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.

Inpatient midwifery staffing levels and postpartum readmissions: a retrospective multicentre longitudinal study.

BACKGROUND: Preventing readmission to hospital after giving birth is a key priority, as rates have been rising along with associated costs. There are many contributing factors to readmission, and some are thought to be preventable. Nurse and midwife understaffing has been linked to deficits in care quality. This study explores the relationship between staffing levels and readmission rates in maternity settings. METHODS: We conducted a retrospective longitudinal study using routinely collected individual patient data in three maternity services in England from 2015 to 2020. Data on admissions, discharges and case-mix were extracted from hospital administration systems. Staffing and workload were calculated in Hours Per Patient day per shift in the first two 12-hour shifts of the index (birth) admission. Postpartum readmissions and staffing exposures for all birthing admissions were entered into a hierarchical multivariable logistic regression model to estimate the odds of readmission when staffing was below the mean level for the maternity service. RESULTS: 64 250 maternal admissions resulted in birth and 2903 mothers were readmitted within 30 days of discharge (4.5%). Absolute levels of staffing ranged between 2.3 and 4.1 individuals per midwife in the three services. Below average midwifery staffing was associated with higher rates of postpartum readmissions within 7 days of discharge (adjusted OR (aOR) 1.108, 95% CI 1.003 to 1.223). The effect was smaller and not statistically significant for readmissions within 30 days of discharge (aOR 1.080, 95% CI 0.994 to 1.174). Below average maternity assistant staffing was associated with lower rates of postpartum readmissions (7 days, aOR 0.957, 95% CI 0.867 to 1.057; 30 days aOR 0.965, 95% CI 0.887 to 1.049, both not statistically significant). CONCLUSION: We found evidence that lower than expected midwifery staffing levels is associated with more postpartum readmissions. The nature of the relationship requires further investigation including examining potential mediating factors and reasons for readmission in maternity populations.

Inpatient-level care at home delivered by virtual wards and hospital at home: a systematic review and meta-analysis of complex interventions and their components.

BACKGROUND: Technology-enabled inpatient-level care at home services, such as virtual wards and hospital at home, are being rapidly implemented. This is the first systematic review to link the components of these service delivery innovations to evidence of effectiveness to explore implications for practice and research. METHODS: For this review (registered here https://osf.io/je39y ), we searched Cochrane-recommended multiple databases up to 30 November 2022 and additional resources for randomised and non-randomised studies that compared technology-enabled inpatient-level care at home with hospital-based inpatient care. We classified interventions into care model groups using three key components: clinical activities, workforce, and technology. We synthesised evidence by these groups quantitatively or narratively for mortality, hospital readmissions, cost-effectiveness and length of stay. RESULTS: We include 69 studies: 38 randomised studies (6413 participants; largely judged as low or unclear risk of bias) and 31 non-randomised studies (31,950 participants; largely judged at serious or critical risk of bias). The 69 studies described 63 interventions which formed eight model groups. Most models, regardless of using low- or high-intensity technology, may have similar or reduced hospital readmission risk compared with hospital-based inpatient care (low-certainty evidence from randomised trials). For mortality, most models had uncertain or unavailable evidence. Two exceptions were low technology-enabled models that involve hospital- and community-based professionals, they may have similar mortality risk compared with hospital-based inpatient care (low- or moderate-certainty evidence from randomised trials). Cost-effectiveness evidence is unavailable for high technology-enabled models, but sparse evidence suggests the low technology-enabled multidisciplinary care delivered by hospital-based teams appears more cost-effective than hospital-based care for those with chronic obstructive pulmonary disease (COPD) exacerbations. CONCLUSIONS: Low-certainty evidence suggests that none of technology-enabled care at home models we explored put people at higher risk of readmission compared with hospital-based care. Where limited evidence on mortality is available, there appears to be no additional risk of mortality due to use of technology-enabled at home models. It is unclear whether inpatient-level care at home using higher levels of technology confers additional benefits. Further research should focus on clearly defined interventions in high-priority populations and include comparative cost-effectiveness evaluation. TRIAL REGISTRATION: https://osf.io/je39y .

Area Deprivation and Postpartum Readmission Facility Location and Timing.

