patients overall, 5 (11.1%) in the EN group and 12 (21.1%) in the non-EN group (crude odds ratio [OR] 0.47, 95% CI 0.15, 1.45, p=0.188). After adjusting for age, sex, BMI and length of stay, there was a persistent trend to lower re-admission rates in the EN group (OR 0.37, 95% CI 0.09, 1.57, p=0.176). EN maintenance after ICU discharge was associated with a trend to lower 30-day unplanned hospital re-admission rates. The clinically relevant reduction of about 50% in unplanned re-admission rates in this exploratory study warrants larger, prospective studies of post-ICU nutrition strategies based on clear discontinuation criteria to optimize nutrition and evaluate patient-centred outcomes.

Association between patient activation and delayed discharge in elective laparoscopic cholecystectomy: A prospective cohort analysis

BackgroundImproving patient activation may be an effective way to reduce healthcare costs and improve patient outcomes after surgery. ObjectiveTo determine whether preoperative patient activation is associated with delayed discharge (i.e., length of stay >24 h) after elective laparoscopic cholecystectomy. Postoperative symptoms, unscheduled access to healthcare facilities within seven days of surgery, unplanned hospital readmissions, and postoperative complications were analyzed as secondary outcomes. DesignThis cohort study was a secondary analysis of the DeDiLaCo study (Delayed Discharge after day-surgery Laparoscopic Cholecystectomy) collecting data of patients undergoing elective laparoscopic cholecystectomy during 2021 in Italy. Data was analyzed from June 2022 to April 2023. Setting90 Italian surgical centers participating in the study. Participants4708 adult patients with an instrumental diagnosis of gallbladder disease and undergoing laparoscopic cholecystectomy. Patient activation was assessed using the Italian translation of Patient Activation Measure in the preoperative setting. ResultsOf 4532 cases analyzed the median (IQR) Patient Activation Measure score was 80.3 (71.2–92.3). Participants were on average 55.5 years of age and 58.1 % were female. Two groups based on the activation level were created: 270 (6 %) had low activation, and 4262 had high activation. The low activation level was associated with the likelihood of delayed discharge (odds ratio [OR] 1.47, 95 % CI, 1.11–1.95; P = .008), higher symptom burden (OR 1.99, 95 % CI 1.49–2.66, P < .0001), and unplanned healthcare utilization within seven days after hospital discharge (OR 1.85, 95 % CI, 1.29–2.63; P = .001). There was no difference between the high and low activation groups in the incidence of postoperative complications (OR 1.28, 95 % CI, 0.95–1.73; P = .10) and hospital readmission after discharge (OR 0.95, 95 % CI, 0.30–3.05; P = .93). ConclusionsOur results suggest that patients with low activation have 1.47 times the risk of delayed discharge compared with patients with higher activation, almost twice the risk of the onset of postoperative symptoms, and 1.85 times the risk of unscheduled use of hospital services. Screening for patient activation in the preoperative setting could not only identify patients not suitable for early discharge, but more importantly, help physicians and nurses develop tailored interventions.

Association of Malnutrition with Surgical and Hospital Outcomes after Spine Surgery for Spinal Metastases: A National Surgical Quality Improvement Program Study of 1613 Patients.

Background: Malnutrition is a common condition that may exacerbate many medical and surgical pathologies. However, few have studied the impact of malnutrition on surgical outcomes for patients undergoing surgery for metastatic disease of the spine. This study aims to evaluate the impact of malnutrition on perioperative complications and healthcare resource utilization following surgical treatment of spinal metastases. Methods: We conducted a retrospective cohort study using the 2011-2019 American College of Surgeons National Surgical Quality Improvement Program database. Adult patients with spinal metastases who underwent laminectomy, corpectomy, or posterior fusion for extradural spinal metastases were identified using the CPT, ICD-9-CM, and ICD-10-CM codes. The study population was divided into two cohorts: Nourished (preoperative serum albumin values ≥ 3.5 g/dL) and Malnourished (preoperative serum albumin values < 3.5 g/dL). We assessed patient demographics, comorbidities, intraoperative variables, postoperative adverse events (AEs), hospital LOS, discharge disposition, readmission, and reoperation. Multivariate logistic regression analyses were performed to identify the factors associated with a prolonged length of stay (LOS), AEs, non-routine discharge (NRD), and unplanned readmission. Results: Of the 1613 patients identified, 26.0% were Malnourished. Compared to Nourished patients, Malnourished patients were significantly more likely to be African American and have a lower BMI, but the age and sex were similar between the cohorts. The baseline comorbidity burden was significantly higher in the Malnourished cohort compared to the Nourished cohort. Compared to Nourished patients, Malnourished patients experienced significantly higher rates of one or more AEs (Nourished: 19.8% vs. Malnourished: 27.6%, p = 0.004) and serious AEs (Nourished: 15.2% vs. Malnourished: 22.6%, p < 0.001). Upon multivariate regression analysis, malnutrition was found to be an independent and associated with an extended LOS [aRR: 3.49, CI (1.97, 5.02), p < 0.001], NRD [saturated aOR: 1.76, CI (1.34, 2.32), p < 0.001], and unplanned readmission [saturated aOR: 1.42, CI (1.04, 1.95), p = 0.028]. Conclusions: Our study suggests that malnutrition increases the risk of postoperative complication, prolonged hospitalizations, non-routine discharges, and unplanned hospital readmissions. Further studies are necessary to identify the protocols that pre- and postoperatively optimize malnourished patients undergoing spinal surgery for metastatic spinal disease.

Predicting 30-day unplanned hospital readmission after revision total knee arthroplasty: machine learning model analysis of a national patient cohort.

Revision total knee arthroplasty (TKA) is associated with a higher risk of readmission than primary TKA. Identifying individual patients predisposed to readmission can facilitate proactive optimization and increase care efficiency. This study developed machine learning (ML) models to predict unplanned readmission following revision TKA using a national-scale patient dataset. A total of 17,443 revision TKA cases (2013-2020) were acquired from the ACS NSQIP database. Four ML models (artificial neural networks, random forest, histogram-based gradient boosting, and k-nearest neighbor) were developed on relevant patient variables to predict readmission following revision TKA. The length of stay, operation time, body mass index (BMI), and laboratory test results were the strongest predictors of readmission. Histogram-based gradient boosting was the best performer in distinguishing readmission (AUC: 0.95) and estimating the readmission probability for individual patients (calibration slope: 1.13; calibration intercept: -0.00; Brier score: 0.064). All models produced higher net benefit than the default strategies of treating all or no patients, supporting the clinical utility of the models. ML demonstrated excellent performance for the prediction of readmission following revision TKA. Optimization of important predictors highlighted by our model may decrease preventable hospital readmission following surgery, thereby leading to reduced financial burden and improved patient satisfaction.