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Risk factors for 30-day readmission in adults hospitalized for pulmonary hypertension.

ABSTRACT: Readmissions for pulmonary hypertension are poorly understood and understudied. We sought to determine national estimates and risk factors for 30-day readmission after pulmonary hypertension-related hospitalizations. We utilized the Healthcare Cost and Utilization Project Nationwide Readmission Database, which has weighted estimates of roughly 35 million discharges in the US. Adult patients with primary International Classification of Disease, Ninth Revision, Clinical Modification diagnosis codes of 416.0 and 416.8 for primary and secondary pulmonary hypertension with an index admission between 2012 and 2014 and any readmission within 30 days of the index event were identified. Predictors of 30-day readmission were identified using multivariable logistic regression with adjustment for covariates. Results showed that the national estimate for Primary Pulmonary Hypertension vs Secondary Pulmonary Hypertension-related index events between 2012 and 2014 with 30-day readmission was 247 vs 2550 corresponding to a national readmission risk estimate of 17% vs 18.3%, respectively. The presence of fluid and electrolyte disorders, renal failure, and alcohol abuse were associated with increased risk of readmission in Primary Pulmonary Hypertension, while factors associated with Secondary Pulmonary Hypertension readmissions included anemia, congestive heart failure, lung disease, fluid and electrolyte disorders, renal failure, diabetes, and liver disease. The median cost of Primary Pulmonary Hypertension admissions and readmissions were $46,132 (IQR: $25,384-$85,647) and $41,604.50 (IQR: $22,481.50-$84,420.50), respectively. The median costs of Secondary Pulmonary Hypertension admissions and readmissions were $34,893 (IQR: $19,670-$66,143) and $36,279 (IQR: $19,059-$74,679), respectively. In conclusion, approximately 19% of Primary Pulmonary Hypertension and Secondary Pulmonary Hypertension hospitalizations result in 30-day readmission, with significant costs accrued during the index hospitalization and readmission. With evolving clinical terminology and diagnostic codes, future study will need to better clarify underlying factors associated with readmissions amongst pulmonary hypertension sub-types, and identify methods and procedures to minimize readmission risk.

SUBMITTER: Bhattacharya PT

PROVIDER: S-EPMC7686634 | biostudies-literature | 2020 Oct-Dec

REPOSITORIES: biostudies-literature

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Risk factors for 30-day readmission in adults hospitalized for pulmonary hypertension.

Bhattacharya Priyanka T PT Hameed Asif M Abdul AMA Bhattacharya Shubhadeep T ST Chirinos Julio A JA Hwang Wei-Ting WT Birati Edo Y EY Menachem Jonathan N JN Chatterjee Saurav S Giri Jay S JS Kawut Steven M SM Kimmel Stephen E SE Mazurek Jeremy A JA

Pulmonary circulation 20201001 4

Readmissions for pulmonary hypertension are poorly understood and understudied. We sought to determine national estimates and risk factors for 30-day readmission after pulmonary hypertension-related hospitalizations. We utilized the Healthcare Cost and Utilization Project Nationwide Readmission Database, which has weighted estimates of roughly 35 million discharges in the US. Adult patients with primary International Classification of Disease, Ninth Revision, Clinical Modification diagnosis code ...[more]

PMID: 33282194

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Project description:Unplanned hospital readmissions following surgical interventions are associated with adverse events and contribute to increasing health care costs. Despite numerous studies defining risk factors following lower extremity bypass surgery, evidence regarding readmission after endovascular interventions is limited. This study aimed to identify predictors of 30-day unplanned readmission following infrainguinal endovascular interventions.We identified all patients undergoing an infrainguinal endovascular intervention in the targeted vascular module of the American College of Surgeons National Surgical Quality Improvement Program between 2012 and 2014. Perioperative outcomes were stratified by symptom status (chronic limb-threatening ischemia [CLI] vs claudication). Patients who died during index admission and those who remained in the hospital after 30 days were excluded. Indications for unplanned readmission related to the index procedure were evaluated. Multivariable logistic regression was used to identify preoperative and in-hospital (during index admission) risk factors of 30-day unplanned readmission.There were 4449 patients who underwent infrainguinal endovascular intervention, of whom 2802 (63%) had CLI (66% tissue loss) and 1647 (37%) had claudication. The unplanned readmission rates for CLI and claudication patients were 16% (n = 447) and 6.5% (n = 107), respectively. Mortality after index admission was higher for readmitted patients compared with those not readmitted (CLI, 3.4% vs 0.7% [P < .001]; claudication, 2.8% vs 0.1% [P < .01]). Approximately 50% of all unplanned readmissions were related to the index procedure. Among CLI patients, the most common indication for readmission related to the index procedure was wound or infection related (42%), whereas patients with claudication were mainly readmitted for recurrent symptoms of peripheral vascular disease (28%). In patients with CLI, predictors of unplanned readmission included diabetes (odds ratio, 1.3; 95% confidence interval, 1.01-1.6), congestive heart failure (1.6; 1.1-2.5), renal insufficiency (1.7; 1.3-2.2), preoperative dialysis (1.4; 1.02-1.9), tibial angioplasty/stenting (1.3; 1.04-1.6), in-hospital bleeding (1.9; 1.04-3.5), in-hospital unplanned return to the operating room (1.9; 1.1-3.5), and discharge other than to home (1.5; 1.1-2.0). Risk factors for those with claudication were dependent functional status (3.5; 1.4-8.7), smoking (1.6; 1.02-2.5), diabetes (1.5; 1.01-2.3), preoperative dialysis (3.6; 1.6-8.3), procedure time exceeding 120 minutes (1.8; 1.1-2.7), in-hospital bleeding (2.9; 1.2-7.4), and in-hospital unplanned return to the operating room (3.4; 1.2-9.4).Unplanned readmission after endovascular treatment is relatively common, especially in patients with CLI, and is associated with substantially increased mortality. Awareness of these risk factors will help providers identify patients at high risk who may benefit from early surveillance, and prophylactic measures focused on decreasing postoperative complications may reduce the rate of readmission.