This cohort study evaluates the role that community-level socioeconomic status plays in hypertension-related hospital readmission within 12 weeks after delivery.

Health Trajectories of Skilled Nursing Facility Patients With Alzheimer's Disease and Related Dementias: Evidence for Practicing Nurses.

PURPOSE: Older adults with Alzheimer's disease and related dementias (ADRD) are at high risk for acute medical problems and their health trajectories frequently include hospital admission and care in a skilled nursing facility (SNF). Their health trajectories after SNF discharge are poorly understood. Therefore, in the current study, we sought to describe health trajectories and factors associated with hospital read-missions for older adults with ADRD during the 30 days following SNF discharge. METHOD: We conducted a secondary analysis of data from a clinical trial of transitional care of older adults with transitions from SNF to home and assisted living. A multiple case study design was used in the analysis of the health trajectories of 49 SNF patients with ADRD, 51% discharged from SNF to their own home, 34% discharged to a family member's home, and 15% transferred to assisted living. RESULTS: Within 30 days of discharge, 20% of patients with ADRD experienced new or recurrent acute needs and hospital readmission. CONCLUSION: Our findings suggest the need for nursing interventions to support patients with ADRD during care transitions, such as focusing care on the patient-caregiver dyad, providing transitional care, referring patients for palliative care consultation, and conducting nurse-led research to improve care transitions of these patients and their caregivers. [Journal of Gerontological Nursing, 50(4), 34-41.].

Increasing and sustaining discharges by noon - a multi-year process improvement project.

High hospital occupancy degrades emergency department performance by increasing wait times, decreasing patient satisfaction, and increasing patient morbidity and mortality. Late discharges contribute to high hospital occupancy by increasing emergency department (ED) patient length of stay (LOS). We share our experience with increasing and sustaining early discharges at a 650-bed academic medical center in the United States. Our process improvement project followed the Institute of Medicine Model for Improvement of successive Plan‒Do‒Study‒Act cycles. We implemented multiple iterative interventions over 41 months. As a result, the proportion of discharge orders before 10 am increased from 8.7% at baseline to 22.2% (p < 0.001), and the proportion of discharges by noon (DBN) increased from 9.5% to 26.8% (p < 0.001). There was no increase in balancing metrics because of our interventions. RA-LOS (Risk Adjusted Length Of Stay) decreased from 1.16 to 1.09 (p = 0.01), RA-Mortality decreased from 0.65 to 0.61 (p = 0.62) and RA-Readmissions decreased from 0.92 to 0.74 (p < 0.001). Our study provides a roadmap to large academic facilities to increase and sustain the proportion of patients discharged by noon without negatively impacting LOS, 30-day readmissions, and mortality. Continuous performance evaluation, adaptability to changing resources, multidisciplinary engagement, and institutional buy-in were crucial drivers of our success.

Acute patients discharged without an established diagnosis: risk of mortality and readmission of nonspecific diagnoses compared to disease-specific diagnoses.

BACKGROUND: Nonspecific discharge diagnoses after acute hospital courses represent patients discharged without an established cause of their complaints. These patients should have a low risk of adverse outcomes as serious conditions should have been ruled out. We aimed to investigate the mortality and readmissions following nonspecific discharge diagnoses compared to disease-specific diagnoses and assessed different nonspecific subgroups. METHODS: Register-based cohort study including hospital courses beginning in emergency departments across 3 regions of Denmark during March 2019-February 2020. We identified nonspecific diagnoses from the R- and Z03-chapter in the ICD-10 classification and excluded injuries, among others-remaining diagnoses were considered disease-specific. Outcomes were 30-day mortality and readmission, the groups were compared by Cox regression hazard ratios (HR), unadjusted and adjusted for socioeconomics, comorbidity, administrative information and laboratory results. We stratified into short (3-<12 h) or lengthier (12-168 h) hospital courses. RESULTS: We included 192,185 hospital courses where nonspecific discharge diagnoses accounted for 50.7% of short and 25.9% of lengthier discharges. The cumulative risk of mortality for nonspecific vs. disease-specific discharge diagnoses was 0.6% (0.6-0.7%) vs. 0.8% (0.7-0.9%) after short and 1.6% (1.5-1.7%) vs. 2.6% (2.5-2.7%) after lengthier courses with adjusted HRs of 0.97 (0.83-1.13) and 0.94 (0.85-1.05), respectively. The cumulative risk of readmission for nonspecific vs. disease-specific discharge diagnoses was 7.3% (7.1-7.5%) vs. 8.4% (8.2-8.6%) after short and 11.1% (10.8-11.5%) vs. 13.7% (13.4-13.9%) after lengthier courses with adjusted HRs of 0.94 (0.90-0.98) and 0.95 (0.91-0.99), respectively. We identified 50 clinical subgroups of nonspecific diagnoses, of which Abdominal pain (n = 12,462; 17.1%) and Chest pain (n = 9,599; 13.1%) were the most frequent. The subgroups described differences in characteristics with mean age 41.9 to 80.8 years and mean length of stay 7.1 to 59.5 h, and outcomes with < 0.2-8.1% risk of 30-day mortality and 3.5-22.6% risk of 30-day readmission. CONCLUSIONS: In unadjusted analyses, nonspecific diagnoses had a lower risk of mortality and readmission than disease-specific diagnoses but had a similar risk after adjustments. We identified 509 clinical subgroups of nonspecific diagnoses with vastly different characteristics and prognosis.

