RESUMEN

Background Irritable bowel syndrome (IBS) continues to pose significant healthcare challenges due to its broad differential diagnosis and the often extensive yet inconclusive workup. We investigated the rates and characteristics of unplanned 30-day readmissions in adult patients hospitalized with IBS. In addition, we identified factors that predict readmission within 30 days of initial discharge. Methods We analyzed the 2020 Nationwide Readmission Database. Using the International Classification of Diseases, Tenth Revision, Clinical Modification code, we identified hospitalizations in adult patients with IBS. We excluded hospitalizations for minors and planned or elective readmissions. To compare baseline characteristics between readmissions and index hospitalizations, χ2 tests were employed. We used multivariate Cox regression analyses to identify independent predictors of readmissions. Results A total of 5,729 adult hospitalizations with IBS as the primary diagnosis were discharged alive, and 638 (11.1%) readmissions occurred within 30 days. The most common diagnoses associated with readmission were noninfective gastroenteritis and colitis, sepsis, enterocolitis due to Clostridium difficile, and irritable bowel syndrome with or without diarrhea. Patients in readmissions had a mean age of 56.3 years, similar to index hospitalizations (54.5 years, p=0.093). Readmissions had a higher burden of comorbidity (Charlson comorbidity index (CMI) scores ≥3: 26.7%, 170 cases vs. 16.6%, 953 cases; p<0.001) and were mostly Medicare beneficiaries (49.5%, 316% vs. 44.9%, 2,578) compared with index hospitalizations. Readmissions had a longer mean length of stay (LOS) (5.2 vs. 3.6 days, p<0.0001), higher inpatient mortality (0.8%, 5% vs. 0.2%, 11; p=0.032), and higher mean hospital costs ($47,852 vs. $34,592; p<0.0001) compared with index admissions. Secondary diagnoses of ulcerative colitis (adjusted hazard ratio (AHR), 2.82; p<0.0001), interstitial cystitis (AHR, 5.37; p=0.007), peripheral vascular disease (AHR, 1.59; p=0.027), and discharge to short-term hospitals (AHR, 1.03; p<0.0001) were significantly associated with a higher likelihood of readmission within 30 days. Conclusion IBS readmissions have poorer outcomes than index hospitalizations. Patients with an existing history of ulcerative colitis, interstitial cystitis, and peripheral vascular disease and those discharged to short-term hospitals following index hospitalization are more likely to be readmitted within 30 days.

RESUMEN

OBJECTIVES: Hospital readmissions are associated with poor health outcomes including illness severity and medical complications. The objective of this study was to identify characteristics associated with 30-day post-stroke readmission in an academic urban hospital network. MATERIALS AND METHODS: We collected data on patients admitted with stroke from 2017 through 2022 who were readmitted within 30 days of discharge and compared them to a subset of non-readmitted stroke patients. Chart review was used to collect demographics, characteristics of the stroke, co-morbid conditions, in-hospital complications, and post-discharge care. Univariate analyses followed by regression analysis were used to assess characteristics associated with post-stroke readmission. RESULTS: We identified 4743 patients with stroke (18 % hemorrhagic, mean age 70.1 (standard deviation (SD) 17.2), 47.3 % female) discharged from the stroke services, of whom 282 (5.9 %) patients were readmitted within 30 days of index hospitalization. Univariate analyses identified 18 significantly different features between admitted and readmitted patients. Regression analysis revealed characteristics associated with readmission included private insurance (odds ratio (OR) 0.4, confidence interval (CI) 0.3-0.6, p < 0.001), comorbid peripheral vascular disease (PVD) (OR 2.7, CI 1.3-5.5, p = 0.009), malignancy (OR 1.6, CI 1.0-2.6, p = 0.04), seizure (OR 3.4, CI 1.4-8.2, p = 0.007), thrombolytic administration (OR 0.4, CI 0.2-0.7, p = 0.003), undergoing thrombectomy (OR 5.4, CI 2.9-10.1, p < 0.001), and higher discharge modified Rankin Scale score (OR 1.2, CI 1.0-1.3, p = 0.047). CONCLUSIONS: Our data demonstrate that thrombectomy, high discharge Rankin score, comorbid malignancy, seizure or PVD, and lack of thrombolytic administration or private insurance predict readmission.