Project description:BackgroundEarly readmissions among older adults hospitalized for acute myocardial infarction (AMI) are costly and difficult to predict. Aging-related functional impairments may inform risk prediction but are unavailable in most studies. Our objective was to, therefore, develop and validate an AMI readmission risk model for older patients who considered functional impairments and was suitable for use before hospital discharge.Methods and resultsSILVER-AMI (Comprehensive Evaluation of Risk in Older Adults with AMI) is a prospective cohort study of 3006 patients of age ≥75 years hospitalized with AMI at 94 US hospitals. Participants underwent in-hospital assessment of functional impairments including cognition, vision, hearing, and mobility. Other variables plausibly associated with readmissions were also collected. The outcome was all-cause readmission at 30 days. We used backward selection and Bayesian model averaging to derive (N=2004) a risk model that was subsequently validated (N=1002). Mean age was 81.5 years, 44.4% were women, and 10.5% were nonwhite. Within 30 days, 547 participants (18.2%) were readmitted. Readmitted participants were older, had more comorbidities, and had a higher prevalence of functional impairments, including activities of daily living disability (17.0% versus 13.0%; P=0.013) and impaired functional mobility (72.5% versus 53.6%; P<0.001). The final risk model included 8 variables: functional mobility, ejection fraction, chronic obstructive pulmonary disease, arrhythmia, acute kidney injury, first diastolic blood pressure, P2Y12 inhibitor use, and general health status. Functional mobility was the only functional impairment variable retained but was the strongest predictor. The model was well calibrated (Hosmer-Lemeshow P value >0.05) with moderate discrimination (C statistics: 0.65 derivation cohort and 0.63 validation cohort). Functional mobility significantly improved performance of the risk model (net reclassification improvement index =20%; P<0.001).ConclusionsIn our final risk model, functional mobility, previously not included in readmission risk models, was the strongest predictor of 30-day readmission among older adults after AMI. The modest discrimination indicates that much of the variability in readmission risk among this population remains unexplained by patient-level factors.Clinical trial registrationURL: https://www.clinicaltrials.gov. Unique identifier: NCT01755052.

Project description:Background: We conducted a retrospective cohort study of thirty-day readmission after abdominal aortic aneurysm (AAA) repair. Patients and methods: Inpatients (2009-2016) undergoing elective AAA repair were selected from the multicenter Cerner Health Facts® database using ICD-9 procedure codes. We identified characteristics associated with 30-day readmission with chi-square analysis and logistic regression. Results: 4,723 patients undergoing elective AAA procedures were identified; 3,101 endovascular aneurysm repairs (EVAR) and 1,622 open procedures. Readmission differed by procedure type (6.5 % EVAR vs. 9.3 % open, p =.0005). Multivariable logistic regression found that patients undergoing EVAR were less likely to be readmitted (OR 0.71, 95 % CI 0.54-0.92) than patients undergoing open repair. The following risk factors were associated with 30-day readmission following any AAA repair: surgical site infection during the index admission (OR 2.79, 95 % CI 1.25-6.22), age (OR 1.03, 95 % CI 1.01-1.05), receipt of bronchodilators (OR 1.34, 95 % CI 1.06-1.70) or steroids (OR 1.45, 95 % CI 1.04-2.02), serum potassium > 5.2 mEq/L (OR 1.89, 95 % CI 1.16-3.06), and higher Charlson co-morbidity scores (OR 1.12, 95 % CI 1.04-1.21). Subgroup analysis revealed that age (OR 1.02, 95 % CI 1.01-1.04), higher Charlson comorbidity scores (OR 1.20, 95 % CI 1.09-1.33), and receipt of post-operative bronchodilators (OR 1.39, 95 % CI 1.03-1.88) were risk factors for 30-day readmission following EVAR. After open procedures, readmission was associated with surgical site infection during the index admission (OR 2.91, 95 % CI 1.17-7.28), chronic heart failure (OR 2.18, 95 % CI 1.22-3.89), and receipt of post-operative steroids (OR 1.92, 95 % CI 1.24-2.96). The most common infections were pneumonia after open procedures and urinary tract infection after EVAR. Conclusions: The risk factor most associated with 30-day readmission after elective AAA repair was surgical site infection. Awareness of these risk factors and vulnerable groups may help identify high-risk patients who could benefit from increased surveillance programs to reduce readmission.