Utility of the LACE index to assess risk of mortality and readmission in patients with spinal infections.

Retrospective cohort study. To assess the utility of the LACE index for predicting death and readmission in patients with spinal infections (SI). SIs are severe conditions, and their incidence has increased in recent years. The LACE (Length of stay, Acuity of admission, Comorbidities, Emergency department visits) index quantifies the risk of mortality or unplanned readmission. It has not yet been validated for SIs. LACE indices were calculated for all adult patients who underwent surgery for spinal infection between 2012 and 2021. Data were collected from a single academic teaching hospital. Outcome measures included the LACE index, mortality, and readmission rate within 30 and 90 days. In total, 164 patients were analyzed. Mean age was 64.6 (± 15.1) years, 73 (45%) were female. Ten (6.1%) patients died within 30 days and 16 (9.8%) died within 90 days after discharge. Mean LACE indices were 13.4 (± 3.6) and 13.8 (± 3.0) for the deceased patients, compared to 11.0 (± 2.8) and 10.8 (± 2.8) for surviving patients (p = 0.01, p < 0.001), respectively. Thirty-seven (22.6%) patients were readmitted ≤ 30 days and 48 (29.3%) were readmitted ≤ 90 days. Readmitted patients had a significantly higher mean LACE index compared to non-readmitted patients (12.9 ± 2.1 vs. 10.6 ± 2.9, < 0.001 and 12.8 ± 2.3 vs. 10.4 ± 2.8, p < 0.001, respectively). ROC analysis for either death or readmission within 30 days estimated a cut-off LACE index of 12.0 points (area under the curve [AUC] 95% CI, 0.757 [0.681-0.833]) with a sensitivity of 70% and specificity of 69%. Patients with SI had high LACE indices that were associated with high mortality and readmission rates. The LACE index can be applied to this patient population to predict the risk of early death or unplanned readmission.

Development of an enhanced scoring system to predict ICU readmission or in-hospital death within 24 hours using routine patient data from two NHS Foundation Trusts.

RATIONALE: Intensive care units (ICUs) admit the most severely ill patients. Once these patients are discharged from the ICU to a step-down ward, they continue to have their vital signs monitored by nursing staff, with Early Warning Score (EWS) systems being used to identify those at risk of deterioration. OBJECTIVES: We report the development and validation of an enhanced continuous scoring system for predicting adverse events, which combines vital signs measured routinely on acute care wards (as used by most EWS systems) with a risk score of a future adverse event calculated on discharge from the ICU. DESIGN: A modified Delphi process identified candidate variables commonly available in electronic records as the basis for a 'static' score of the patient's condition immediately after discharge from the ICU. L1-regularised logistic regression was used to estimate the in-hospital risk of future adverse event. We then constructed a model of physiological normality using vital sign data from the day of hospital discharge. This is combined with the static score and used continuously to quantify and update the patient's risk of deterioration throughout their hospital stay. SETTING: Data from two National Health Service Foundation Trusts (UK) were used to develop and (externally) validate the model. PARTICIPANTS: A total of 12 394 vital sign measurements were acquired from 273 patients after ICU discharge for the development set, and 4831 from 136 patients in the validation cohort. RESULTS: Outcome validation of our model yielded an area under the receiver operating characteristic curve of 0.724 for predicting ICU readmission or in-hospital death within 24 hours. It showed an improved performance with respect to other competitive risk scoring systems, including the National EWS (0.653). CONCLUSIONS: We showed that a scoring system incorporating data from a patient's stay in the ICU has better performance than commonly used EWS systems based on vital signs alone. TRIAL REGISTRATION NUMBER: ISRCTN32008295.

