Dataset Information

Nonadherence to CPAP Associated With Increased 30-Day Hospital Readmissions.

ABSTRACT: The primary objective of this study was to determine if nonadherence to continuous positive airway pressure (CPAP) is associated with increased 30-day all-cause, cardiovascular-cause, and pulmonary-cause hospital readmissions.Retrospective cohort study at a Veterans Affairs hospital of patients with obstructive sleep apnea (OSA) who were hospitalized from January 1, 2007 to December 31, 2015. Odds ratio of 30-day readmission was calculated for all-cause, cardiovascular-cause, and pulmonary-cause readmissions. Logistic regression model was used to evaluate odds of nonadherent versus adherent group while adjusting for age, sex, body mass index, living situation, race, comorbidities, and medication adherence.Out of 2,077 records reviewed, 345 patients (183 adherent and 162 nonadherent) met our inclusion criteria. The adherent group had a total of 215 initial admissions, and the nonadherent group had a total of 268 index admissions. Thirty-day all-cause readmission rate was significantly higher in the nonadherent group, with an adjusted odds ratio (OR) of 3.52 (95% confidence interval [CI], 2.04-6.08, P < .001). Thirty-day cardiovascular-cause readmission rate was significantly higher in the nonadherent group, with an adjusted OR of 2.31 (95% CI, 1.11-4.78, P = .024). Difference in 30-day pulmonary-cause readmissions was not statistically significant, with an adjusted OR of 3.66 (95% CI, 0.41-32.76, P = .25).Nonadherence to CPAP is associated with increased 30-day all-cause and cardiovascular-cause readmission in patients with OSA. Ensuring CPAP adherence is crucial in addressing general and cardiovascular-related healthcare utilization and morbidity in patients with OSA.A commentary on this article appears in this issue on page 161.

SUBMITTER: Truong KK

PROVIDER: S-EPMC5786836 | biostudies-other | 2018 Feb

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:IntroductionNew financial incentives, such as reduced Medicare reimbursements, have led hospitals to closely monitor their readmission rates and initiate efforts aimed at reducing them. In this context, many surgical departments participate in the American College of Surgeons National Surgical Quality Improvement Program (NSQIP), which collects detailed demographic, laboratory, clinical, procedure and perioperative occurrence data. The availability of such data enables the development of data science methods which predict readmissions and, as done in this paper, offer specific recommendations aimed at preventing readmissions.Materials and methodsThis study leverages NSQIP data for 722,101 surgeries to develop predictive and prescriptive models, predicting readmissions and offering real-time, personalized treatment recommendations for surgical patients during their hospital stay, aimed at reducing the risk of a 30-day readmission. We applied a variety of classification methods to predict 30-day readmissions and developed two prescriptive methods to recommend pre-operative blood transfusions to increase the patient's hematocrit with the objective of preventing readmissions. The effect of these interventions was evaluated using several predictive models.ResultsPredictions of 30-day readmissions based on the entire collection of NSQIP variables achieve an out-of-sample accuracy of 87% (Area Under the Curve-AUC). Predictions based only on pre-operative variables have an accuracy of 74% AUC, out-of-sample. Personalized interventions, in the form of pre-operative blood transfusions identified by the prescriptive methods, reduce readmissions by 12%, on average, for patients considered as candidates for pre-operative transfusion (pre-operative hematoctic <30). The prediction accuracy of the proposed models exceeds results in the literature.ConclusionsThis study is among the first to develop a methodology for making specific, data-driven, personalized treatment recommendations to reduce the 30-day readmission rate. The reported predicted reduction in readmissions can lead to more than $20 million in savings in the U.S. annually.

Project description:Identification of patients at a high risk of potentially avoidable readmission allows hospitals to efficiently direct additional care transitions services to the patients most likely to benefit.To externally validate the HOSPITAL score in an international multicenter study to assess its generalizability.International retrospective cohort study of 117?065 adult patients consecutively discharged alive from the medical department of 9 large hospitals across 4 different countries between January 2011 and December 2011. Patients transferred to another acute care facility were excluded.The HOSPITAL score includes the following predictors at discharge: hemoglobin, discharge from an oncology service, sodium level, procedure during the index admission, index type of admission (urgent), number of admissions during the last 12 months, and length of stay.30-day potentially avoidable readmission to the index hospital using the SQLape algorithm.Overall, 117?065 adults consecutively discharged alive from a medical department between January 2011 and December 2011 were studied. Of all medical discharges, 16?992 of 117?065 (14.5%) were followed by a 30-day readmission, and 11?307 (9.7%) were followed by a 30-day potentially avoidable readmission. The discriminatory power of the HOSPITAL score to predict potentially avoidable readmission was good, with a C statistic of 0.72 (95% CI, 0.72-0.72). As in the derivation study, patients were classified into 3 risk categories: low (n?=?73?031 [62.4%]), intermediate (n?=?27?612 [23.6%]), and high risk (n?=?16?422 [14.0%]). The estimated proportions of potentially avoidable readmission for each risk category matched the observed proportion, resulting in an excellent calibration (Pearson ?2 test P?=?.89).The HOSPITAL score identified patients at high risk of 30-day potentially avoidable readmission with moderately high discrimination and excellent calibration when applied to a large international multicenter cohort of medical patients. This score has the potential to easily identify patients in need of more intensive transitional care interventions to prevent avoidable hospital readmissions.

Project description:This study sought to determine the range and prevalence of practices being implemented by hospitals to reduce 30-day readmissions of patients with heart failure or acute myocardial infarction (AMI).Readmissions of patients with heart failure or AMI are both common and costly; however, evidence on strategies adopted by hospitals to reduce readmission rates is limited.We used a Web-based survey to conduct a cross-sectional study of hospitals' reported use of specific practices to reduce readmissions for patients with heart failure or AMI. We contacted all hospitals enrolled in the Hospital to Home (H2H) quality improvement initiative as of July 2010. Of 594 hospitals, 537 completed the survey (response rate of 90.4%). We used standard frequency analysis to describe the prevalence of key hospital practices in the areas of: 1) quality improvement resources and performance monitoring; 2) medication management efforts; and 3) discharge and follow-up processes.Nearly 90% of hospitals agreed or strongly agreed that they had a written objective of reducing preventable readmission for patients with heart failure or AMI. More hospitals reported having quality improvement teams to reduce preventable readmissions for patients with heart failure (87%) than for patients with AMI (54%). Less than one-half (49.3%) of hospitals had partnered with community physicians and only 23.5% had partnered with local hospitals to manage patients at high risk for readmissions. Inpatient and outpatient prescription records were electronically linked usually or always in 28.9% of hospitals, and the discharge summary was always sent directly to the patient's primary medical doctor in only 25.5% of hospitals. On average, hospitals used 4.8 of 10 key practices; <3% of hospitals utilized all 10 practices.Although most hospitals have a written objective of reducing preventable readmissions of patients with heart failure or AMI, the implementation of recommended practices varied widely. More evidence establishing the effectiveness of various practices is needed.

Dataset Information

Nonadherence to CPAP Associated With Increased 30-Day Hospital Readmissions.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets