Risk Factors For Hospital Readmission Research Articles

Hospital admissions among patients with Comorbid Substance Use disorders: a secondary analysis of predictors from the NavSTAR Trial

BackgroundIndividuals with substance use disorders (SUDs) frequently use acute hospital services. The Navigation Services to Avoid Rehospitalization (NavSTAR) trial found that a patient navigation intervention for hospitalized patients with comorbid SUDs reduced subsequent inpatient admissions compared to treatment-as-usual (TAU).MethodsThis secondary analysis extends previous findings from the NavSTAR trial by examining whether selected patient characteristics independently predicted hospital service utilization and moderated the effect of the NavSTAR intervention. Participants were 400 medical/surgical hospital patients with comorbid SUDs. We analyzed 30- and 90-day inpatient readmissions (one or more readmissions) and cumulative incidence of inpatient admissions through 12 months using multivariable logistic and negative binomial regression, respectively.ResultsConsistent with primary findings and controlling for patient factors, NavSTAR participants were less likely than TAU participants to be readmitted within 30 (P = 0.001) and 90 (P = 0.03) days and had fewer total readmissions over 12 months (P = 0.008). Hospitalization in the previous year (P < 0.001) was associated with cumulative readmissions over 12 months, whereas Medicaid insurance (P = 0.03) and index diagnoses of infection (P = 0.001) and injuries, poisonings, or procedural complications (P = 0.004) were associated with fewer readmissions. None of the selected covariates moderated the effect of the NavSTAR intervention.ConclusionsPrevious findings showed that patient navigation could reduce repeat hospital admissions among patients with comorbid SUDs. Several patient factors were independently associated with readmission. Future research should investigate risk factors for hospital readmission among patients with comorbid SUDs to optimize interventions.Trial RegistrationNIH ClinicalTrials.gov NCT02599818, Registered November 9, 2015 https://classic.clinicaltrials.gov/ct2/show/NCT02599818.

Risk Factors for Hospital Readmission Following Noncardiac Surgery: International Cohort Study

Objective: To determine timing and risk factors associated with readmission within 30 days of discharge following noncardiac surgery. Background: Hospital readmission after noncardiac surgery is costly. Data on the drivers of readmission have largely been derived from single-center studies focused on a single surgical procedure with uncertainty regarding generalizability. Methods: We undertook an international (28 centers, 14 countries) prospective cohort study of a representative sample of adults ≥45 years of age who underwent noncardiac surgery. Risk factors for readmission were assessed using Cox regression (ClinicalTrials.gov, NCT00512109). Results: Of 36,657 eligible participants, 2744 (7.5%; 95% confidence interval [CI], 7.2–7.8) were readmitted within 30 days of discharge. Rates of readmission were highest in the first 7 days after discharge and declined over the follow-up period. Multivariable analyses demonstrated that 9 baseline characteristics (eg, cancer treatment in past 6 months; adjusted hazard ratio [HR], 1.44; 95% CI, 1.30–1.59), 5 baseline laboratory and physical measures (eg, estimated glomerular filtration rate or on dialysis; HR, 1.47; 95% CI, 1.24–1.75), 7 surgery types (eg, general surgery; HR, 1.86; 95% CI, 1.61–2.16), 5 index hospitalization events (eg, stroke; HR, 2.21; 95% CI, 1.24–3.94), and 3 other factors (eg, discharge to nursing home; HR, 1.61; 95% CI, 1.33–1.95) were associated with readmission. Conclusions: Readmission following noncardiac surgery is common (1 in 13 patients). We identified perioperative risk factors associated with 30-day readmission that can help frontline clinicians identify which patients are at the highest risk of readmission and target them for preventive measures.

Multifactorial risk factors for hospital readmissions among patients with symptoms of advanced heart failure.

Economic burden of heart failure is attributed to hospital readmissions. Previous studies assessing risk factors for readmissions have focused on single group of risk factors, were limited to 30-day readmissions, or did not account for competing risk of mortality. This study investigates the biological, socio-economic, and behavioural risk factors predicting hospital readmissions while accounting for the competing risk of mortality. In this prospective cohort study, we recruited 250 patients hospitalized with symptoms of advanced heart failure [New York Heart Association (NYHA) Class III and IV] between July 2017 and April 2019. We analysed their baseline survey data and their hospitalization records over the next 4.5years (July 2017 to January 2022). We used a joint-frailty model to determine the multifactorial risk factors for all-cause and unplanned hospital readmissions and mortality. At the time of recruitment, patients' mean (SD) age was 66 (12) years, majority being male (72%) and NYHA class IV (68%) with reduced ejection fraction (72%). 87% of the patients had poor self-care behaviours, 51% had diabetes and 56% had weak grip strength. Within 2years of a hospital admission, 74% of the patients had at least one readmission. Among all readmissions during follow-up, 68% were unplanned. Results from the multivariable regression analysis shows that the independent risk factors for hospital readmissions were biologic-weak grip strength [hazard ratio (95% CI): 1.59 (1.06, 2.13)], poor functional status [1.79 (0.98, 2.61)], diabetes [1.42 (0.97, 1.86)]; behavioural-poor self-care [1.66 (0.84, 2.49)], and socio-economic-preference for maximal life extension at high cost for those with high education [1.98 (1.17, 2.80)]. Risk factors for unplanned hospital readmissions were similar. A higher hospital readmission rate increased the risk of mortality [1.86 (1.23, 2.50)]. Other risk factors for mortality were biologic-weak grip strength [3.65 (0.57, 6.73)], diabetes [2.52 (0.62, 4.42)], socio-economic-lower education [2.45 (0.37, 4.53)], and being married [2.53 (0.37, 4.69)]. Having a private health insurance [0.40 (0.08, 0.73)] lowered the risk for mortality. Risk factors for hospital readmissions and mortality are multifactorial. Many of these factors, such as weak grip strength, diabetes, poor self-care behaviours, are potentially modifiable and should be routinely assessed and managed in cardiac clinics and hospital admissions.

Risk Factors for Hospital Readmission in Patients With Interstitial Lung Disease.

Little is known about the rates, causes, or risk factors for hospital readmission among patients with interstitial lung disease (ILD). We investigated the prevalence, features, and comorbidities of subjects hospitalized with ILD and their subsequent re-hospitalizations in this retrospective study. A retrospective analysis of subjects enrolled in the University of Chicago ILD Natural History registry was conducted. Demographic data, comorbidities, and timing and cause of subsequent hospitalizations were collected from the medical record. The primary outcome was time to first readmission via a cause-specific Cox hazards model with a sensitivity analysis with the Fine-Gray cumulative hazard model; the secondary outcome was the number of hospitalizations per subject via a Poisson multivariable model. Among 1,796 patients with ILD, 443 subjects were hospitalized, with 978 total hospitalizations; 535 readmissions were studied, 282 (53%) for a respiratory indication. For the outcome of time to readmission, Black race was the only subject characteristic associated with an increased hazard of readmission in the Cox model (hazard ratio 1.50, P = .03) while Black race, hypersensitivity pneumonitis, and sarcoidosis were associated with increased hazard of readmission in the Fine-Gray model. Black race, female sex, atrial fibrillation, obstructive lung disease, and pulmonary hypertension were associated with an increased number of hospitalizations in the Poisson model. We demonstrated that hospital readmission from any cause was a common occurrence in subjects with ILD. Further efforts to improve quality of life among these subjects could focus on risk scores for readmission, mitigating racial health disparities, and treatment of comorbidities.

Orthognathic Surgery in the US. What are the Risk Factors for Readmission?

Purpose: Contemporary orthognathic surgery is safe and predicable. However, there are opportunities for further improvement. The purpose of this study was to estimate the frequency and identify risk factors for readmission following orthognathic surgery in the US. Materials and methods: A retrospective cohort study was conducted using the Nationwide Readmissions Database (NRD) on patients who underwent orthognathic surgery in 2017 and 2018. There were multiple heterogenous predictor variables that were broadly comprised of patient characteristics and hospitalization characteristics. The primary outcome variable was readmission. Logistic regression analysis was used to determine risk factors for hospital readmission. A P-value less than .05 was considered statistically significant. Results: The final study sample consisted of 8578 patients (mean age, 27.2 years), of whom 74 patients (0.9%) readmitted. Relative to a length of stay (LOS) of 0 to 2 days, a LOS of &gt;2 days (OR 1.90, P &lt; .05) was a risk factor for readmission. Patients with acute post procedural pain were 3 times more likely to readmit ( P &lt; .05). Conclusion: Patients with an LOS of &gt;2 days were at risk for readmission relative to patients with an LOS of 0 to 2 days. Post-procedural pain was also a significant risk factor for readmission. Finally, patients with mandibular hypoplasia were less likely to readmit.

Impact of Preexisting Depression and Anxiety on Hospital Readmission and Long-Term Survival After Cardiac Arrest.

While sudden cardiac arrest (CA) survivors are at risk for developing psychiatric disorders, little is known about the impact of preexisting mental health conditions on long-term survival or postacute healthcare utilization. We examined the prevalence of preexisting psychiatric conditions in CA patients who survived hospital discharge, characterized incidence and reason for inpatient psychiatry consultation during these patients' acute hospitalizations, and determined the association of pre-CA depression and anxiety with hospital readmission rates and long-term survival. We hypothesized that prior depression or anxiety would be associated with higher hospital readmission rates and lower long-term survival. We conducted a retrospective cohort study including patients resuscitated from in- and out-of-hospital CA who survived both admission and discharge from a single hospital between January 1, 2010, and December 31, 2017. We identified patients from our prospective registry, then performed a structured chart review to abstract past psychiatric history, prescription medications for psychiatric conditions, and identify inpatient psychiatric consultations. We used administrative data to identify readmissions within 1 year and vital status through December 31, 2020. We used multivariable Cox regressions controlling for patient demographics, medical comorbidities, discharge Cerebral Performance Category and disposition, depression, and anxiety history to predict long-term survival and hospital readmission. We included 684 subjects. Past depression or anxiety was noted in 24% (n = 162) and 19% (n = 129) of subjects. A minority of subjects (n = 139, 20%) received a psychiatry consultation during the index hospitalization. Overall, 262 (39%) subjects had at least 1 readmission within 1 year. Past depression was associated with an increased hazard of hospital readmission (hazard ratio 1.50, 95% CI 1.11-2.04), while past anxiety was not associated with readmission. Neither depression nor anxiety were independently associated with long-term survival. Depression is an independent risk factor for hospital readmission in CA survivors.

Association of homelessness and psychiatric hospital readmission—a retrospective cohort study 2016–2020

BackgroundA large proportion of adult psychiatric inpatients experience homelessness and are often discharged to unstable accommodation or the street. It is unclear whether homelessness impacts psychiatric hospital readmission. Our primary objective was to examine the association between homelessness and risk for 30-day and 90-day readmission following discharge from a psychiatric unit at a single urban hospital.MethodsA retrospective cohort study involving health administrative data among individuals (n = 3907) in Vancouver, Canada with an acute psychiatric admission between January 2016 and December 2020. Participants were followed from the date of index admission until censoring (December 30, 2020). Homelessness was measured at index admission and treated as a time-varying exposure. Adjusted Hazard Ratios (aHRs) of acute readmission (30-day and 90-day) for psychiatric and substance use disorders were estimated using multivariable Cox proportional hazards regression.ResultsThe cohort comprised 3907 individuals who were predominantly male (61.89%) with a severe mental illness (70.92%), substance use disorder (20.45%) and mean age of 40.66 (SD, 14.33). A total of 686 (17.56%) individuals were homeless at their index hospitalization averaging 19.13 (21.53) days in hospital. After adjusting for covariates, patients experiencing homelessness had a 2.04 (1.65, 2.51) increased rate of 30-day readmission and 1.65 (1.24, 2.19) increased rate of 90-day readmission during the observation period.ConclusionsHomelessness was significantly associated with increased 30-day and 90-day readmission rates in a large comprehensive sample of adults with mental illness and substance use disorders. Interventions to reduce homelessness are urgently needed.QuestionIs homelessness associated with risk for 30-day and 90-day psychiatric hospital readmission?FindingsIn this retrospective cohort study of 3907 individuals, homelessness at discharge was associated with increased 30-day and 90-day psychiatric readmission.MeaningHousing status is an important risk factor for hospital readmission. High-quality interventions focused on housing supports have the potential to reduce psychiatric readmission.

Risk Factors for Hospital Re-admission for Diabetes Related Foot Disease: A Prospective Cohort Study

Diabetes related foot disease (DFD) is a common reason for admission to hospital, but the predictive factors for repeat admission are poorly defined. The primary aim of this study was to identify rates and predictive factors for DFD related hospital re-admission. Patients admitted to hospital for treatment of DFD at a single regional centre were recruited prospectively between January 2020 and December 2020. Participants were followed for 12 months to evaluate the primary outcome of hospital re-admission. The relationship between predictive factors and re-admission were examined using non-parametric statistical tests and Cox proportional hazard analyses. The median age of the 190 participants was 64.9 (standard deviation 13.3) years and 68.4% were male. Forty-one participants (21.6%) identified themselves as Aboriginal or Torres Strait Islander people. One hundred participants (52.6%) were re-admitted to hospital at least once over 12 months. The commonest reason for re-admission was for treatment of foot infection (84.0% of first re-admission). Absent pedal pulses (unadjusted hazard ratio [HR] 1.90; 95% confidence interval [CI] 1.26 - 2.85), loss of protective sensation (LOPS) (unadjusted HR 1.98; 95% CI 1.08 - 3.62), and male sex (unadjusted HR 1.62; 95% CI 1.03 - 2.54) increased the risk of re-admission. After risk adjustment, only absence of pedal pulses (HR 1.92, 95% CI 1.27 - 2.91) and LOPS (HR 2.02, 95% CI 1.09 - 3.74) significantly increased the risk of re-admission. Over 50% of patients admitted to hospital for treatment of DFD are re-admitted within one year. Patients with absent pedal pulses and those with LOPS are twice as likely to be re-admitted.

Risk Factors for Unexpected Hospital Admission Following Achilles Tendon Repair: A National Database Study

INTRODUCTION Achilles tendon rupture (ATR) repair is one of the most common orthopaedic surgeries performed in the United States, however there is a paucity of literature on predisposing risk factors for hospital readmissions. The purpose of this study is to identify risk factors for 30-day readmission in patients undergoing ATR repair with emphasis on procedures performed in the outpatient setting. Specifically, we examine: 1) 30-day post-operative hospital readmission rates; 2) the medical comorbidities and patient characteristics that predisposed this cohort to post-operative complications; and 3) the complications leading to readmission. METHODS The ACS-NSQIP was queried for patients who underwent ATR from 2015 to 2019 using CPT code 27650 in all fields yielding a sample size of 3,887 cases. The following demographic, lifestyle, and comorbidity variables were recorded: age, sex, race, BMI, morbid obesity (BMI ≥ 40.00 kg/m2), bleeding disorders, chronic obstructive pulmonary disease (COPD), diabetes mellitus, hypertension, tobacco use, and chronic steroid use. The primary outcome of 30-day readmission was defined as unplanned hospital readmission likely related to the principal procedure. Independent samples Student’s t-tests, chi-squared, and, where appropriate, Fisher’s exact tests were used in univariate analyses to identify demographic, lifestyle, and peri-operative variables related to 30-day readmission following ATR. Multivariate logistic regression modeling was subsequently performed. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated and reported. RESULTS Of the 3,887 patients included in our sample, 28 were readmitted within the 30-day post-operative period, corresponding to a readmission rate of 0.73%. Significant relationships with univariate analyses between readmission status and the following patient variables included: mean patient age (p = 0.02); hypertension (p &lt; 0.001); BMI (p = 0.01); morbid obesity (p = 0.002); ASA Classification (p = 0.006); and bleeding disorders (p = 0.03). Multivariate logistic regression modeling confirmed that the following patient variables were associated with statistically significantly increased odds of readmission: age, p = 0.02), OR = 1.03, 95% CI [1.01, 1.06]; hypertension, p &lt; 0.001, OR = 3.82, 95% CI [1.81, 8.06]; BMI, p = 0.01, OR = 1.06, 95% CI [1.01, 1.11]; morbid obesity, p = 0.004, OR = 3.53, 95% CI [1.49, 8.36]. CONCLUSION Our study indicated that only 0.73% of patients were readmitted after their outpatient procedure. Patients who: 1) have BMIs greater than 40; 2) are older in age 3) have hypertension; and 4) a higher ASA Classification were at increased risk for readmission.

Trends in Venous Thromboembolism Readmission Rates after Ischemic Stroke and Intracerebral Hemorrhage.

Venous thromboembolism (VTE) is a life-threatening complication of stroke. We evaluated nationwide rates and risk factors for hospital readmissions with VTE after an intracerebral hemorrhage (ICH) or acute ischemic stroke (AIS) hospitalization. Using the Healthcare Cost and Utilization Project (HCUP) Nationwide Readmission Database, we included patients with a principal discharge diagnosis of ICH or AIS from 2016 to 2019. Patients who had VTE diagnosis or history of VTE during the index admission were excluded. We performed Cox regression models to determine factors associated with VTE readmission, compared rates between AIS and ICH and developed post-stroke VTE risk score. We estimated VTE readmission rates per day over a 90-day time window post-discharge using linear splines. Of the total 1,459,865 patients with stroke, readmission with VTE as the principal diagnosis within 90 days occurred in 0.26% (3,407/1,330,584) AIS and 0.65% (843/129,281) ICH patients. The rate of VTE readmission decreased within first 4-6 weeks (P<0.001). In AIS, cancer, obesity, higher National Institutes of Health Stroke Scale (NIHSS) score, longer hospital stay, home or rehabilitation disposition, and absence of atrial fibrillation were associated with VTE readmission. In ICH, longer hospital stay and rehabilitation disposition were associated with VTE readmission. The VTE rate was higher in ICH compared to AIS (adjusted hazard ratio 2.86, 95% confidence interval 1.93-4.25, P<0.001). After stroke, VTE readmission risk is highest within the first 4-6 weeks and nearly three-fold higher after ICH vs. AIS. VTE risk is linked to decreased mobility and hypercoagulability. Studies are needed to test short-term VTE prophylaxis beyond hospitalization in high-risk patients.

Initiating Occupational and Physical Therapy in the Hospital After Birth: Access, Reimbursement, and Outcomes

Acute care therapists routinely screen body systems, activity tolerance, safe mobility, activities of daily living/instrumental activities of daily living performance, cognition, caregiver support, home environment, and risk factors for hospital readmission. Despite most elective procedures, such as joint replacement and spine surgery, which receive automatic orders for acute care therapy, individuals who elect to give birth in a hospital are typically not offered rehabilitation services to optimize their recovery. Across hospitals in the United States, individuals receiving obstetric care have limited access to acute care therapy despite increasing postpartum readmission rates, severe maternal morbidity, and disproportionate levels of maternal mortality. Cardiovascular conditions, infection, and hemorrhage remain the leading causes of death in the obstetric population during the first 6 weeks postpartum. However, individuals are frequently discharged from the hospital after birth without a formal assessment by an acute care occupational or physical therapist. Extensive education to maternal care providers on obstetric rehabilitation is needed to improve outcomes after hospital birth with inpatient occupational and physical therapy. Supplemental video abstract available at https://www.youtube.com/watch?v=zfdU-1DuQiM.

A comprehensive mobility discharge assessment framework for older adults transitioning from hospital-to-home in the community—What mobility factors are critical to include? Protocol for an international e-Delphi study

BackgroundMobility deficits have been identified as an independent risk factor for hospital readmission for adults ≥65 years. Despite evidence indicating how determinants additively influence and predict mobility, no hospital-to-home care transition models comprehensively assess all seven mobility determinants, cognitive, financial, environmental, personal, physical, psychological, and social. There is currently a lack of clarity regarding what factors clinicians and researchers should evaluate for each mobility determinant. The purpose of this e-Delphi study is to prioritize and reach consensus on the factors for each mobility determinant that are critical to assess as part of the Comprehensive Mobility Discharge Assessment Framework (CMDAF) when older adults are discharged from hospital-to-home.MethodsThis protocol paper is an international modified e-Delphi study following the Recommendations for the Conducting and Reporting of Delphi Studies. International researchers, clinicians, older adults and family caregivers residing in a country with universal or near-universal health coverage will be invited to participate as ‘experts’ in three e-Delphi rounds administered through DelphiManager©. The e-Delphi Round 1 questionnaire will be developed based on scoping review findings and will be pilot tested. For each round, experts will be asked to rate factors for each determinant that are critical to assess as part of the CMDAF using a 9-point scale: Not Important (1–3), Important but Not Critical (4–6), and Critical (7–9). The scale will include a selection option of "unable to score" and experts will also be asked to provide a rationale for their scoring and suggest missing factors. Experts will receive feedback summaries in Rounds 2 and 3 to guide them in reflecting on their initial responses and re-rating of factors that have not reached consensus. The criteria for reaching consensus will be if ≥70% of experts rate a factor as "critical" (scores ≥7) and ≤ 15% of experts rate a factor as "not important" (scores≤ 3). Quantitative data will be analyzed using median values, frequencies, percentages, interquartile range, and bar graphs; Wilcoxon matched-pairs signed-rank test will be used to assess the stability of participants’ responses. Rationale (qualitative data) provided in the open-ended comments section will be analyzed using content analysis.ConclusionThis study is a first step in developing the CMDAF and will be used to guide a subsequent e-Delphi survey to decide on the tools that should be used to measure the examples of each factor included in our framework.

Discharge destination and readmissions among patients with head and neck cancer.

ObjectiveLowering hospital readmission rates is a national goal, and presents an opportunity to lower health care costs, improve quality, and increase patient satisfaction. We aim to assess whether discharge disposition is associated with readmission.MethodsA retrospective cohort study using logistic regression to quantify risk factors of hospital readmission in patients with confirmed head and neck cancer (HNC) who underwent surgery from 2010 to 2018 contained in the Pennsylvania Health Care Cost Containment Council database, which includes patients treated in Pennsylvania hospitals.ResultsThe readmission rate in this study was 18.1%. Cancers of the hypopharynx had the highest rates of readmission (29.2%). Male sex (odds ratio [OR]: 0.87, 95% CI: 0.75–1.00), emergent admission (vs. elective admission: OR = 1.33, 95% CI: 1.02–1.74), discharge to home health (vs. home: OR = 1.85, 95% CI: 1.59–2.16), discharge to skilled nursing facility (SNF) (vs. home: OR = 2.21, 95% CI: 1.80–2.72), and having 4+ comorbidities (vs. 0–1: OR = 1.39, 95% CI: 1.09–1.76) were significant risk factors for hospital readmission.ConclusionIt is necessary to consider the readmission risk associated with HNC patients. Reasons for readmission are multifactorial and can be related to demographics, hospital course, comorbidities, or discharge disposition–this requires further assessment. There is importance in increasing HNC awareness and staff education about the unique needs of this population.Level of Evidence4.

Developmental delay: is this pediatric patient population at risk for complications following open treatment of femoral shaft fracture?

