Introduction: It is unknown whether patients admitted for all-cause dental conditions (ACDC) are at high risk for hospital readmission, or what are the risk factors for dental hospital readmission.
Objective: We examined the prevalence of, and risk factors associated with, 30-day hospital readmission for patients with an all-cause dental admission. We applied artificial intelligence to develop machine learning (ML) algorithms to predict patients at risk of 30-day hospital readmission.
Methods: This study used data extracted from the 2013 Nationwide Readmissions Database (NRD). There were a total of 11,341 cases for all-cause index admission for dental patients admitted to the hospitals. Descriptive statistics were used to analyze patient characteristics. This study applied five techniques to build risk prediction models and to identify risk factors. Model performance was evaluated using area under the receiver operating characteristic curve (AUC), and accuracy, sensitivity, specificity and precision.
Results: There were 11% of patients admitted for ACDC readmitted within 30 days of hospital discharge. On average, the total charge per patient was $131,004 for those with 30-day readmission (n=1254) and $69,750 for those without readmission (n=10,087). Factors significantly associated with 30-day hospital readmission included total charges, number of diagnoses, age, number of chronic conditions, length of hospital stays, number of procedures, Medicare insurance and Medicaid insurance, and severity of illness. Model performance from all methods was similar with the artificial neural network showing the highest AUC of 0.739.
Conclusion: Our results demonstrate that readmission after hospitalization with ACDC is fairly common. If one-third of the 30-day readmission cases can be avoided, there is a potential annual saving of over $25 million among the twenty-one states represented in the NRD. The ML algorithms can predict hospital readmission in dental patients and should be further tested to aid the reduction of hospital readmission and enhancement of patient-centered care.
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http://dx.doi.org/10.2147/RMHP.S272824 | DOI Listing |
Cureus
January 2025
Department of Gastroenterology and Hepatology, Salmaniya Medical Complex, Manama, BHR.
Background Upper gastrointestinal bleeding (UGIB) is one of the most common major medical emergencies. This study sought to determine the epidemiology, clinical characteristics, and outcomes of UGIB in the largest major tertiary care center in Bahrain, compared to regional and international cohorts. Methods We conducted a retrospective cohort study of all patients diagnosed with UGIB between April 2021 and April 2022 in Salmaniya Medical Complex, Bahrain's largest tertiary-level public hospital.
View Article and Find Full Text PDFAnn Thorac Surg Short Rep
September 2023
Cardiovascular Outcomes Research Laboratories (CORELAB), David Geffen School of Medicine at UCLA, Los Angeles, California.
Background: As patients with congenital heart disease are increasingly surviving well into adulthood, the morbidity, mortality, and resource utilization of adult congenital cardiac operations are of increasing interest. Therefore, we evaluated factors associated with perioperative morbidity and outcomes in adults undergoing congenital operations.
Methods: The Nationwide Readmissions Database was tabulated for all adults (≥18 years old) with congenital heart disease between 2010 and 2017.
HCA Healthc J Med
December 2024
St George's University, Grenada, West Indies.
Background: The United States Food and Drug Administration approved 6 atypical antipsychotics for pediatric treatment of schizophrenia. However, little has been published on the effectiveness of these medications in the acute treatment setting of adolescents with psychosis. Since the clinical uncertainty and poor prognosis proceeding the early onset of schizophrenia has a significant impact on a child's development, there is a critical need for evidence-based data on this population.
View Article and Find Full Text PDFAnn Thorac Surg Short Rep
December 2024
Sanger Heart & Vascular Institute, Charlotte, North Carolina.
Background: Our remote patient monitoring (RPM) program for adult cardiac surgery patients aims to remove barriers to access, provide continuity of expert care, and increase their time-at-home. The RPM program integrates novel biosensors, an application for audiovisual visits, messaging, biometric data tracking, patient-reported outcomes, and scheduling with the aim of reducing postoperative length of stay and 30-day readmissions, while simultaneously increasing the rate of patients discharged to home.
Methods: Our institutional database was utilized for this retrospective review of 1000 consecutive RPM patients who underwent coronary artery bypass, valve, and coronary artery bypass + valve, at 3 hospitals from July 2019 through April 2023.
Ann Thorac Surg Short Rep
December 2024
Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas.
Background: Rising rates of substance use (SU) have resulted in an increasing need for left-sided valve surgery for SU-associated infective endocarditis (SU-IE). We compared outcomes, readmissions, and costs between IE patients with and without SU-IE in a national cohort.
Methods: Using the Nationwide Readmissions Database (2016-2018), we identified 10,098 patients with infective endocarditis (IE) who underwent isolated aortic or mitral valve replacement.
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