RESUMEN

BACKGROUND: Avoidant restrictive food intake disorder (ARFID) is a relatively new feeding and eating disorder added to the DSM-5 in 2013 and ICD-10 in 2018. Few studies have examined hospital utilization for patients with ARFID specifically, and none to date have used large administrative cohorts. We examined inpatient admission volume over time and hospital utilization and 30-day readmissions for patients with ARFID at pediatric hospitals in the United States. METHODS: Using data from the Pediatric Health Information System (PHIS), we identified inpatient admissions for patients with ARFID (by principal International Classification of Diseases, 10th Revision, ICD-10 diagnosis code) discharged October 2017-June 2022. We examined the change over time in ARFID volume and associations between patient-level factors (e.g., sociodemographic characteristics, co-morbid conditions including anxiety and depressive disorders and malnutrition), hospital ARFID volume, and hospital utilization including length of stay (LOS), costs, use of enteral tube feeding or GI imaging during admission, and 30-day readmissions. Adjusted regression models were used to examine associations between sociodemographic and clinical factors on LOS, costs, and 30-day readmissions. RESULTS: Inpatient ARFID volume across n = 44 pediatric hospitals has increased over time (ß = 0.36 per month; 95% CI 0.26-0.46; p < 0.001). Among N = 1288 inpatient admissions for patients with ARFID, median LOS was 7 days (IQR = 8) with median costs of $16,583 (IQR = $18,115). LOS and costs were highest in hospitals with higher volumes of ARFID patients. Younger age, co-morbid conditions, enteral feeding, and GI imaging were also associated with LOS. 8.5% of patients were readmitted within 30 days. In adjusted models, there were differences in the likelihood of readmission by age, insurance, malnutrition diagnosis at index visit, and GI imaging procedures during index visit. CONCLUSIONS: Our results indicate that the volume of inpatient admissions for patients with ARFID has increased at pediatric hospitals in the U.S. since ARFID was added to ICD-10. Inpatient stays for ARFID are long and costly and associated with readmissions. It is important to identify effective and efficient treatment strategies for ARFID in the future.

Recent studies indicate that Avoidant Restrictive Food Intake Disorder (ARFID) is a complex feeding and eating disorder often diagnosed in younger children. To date, there are no large studies using administrative data to examine hospital utilization or costs among patients with ARFID. In a geographically diverse cohort of pediatric hospitals in the United States, we found inpatient admissions for ARFID have increased over time and that ARFID is associated with long, costly stays and readmissions which has important implications for identifying efficient treatment strategies. Future studies are needed to explore effective and efficient treatment strategies and prevent readmissions in this patient population.

RESUMEN

OBJECTIVES: We aimed to evaluate the utility of an Observation Unit (OU) in management of acute exacerbations of chronic obstructive pulmonary disease (AECOPD) and to identify the clinical characteristics of patients readmitted within 30-days for AECOPD following index admission to the OU or inpatient floor from the OU. METHODS: This is a retrospective observational study of patients admitted from January to December 2017 for AECOPD to an OU in an urban-based tertiary care hospital. Primary outcome was rate of 30-day readmission after admission for AECOPD for patients discharged from the OU versus inpatient service after failing OU management. Regression analyses were used to define risk factors. RESULTS: 163 OU encounters from 92 unique patients were included. There was a lower readmission rate (33%) for patients converted from OU to inpatient care versus patients readmitted after direct discharge from the OU (44%). Patients with 30-day readmissions were more likely to be undomiciled, with history of congestive heart failure (CHF), pulmonary embolism (PE), or had previous admissions for AECOPD. Patients with >6 annual OU visits for AECOPD had higher rates of substance abuse, psychiatric diagnosis, and prior PE; when these patients were excluded, the 30-day readmission rate decreased to 13.5%. CONCLUSION: Patients admitted for AECOPD with a history of PE, CHF, prior AECOPD admissions, and socioeconomic deprivation are at higher risk of readmission and should be prioritized for direct inpatient admission. Further prospective studies should be conducted to determine the clinical impact of this approach on readmission rates.

