Lower Risk Of Readmission Research Articles

Cardiac rehabilitation for patients with heart failure: a national Danish register-based study of predictors of referral and outcomes

Abstract Funding Acknowledgements Type of funding sources: Foundation. Main funding source(s): The Danish Heart Foundation Background Heart failure (HF) places a large burden on patients and society as a major cause of morbidity, mortality and healthcare costs. Participation in exercise-based cardiac rehabilitation (CR) in people with HF is a clinically and cost-effective strategy and recommended in international clinical guidelines. Purpose The aims of this study were to: (1) examine the temporal trends and predictors of national CR referral, and (2) compare the risk of hospital readmission and mortality in those referred for CR compared to no referral. Methods All patients in Denmark with incident HF were identified by the Danish Heart Failure Register in the period 2010 to 2018 (n = 33,257) and CR referral assessed within 120 days of hospital admission. Multivariable logistic regression models were used to evaluate the association between CR referral and predictors and to compare risk of hospital readmission and mortality until 1 year between referred and not referred patients. Results Overall, 45.0% of HF patients were referred to exercise-based CR, increasing from 31.7% in 2010 to 52.2% in 2018. Factors independently associated with higher CR referral were: NYHA functional class II, LVEF <50%, diagnosis of myocardial infarction and use of ACE inhibitor. Male gender, older age, region, unemployment, retirement, living alone, non-Danish ethnic origin, lower educational level, NYHA class IV, treatment for hypertension, existing chronic obstructive lung disease and stroke were associated with lower CR referral. CR referral was associated with lower risk of readmission (adjusted odds ratio: 0.90;95%CI: 0.85-0.95), HF-specific mortality (0.61; 0.39-0.95) and all-cause mortality (0.61; 0.55-0.69) as compared to no referral. Conclusions Although CR referral has increased over time, only some 1 in 2 diagnosed HF patients in Denmark are referred to exercise-based CR. CR referral is associated with lower risk in readmissions and mortality. Strategies to promote CR referral including healthcare professional education on the benefits of CR and alternative methods of CR delivery are urgently needed to improve access to CR, especially for high-risk groups.

Association between Initiation of Pulmonary Rehabilitation and Rehospitalizations in Patients Hospitalized with Chronic Obstructive Pulmonary Disease.

Rationale: Although clinical trials have found that pulmonary rehabilitation (PR) can reduce the risk of readmissions after hospitalization for a chronic obstructive pulmonary disease (COPD) exacerbation, less is known about PR’s impact in routine clinical practice. Objectives: To evaluate the association between initiation of PR within 90 days of discharge and rehospitalization(s). Methods: We analyzed a retrospective cohort of Medicare beneficiaries (66 years of age or older) hospitalized for COPD in 2014 who survived at least 30 days after discharge. Measurements and Main Results: We used propensity score matching and estimated the risk of recurrent all-cause rehospitalizations at 1 year using a multistate model to account for the competing risk of death. Of 197,376 total patients hospitalized in 4,446 hospitals, 2,721 patients (1.5%) initiated PR within 90 days of discharge. Overall, 1,534 (56.4%) patients who initiated PR and 125,720 (64.6%) who did not were rehospitalized one or more times within 1 year of discharge. In the propensity-score–matched analysis, PR initiation was associated with a lower risk of readmission in the year after PR initiation (hazard ratio, 0.83; 95% confidence interval, 0.77–0.90). The mean cumulative number of rehospitalizations at 1 year was 0.95 for those who initiated PR within 90 days and 1.15 for those who did not (P < 0.001). Conclusions: After hospitalization for COPD, Medicare beneficiaries who initiated PR within 90 days of discharge experienced fewer rehospitalizations over 1 year. These results support findings from randomized controlled clinical trials and highlight the need to identify effective strategies to increase PR participation.

A varied approach to left ventricular assist device follow-up improves cost-effectiveness

Background Left ventricular assist device (LVAD) implantation improves outcomes in advanced heart failure, however, the optimal frequency of outpatient assessments to improve cost-effectiveness and potentially avert readmissions is unclear. Methods To test if varying the frequency of follow-up after LVAD implantation reduces readmissions and improves cost-effectiveness, a less intensive follow-up (LIFU) strategy with scheduled visits at 1 month and then every 6 months was compared to an intensive follow-up (IFU) group with scheduled visits at 1, 2, and 4 weeks, and then every 3 months post-implant. We developed a decision-tree model to evaluate the cost-effectiveness of different follow-up schedules at 3, 6, and 12-months. The readmission rates for LIFU and IFU, along with the associated costs, were estimated using data from the IBM MarketScan Commercial Claims Databases (2015–2018). A total of 349 patients were enrolled, with 193 and 156 in the IFU and LIFU groups. Results Patients with IFU were found to have a lower risk for readmission at 3 months (HR: 0.69, 95% confidence interval (CI): 0.60–0.79), but this difference diminished overtime at 6 months (HR: 0.84, 95% CI: 0.73–0.96) and 12 months (HR: 0.94, 95% CI: 0.83–1.06). The incremental net benefit of IFU, when compared with LIFU, is greatest in the first 3 months and also diminishes over time (3 months: $19616, 6 months $9257, 12 months $717). Conclusions An initial IFU strategy, followed by a period of de-escalation at the 6-month post-implant mark in lower-risk patients, may be a more cost-effective strategy to provide follow-up care while not predisposing patients to a higher risk of readmission.

Patient-Reported Outcomes and Risk of Hospitalization and Readmission in Patients with Inflammatory Bowel Diseases.

Patient-reported outcome measures (PROMs) provide a wholesome view of patient well-being. We conducted a retrospective cohort study to evaluate whether PROMs inform risk of unplanned healthcare utilization in patients with IBD. We identified adult patients with IBD who completed at least two surveys in a large Internet-based cohort within 1year. We evaluated the association between baseline patient characteristics, disease activity indices, medication use, and PROMs, assessed using NIH Patient-Reported Outcome Measurement Information System (PROMIS) and subsequent risk of incident hospitalization (at time of first follow-up) within 1year, and readmission within 1year (in patients with hospitalization at first follow-up), using multivariable logistic regression. Of 7902 patients with IBD (45.5year, 72% females, 63% Crohn's disease), 1377 (17.4%) were hospitalized within 1year. Among PROMs, pain interference (adjusted OR per 5-point increase in PROMIS, 1.09; 95% CI 1.05-1.14), but not depression, anxiety, fatigue or sleep disturbance, was predictive of higher risk of hospitalization. Prior surgery or hospitalization, symptomatic disease, biologic, and corticosteroid use were also associated with higher risk of hospitalization. Of 521 patients hospitalized with IBD, 133 (25.5%) were readmitted within 1year. Anxiety and pain interference were predictive of higher risk of readmission, whereas depression was associated with lower risk of readmission. In a large Internet-based cohort study, PROMs may have a modest effect on modifying risk of unplanned healthcare utilization in patients with IBD, with pain interference being most consistently associated with increased risk of hospitalization and readmission.

1011-P: Major Depressive Disorder Is Associated with Higher Risk of Readmission following DKA

Introduction: Diabetic ketoacidosis (DKA) is a medical emergency associated with significant patient mortality and morbidity. Studies have shown that the presence of Major Depressive Disorder (MDD) is associated with an increased incidence of DKA. We aimed to assess whether MDD was associated with increased risk of readmission following DKA. Methods: We utilized the National Readmission Database for 2016 to identify hospitalized adult patients with a principal diagnosis of DKA and a secondary diagnosis of MDD from January 1 to November 30, 2016. We excluded patients with elective and traumatic admissions. We utilized a multivariate cox regression model to identify independent predictors of readmission. Results: Of 15,981 patients with MDD and DKA who were discharged, 23.2%(n=3710) were readmitted within 30-days. The most common reason for readmission was DKA (63.9%, n=2371). In the multivariate cox regression model, MDD was associated with higher risk of readmission (HR: 1.17, 95% CI: 1.1 - 1.26, p=0.04) when adjusted for comorbidities and hospital characteristics. Of those MDD patients with DKA who were readmitted, type 1 DM (HR: 1.14, 95% CI: 1 - 1.3, p=0.04), CHF (HR: 1.40, 95% CI: 1.1 - 1.78, p=0.006), and CKD (HR: 1.44, 95% CI: 1.17 - 1.79, p=0.001) were associated with higher risk of readmission. Obesity (HR: 0.75, 95% CI: 0.59 - 0.97, p=0.025), private insurance (HR: 0.64, 95% CI: 0.53 - 0.79, p&amp;lt;0.001), median patient household income between $54,000-$70,999 (HR: 0.73, 95% CI: 0.63 - 0.85, p&amp;lt;0.001) and $71,000 or more (HR: 0.74, 95% CI: 0.62- 0.89, p=0.002) were associated with lower risk of readmission. Conclusion: In this study, we found that patients with MDD admitted for DKA had a 17% increased risk of readmission within 30 days of discharge in comparison to those without MDD. This could be explained by their propensity for poor adherence to diet, exercise, and recommended pharmacological therapy. Further studies need to be done to assess and target the exact precipitants of readmission. Disclosure M. Ramirez: None. M. Murthi: None. B. Sharma: None. R. Atluri: None. H. Shaka: None. G. Velazquez: None.