Cost variation of nonelective surgery for ulcerative colitis across the United States.

BACKGROUND: Although clinical outcomes of surgery for ulcerative colitis (UC) have improved in the modern biologic era, expenditures continue to increase. A contemporary cost analysis of UC operative care is lacking. The present study aimed to characterize risk factors and center-level variation in hospitalization costs after nonelective resection for UC. METHODS: All adults with UC in the 2016-2020 Nationwide Readmissions Database undergoing nonelective colectomy or rectal resection were identified. Mixed-effects models were developed to evaluate patient and hospital factors associated with costs. Random effects were estimated and used to rank hospitals by increasing risk-adjusted center-level costs. High-cost hospitals (HCHs) in the top decile of expenditure were identified, and their association with select outcomes was subsequently assessed. RESULTS: An estimated 10,280 patients met study criteria with median index hospitalization costs of $40,300 (IQR, $26,400-$65,000). Increased time to surgery was significantly associated with a +$2500 increment in costs per day. Compared with low-volume hospitals, medium- and high-volume centers demonstrated a -$5900 and -$8200 reduction in costs, respectively. Approximately 19.2% of variability in costs was attributable to interhospital differences rather than patient factors. Although mortality and readmission rates were similar, HCH status was significantly associated with increased complications (adjusted odds ratio [AOR], 1.39), length of stay (+10.1 days), and nonhome discharge (AOR, 1.78). CONCLUSION: The present work identified significant hospital-level variation in the costs of nonelective operations for UC. Further efforts to optimize time to surgery and regionalize care to higher-volume centers may improve the value of UC surgical care in the United States.

Social determinants of health predict readmission following COVID-19 hospitalization: a health information exchange-based retrospective cohort study.

Introduction: Since February 2020, over 104 million people in the United States have been diagnosed with SARS-CoV-2 infection, or COVID-19, with over 8.5 million reported in the state of Texas. This study analyzed social determinants of health as predictors for readmission among COVID-19 patients in Southeast Texas, United States. Methods: A retrospective cohort study was conducted investigating demographic and clinical risk factors for 30, 60, and 90-day readmission outcomes among adult patients with a COVID-19-associated inpatient hospitalization encounter within a regional health information exchange between February 1, 2020, to December 1, 2022. Results and discussion: In this cohort of 91,007 adult patients with a COVID-19-associated hospitalization, over 21% were readmitted to the hospital within 90 days (n = 19,679), and 13% were readmitted within 30 days (n = 11,912). In logistic regression analyses, Hispanic and non-Hispanic Asian patients were less likely to be readmitted within 90 days (adjusted odds ratio [aOR]: 0.8, 95% confidence interval [CI]: 0.7-0.9, and aOR: 0.8, 95% CI: 0.8-0.8), while non-Hispanic Black patients were more likely to be readmitted (aOR: 1.1, 95% CI: 1.0-1.1, p = 0.002), compared to non-Hispanic White patients. Area deprivation index displayed a clear dose-response relationship to readmission: patients living in the most disadvantaged neighborhoods were more likely to be readmitted within 30 (aOR: 1.1, 95% CI: 1.0-1.2), 60 (aOR: 1.1, 95% CI: 1.2-1.2), and 90 days (aOR: 1.2, 95% CI: 1.1-1.2), compared to patients from the least disadvantaged neighborhoods. Our findings demonstrate the lasting impact of COVID-19, especially among members of marginalized communities, and the increasing burden of COVID-19 morbidity on the healthcare system.

Impact of care coordination on 30-day readmission, mortality, and costs for heart failure.