Asunto(s)

RESUMEN

Objectives: The US government implemented the Hospital Readmission Reduction Program on 1 October 2012 to reduce readmission rates through financial penalties to hospitals with excessive readmissions. We conducted a pooled cross-sectional analysis of US hospitals from 2009 to 2015 to determine the association of the Hospital Readmission Reduction Program with 30-day readmissions. Methods: We utilized multivariable linear regression with year and state fixed effects. The model was adjusted for hospital and market characteristics lagged by 1 year. Interaction effects of hospital and market characteristics with the Hospital Readmission Reduction Program indicator variable was also included to assess whether associations of Hospital Readmission Reduction Program with 30-day readmissions differed by these characteristics. Results: In multivariable adjusted analysis, the main effect of the Hospital Readmission Reduction Program was a 3.80 percentage point (p < 0.001) decrease in readmission rates in 2013-2015 relative to 2009-2012. Hospitals with lower readmission rates overall included not-for-profit and government hospitals, medium and large hospitals, those in markets with a larger percentage of Hispanic residents, and population 65 years and older. Higher hospital readmission rates were observed among those with higher licensed practical nurse staffing ratio, larger Medicare and Medicaid share, and less competition. Statistically significant interaction effects between hospital/market characteristics and the Hospital Readmission Reduction Program on the outcome of 30-day readmission rates were present. Teaching hospitals, rural hospitals, and hospitals in markets with a higher percentage of residents who were Black experienced larger decreases in readmission rates. Hospitals with larger registered nurse staffing ratios and in markets with higher uninsured rate and percentage of residents with a high school education or greater experienced smaller decreases in readmission rates. Conclusion: Findings of the current study support the effectiveness of the Hospital Readmission Reduction Program but also point to the need to consider the ability of hospitals to respond to penalties and incentives based on their characteristics during policy development.

RESUMEN

Background: Tobacco carcinogens have adverse effects on bone health and are associated with inferior outcomes following orthopedic procedures. The purpose of this study was to assess the impact tobacco use has on readmission and complication rates following shoulder arthroplasty. Methods: The 2016-2018 National Readmissions Database was queried to identify patients who underwent anatomical, reverse, and hemi-shoulder arthroplasty. ICD-10 codes Z72.0 × (tobacco use disorder) and F17.2 × (nicotine dependence) were used to define "tobacco-users." Demographic, 30-/90-day readmission, surgical complication, and medical complication data were collected. Inferential statistics were used to analyze complications for both the cohort as a whole and for each procedure separately (i.e. anatomical, reverse, and hemiarthroplasty). Results: 164,527 patients were identified (92% nontobacco users). Tobacco users necessitated replacement seven years sooner than nonusers (p < 0.01) and were more likely to be male (52% vs. 43%; p < 0.01). Univariate analysis showed that tobacco users had higher rates of readmission, revisions, shoulder complications, and medical complications overall. In the multivariate analysis for the entire cohort, readmission, revision, and complication rates did not differ based on tobacco usage; however, smokers who underwent reverse shoulder arthroplasty in particular were found to have higher 90-day readmission, dislocation, and prosthetic complication rates compared to nonsmokers. Conclusion: Comparatively, tobacco users required surgical correction earlier in life and had higher rates of readmission, revision, and complications in the short term following their shoulder replacement. However, when controlling for tobacco usage as an independent predictor of adverse outcomes, these aforementioned findings were lost for the cohort as a whole. Overall, these findings indicate that shoulder replacement in general is a viable treatment option regardless of patient tobacco usage at short-term follow-up, but this conclusion may vary depending on the replacement type used.

RESUMEN

Introduction  Rotator cuff repair (RCR) procedures are some of the most common orthopaedic surgeries performed in the United States. Compared to other orthopaedic procedures, RCRs are of relatively low morbidity. However, complications may arise that result in readmission to an inpatient healthcare facility. The purpose of this study is to identify the demographics and risk factors associated with unplanned 30-day readmission after RCR. Methods The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database was used to identify patients that underwent elective RCR from 2015-2019. Univariate and multivariate analyses were utilized to assess patient demographics, comorbidities, and peri-operative variables predicting unplanned 30-day readmission. Results Of the identified 45,548 patients that underwent RCR, 597 (1.3%) required readmission within 30 days of the procedure. Multivariate analysis identified male sex (OR 1.36, 95% CI: 1.10, 1.67), hypertension (OR 1.29, 95% CI:1.03, 1.62), chronic obstructive pulmonary disease (COPD) (OR 2.07, 95% CI: 1.46, 2.93), American Society of Anesthesiologists (ASA) Class III (OR 1.85, 95% CI: 1.07, 3.18), ASA Class IV (OR 5.38, 95% CI: 2.70, 10.72), and total operative time (OR 1.002, 95% CI: 1.000, 1.004) as independent risk factors for unplanned readmission. Conclusion Unplanned 30-day readmission after RCR is infrequent. However, certain patients may be at increased risk for unplanned 30-day admission to an inpatient facility. This study confirmed male sex, COPD, hypertension, ASA Class III, ASA Class IV, and total operative time to be independent risk factors for readmission following outpatient RCR.

RESUMEN

OBJECTIVE: The objective of this study was to leverage a national database of TAVR procedures to create a risk model for 30-day readmissions. METHODS: The National Readmissions Database was reviewed for all TAVR procedures from 2011 to 2018. Previous ICD coding paradigms created comorbidity and complication variables from the index admission. Univariate analysis included any variables with a P-value of ≤0.2. A bootstrapped mixed-effects logistic regression was run using the hospital ID as a random effect variable. By bootstrapping, a more robust estimate of the variables' effect can be generated, reducing the risk of model overfitting. The odds ratio of variables with a P-value <0.1 was turned into a risk score following the Johnson scoring method. A mixed-effect logistic regression was run using the total risk score, and a calibration plot of the observed to expected readmission was generated. RESULTS: A total of 237,507 TAVRs were identified, with an in-hospital mortality of 2.2 %. A total of 17.4 % % of TAVR patients were readmitted within 30 days. The median age was 82 with 46 % of the population being women. The risk score values ranged from -3 to 37 corresponding to a predicted readmission risk between 4.6 % and 80.4 %, respectively. Discharge to a short-term facility and being a resident of the hospital state were the most significant predictors of readmission. The calibration plot shows good agreement between the observed and expected readmission rates with an underestimation at higher probabilities. CONCLUSION: The readmission risk model agrees with the observed readmissions throughout the study period. The most significant risk factors were being a resident of the hospital state and discharge to a short-term facility. This suggests that using this risk score in conjunction with enhanced post-operative care in these patients could reduce readmissions and associated hospital costs, improving outcomes.

Asunto(s)

RESUMEN

INTRODUCTION: Much attention has been focused on decreasing chronic obstructive pulmonary disease (COPD) hospital readmissions. The US health system has struggled to meet this goal. The objective of this study was to assess the efficacy of telehealth services on the reduction of hospital readmission and mortality rates for COPD. METHODS: We used a cross-sectional design to examine the association between hospital risk-adjusted readmission and mortality rates for COPD and hospital use of post-discharge telemonitoring (TM). Data for 777 hospitals were sourced from the Centers for Medicare & Medicaid Services and the American Hospital Association annual surveys. Propensity score matching using the kennel weights method was applied to calculate the weighted probability of being a hospital that offers post-discharge TM services. RESULTS: Hospitals with post-discharge TM had about 34% significantly higher odds (adjusted odds ratio (AOR) = 1.34; 95% confidence interval (CI) 1.06-1.70) of 30-day COPD readmission and 33% significantly lower odds (AOR = 0.67; 95% CI 0.50-0.90) of 30-day COPD mortality compared to hospitals without post-discharge TM services. DISCUSSION: Overall, hospitals that offer post-discharge TM services have seen an improvement in 30-day COPD mortality rates. However, those same hospitals have also experienced a significant increase in 30-day COPD readmissions. TM can potentially decrease mortality in patients recently admitted for acute exacerbation of COPD. The results provide further evidence that readmissions present a problematic assessment of health-care quality, as the need for readmission may or may not be directly related to the quality of care received while in hospital.

Asunto(s)

RESUMEN

Objective: Unplanned 30-day readmissions result in increased costs and decreased patient satisfaction. The objective of this study was to compare readmission rates before and after a multidisciplinary quality improvement initiative that focuses on patient and staff education, use of targeted skilled nursing facilities, and appropriate use of patient observation status. Methods: This was a quality improvement study of all unplanned admissions to the Head and Neck Oncology service at a tertiary care facility during a 3-year period between October 2015 and September 2018. In October 2016, when the Head and Neck Oncology service revised its discharge practices for patients undergoing extirpative and/or reconstructive surgery. These changes included enhancing patient education, increasing the use of a skilled nursing facility with directed staff education and patient handoffs by advanced practice nurses, and appropriate utilization of 23-h observation status for returning patients. The readmission rate from the pre-intervention era (October 2015 through September 2016) was compared to the readmission rate from the post-intervention era (October 2016 through September 2018). Secondary outcomes were the rates of 23-h observation within 30 days of the discharge as well as emergency room visits within 30 days of discharge. Results: In this sample of 449 patients, 161 (35.9%) were observed before the change-in-practice (before October 2016), and 288 (64.1%) were observed following the change-in-practice (after September 2016). On univariable analysis, the risk of readmission declined by approximately 41.4% from the pre-intervention era, though this conclusion was not statistically significant (P = 0.06). On multivariable analysis, patients at moderate or high risk of death were 2.31 times more likely than those at minor risk of death to readmit within 30 days (P = 0.03). Similarly, those with recurrent or persistent cancer were 3.33 times more likely than those undergoing initial curative surgical management of cancer to readmit within 30 days (P = 0.001). No patient characteristics were associated with a 23-h observation following discharge (all P > 0.05). Conclusions were similar for emergency room visits following discharge. Conclusions: A three-part quality improvement strategy resulted in a clinically important decrease in 30-day readmissions, though the decline was not statistically significant. There were no significant changes in 23-h observation within 30 days of discharge or emergency room visits within 30 days of discharge.