Electroconvulsive therapy is associated with lower readmission rates in patients with schizophrenia

BackgroundElectroconvulsive therapy is an important somatic treatment for severe mental disorders with established efficacy and safety. However, data on the relationship between ECT and the readmission rate of patients with schizophrenia are scarce. This study will explore the association between the administration of ECT and readmission rates using a machine learning method. MethodsInpatient medical records from the year of 2016 in one large psychiatric hospital in Beijing, China, were analyzed using a machine learning algorithm to determine the most important variables affecting readmission of patients with schizophrenia. ResultsThe medical records of 2131 inpatients with schizophrenia were reviewed. 1099 patients were followed up within 3 months of their index admission (642 ECT cases and 457 non-ECT cases) and 1032 patients were followed up within 6 months (596 ECT cases and 436 non-ECT cases) after discharge. The 3- and 6-month readmission rates in the ECT group (11.37% and 17.94%, respectively) were significantly lower than that of the patients who did not receive ECT (18.79% and 29.36%, respectively, both p < 0.001). The risk of readmission was significantly associated with male sex, older age, being married, having a lower income, a shorter inpatient length of stay, and receiving specific antipsychotic medications including olanzapine, paliperidone, clozapine, and haloperidol during the index admission. In the ECT group, patients who received 9 or more treatments were significantly less likely to be readmitted. ConclusionReceiving ECT may be associated with a lower risk of readmission in patients with schizophrenia.

#35: Safety of Early Hospital Discharge of Neutropenic Pediatric Oncology Patients After Febrile Neutropenia

Abstract Background Cancer is one of the leading causes of death in children in Mexico. Infections are the main cause of morbidity and mortality in these patients. Febrile neutropenia (FN) constitutes an infectious emergency and early aggressive antibiotic treatment is the standard of care. Recent guidelines suggest discontinuing empirical antibiotics in patients who have negative blood cultures at 48 hours, who have been afebrile for at least 24 hours, and who have evidence of marrow recovery. Nevertheless, recommendations about discontinuing antibiotics and discharging patients while they are still neutropenic are less clear. We aimed to evaluate the safety of early hospital discharge of FN patients who are still neutropenic. Methods Observational, case–control study nested in a prospective cohort of pediatric oncology patients with FN at Hospital Infantil de México Federico Gómez (HIMFG) in Mexico City from May 2015 to September 2017. We defined early discharge as when a patient is discharged while neutropenic (ANC &amp;lt;500 cell/mm3) and has completed at least 7 days of antibiotics. Patients with FN who were discharged with neutropenia were defined as cases and patients with FN who were discharged after recovering from neutropenia were controls. To assess the safety of hospital early discharge, the following outcomes were analyzed until 7 days after discharge: new onset of fever, hospital readmission, need to restart antibiotic treatment, septic shock, and death. Descriptive statistics were performed with measures of central tendency. Variables of interest were compared with Pearson’s χ 2 or Student’s test. Results In total, 929 febrile neutropenia episodes were analyzed. The mean age was 7.5 years, 55.3% were female. Hematologic malignancies were the most frequent type of malignances in 50.8%. Acute lymphoblastic leukemia (ALL) was the underlying disease in 41%. Of the 929 FN episodes, 180 (19.3%) were discharged with neutropenia. Patients with ALL were the most frequent in 49.4%, followed by acute myeloid leukemia 18.8% and rhabdomyosarcoma 6.6%. Thirty-five percent were in maintenance therapy, 22% in remission induction therapy, and 9% in consolidation. 19.4% of discharged patients received granulocyte-colony stimulating factor. Ten patients (5.5%) were re-admitted during the 7 days following discharge. Six patients returned for chemotherapy administration and one was scheduled for liver biopsy. Three patients were re-admitted due to infectious complications (1.6%), none of them were under oral antibiotic treatment; two patients due to FN without microbiological isolation and one patient with septic shock due to multi-drug-resistant Pseudomonas aeruginosa. Older patients had a higher risk of readmission, with a mean age of 14.6 years (SD 4.6 years, 95% CI 7.7–21.6) (P = 0.01), compared with the mean of 7.7 years (SD 2.7 years, (95% CI 7.0, – 8.4) of patients who were not re-admitted. Conclusions In our population of pediatric patients with FN who were discharged before neutrophil recovery, readmission due to infectious complications was low (1.6%). Discharging patients with persistent neutropenia who are afebrile and had completed a course of antibiotics seems an acceptable practice with a low risk of readmission.