OBJECTIVES: Although coordination of care has become the main focus of health care reform efforts to improve outcomes and decrease costs, limited information is available concerning the impact of care coordination on 30-day outcomes and costs. We used nationwide, population-based data to examine the influence of care coordination on 30-day readmission, mortality, and costs for heart failure (HF). STUDY DESIGN: We analyzed 20,713 patients with HF 18 years or older discharged from hospitals in 2016 using Taiwan's National Health Insurance Research Database. The coordination of care among a patient's outpatient physicians was measured with care density. METHODS: Multilevel regression models were used after adjustment for patient and hospital characteristics to explore the impact of care density on 30-day readmission, mortality, and costs. RESULTS: Patients with high care coordination had lower odds of 30-day readmission (OR, 0.90; 95% CI, 0.82-0.98) and mortality (OR, 0.83; 95% CI, 0.70-0.99) and lower costs (cost ratio [CR], 0.84; 95% CI, 0.79-0.90) compared with those with low care coordination. Patients with medium care coordination had lower costs (CR, 0.92; 95% CI, 0.86-0.98) than those with low care coordination. CONCLUSIONS: High care coordination is associated with decreased 30-day readmission, mortality, and costs for HF. Enhancing coordination of care has the potential to increase the value of care. It is important to monitor coordination of care and develop strategies to maintain high levels of care coordination for HF.

Systematic review and meta-analysis of the management of acute uncomplicated diverticulitis: time to change traditional practice.

BACKGROUND: To evaluate comparative outcomes of outpatient (OP) versus inpatient (IP) treatment and antibiotics (ABX) versus no antibiotics (NABX) approach in the treatment of uncomplicated (Hinchey grade 1a) acute diverticulitis. METHODS: A systematic online search was conducted using electronic databases. Comparative studies of OP versus IP treatment and ABX versus NABX approach in the treatment of Hinchey grade 1a acute diverticulitis were included. Primary outcome was recurrence of diverticulitis. Emergency and elective surgical resections, development of complicated diverticulitis, mortality rate, and length of hospital stay were the other evaluated secondary outcome parameters. RESULTS: The literature search identified twelve studies (n = 3,875) comparing NABX (n = 2,008) versus ABX (n = 1,867). The NABX group showed a lower disease recurrence rate and shorter length of hospital stay compared with the ABX group (P = 0.01) and (P = 0.004). No significant difference was observed in emergency resections (P = 0.33), elective resections (P = 0.73), development of complicated diverticulitis (P = 0.65), hospital re-admissions (P = 0.65) and 30-day mortality rate (P = 0.91). Twelve studies (n = 2,286) compared OP (n = 1,021) versus IP (n = 1,265) management of uncomplicated acute diverticulitis. The two groups were comparable for the following outcomes: treatment failure (P = 0.10), emergency surgical resection (P = 0.40), elective resection (P = 0.30), disease recurrence (P = 0.22), and mortality rate (P = 0.61). CONCLUSION: Observation-only treatment is feasible and safe in selected clinically stable patients with uncomplicated acute diverticulitis (Hinchey 1a classification). It may provide better outcomes including decreased length of hospital stay. Moreover, the OP approach in treating patients with Hinchey 1a acute diverticulitis is comparable to IP management. Future high-quality randomised controlled studies are needed to understand the outcomes of the NABX approach used in an OP setting in managing patients with uncomplicated acute diverticulitis.

Co-design of an intervention to improve patient participation in discharge medication communication.

Patients can experience medication-related harm and hospital readmission because they do not understand or adhere to post-hospital medication instructions. Increasing patient medication literacy and, in turn, participation in medication conversations could be a solution. The purposes of this study were to co-design and test an intervention to enhance patient participation in hospital discharge medication communication. In terms of methods, co-design, a collaborative approach where stakeholders design solutions to problems, was used to develop a prototype medication communication intervention. First, our consumer and healthcare professional stakeholders generated intervention ideas. Next, inpatients, opinion leaders, and academic researchers collaborated to determine the most pertinent and feasible intervention ideas. Finally, the prototype intervention was shown to six intended end-users (i.e. hospital patients) who underwent usability interviews and completed the Theoretical Framework of Acceptability questionnaire. The final intervention comprised of a suite of three websites: (i) a medication search engine; (ii) resources to help patients manage their medications once home; and (iii) a question builder tool. The intervention has been tested with intended end-users and results of the Theoretical Framework of Acceptability questionnaire have shown that the intervention is acceptable. Identified usability issues have been addressed. In conclusion, this co-designed intervention provides patients with trustworthy resources that can help them to understand medication information and ask medication-related questions, thus promoting medication literacy and patient participation. In turn, this intervention could enhance patients' medication self-efficacy and healthcare utilization. Using a co-design approach ensured authentic consumer and other stakeholder engagement, while allowing opinion leaders and researchers to ensure that a feasible intervention was developed.