Femoral shaft fractures are common in the pediatric population, accounting for over 20% of inpatient pediatric fractures. Patients with developmental delays are a population group whose medical care and recovery come with a unique set of considerations and challenges. The purpose of this study was to evaluate the impact of developmental delay on outcomes following open treatment of femoral shaft fractures in the pediatric population. Pediatric patients undergoing open treatment of femoral shaft fracture from 2012 to 2019 were identified in the National Surgical Quality Improvement Program-Pediatric database. Patients were divided into two groups: patients with developmental delay and patients without developmental delay. Patient demographics, comorbidities, and various postoperative outcomes were compared between the two groups using bivariate and multivariate analyses. Of the 5896 pediatric patients who underwent open treatment of femoral shaft fracture, 5479 patients (92.9%) did not have developmental delay whereas 417 (7.1%) had developmental delay. Patients with developmental delay were more likely to have other medical comorbidities. Following adjustment on multivariable regression analysis to control for the baseline differences between the two groups, patients with developmental delay had an increased risk of readmission to the hospital (OR 4.762; p = 0.014). Developmental delay in the pediatric population was found to be an independent risk factor for hospital readmission following open treatment of femoral shaft fractures. Taking these patients into special consideration when evaluating the optimal treatment plan can be beneficial to reduce the risks of readmission, which can decrease costs for both the patient and the hospital.

Risk Factors for Hospital Readmission for Clostridioides difficile Infection: A Statewide Retrospective Cohort Study.

(1) Background: Clostridioides difficile infection (CDI) is associated with a high recurrence rate, and a significant proportion of patients with CDI are readmitted following discharge. We aimed to identify the risk factors for CDI-related readmission within 90 days following an index hospital stay for CDI. (2) Methods: We analyzed the electronic medical data of admitted patients in our health system over a two-year period. A multivariate logistic regression model, supplemented with bias-corrected and accelerated confidence intervals (BCa-CI), was implemented to assess the risk factors. (3) Results: A total of 1253 adult CDI index cases were included in the analysis. The readmission rate for CDI within 90 days of discharge was 11% (140/1253). The risk factors for CDI-related readmission were fluoroquinolone exposure within 90 days before the day of index CDI diagnosis (aOR: 1.58, 95% CI: 1.05–2.37), higher Elixhauser comorbidity score (aOR: 1.05, 95% CI: 1.02–1.07), and being discharged home (aOR: 1.64, 95% CI: 1.06–2.54). In contrast, a longer length of index stay (aOR: 0.97, 95% BCa-CI: 0.95–0.99) was associated with reduced odds of readmission for CDI. (4) Conclusion: More than 1 out of 10 patients were readmitted for CDI following an index hospital stay for CDI. Patients with recent previous fluoroquinolone exposure, greater overall comorbidity burden, and those discharged home are at higher risk of readmission for CDI.

Risk factors for hospital readmissions in pneumonia patients: A systematic review and meta-analysis.

BACKGROUNDFactors that are associated with the short-term rehospitalization have been investigated previously in numerous studies. However, the majority of these studies have not produced any conclusive results because of their smaller sample sizes, differences in the definition of pneumonia, joint pooling of the in-hospital and post-discharge deaths and lower generalizability.AIMTo estimate the effect of various risk factors on the rate of hospital readmissions in patients with pneumonia.METHODSSystematic search was conducted in PubMed Central, EMBASE, MEDLINE, Cochrane library, ScienceDirect and Google Scholar databases and search engines from inception until July 2021. We used the Newcastle Ottawa (NO) scale to assess the quality of published studies. A meta-analysis was carried out with random-effects model and reported pooled odds ratio (OR) with 95% confidence interval (CI). RESULTSIn total, 17 studies with over 3 million participants were included. Majority of the studies had good to satisfactory quality as per NO scale. Male gender (pooled OR = 1.22; 95%CI: 1.16-1.27), cancer (pooled OR = 1.94; 95%CI: 1.61-2.34), heart failure (pooled OR = 1.28; 95%CI: 1.20-1.37), chronic respiratory disease (pooled OR = 1.37; 95%CI: 1.19-1.58), chronic kidney disease (pooled OR = 1.38; 95%CI: 1.23-1.54) and diabetes mellitus (pooled OR = 1.18; 95%CI: 1.08-1.28) had statistically significant association with the hospital readmission rate among pneumonia patients. Sensitivity analysis showed that there was no significant variation in the magnitude or direction of outcome, indicating lack of influence of a single study on the overall pooled estimate.CONCLUSIONMale gender and specific chronic comorbid conditions were found to be significant risk factors for hospital readmission among pneumonia patients. These results may allow clinicians and policymakers to develop better intervention strategies for the patients.