A Varied Approach to LVAD Follow-Up Improves Cost-Effectiveness

<h3>Purpose</h3> Left ventricular assist device (LVAD) implantation has improved mortality and quality of life in end-stage HF. However, the optimal frequency of outpatient assessments to improve cost-effectiveness and potentially avert readmissions is unclear. <h3>Methods</h3> The readmission rate, cost of readmission, and follow-up visits were obtained via claims from the 2016-2017 IBM® MarketScan®Commercial Claims Databases. These databases contain de-identified patient claims data across the continuum of care (e.g., inpatient, outpatient, pharmacy) from large employers and health plans in the U.S. who provide private insurance coverage for their employees. Patients who received LVAD in 2016 and 2017 were identified and grouped into one of the two groups: The intervention group was intensivefollow-up (IFU) at 1 week, 2 weeks, 4 weeks, and then every 3 months post-implant, which was compared to a control of less intensive follow-up (LIFU) at one month and then every 6 months. We used the Cox proportional hazard regression to compare the risk of readmission between IFU and LIFU at 3, 6, and 12 months. The health utilities associated with post LVAD with and without readmission were extracted through literature review. <h3>Results</h3> 193 and 156 patients were identified for IFU and LIFU groups, respectively. Patients with IFU were found to have a lower risk for readmission at 3 months (HR:0.69, 95% confidence interval (CI): 0.60-0.79), but this difference diminished over time at 6 (HR: 0.84, 95% CI: 0.73-0.96), and 12 months (HR:0.94, 95% CI: 0.83-1.06). Results from our cost-effectiveness analysis indicate that the incremental net benefit of IFU, when compared with LIFU, increased when looking at a longer time window (3 month: $19616, 6 month $9257, 12 month $717, based on $50,000/ quality-adjusted life year) [Figure]. <h3>Conclusion</h3> An initial intensive follow-up strategy, followed by a period of de-escalation at the 6 month post-implant mark, maybe a more cost-effective strategy to provide follow-up care while not predisposing patients to a higher risk of readmission.

Association between 30-day readmission rates and health information technology capabilities in US hospitals.

Health information technology (IT) is often proposed as a solution to fragmentation of care, and has been hypothesized to reduce readmission risk through better information flow. However, there are numerous distinct health IT capabilities, and it is unclear which, if any, are associated with lower readmission risk.To identify the specific health IT capabilities adopted by hospitals that are associated with hospital-level risk-standardized readmission rates (RSRRs) through path analyses using structural equation modeling.This STROBE-compliant retrospective cross-sectional study included non-federal U.S. acute care hospitals, based on their adoption of specific types of health IT capabilities self-reported in a 2013 American Hospital Association IT survey as independent variables. The outcome measure included the 2014 RSRRs reported on Hospital Compare website.A 54-indicator 7-factor structure of hospital health IT capabilities was identified by exploratory factor analysis, and corroborated by confirmatory factor analysis. Subsequent path analysis using Structural equation modeling revealed that a one-point increase in the hospital adoption of patient engagement capability latent scores (median path coefficient ß = -0.086; 95% Confidence Interval, -0.162 to -0.008), including functionalities like direct access to the electronic health records, would generally lead to a decrease in RSRRs by 0.086%. However, computerized hospital discharge and information exchange capabilities with other inpatient and outpatient providers were not associated with readmission rates.These findings suggest that improving patient access to and use of their electronic health records may be helpful in improving hospital performance on readmission; however, computerized hospital discharge and information exchange among clinicians did not seem as beneficial - perhaps because of the quality or timeliness of information transmitted. Future research should use more recent data to study, not just adoption of health IT capabilities, but also whether their usage is associated with lower readmission risk. Understanding which capabilities impact readmission risk can help policymakers and clinical stakeholders better focus their scarce resources as they invest in health IT to improve care delivery.

Risk factors of readmission after geriatric hospital care: An interRAI-based cohort study in Finland

PurposeTo identify risk factors for readmission after geriatric hospital care. MethodsA retrospective cohort study of 1,167 community-dwelling patients aged ≥70 years who were hospitalised in two geriatric hospitals and discharged to their homes over a three-year period. We combined the results of the interRAI-post acute care instrument (interRAI-PAC) with hospital discharge records. Factors associated with readmissions within 90 days following discharge were analysed using logistic regression analysis. ResultsThe patients' mean age was 84.5 (SD 6.2) years, and 71% (n = 827) were women. The 90-day readmission rate was 29.5%. The risk factors associated with readmission in the univariate analysis were as follows: age, admission from home vs. acute care hospital, Alzheimer's disease, unsteady gait, fatigue, unstable conditions, Activities of Daily Living Hierarchy Scale (ADLH) score, Cognitive Performance Scale (CPS) score, body mass index (BMI), frailty index, bowel incontinence, hearing difficulties, and poor self-rated health. In the multivariable analysis, age of ≥90 years, ADLH ≥1, unsteady gait, BMI <25 or ≥30 kg/m 2 , and frailty remained as risk factors for readmission. Surgical operation during the treatment period was associated with a lower readmission risk. Conclusions and implicationsInterRAI-PAC performed upon admission to geriatric hospitals revealed patient-related risk factors for readmission. Based on the identified risk factors, we recommend that the patient's functional ability, activities of daily living (ADL) needs, and individual factors underlying ADL disability, as well as nutritional and mobility problems should be carefully addressed and managed during hospitalization to diminish the risk for readmission.