RESUMEN

BACKGROUND: An overview of systematic reviews(SRs) and network meta-analysis(NMA) were conducted to evaluate the comparative effectiveness of peri-discharge complex interventions for reducing 30-day readmissions among chronic obstructive pulmonary disease(COPD) patients. METHODS: Five databases were searched for SRs of randomized controlled trials(RCTs). An additional search was conducted for updated RCTs from database inception until Jun 2020. Pooled effect of peri-discharge complex interventions was assessed using random-effect pairwise meta-analyses. Comparative effectiveness across different peri-discharge complex interventions was evaluated using NMA. RESULTS: Nine SRs and 11 eligible RCTs(n = 1,422) assessing eight different peri-discharge complex interventions were included. For reducing 30-day all-cause readmissions, pairwise meta-analysis showed no significant difference between peri-discharge complex interventions and usual care, while NMA indicated no significant differences among different peri-discharge complex interventions as well as usual care. For reducing 30-day COPD-related readmissions, peri-discharge complex interventions were significantly more effective than usual care (pooled RR = 0.45, 95% CI:0.24-0.84). CONCLUSIONS: Peri-discharge complex interventions may not differ from usual care in reducing 30-day all-cause readmissions among COPD patients but some are more effective for lowering 30-day COPD-related readmission. Thus, complex intervention comprising core components of patient education, self-management, patient-centred discharge instructions, and telephone follow up may be considered for implementation, but further evaluation is warranted.

RESUMEN

BACKGROUND: Discharge to an inpatient care facility (skilled-care or rehabilitation) has been shown to be associated with adverse outcomes following elective total joint arthroplasties. Current evidence with regard to hip fracture surgeries remains limited. METHODS: The 2015-2016 ACS-NSQIP database was used to query for patients undergoing total hip arthroplasty, hemiarthroplasty and open reduction internal fixation for hip fractures. A total of 15,655 patients undergoing hip fracture surgery were retrieved from the database. Inpatient facility discharge included discharges to skilled-care facilities and inpatient rehabilitation units. Multi-variate regression analysis was used to assess for differences in 30-day post-discharge outcomes between home-discharge versus inpatient care facility discharge, while adjusting for baseline differences between the 2 study populations. RESULTS: A total of 12,568 (80.3%) patients were discharged to an inpatient care facility. Discharge to an inpatient care facility was associated with higher odds of any complication (OR 2.03 [95% CI, 1.61-2.55]; p < 0.001), wound complications (OR 1.79 [95% CI, 1.10-2.91]; p = 0.019), cardiac complications (OR 4.49 [95% CI, 1.40-14.40]; p = 0.012), respiratory complication (OR 2.29 [95% CI, 1.39-3.77]; p = 0.001), stroke (OR 7.67 [95% CI, 1.05-56.29]; p = 0.045, urinary tract infections (OR 2.30 [95% CI, 1.52-3.48]; p < 0.001), unplanned re-operations (OR 1.37 [95% CI, 1.03-1.82]; p = 0.029) and readmissions (OR 1.38 [95% CI, 1.16-1.63]; p < 0.001) following discharge. CONCLUSION: Discharge to inpatient care facilities versus home following hip fracture surgery is associated with higher odds of post-discharge complications, re-operations and readmissions. These results stress the importance of careful patient selection prior to discharge to inpatient care facilities to minimise the risk of complications.