HR-BGCN : Predicting readmission for heart failure from electronic health records.

Heart failure has become a huge public health problem, and failure to accurately predict readmission will further lead to the disease's high cost and high mortality. The construction of readmission prediction model can assist doctors in making decisions to prevent patients from deteriorating and reduce the cost burden. This paper extracts the patient discharge records from the MIMIC-III database. It divides the patients into three research categories: no readmission, readmission within 30 days, and readmission after 30 days, to predict the readmission of patients. We propose the HR-BGCN model to predict the readmission of patients. First, we use the Adaptive-TMix to improve the prediction indicators of a few categories and reduce the impact of unbalanced categories. Then, the knowledge-informed graph attention mechanism is proposed. By introducing a document-level explicit diagram structure, the coding ability of graph node features is significantly improved. The paragraph-level representation obtained through graph learning is combined with the context token-level representation of BERT, and finally, the multi-classification task is carried out. We also compare several typical graph learning classification models to verify the model's effectiveness, such as the IA-GCN model, GAT model, etc. The results show that the average F1 score of the HR-BGCN model proposed in this paper for 30-day readmission of heart failure patients is 88.26%, and the average accuracy is 90.47%. The HR-BGCN model is significantly better than the graph learning classification model for predicting heart failure readmission. It can help doctors predict the 30-day readmission of patients, then reduce the readmission rate of patients.

Robotic repair of moderate-sized midline ventral hernias reduced complications, readmissions, and length of hospitalization compared to open techniques.

PURPOSE: To compare outcomes of robotic and open repair for uncomplicated, moderate-sized, midline ventral hernias. METHODS: From 2017 to 2021, patient characteristics and 30 day outcomes for all ventral hernias at our center were prospectively collected. We studied hernias potentially suitable for robotic repair: elective, midline, 3-10 cm rectus separation, no prior mesh, and no need for concomitant procedure. Robotic or open repair was performed by surgeon or patient preference. The primary outcome was any complication using Clavien-Dindo scoring. Secondary outcomes were operative time, length-of-stay, and readmissions. Regression identified predictors of complications. RESULTS: Of 648 hernias repaired, 70 robotic and 52 open repairs met inclusion criteria. The groups had similar patient demographics, co-morbidities, and hernia size, except that there were more immunosuppressed patients in the open group (11 versus 5 patients, p = 0.031). Complications occurred after 7 (13%) open repairs versus 2 (3%) robotic repairs, p = 0.036. Surgical site infection occurred after four open repairs but no robotic repair, p = 0.004. Length-of-stay averaged almost 3 days longer after open repair (4.3 ± 2.7 days versus 1.5 ± 1.4 days, p = 0.031). Readmission occurred after 6 (12%) oppen repairs but only 1 (1%) robotic repair. A long-term survey (61% response rate after mean follow-up of 2.8 years) showed that the HerQLes QOL score was better after robotic repair (46 ± 15 versus 40 ± 17, = 0.049). In regression models, only open technique predicted complications. CONCLUSIONS: Robotic techniques were associated with fewer complications, shorter hospitalization, fewer infections, and fewer readmissions compared to open techniques. Open surgical technique was the only predictor of complications.

Timing of readmissions for complications following emergency colectomy: follow-up beyond post-operative day 30 matters.