Perceived Versus Actual Risks of 30-Day Readmission in Patients With Cardiovascular Disease.

Cardiovascular disease (CVD) is the leading cause of hospitalization in the United States, and patients with CVD are at a high risk of readmission after discharge. We examined whether patients' perceived risk of readmission at discharge was associated with actual 30-day readmissions in patients hospitalized with CVD. We recruited 730 patients from the Duke Heart Center who were admitted for treatment of CVD between January 1, 2015, and August 31, 2017. A standardized survey was linked with electronic health records to ascertain patients' perceived risk of readmission, and other sociodemographic, psychosocial, behavioral, and clinical data before discharge. All-cause readmission within 30 days after discharge was examined. Nearly 1-in-3 patients perceived a high risk of readmission at index admission and those who perceived a high risk had significantly more readmissions within 30 days than patients who perceived low risks of readmission (23.6% versus 15.8%, P=0.016). Among those who perceived a high risk of readmission, non-White patients (odds ratio [OR], 2.07 [95% CI, 1.28-3.36]), those with poor self-rated health (OR, 2.30 [95% CI, 1.38-3.85]), difficulty accessing care (OR, 2.72 [95% CI, 1.24-6.00]), and prior hospitalizations in the past year (OR, 2.13 [95% CI, 1.21-3.74]) were more likely to be readmitted. Among those who perceived a low risk of readmission, patients who were widowed (OR, 2.69 [95% CI, 1.60-4.51]) and reported difficulty accessing care (OR, 1.89 [95% CI, 1.07-3.33]) were more likely to be readmitted. Patients who perceived a high risk of readmission had a higher rate of 30-day readmission than patients who perceived a low risk. These findings have important implications for identifying CVD patients at a high risk of 30-day readmission and targeting the factors associated with perceived and actual risks of readmission.

Abstract 12818: Identifying Drivers of Hospital Readmission Through Analysis of Discrepant Predicted and Observed Readmission Status

Introduction: The Hospital Readmissions Reduction Program (HRRP) lowers Medicare payments to hospitals with excess readmissions for certain conditions. We analyzed FY2020 HRRP data for Brigham and Women’s Hospital (July 2015 to June 2018). We conducted an analysis to identify patients with a discrepant expected vs observed readmission status for AMI, HF and CABG, followed by a chart review to explain this discrepancy. Methods: We calculated the risk of readmission for each patient, which was a summed value of the weights associated with all recorded comorbidities in the CMS data. A negative risk score indicated a patient was unlikely to be readmitted and a positive score indicated the opposite. We then performed a chart review focused on patients who had a high risk of readmission but were not readmitted, and those who had a low risk of readmission but were readmitted. Results: For AMI, 18% (108/596) of patients were readmitted within 30 days, CABG 14% (50/357) of patients, and HF 27% (367/1382) of patients. For AMI, risk of readmission scores ranged from 2.75 to -0.095. 5/596 patients had a negative score, and none were readmitted. For CABG, scores ranged from 2.64 to -0.31, 58/357 people had a negative score, and 6 were readmitted. For HF, scores ranged from 1.94 to 0.055. There were no negative scores, but of the lowest 20/1382 scores, 2 were readmitted. We then performed a chart review of 37 patients whose readmission status was discordant with their risk score, and examined why this occurred. For patients who were low risk but were readmitted across all three conditions, 30% (range 10% - 54%) did not have a follow up appointment scheduled before discharge, 11% (range 0% - 29%) did not have an advanced care plan and 95% (range 86% - 100%) had not had a SIC. Patients who were high risk but not readmitted were evaluated but did not have any notable characteristics. We did not find any evidence of under-coding of risk comorbidities that would have led to falsely low risk scores. Conclusions: Patients with more comorbidities were more likely to get readmitted, and we found these risk factors to be accurately recorded. Clinical care insights from this project include the need for more SICs and palliative care consults and a more targeted effort to ensure patients have appropriate follow-up.