Asunto(s)

RESUMEN

Background There has been a steady rise in types 1 and 2 diabetes mellitus among the youth in the USA from 2001 to 2017. Diabetic ketoacidosis (DKA) is a common and preventable presentation of both types of diabetes mellitus. According to the Centers for Disease Control and Prevention's (CDC) United States Diabetes Surveillance System, during 2004-2019 an increase in DKA hospitalization rates by 59.4% was noted, with people aged less than 45 years having the highest rates. Readmissions reflect the quality of disease management, which is integrally tied to care coordination and communication with the patient and their families. This study analyzes the trends and risk factors contributing to 30-day unplanned DKA readmissions in the pediatric age group and looks into possible preventive measures to decrease them. Methods A retrospective study was performed using the National Readmission Database (NRD) from January 1, 2017, to December 1, 2017. Pediatric patients aged 18 years and younger with the primary diagnosis of DKA were included using the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) code E10.10. All statistical analysis was performed using IBM SPSS Statistics for Windows, version 1.0.0.1327 (IBM Corp., Armonk, NY, USA). Pearson's chi-square test was used for categorical variables and Mann-Whitney U test was used for continuous variables. To independently determine the predictors of readmission within each clinical variable, multiple logistic regressions with values presented as odds ratios (OR) with 95% confidence intervals (CI) were performed. Results A weighted total of 19,519 DKA-related pediatric index admissions were identified from the 2017 NRD. Of these pediatric patients, 831 (4.3%) had 30-day DKA readmission. The median age of a child for readmission was 16 years with an interquartile range of 0 to 18 years. A sharp rise in 30-day DKA readmissions was noted for ages 16 years and over. Females in the 0-25th percentile median household income category, with Medicaid covered, large metropolitan areas with at least 1 million residents, and metropolitan teaching hospitals were found to have a statistically significant higher percentage of readmissions. The mean length of stay for those who had a DKA readmission was 2.06 days, with a standard deviation of 1.84 days. The mean hospital charges for those who had a DKA readmission were $ 20,339.70. The 30-day DKA readmission odds were seen to be increased for female patients, Medicaid-insured patients, admissions at metropolitan non-teaching hospitals, and children from 0-25th percentile median household income category. Conclusion There has not been much of a change in the trend and risk factors contributing to the 30-day unplanned DKA readmissions over the years despite the steady rise in cases of diabetes mellitus. The length of stay for those who did not get readmitted within 30 days was longer than for those who did. This could reflect more comprehensive care and discharge planning that may have prevented them from readmission. Diabetes mellitus is a chronic disease that demands a team effort from the patient, family, healthcare personnel, insurance companies, and lawmakers. There is scope for a lot of improvement with the way our patients are being managed, and a more holistic approach needs to be devised.

RESUMEN

Background Long-term air pollution exposure is a significant risk factor for inpatient hospital admissions in the general population. However, we lack information on whether long-term air pollution exposure is a risk factor for hospital readmissions, particularly in individuals with elevated readmission rates. Methods and Results We determined the number of readmissions and total hospital visits (outpatient visits+emergency room visits+inpatient admissions) for 20 920 individuals with heart failure. We used quasi-Poisson regression models to associate annual average fine particulate matter at the date of heart failure diagnosis with the number of hospital visits and 30-day readmissions. We used inverse probability weights to balance the distribution of confounders and adjust for the competing risk of death. Models were adjusted for age, race, sex, smoking status, urbanicity, year of diagnosis, short-term fine particulate matter exposure, comorbid disease, and socioeconomic status. A 1-µg/m3 increase in fine particulate matter was associated with a 9.31% increase (95% CI, 7.85%-10.8%) in total hospital visits, a 4.35% increase (95% CI, 1.12%-7.68%) in inpatient admissions, and a 14.2% increase (95% CI, 8.41%-20.2%) in 30-day readmissions. Associations were robust to different modeling approaches. Conclusions These results highlight the potential for air pollution to play a role in hospital use, particularly hospital visits and readmissions. Given the elevated frequency of hospitalizations and readmissions among patients with heart failure, these results also represent an important insight into modifiable environmental risk factors that may improve outcomes and reduce hospital use among patients with heart failure.

Asunto(s)