BACKGROUND AND PURPOSE: Emergency colectomies are associated with a higher risk of complications compared to elective ones. A critical assessment of complications occurring beyond post-operative day 30 (POD30) is lacking. This study aimed to assess the readmission rate and factors associated with readmission 6-months following emergency colectomy. METHODS: A retrospective cohort study of adult patients who underwent emergency colectomy (2010-2018) was performed using the Nationwide Readmissions Database. The cohort was divided into two groups: (i) no readmission and (ii) emergency readmission(s) for complications related to colectomy (defined using ICD-9/10 codes). Readmissions were categorized as either "early" (POD0-30) or "late" (> POD30). Differences between groups were described and multivariable regression controlling for relevant covariates defined a priori were used to identify factors associated with timing of readmission and cost. RESULTS: Of 141,481 eligible cases, 13.22% (n = 18,699) were readmitted within 6-months of emergency colectomy for colectomy-related complications, 61.63% of which were "late" readmissions (> POD30). The most common reasons for "late" readmission were for bleeding, gastrointestinal, and infectious complications (20.80%, 25.30%, and 32.75%, respectively). On multiple logistic regression, female gender (OR 1.12; 95%CI 1.04-1.21), open procedures (OR 1.12, 95%CI 1.011-1.24), and sigmoidectomies (OR 1.51, 95%CI 1.39-1.65, relative to right hemicolectomies) were the strongest predictors of "late" readmission. On multiple linear regression, "late" readmissions were associated with a $1717.09 USD (95%CI $1717.05-$1717.12) increased cost compared to "early" readmissions. DISCUSSION: The majority of colectomy-related readmissions following emergency colectomy occur beyond POD30 and are associated with cases that are of overall higher morbidity, as well as open sigmoidectomies. Given the associated increased cost of care, mitigation of such readmissions by close follow-up prior to and beyond POD30 is advisable.

Association of hospital-based substance use supports on emergency department revisits: a retrospective cohort study in Sudbury, Canada from 2018 to 2022.

BACKGROUND: This study compares emergency department (ED) revisits for patients receiving hospital-based substance-use support compared to those who did not receive specialized addiction services at Health Sciences North in Sudbury, Ontario, Canada. METHODS: The study is a retrospective observational study using administrative data from all patients presenting with substance use disorder (SUD) at Health Sciences North from January 1, 2018, and August 31, 2022 with ICD-10 codes from the Discharge Abstract Database (DAD) and the National Ambulatory Care Database (NACRS). There were two interventions under study: addiction medicine consult services (AMCS group), and specialized addiction medicine unit (AMU group). The AMCS is a consult service offered for patients in the ED and those who are admitted to the hospital. The AMU is a specialized inpatient medical unit designed to offer addiction support to stabilize patients that operates under a harm-reduction philosophy. The primary outcome was all cause ED revisit within 30 days of the index ED or hospital visit. The secondary outcome was all observed ED revisits in the study period. Kaplan-Meier curves were used to measure the proportion of 30-day revisits by exposure group. Odds ratios and Hazard Ratios were calculated using logistic regression models with random effects and Cox-proportional hazard model respectively. RESULTS: A total of 5,367 patients with 10,871 ED index visits, and 2,127 revisits between 2018 and 2022 are included in the study. 45% (2,340/5,367) of patient were not admitted to hospital. 30-day revisits were less likely among the intervention group: Addiction Medicine Consult Services (AMCS) in the ED significantly reduced the odds of revisits (OR 0.53, 95% CI 0.39-0.71, p < 0.01) and first revisits (OR 0.42, 95% CI 0.33-0.53, p < 0.01). The AMU group was associated with lower revisits odds (OR 0.80, 95% CI 0.66-0.98, p = 0.03). For every additional year of age, the odds of revisits slightly decreased (OR 0.99, 95% CI 0.98-1.00, p = 0.01) and males were found to have an increased risk compared to females (OR 1.50, 95% CI 1.35-1.67, p < 0.01). INTERPRETATION: We observe statistically significant differences in ED revisits for patients receiving hospital-based substance-use support at Health Sciences North. Hospital-based substance-use supports could be applied to other hospitals to reduce 30-day revisits.

Association between admission albumin levels and 30-day readmission after hip fracture surgery in geriatric patients: a propensity score-matched study.