Abstract 13880: A Novel, Evidence-based, Standardized Discharge Checklist Reduces Thirty Day Heart Failure Readmissions in an Urban Safety Net Hospital

Introduction: Safety net hospitals are more likely to be penalized for heart failure (HF) readmissions. There is limited evidence as to whether readmission reduction strategies are effective in this setting. We hypothesized that a discharge checklist would reduce readmissions in an urban safety net hospital. Methods: We implemented a novel HF discharge checklist in an academic safety net hospital in San Francisco from October 2018 to April 2019. The checklist included 1) achievement of euvolemia based on physical exam, 2) prescription of guideline-directed medical therapy, and 3) establishment of scheduled follow-up within 7 days of discharge. All HF patients who were discharged with the checklist in the 6 month study period were retrospectively compared to all HF patients discharged in the 6 months prior to the implementation of the checklist. The primary outcome was the 30-day readmission rate and multivariate modeling was used to assess the significance of each checklist component. Results: Demographics were similar between the intervention (n=118) and control (n=265) groups. Of all 383 patients, mean age was 60±13 years, 102 (27%) patients were women, 170 (44%) were black, 88 (23%) were latinx, 127 (33%) were not housed, 208 (54%) used illicit substances, and 289 (76%) had ejection fraction ≤ 40%. Use of the checklist was associated with a 13.3% absolute reduction in the 30-day readmission rate (33.6% vs 20.3%, p=0.009). The intervention group was more likely to be discharged on guideline-directed medical therapy (54% vs 25%, p&lt;0.0001) including beta blockers (89% vs 71%, p&lt;0.0001), ACEI/ARBs (88% vs 66%, p&lt;0.0001) and MRAs (50% vs 23%, p&lt;0.0001). The intervention group was also more likely to have scheduled follow-up within 7 days (70 vs 58%, p=0.02). There was no difference between the groups in achievement of euvolemia. In all patients, multivariate analysis adjusted for demographics and insurance status demonstrated that the prescription of guideline-directed medical therapy was associated with lower risk of readmission (OR 0.31, 0.15-0.64). Conclusions: A novel, inexpensive discharge checklist increased the prescription of guideline-directed medical therapy and significantly reduced 30-day HF readmissions in a safety net hospital.

Causes and Predictors of 30-Day Readmission in Elderly Patients With Delirium.

To study 30-day readmission (30-DR) rate and predictors for readmission among elderly patients with delirium. This was a retrospective observational cohort study of patients aged ≥65 years with discharge diagnosis of delirium identified from the Nationwide Readmission Database using common International Classification of Diseases, Ninth Revision, and Clinical Modification codes linked to delirium diagnosis. Multivariate logistic regression analyses were performed adjusting for stratified cluster design to identify patient/system-specific factors associated with 30-DR. Overall, the 30-DR rate was 17% (7,140 of 42,655 weighted index admissions). The common causes of readmission were systemic diseases (43%), infections (27%), and neurologic diseases (18%). Compared with initial hospitalization, readmission costs were higher ($11,442 vs $10,350, p < 0.0001) with a longer length of stay (6.6 vs 6.1 days, p < 0.0001). Independent predictors of readmission included discharge against medical advice (odds ratio [OR] 1.8, p < 0.0034), length of stay (OR 1.3, p < 0.0001), and chronic systemic diseases (anemia, OR 2.4, p < 0.0001, chronic renal failure OR 1.4, p < 0.0001, congestive heart failure OR 1.3, p < 0.0001, lung disease OR 1.2, p < 0.0004, and liver disease OR 1.2, p < 0.03). Private insurance was associated with a lower risk of readmission (OR 0.78, p < 0.02). The main predictors of readmission were chronic systemic diseases and discharge against medical advice. These data may help design directed clinical care pathways to optimize medical management and postdischarge care to reduce readmission rates.

Deprescribing in geriatric inpatients is associated with a lower readmission risk: a case control study.

Background Polypharmacy is prevalent in older adults and has been associated with iatrogenic harm. Deprescribing has been promoted to reduce polypharmacy. It remains however unclear whether deprescribing during hospital stay can reduce the readmission risk. Objective We sought to determine whether deprescribing in geriatric inpatients was associated with a lower readmission risk at three months post-discharge. Method A case control study was performed, using data from a prospective, controlled study in geriatricinpatients. Deprescribing was defined as the percentage of discontinued preadmission medications and was assessed upon discharge. A logistic regression analysis was used to determine the odds ratio for deprescribing and the outcome of readmissions. An adjusted odds ratio was then estimated, taking into account age, sex, mortality, the number of preadmission medications and the Charlson Comorbidity Index. Results Data of 166 patients were analysed, of whom 61 had experienced at least one readmission. Adjusting for age, number of preadmission medications and mortality resulted in the most informative regression model, based on the lowest Akaike information criterion (adjusted odds ratio 0.981, 95% confidence interval 0.964 to 0.998). Conclusion Deprescribing in geriatric inpatients was associated with a reduced readmission risk at three months post-discharge.Trial registration S53664.