Project description:BackgroundReadmission in older adults is typically complex with multiple contributing factors. We aim to examine how two prevalent and potentially modifiable geriatric conditions - depressive symptoms and malnutrition - relate to other geriatric syndromes and 30-day readmission in hospitalized older adults.MethodsConsecutive admissions of patients ≥ 65 years to a general medical department were recruited over 16 months. Patients were screened for depression, malnutrition, delirium, cognitive impairment, and frailty at admission. Medical records were reviewed for poor oral intake and functional decline during hospitalization. Unplanned readmission within 30-days of discharge was tracked through the hospital's electronic health records and follow-up telephone interviews. We use directed acyclic graphs (DAGs) to depict the relationship of depressive symptoms and malnutrition with geriatric syndromes that constitute covariates of interest and 30-day readmission outcome. Multiple logistic regression was performed for the independent associations of depressive symptoms and malnutrition with 30-day readmission, adjusting for variables based on DAG-identified minimal adjustment set.ResultsWe recruited 1619 consecutive admissions, with mean age 76.4 (7.9) years and 51.3% females. 30-day readmission occurred in 331 (22.0%) of 1,507 patients with follow-up data. Depressive symptoms, malnutrition, higher comorbidity burden, hospitalization in the one-year preceding index admission, frailty, delirium, as well as functional decline and poor oral intake during the index admission, were more commonly observed among patients who were readmitted within 30 days of discharge (P < 0.05). Patients with active depressive symptoms were significantly more likely to be frail (OR = 1.62, 95% CI 1.22-2.16), had poor oral intake (OR = 1.35, 95% CI 1.02-1.79) and functional decline during admission (OR = 1.58, 95% CI 1.11-2.23). Malnutrition at admission was significantly associated with frailty (OR = 1.53, 95% CI 1.07-2.19), delirium (OR = 2.33, 95% CI 1.60-3.39) cognitive impairment (OR = 1.88, 95% CI 1.39-2.54) and poor oral intake during hospitalization (OR = 2.70, 95% CI 2.01-3.64). In minimal adjustment set identified by DAG, depressive symptoms (OR = 1.38, 95% CI 1.02-1.86) remained significantly associated with 30-day readmission. The association of malnutrition with 30-day readmission was no longer statistically significant after adjusting for age, ethnicity and depressive symptoms in the minimal adjustment set (OR = 1.40, 95% CI 0.99-1.98).ConclusionThe observed causal associations support screening and targeted interventions for depressive symptoms and malnutrition during admission and in the post-acute period.

Project description:ImportanceIn the US, more than 600 000 adults will experience an acute myocardial infarction (AMI) each year, and up to 20% of the patients will be rehospitalized within 30 days. This study highlights the need for consideration of calibration in these risk models.ObjectiveTo compare multiple machine learning risk prediction models using an electronic health record (EHR)-derived data set standardized to a common data model.Design, setting, and participantsThis was a retrospective cohort study that developed risk prediction models for 30-day readmission among all inpatients discharged from Vanderbilt University Medical Center between January 1, 2007, and December 31, 2016, with a primary diagnosis of AMI who were not transferred from another facility. The model was externally validated at Dartmouth-Hitchcock Medical Center from April 2, 2011, to December 31, 2016. Data analysis occurred between January 4, 2019, and November 15, 2020.ExposuresAcute myocardial infarction that required hospital admission.Main outcomes and measuresThe main outcome was thirty-day hospital readmission. A total of 141 candidate variables were considered from administrative codes, medication orders, and laboratory tests. Multiple risk prediction models were developed using parametric models (elastic net, least absolute shrinkage and selection operator, and ridge regression) and nonparametric models (random forest and gradient boosting). The models were assessed using holdout data with area under the receiver operating characteristic curve (AUROC), percentage of calibration, and calibration curve belts.ResultsThe final Vanderbilt University Medical Center cohort included 6163 unique patients, among whom the mean (SD) age was 67 (13) years, 4137 were male (67.1%), 1019 (16.5%) were Black or other race, and 933 (15.1%) were rehospitalized within 30 days. The final Dartmouth-Hitchcock Medical Center cohort included 4024 unique patients, with mean (SD) age of 68 (12) years; 2584 (64.2%) were male, 412 (10.2%) were rehospitalized within 30 days, and most of the cohort were non-Hispanic and White. The final test set AUROC performance was between 0.686 to 0.695 for the parametric models and 0.686 to 0.704 for the nonparametric models. In the validation cohort, AUROC performance was between 0.558 to 0.655 for parametric models and 0.606 to 0.608 for nonparametric models.Conclusions and relevanceIn this study, 5 machine learning models were developed and externally validated to predict 30-day readmission AMI hospitalization. These models can be deployed within an EHR using routinely collected data.

Dataset Information

Risk factors for 30-day readmission in adults hospitalized for pulmonary hypertension.

Publications

Risk factors for 30-day readmission in adults hospitalized for pulmonary hypertension.

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