PURPOSE: This study aimed to evaluate the correlation admission albumin levels and 30-day readmission after hip fracture surgery in geriatric patients. METHODS: In this retrospective cohort study, 1270 geriatric patients admitted for hip fractures to a level I trauma center were included. Patients were stratified by clinical thresholds and albumin level quartiles. The association between admission albumin levels and 30-day readmission risk was assessed using multivariate logistic regression and propensity score-matched analyses. The predictive accuracy of albumin levels for readmission was evaluated by ROC curves. The dose-response relationship between albumin levels and readmission risk was examined. RESULTS: The incidence of 30-day readmission was significantly higher among hypoalbuminemia patients than those with normal albumin levels (OR = 2.090, 95%CI:1.296-3.370, p = 0.003). Furthermore, propensity score-matched analyses demonstrated that patients in the Q2(35.0-37.9 g/L) (OR 0.621, 95%CI 0.370-1.041, p = 0.070), Q3(38.0-40.9 g/L) (OR 0.378, 95%CI 0.199-0.717, p < 0.001) and Q4 (≥ 41 g/L) (OR 0.465, 95%CI 0.211-0.859, p = 0.047) quartiles had a significantly lower risk of 30-day readmission compared to those in the Q1(< 35 g/L) quartile. These associations remained significant after propensity score matching (PSM) and subgroup analyses. Dose-response relationships between albumin levels and 30-day readmission were observed. CONCLUSIONS: Lower admission albumin levels were independently associated with higher 30-day readmission rates in elderly hip fracture patients. Our findings indicate that serum albumin may assist perioperative risk assessment, and prompt correction of hypoalbuminemia and malnutrition could reduce short-term readmissions after hip fracture surgery in this high-risk population.

Risk factors for readmission after a cholecystectomy: a case-control study.

OBJECTIVE: The aim of this study was to assess the risk factors associated with 30-day hospital readmissions after a cholecystectomy. METHODS: We conducted a case-control study, with data obtained from UC-Christus from Santiago, Chile. All patients who underwent a cholecystectomy between January 2015 and December 2019 were included in the study. We identified all patients readmitted after a cholecystectomy and compared them with a randomized control group. Univariate and multivariate analyses were conducted to identify risk factors. RESULTS: Of the 4866 cholecystectomies performed between 2015 and 2019, 79 patients presented 30-day hospital readmission after the surgical procedure (1.6%). We identified as risk factors for readmission in the univariate analysis the presence of a solid tumor at the moment of cholecystectomy (OR = 7.58), high pre-operative direct bilirubin (OR = 2.52), high pre-operative alkaline phosphatase (OR = 3.25), emergency admission (OR = 2.04), choledocholithiasis on admission (OR = 4.34), additional surgical procedure during the cholecystectomy (OR = 4.12), and post-operative complications. In the multivariate analysis, the performance of an additional surgical procedure during cholecystectomy was statistically significant (OR = 4.24). CONCLUSION: Performing an additional surgical procedure during cholecystectomy was identified as a risk factor associated with 30-day hospital readmission.

OBJETIVO: El objetivo de este estudio fue evaluar los factores de riesgo asociados al reingreso hospitalario en los primeros 30 días post colecistectomía. MÉTODOS: Estudio de casos-controles con datos obtenidos del Hospital Clínico de la UC-Christus, Santiago, Chile. Se ­incluyeron las colecistectomías realizadas entre los años 2015-2019. Se consideraron como casos aquellos pacientes que reingresaron en los 30 primeros días posterior a una colecistectomía. Se realizó un análisis univariado y multivariado de diferentes posibles factores de riesgo. RESULTADOS: De un total de 4866 colecistectomías, 79 pacientes presentaron reingreso hospitalario. Los resultados estadísticamente significativos en el análisis univariado fueron; tumor sólido al momento de la colecistectomía (OR = 7.58) bilirrubina directa preoperatoria alterada (OR = 2.52), fosfatasa alcalina preoperatoria alterada (OR = 3.25), ingreso de urgencia (OR = 2.04), coledocolitiasis al ingreso (OR = 4.34) realización de otros procedimientos (OR = 4.12) y complicaciones postoperatorias. En el análisis multivariado sólo la realización de otro procedimiento durante la colecistectomía fue estadísticamente significativa (OR = 4.24). CONCLUSIÓN: La realización de otros procedimientos durante la colecistectomía es un factor de riesgo de reingreso hospitalario en los 30 días posteriores a la colecistectomía.