Discharge before noon: is the sun half up or half down?

To analyze the impact of discharge before noon (DBN) on length of stay (LOS) and readmission of adultinpatients. Retrospective analysis of 78,826 patients from a single tertiary care center between January 1, 2016, and December 31, 2018. The patient population was divided between patients discharged before and after noon. Outcomes were analyzed with univariate and multivariate analyses. DBN was independently associated with higher likelihood of LOS above the median (odds ratio [OR], 1.26; 95% CI, 1.18-1.35; P < .001) among medical patients. This association was not seen among surgical patients, in whom DBN was associated with a shorter LOS (OR, 0.78; 95% CI, 0.71-0.86; P < .001). Factors associated with higher LOS in both medical and surgical groups included higher case mix index, Medicaid payer, weekday discharges, and discharge to skilled nursing or rehabilitation facilities. For the variable of readmission, DBN in surgical patients was associated with a lower readmission rate (OR, 0.81; 95% CI, 0.69-0.95; P = .008). The finding that DBN was associated with higher LOS among medical patients suggests that some patients may have been able to be safely discharged the evening prior. In patients with surgical diagnoses, DBN was associated with a lower LOS and a lower risk of readmission. Patients with later discharges were more likely to be sent to a rehabilitation center or skilled nursing facility and were more frequently discharged during a weekday. Identification of these factors may help health systems transition patients safely and efficiently out of the hospital.

Influenza Vaccination and Hospitalization Outcomes Among Older Patients With Cardiovascular or Respiratory Diseases.

Influenza vaccination has been suggested to protect against death and recurrent events among patients with cardiovascular disease or chronic obstructive respiratory disease, but there is limited evidence in older adults, who have higher risks of influenza-associated hospitalization and mortality. Patients aged ≥60 years hospitalized for cardiovascular or respiratory diseases from the Beijing Urban Employee Basic Medical Insurance database during 3 influenza seasons (2013-2014 through 2015-2016) were pooled to estimate the effects of influenza vaccination on hospitalization outcomes. Vaccination status was ascertained through cross-referencing the Beijing Elderly Influenza Vaccination database. The summer months (June-August) were used as a reference period to adjust for unmeasured confounders during influenza seasons. After adjustment for both measured and unmeasured confounders, influenza vaccination was associated with lower risks of in-hospital deaths among patients hospitalized for cardiovascular (odds ratio [95% confidence interval], 0.85 [.68-1.06]) or respiratory diseases (0.66 [.54-.82]). Influenza vaccination was associated with a lower risk of readmission among patients with cardiovascular (odds ratio [95% confidence interval], 0.81 [.69-.95]) but not respiratory diseases (1.12 [.92-1.35]). Influenza vaccination was also associated with lower direct medical costs, but not with length of stay. Influenza vaccination protected against hospitalization outcomes among older adults with cardiovascular or respiratory diseases.

Association between Electronic Medical Records and Healthcare Quality

The implementation of electronic medical records (EMRs) has generally been thought to improve medical efficiency and safety, but consistent evidence of improved healthcare quality due to EMRs in population-based studies is lacking. We assessed the relationship between the degree of EMR adoption and patient outcomes.We performed an observational study using discharge data from Tri-service General Hospital from 2013 to 2018. The levels of EMR utilization were divided into no EMRs, partial EMRs and full EMRs. The primary healthcare quality indicators were inpatient mortality, readmission within 14 days, and 48-hour postoperative mortality. We performed a Cox proportional hazards regression analysis to evaluate the relationship between the EMR utilization level and healthcare quality.In total, 262,569 patients were included in this study. Compared with no EMRs, full EMR implementation led to lower inpatient mortality [adjusted hazard ratio (HR) 0.947, 95% confidence interval (CI): 0.897–0.999, P = ..049] and a lower risk of readmission within 14 days (adjusted HR 0.627, 95% CI: 0.577–0.681, P < .001). Full EMR implementation was associated was a lower risk of 48-hour postoperative mortality (adjusted HR 0.372, 95% CI: 0.208–0.665, P = .001) than no EMRs. Partial EMR implementation was associated with a higher risk of readmission within 14 days than no EMRs (HR 1.387, 95% CI: 1.298–1.485, P < .001).Full EMR adoption improves healthcare quality in medical institutions treating severely ill patients. A prospective study is needed to confirm this finding.

Impact of Instrumental Activities of Daily Living Limitations on Hospital Readmission: an Observational Study Using Machine Learning.