A Systematic Review of Asthma Readmission Risk Factors

A Systematic Review of Asthma Readmission Risk Factors

Frequency and factors associated with hospital readmission after COVID-19 hospitalization: the importance of post-COVID diarrhea

PurposeThe aim of this study was to describe the incidence and risk factors for hospital readmission and infection during the months after COVID-19 hospital admission. MethodsThis prospective study included adult patients who were hospitalized due to COVID-19 and had been discharged from April 2020 to August 2020. All patients had a medical evaluation with a structured questionnaire 6 to 11 months after hospital admission. The authors included only patients with confirmed COVID-19 by RT-PCR. Patients with pregnant/postpartum women, with a proven COVID-19 reinfection or incapable of answering the questionnaire were excluded. ResultsA total of 822 patients completed the follow-up assessment, and 68% reported at least one recurrent symptom related to COVID-19. The most frequent symptom was myalgia (42%). Thirty-two percent of patients visited an emergency room after COVID-19 hospitalization, and 80 (10%) patients required re-hospitalization. Risk factors for hospital readmission were orotracheal intubation during COVID-19 hospitalization (p = 0.003, OR = 2.14), Charlson score (p = 0.002, OR = 1.21), congestive heart failure (p = 0.005, OR = 2.34), peripheral artery disease (p = 0.06, OR = 2.06) and persistent diarrhea after COVID-19 hospitalization discharge (p = 0.02, OR = 1.91). The main cause of hospital readmission was an infection, 43 (54%). Pneumonia was the most frequent infection (29%). ConclusionsThe presence of symptoms after six months of COVID-19 diagnosis was frequent, and hospital readmission was relatively high.

Hospital Readmissions after Postpartum Emergency Department Visit

Up to 12% of pregnant patients have an emergency department (ED) visit within 6 weeks postpartum. However, little is known about the relationship between postpartum ‘treat-and-discharge’ ED visits and subsequent hospital readmission. Given that preventing hospital readmissions is central to postpartum quality improvement, we sought to examine the incidence of and risk factors for hospital readmission after a ‘treat-and-discharge’ postpartum ED visit.

Risk factors for hospital readmission among infants with prolonged neonatal intensive care stays.

To assess risk factors associated with 30-day hospital readmission after a prolonged neonatal intensive care stay. Retrospective analysis of 57,035 infants discharged >14 days from the NICU between 2013 and 2016. Primary outcome was 30-day, all-cause hospital readmission. Adjusted likelihood of readmission accounting for demographic and clinical characteristics, including chronic conditions was also estimated. The 30-day readmission rate was 10.7%. Respiratory problems accounted for most (31.0%) readmissions. In multivariable analysis, shunted hydrocephalus [OR 2.2 (95%CI 1.8-2.7)], gastrostomy tube [OR 2.0 (95%CI 1.8-2.3)], tracheostomy [OR 1.5 (95%CI 1.2-1.8)], and use of public insurance [OR 1.3 (95%CI 1.2-1.4)] had the highest likelihood of readmission. Adjusted hospital readmission rates varied significantly (p < 0.001) across hospitals. The likelihood of hospital readmission was highest for infants with indwelling medical devices and public insurance. These findings will inform future initiatives to reduce readmission for high risk infants with medical and social complexity.