View clinical trials related to Patient Readmission.
Filter by:The purpose of this research is to use a handheld ultrasound to assess patients with congestive heart failure (CHF) to see if the ultrasound can help predict readmission to the hospital. The study will include patients who are admitted to the hospital for CHF. Participants will have two ultrasounds at hospital discharge and at a follow up visit.
Unplanned 30-day hospital readmissions are an critical healthcare quality metric, with meaningful effects on patients and health systems operations. Interventions to reduce unplanned readmissions have primarily operated within a healthcare-centric frame, with enhancements to either pre- or post-discharge care planning, medication reconciliation, or visit frequency. Associations of 30-day readmission rates with poverty status and other social factors, however, suggest that attending to unmet social needs may yield added benefits to models focused on healthcare delivery. The purpose of the present trial is to provide evidence regarding the effects on 30-day readmissions of providing a one-time post-discharge income supplement to socially vulnerable older adults with medical complexity participating in an enhanced care coordination program.
This study will look to implement a plan for enhanced transitional care for patients at high risk of unplanned hospital readmission in hopes of reducing their risk for readmission in the first 30 days post discharge from an inpatient encounter. Hospital readmissions are an undesirable occurrence that can increase cost for hospitals, and can cause further negative outcomes for patients. Identifying factors that increase a patient's chances of being readmitted to the hospital, as well as developing an intervention to effectively reduce this risk, has historically been challenging. Our new method uses a combination of common features such as diagnosis and length of hospital stay, with a novel artificial intelligence (AI) algorithm, the RecuR Score model developed by the University of Maryland Medical System, that identifies patients at the highest risk of having an unplanned hospital readmission. Participants identified as higher risk will then be enrolled into our pilot where they will be randomized to receive either the standard of care treatment or an enhanced protocol that includes additional disease education, coordination of home health services, and a focus on their readmission during existing multidisciplinary team huddles. The main goal of this study is to reduce unplanned hospital readmission within 30 days of initial discharge, in those most at risk of being readmitted, using the aforementioned novel methods for identifying these participants and a transitional care intervention. This success of this goal will be analyzed across different readmission risk levels in the study population. Secondary goals of this study include reducing unplanned hospital readmission within 90 days, reducing 30-day post-discharge mortality, and reducing 30- and 90-day emergency department (ED) usage after an initial hospitalization.
The purpose of this study is to examine if educational intervention in high risk patients can lead to decreased hospital readmissions when compared to patients who are not in the intervention program. Additionally, to determine patient satisfaction with the educational program.
Chronic obstructive pulmonary disease (COPD) is a common smoking-related lung disease. Patients with COPD are at increased risk of readmission to hospitals within the following 30 days. Hospital readmissions of COPD contribute to clinical and economic burden on society. Understanding why some COPD patients are readmitted remains a key area of unmet need. To our knowledge, no previous study has fully investigated both the social and clinical risk factors associated with these types of patients. The investigators want to prospectively and comprehensively explore the possible causes, whether clinical or social factors, that cause rehospitalisation. The investigators will be collecting demographic and clinical information including daily physical activity level, lung function, blood and sputum samples. These measurements will be collected at patient admission, discharge and at follow-up of 30 and 90 days. This process could lead to a better understanding of the reasons which prevent early hospital readmission for those patients.
This study is a population-based, patient-level analysis of heart failure in England over a 5-year period using a dataset created by linking HES and NICOR databases. Our analyses will look into the re-occurrence of hospitalisation after the initial diagnosis of heart failure, the influence of population factors on risk of re-hospitalisation, and the resultant cost implications in an NHS environment.
This study evaluates the impact of optimizing drug prescriptions on re-admissions of elderly patients within 30 days after hospital discharge. It compares a group of patients receiving comprehensive care (medication reconciliation at hospital entry, multidisciplinary medication review, and medication reconciliation at discharge), versus another group that does not benefit from the program.
The study evaluates the feasibility of providing tele-transition of care, using risk stratification, novel data tools, remote patient monitoring and virtual visits. A new communication tool for relaying tele-communication among providers caring for the virtual patient is introduced. The primary endpoint is 30-day readmissions.
Hospital rehospitalizations within 30 days are frequent and represent a burden for the patients, but also for the entire health care system. This study evaluates the impact of an intervention targeted to high-risk medical patients in order to reduce their risk of rehospitalization. Half of the patients will receive a set of interventions before and after their hospital discharge, while the other half will receive usual care.
Unplanned hospital readmissions are associated with increases in morbidity, mortality, cost and patient dissatisfaction,. Policymakers continue to seek effective policy solutions to avoid readmissions in order to improve quality of care and reduce unnecessary expenditures,. One attempt to reduce readmissions was implemented on June 1 2012, when the Specialist Services Committee of British Columbia (a partnership of Doctors of BC and the Ministry of Health) introduced the new "G78717" fee code for physicians. The objective of the fee code was to create a financial incentive for physicians to provide a point-of-care supplemental discharge summary to patients and their primary care providers prior to discharge from hospital. Initially, only urgent hospital admissions were eligible for this incentive payment but on Nov 1 2015 the incentive was extended to include elective admissions as well. The other eligibility criteria remained unchanged. The effectiveness and cost-effectiveness of the fee code intervention is unknown. This study will address important questions relevant to this policy intervention using rigorous methods and empirical data. This study will employ two methods for measuring changes in readmission risk. First, we will use interrupted (multivariate) time series to measure whether there was a temporal change in provincial readmission risk associated with the implementation of the new fee code. We will complement the above analyses with a stronger design, comparing hospitalizations for which the fee code was charged (intervention group) with a cohort of clinically similar hospitalizations for which the fee code was not charged (control group). For this approach, multivariate logistic regression will be the primary statistical method. Using this analytic strategy, 30-day readmission risk between the intervention and control group will be measured over time, adjusted for patient-, provider-, and hospitalization-level covariates.