Limitations in instrumental activities of daily living (IADL) hinder a person's ability to live independently in the community and self-manage their conditions, but its impact on hospital readmission has not been firmly established. To test the importance of IADL dependency as a predictor of 30-day readmissions and quantify its impact relative to other morbidities. A retrospective cohort study of the population-based Health and Retirement Study linked to Medicare claims data. Random forest was used to rank each predictor variable in terms of its ability to predict readmission. Classification and regression tree (CART) was used to identify complex multimorbidity combinations associated with high or low risk of readmission. Generalized linear regression was used to estimate the adjusted relative risk of readmission for IADL limitations. Hospitalizations of adults age 65 and older (n = 20,007), from 6617 unique subjects. The main outcome was 30-day all-cause unplanned readmission. The main predictor of interest was self-reported IADL limitation. Other key predictors were self-reported complex multimorbidity including chronic diseases, geriatric syndromes, and activities of daily living (ADL) limitations, along with demographic, socioeconomic, and behavioral factors. The overall 30-day readmission rate in the study was 16.4%. Random forest analysis ranked ADLs and IADL limitations as the two most important predictors of 30-day readmission. CART identified hospitalizations of patients with IADL limitations and diabetes as a subgroup at the highest risk of readmission (26% readmitted). Multivariable regression analyses showed that ADL limitations were associated with 1.17 (1.06-1.29) times higher risk of readmission even after adjusting for other patient covariates. Risk prediction was modest though for even the best model (AUC = 0.612). IADL limitations are key predictors of 30-day readmission as demonstrated using several machine learning methods. Routine assessment of functional abilities in hospital settings could help identify those most at risk.

Abstract 107: Home Health Care After Discharge is Associated With Less Early Readmissions for Patients With Acute Myocardial Infarction

Objective: Home health care (HHC) is a support tool to transition patients after discharge and acute myocardial infarction (AMI) is a significant cause of morbidity and mortality in the U.S. However, little is known regarding the impact of HHC on AMI patients. We sought to identify predictors of readmissions among AMI patients, characteristics of those who receive HHC and investigate the association of HHC with readmission. Methods: We queried the National Readmission Database (NRD) (January 2012 - December 2014), to identify patients discharged after AMI and selected patients who were discharged home with (HHC+) and without HHC (HHC-). We reported national estimates with survey methods with weights provided in our data. After univariate exploratory analyses, we developed a regression model to identify the probability of each patient to receive HHC. From the propensity score, we calculated average treatment on the treated (ATT) weights. These ATT weights were included in the logistic regression model to determine the impact of HHC on readmission after adjusting for available clinical confounders. We considered post-weighting standardized differences &lt;10% as appropriate for our ATT model. To determine clinical factors associated with readmission, we also performed a multi-variable logistic regression with readmission as the end-point. All results were reported as risk ratios (RR) with their 95% confidence intervals (CI). Results: Between January 2012 to December 2014, 406,237 patients were treated for AMI and discharged home with or without HHC. Among these 9.4% (38,215) received HHC. HHC+ patients were older (mean age 77 ± 11 vs 60 ±12 years p&lt;0.001), more likely to be female (53.6% vs. 26.9%, p &lt;0.001), and have cancer (3.7% vs 1.3%, p &lt;0.001), congestive heart failure (5.7% vs. 0.5%, p &lt;0.001), chronic pulmonary disease (23.2% vs. 12.7%, p &lt;0.001), chronic kidney disease (26.9% vs 6.9%, p &lt;0.001), diabetes (35.6% vs. 26.7%, p &lt;0.001), hypertension (70.7% vs. 64.8%, p &lt;0.001) and peripheral vascular disease (14.6% vs 6.4%, p &lt;0.001). Patients readmitted after MI were more likely to be older and have diabetes (RR 1.42, 95% CI 1.37-1.48), CHF (RR 5.89, CI 5.55-6.26) or COPD (RR 1.59, 1.52-1.65). Unadjusted 30-day readmission rate was 20.9% for HHC+ and 8.2% for HHC- patients. Propensity-weighted adjustment for covariates yielded 36,979 HHC+ patients and 37,785 HHC- patients. Adjusted risk rations (RR) for 30-day readmission were computed using ATT weights, and HHC+ patients had significantly lower readmission risk (RR 0.89, 95% CI 0.82 - 0.96) compared to HHC- (RR 1.12, 95% CI 1.04 - 1.21; p &lt; 0.001) Conclusion: In the United States, a small proportion of patients receive home health care after discharge post-AMI. Older, females and those with diabetes or heart failure are more likely to receive home health care. Use of home health care may be associated with lower 30-day readmission rates after AMI.