RESUMEN

Background and Purpose: Hospital readmissions impose a substantial burden on the healthcare system. Reducing readmissions after stroke could lead to improved quality of care especially since stroke is associated with a high rate of readmission. The goal of this study is to enhance our understanding of the predictors of 30-day readmission after ischemic stroke and develop models to identify high-risk individuals for targeted interventions. Methods: We used patient-level data from electronic health records (EHR), five machine learning algorithms (random forest, gradient boosting machine, extreme gradient boosting-XGBoost, support vector machine, and logistic regression-LR), data-driven feature selection strategy, and adaptive sampling to develop 15 models of 30-day readmission after ischemic stroke. We further identified important clinical variables. Results: We included 3,184 patients with ischemic stroke (mean age: 71 ± 13.90 years, men: 51.06%). Among the 61 clinical variables included in the model, the National Institutes of Health Stroke Scale score above 24, insert indwelling urinary catheter, hypercoagulable state, and percutaneous gastrostomy had the highest importance score. The Model's AUC (area under the curve) for predicting 30-day readmission was 0.74 (95%CI: 0.64-0.78) with PPV of 0.43 when the XGBoost algorithm was used with ROSE-sampling. The balance between specificity and sensitivity improved through the sampling strategy. The best sensitivity was achieved with LR when optimized with feature selection and ROSE-sampling (AUC: 0.64, sensitivity: 0.53, specificity: 0.69). Conclusions: Machine learning-based models can be designed to predict 30-day readmission after stroke using structured data from EHR. Among the algorithms analyzed, XGBoost with ROSE-sampling had the best performance in terms of AUC while LR with ROSE-sampling and feature selection had the best sensitivity. Clinical variables highly associated with 30-day readmission could be targeted for personalized interventions. Depending on healthcare systems' resources and criteria, models with optimized performance metrics can be implemented to improve outcomes.

RESUMEN

The aim of the current study was to assess the impact of hospital readmissions within 30-days of discharge, on long-term postoperative outcomes. All patients who underwent cardiac surgery from 2011 - 2018 were included. Patients who had transcatheter procedures, VAD, and transplant were excluded. Inverse probability of treatment weighting (IPTW) propensity scoring was used for population risk adjustment. Multivariable analysis was performed to identify association with long-term mortality and readmission. The total risk adjusted (propensity scoring with IPTW) patient population consisted of 14,538 patients divided into those who were not readmitted in 30-days (nonreadmitted) (n = 12,627) and patients who were readmitted within 30-days (30-day readmitted) (n = 1911). Following IPTW, all baseline characteristics and postoperative complications were equivalent between cohorts (SMD <0.10). Patients who required intraoperative [OR 1.178 (1.05, 1.32); P = 0.006] and postoperative [1.32 (1.18, 1.48); P < 0.001] blood transfusions were at greater risk for 30-day readmission. Median follow-up period was 4.19 years (2.45 - 6.10). The 30-day readmission cohort had a significantly higher mortality risk during early (6 months) follow-up [HR 2.49 (2.01-3.10); P < 0.001] and late (60 months) follow-up [HR 1.30 (1.16-1.47); P < 0.001]. After risk adjustment, the 30-day readmission cohort was significantly associated with increased mortality over the study follow-up period [HR 1.62 (1.48, 1.78); P < 0.001]. 30-day readmissions were an independent predictor of subsequent long-term hospital readmission [HR 1.61 (1.50, 1.73); P < 0.001]. Patients who require 30-day readmissions following cardiac surgery are at increased risk of long-term mortality and repeat readmissions. Early postoperative hospital readmission may be a marker for worse long-term outcomes in cardiac surgery.

Asunto(s)

RESUMEN

Hospital at Home (HaH) is a sustainable, innovative, and next-generation model of healthcare. From the healthcare management point of view, this model provides cost benefits and quality improvement, and from the physicians' point of view, it helps in providing patient-centered medical care and keeps patients away from hospital admission and its complications. The HaH model was first introduced at John Hopkins in the United States in 1995, which showed very promising results in context to the length of stay, readmission rates, patient satisfaction, and hospital-acquired infections. The HaH model of care provides acute critical care to patients at home and reduces unnecessary hospitalization and related complications. The identified patients for this model of care are elderly patients with chronic conditions and multiple comorbidities. The emergence of technology in today's world and the impact of coronavirus disease 2019 (COVID-19) have increased the demand for the HaH model of care. Although there are many benefits and advantages, the HaH model of care has significant barriers and limitations, such as reimbursement for payment, physician and patient resistance, patient safety, and lack of quantifying research data to support the use of this model. Specific training for the physician, nursing, and other members of the HaH multidisciplinary team is necessary for HaH treatment protocols, along with patient and family caregiver education for those who elect the HaH model of care. HaH is the future of comprehensive healthcare services and helps in achieving the triple aim of access to healthcare, improved quality of care, and reduced cost for healthcare.

RESUMEN

BACKGROUND: Outcome data following transcatheter mitral valve repair (TMVR) with the MITRACLIP® device are scarce outside the pivotal randomized controlled trials. METHODS: The Nationwide Readmission Data base (NRD) was utilized for years 2013-2017 to identify the study population. Thirty-day readmission pattern, in-hospital complications, causes of readmissions, and multivariate predictors for readmission, complications and mortality were explored. RESULTS: We noted a total of 14,647 index admissions related to MITRACLIP of which 48% of procedures were performed at high volume centers (Annual hospital volume ≥ 25). A total of 15% of patients were readmitted within 30 days of discharge most frequently due to cardiac causes. Approximately 33% of patients were discharged within 24 h of the procedure. The in-hospital mortality rate was 2.8% and in-hospital complication rate was 14.6%. The most common complications were cardiac complications (8.2%), bleeding related complications (5.9%) and vascular complications (0.65%). On multivariate modeling, female sex, CHF, Atrial fibrillation, prior PCI, COPD, CKD, transfer to skilled nursing facility, length of stay ≥2 days were associated with a high risk of readmission. Additionally, coagulopathy, chronic kidney disease and lengthier hospital stays were associated with high risk of complication or death. CONCLUSION: The 30-day readmission rate following commercial treatment with the MITRACLIP device is 15%. Half of these admission were from a cardiac etiology. Heart failure, atrial arrhythmias and clip related complications round out the top 3 cardiac reasons for readmission. There was no impact of hospital size, teaching status or case volume on mortality and in hospital complication rates.

Asunto(s)

RESUMEN

In 2013, the Centers for Medicare and Medicaid Services (CMS) implemented the Hospital Readmissions Reduction Program (2013 HRRP), which financially penalized hospitals if their 30-day readmissions were higher than the national average. Without adjusting for socioeconomic status of patients, the 2013 HRRP overly penalized hospitals caring for the poor, especially hospitals in the Mississippi Delta region, one of the poorest regions in the U.S. In 2019, CMS revised the HRRP (2019 Revised HRRP) to stratify hospitals into quintiles based on the proportion of patients that are dual-eligible Medicare and Medicaid beneficiaries. This study aimed to examine the effect of the 2019 Revised HRRP on financial penalties for Delta hospitals using a difference-in-difference (DID) approach with data from the 2018 and 2019 HRRP Supplemental Files. The DID analysis found that relative to non-Delta hospitals, penalties in Delta hospitals were reduced by 0.08 percentage points from 2018 to 2019 (95% CI for the coefficient: -0.15, -0.01; P = .02), and the probability of a penalty was reduced by 6.64 percentage points (95% CI for the coefficient: -9.54, -3.75; P < .001). The stratification under the 2019 Revised HRRP is an important first step in reducing unfair penalties to hospitals that serve poor populations.

Asunto(s)

RESUMEN

Patients with alcohol-related diagnoses at initial hospitalization are at high risk of 30-day readmission. Understanding risk factors for 30-day readmission among these patients may help to identify those who would benefit from efforts to reduce risk of readmission. The Nationwide Readmissions Database was used to estimate 30-day all-cause readmissions among United States patients with an alcohol-related index hospitalization and to evaluate risk factors and costs associated with these readmissions. Included patients were 18 years of age or older at initial hospitalization, had an alcohol-related primary diagnosis (based on ICD-9-CM codes), and were discharged between 2010 and 2015. They were followed for 30 days after initial hospitalization within the calendar year to identify all-cause readmissions. A logistic regression analysis assessed the association between risk factors and 30-day readmission. Average costs of initial admissions and readmissions were estimated. Among 113,931,723 adult index hospitalizations, 1,124,228 had alcohol-related diagnoses. Patients had a mean age of 49 years, 73% were male, and 45% had public insurance coverage. The annual rate of 30-day readmissions among patients with index alcohol-related hospitalizations increased from 119 readmissions per 1000 admissions in 2010 to 140 per 1000 in 2015, while the rate of readmissions among patients with all-cause hospitalizations declined from 103 to 98 per 1000. The regression analysis suggested that age, male sex, comorbid conditions, discharge against medical advice, admission to large and teaching hospitals, and Medicaid vs. non-Medicaid payment were all risk factors for 30-day readmission. Mean costs of initial alcohol-related hospitalizations were greater among those with a 30-day readmission than without a 30-day readmission, and the mean cost of 30-day readmission was even greater. Mitigating the upward trend in rates of readmission following alcohol-related initial hospitalizations may be addressed through better identification of high-risk patients who are admitted with an alcohol-related diagnosis and greater use of existing evidence-based psychosocial and pharmacotherapy treatment methods.

Asunto(s)